  An electron beam has gained a maximum energy of 9 GeV per particle in a 1.3
m-long electron beam-driven plasma wakefield accelerator. The amount of charge
accelerated in the spectral peak was 28.3 pC, and the root-mean-square energy
spread was 5.0%. The mean accelerated charge and energy gain per particle of
the 215 shot data set was 115 pC and 5.3 GeV, respectively, corresponding to an
acceleration gradient of 4.0 GeV/m at the spectral peak. The mean energy spread
of the data set was 5.1%. These results are consistent with the extrapolation
of the previously reported energy gain results using a shorter, 36 cm-long
plasma source to within 10%, evincing a non-evolving wake structure that can
propagate distances of over a meter in length. Wake-loading effects were
evident in the data through strong dependencies observed between various
spectral properties and the amount of accelerated charge.


  Hall effect of two-dimensional holes that are spin-polarized by a strong
parallel magnetic field was explored with a small tilt angle. The Hall
resistivity increases nonlinearly with the magnetic field and exhibits negative
corrections. The anomalous negative corrections increase with the perpendicular
magnetization of the two-dimensional hole system. We attribute this to the
anomalous Hall effect of spin-polarized carriers in a nonmagnetic system. The
anomalous corrections to the conductivity exhibit non-monotonic dependence on
the magnetic field.


  Molecular valves are becoming popular for potential biomedical applications.
However, little is known concerning their performance in energy and
environmental areas. Zeolite RHO shows unique pore deformations upon changes in
hydration, cation siting, cation type, or temperature-pressure conditions. By
varying the level of distortion of double eight-rings, it is possible to
control the adsorption properties, which confer a molecular valve behavior to
this material. We have employed interatomic potentials-based simulations to
obtain a detailed atomistic view of the structural distortion mechanisms of
zeolite RHO, in contrast with the averaged and space group restricted
information provided by diffraction studies. We have modeled four
aluminosilicate structures, containing Li$^+$, Na$^+$, K$^+$, Ca$^{2+}$, and
Sr$^{2+}$ cations. The distortions of the three different zeolite rings are
coupled, and the six- and eight-membered rings are largely flexible. A large
dependence on the polarizing power of the extra-framework cations and with the
loading of water has been found for the minimum aperture of the eight-membered
rings that control the nanovalve effect. The calculated energy barriers for
moving the cations across the eight-membered rings are very high, which
explains the experimentally observed slow kinetics of the phase transition as
well as the appearance of metastable phases.


  We prove Manin's conjecture for bi-equivariant compactifications of unipotent
groups.


  This paper studies the $d$-dimensional extension of a fictitious domain
penalization technique that we previously proposed for Neumann or Robin
boundary conditions. We apply Droniou's approach for non-coercive linear
elliptic problems to obtain the existence and uniqueness of the solution of the
penalized problem, and we derive a boundary layer approach to establish the
convergence of the penalization method. The developed boundary layer approach
is adapted from the one used for Dirichlet boundary conditions, but in contrast
to the latter where coercivity enables a straightforward estimate of the
remainders, we reduce the convergence of the penalization method to the
existence of suitable supersolutions of a dual problem. These supersolutions
are then constructed as approximate solutions of the dual problem using an
additional formal boundary layer approach. The proposed approach results in an
advection-dominated problem, requiring the use of appropriate numerical methods
suitable for singular perturbation problems. Numerical experiments, using
upwind finite differences, validate both the convergence rate and the boundary
layer thickness, illuminating the theoretical results.


  Novel time-resolved imaging techniques for the investigation of ultrafast
nanoscale magnetization dynamics are indispensable for further developments in
light-controlled magnetism. Here, we introduce femtosecond Lorentz microscopy,
achieving a spatial resolution below 100 nm and a temporal resolution of 700
fs, which gives access to the transiently excited state of the spin system on
femtosecond timescales and its subsequent relaxation dynamics. We demonstrate
the capabilities of this technique by spatio-temporally mapping the
light-induced demagnetization of a single magnetic vortex structure and
quantitatively extracting the evolution of the magnetization field after
optical excitation. Tunable electron imaging conditions allow for an
optimization of spatial resolution or field sensitivity, enabling future
investigations of ultrafast internal dynamics of magnetic topological defects
on 10-nanometer length scales.


  One of the consequences of persistent technological change is that it force
individuals to make decisions under extreme uncertainty. This means that
traditional decision-making frameworks cannot be applied. To address this issue
we introduce a variant of Case-Based Decision Theory, in which the solution to
a problem obtains in terms of the distance to previous problems. We formalize
this by defining a space based on an orthogonal basis of features of problems.
We show how this framework evolves upon the acquisition of new information,
namely features or values of them arising in new problems. We discuss how this
can be useful to evaluate decisions based on not yet existing data.


  In this paper, we design two classes of stabilized mixed finite element
methods for linear elasticity on simplicial grids. In the first class of
elements, we use $\boldsymbol{H}(\mathbf{div}, \Omega; \mathbb{S})$-$P_k$ and
$\boldsymbol{L}^2(\Omega; \mathbb{R}^n)$-$P_{k-1}$ to approximate the stress
and displacement spaces, respectively, for $1\leq k\leq n$, and employ a
stabilization technique in terms of the jump of the discrete displacement over
the faces of the triangulation under consideration; in the second class of
elements, we use $\boldsymbol{H}_0^1(\Omega; \mathbb{R}^n)$-$P_{k}$ to
approximate the displacement space for $1\leq k\leq n$, and adopt the
stabilization technique suggested by Brezzi, Fortin, and Marini. We establish
the discrete inf-sup conditions, and consequently present the a priori error
analysis for them. The main ingredient for the analysis is two special
interpolation operators, which can be constructed using a crucial
$\boldsymbol{H}(\mathbf{div})$ bubble function space of polynomials on each
element. The feature of these methods is the low number of global degrees of
freedom in the lowest order case. We present some numerical results to
demonstrate the theoretical estimates.


  Turbulence is a challenging feature common to a wide range of complex
phenomena. Random fibre lasers are a special class of lasers in which the
feedback arises from multiple scattering in a one-dimensional disordered
cavity-less medium. Here, we report on statistical signatures of turbulence in
the distribution of intensity fluctuations in a continuous-wave-pumped
erbium-based random fibre laser, with random Bragg grating scatterers. The
distribution of intensity fluctuations in an extensive data set exhibits three
qualitatively distinct behaviours: a Gaussian regime below threshold, a mixture
of two distributions with exponentially decaying tails near the threshold, and
a mixture of distributions with stretched-exponential tails above threshold.
All distributions are well described by a hierarchical stochastic model that
incorporates Kolmogorov's theory of turbulence, which includes energy cascade
and the intermittence phenomenon. Our findings have implications for explaining
the remarkably challenging turbulent behaviour in photonics, using a random
fibre laser as the experimental platform.


  This paper addresses a graph optimization problem, called the Witness Tree
problem, which seeks a spanning tree of a graph minimizing a certain non-linear
objective function. This problem is of interest because it plays a crucial role
in the analysis of the best approximation algorithms for two fundamental
network design problems: Steiner Tree and Node-Tree Augmentation. We will show
how a wiser choice of witness trees leads to an improved approximation for
Node-Tree Augmentation, and for Steiner Tree in special classes of graphs.


  Let $p\in(1, \infty)$, $\kappa\in(0, 1)$ and $w\in A_p(\mathbb C).$ In this
article, the authors obtain a boundedness (resp., compactness) characterization
of the Buerling-Ahlfors commutator $[\mathcal B, b]$ on the weighted Morrey
space $L_w^{p,\,\kappa}(\mathbb C)$ via $\mathrm{BMO}(\mathbb C)$ [resp.,
$\mathrm{CMO}(\mathbb C)$], where $\mathcal B$ denotes the Buerling-Ahlfors
transform and $b\in \mathrm{BMO}(\mathbb C)$ [resp., $\mathrm{CMO}(\mathbb
C)$]. Moreover, an application to the Beltrami equation is also given.


  Within the model of self-gravitating Bose--Einstein condensate (BEC) dark
matter (DM) it is argued that the axion-like self-interaction of ultralight
bosons provides the existence of rarefied and dense phases, which are predicted
earlier on the base of the models with polynomial-like self-interactions.
Associating the very short scattering length in BEC DM with the predominant
participating composites of few DM particles, we attempt to form a dimer of two
particles at a quantum mechanical level, using a smooth $\mu$-deformation of
the axion cosine-like potential and replacing the field-dependent argument with
the distance between particles. Part of the obtained results concerns potential
two-particle scattering with $\mu$-deformed interaction, and they allow us to
focus on a special option with unique values of the deformation parameter
$\mu=1$ and the coupling constant. In this case of the potential with an
infinite scattering length, we get a rather simple solution for the dimer in
the ground state. We involve two-channel scattering and Feshbach resonance to
describe the formation of a dimer in space. Specifying the parameters of
interactions, we reveal a long-lived resonance that occurs when a pair of
particles jumps between the open and closed scattering channels with close
energy values. This indicates the possibility of participation of such dimers
in forming BEC DM halo of galaxies.


  As a new step in the study of rectangularly-colored knot polynomials, we
reformulate the prescription of arXiv:1606.06015 for twist knots in the
double-column representations $R=[rr]$ in terms of skew Schur polynomials.
These, however, are mysteriously shifted from the standard topological locus,
what makes further generalization to arbitrary $R=[r^s]$ not quite
straightforward.


  The demand for seamless Internet access under extreme user mobility, such as
on high-speed trains and vehicles, has become a norm rather than an exception.
However, the 4G/5G mobile network is not always reliable to meet this demand,
with non-negligible failures during the handover between base stations. A
fundamental challenge of reliability is to balance the exploration of more
measurements for satisfactory handover, and exploitation for timely handover
(before the fast-moving user leaves the serving base station's radio coverage).
This paper formulates this trade-off in extreme mobility as a composition of
two distinct multi-armed bandit problems. We propose Bandit and Threshold
Tuning (BATT) to minimize the regret of handover failures in extreme mobility.
BATT uses $\epsilon$-binary-search to optimize the threshold of the serving
cell's signal strength to initiate the handover procedure with
$\mathcal{O}(\log J \log T)$ regret.It further devises opportunistic Thompson
sampling, which optimizes the sequence of the target cells to measure for
reliable handover with $\mathcal{O}(\log T)$ regret.Our experiment over a real
LTE dataset from Chinese high-speed rails validates significant regret
reduction and a 29.1% handover failure reduction.


  In this article, inspired by Lawrence Krauss' plenary talk at the 2007 CAP
congress, the relation between faith and science is examined.


  We analyze control of the familywise error rate (FWER) in a multiple testing
scenario with a great many null hypotheses about the distribution of a
high-dimensional random variable among which only a very small fraction are
false, or "active". In order to improve power relative to conservative
Bonferroni bounds, we explore a coarse-to-fine procedure adapted to a situation
in which tests are partitioned into subsets, or "cells", and active hypotheses
tend to cluster within cells. We develop procedures for a standard linear model
with Gaussian data and a non-parametric case based on generalized permutation
testing, and demonstrate considerably higher power than Bonferroni estimates at
the same FWER when the active hypotheses do cluster. The main technical
difficulty arises from the correlation between the test statistics at the
individual and cell levels, which increases the likelihood of a hypothesis
being falsely discovered when the cell that contains it is falsely discovered
(survivorship bias). This requires sharp estimates of certain quadrant
probabilities when a cell is inactive.


  Anderson localization is a multiple-scattering phenomenon of linear waves
propagating within a disordered medium. Discovered in the late 50s for
electrons, it has since been observed experimentally with cold atoms and with
classical waves (optics, microwaves, and acoustics), but whether wave
localization is enhanced or weakened for nonlinear waves is a long-standing
debate. Here, we show that the nonlinearity strengthens the localization of
surface-gravity waves propagating in a canal with a random bottom. We also show
experimentally how the localization length depends on the nonlinearity, which
has never been reported previously with any type of wave. To do so, we use a
full space-and-time-resolved wavefield measurement as well as numerical
simulations. The effects of the disorder level and the system's finite size on
localization are also reported. We also highlight the first experimental
evidence of the macroscopic analog of Bloch's dispersion relation of linear
hydrodynamic surface waves over periodic bathymetry.


  This work examines the idea of applying the Chapman-Enskog (CE) method for
approximating the solution of the Boltzmann equation beyond the realm of
physics, using an information theory approach. Equations describing the
evolution of averages and their fluctuations in a generalized phase space are
established up to first order in the Knudsen parameter, which is defined as the
ratio of the time between interactions (mean free time) and a characteristic
macroscopic time. Although the general equations here obtained may be applied
in a wide range of disciplines, in this paper only a particular case related to
the evolution of averages in speculative markets is examined.


  We study the effects of field modulation on the energy spectrum of an
electron in a two-dimensional bipartite periodic lattice subject to a magnetic
field. Dependence of the energy spectrum on both the period and the strength of
field modulation is discussed in detail. Our main finding is that introducing
field modulation drastically changes the energy spectrum and the localization
properties of the system appearing in the absence of field modulation; the
degeneracies induced by a uniform magnetic field are broken and the resultant
energy spectrum shows a dispersive band structure, indicating that most of
Aharonov-Bohm cages become unbounded. The effects of field modulation on the
superconducting transition temperature and the critical current in a wire
network with the same geometry are also discussed.


  We investigate a Bose gas with finite-range interaction using a scheme to
eliminate unphysical processes in the T-matrix approximation. In this way the
corrected T-matrix becomes suitable to calculate properties below the critical
temperature. For attractive interaction, an Evans-Rashid transition occurs
between a quasi-ideal Bose gas and a BCS-like phase with a gaped dispersion.
The gap decreases with increasing density and vanishes at a critical density
where the single-particle dispersion becomes linear for small momenta
indicating Bose-Einstein condensation. The investigation of the pressure shows
however, that the mentioned quantum phase transitions might be inaccessible due
to a preceding first order transition.


  The post-main sequence evolution of stars of intermediate or large masses is
notoriously complex. In the recent past, a number of workshops and meetings
have focused on either the Asymptotic Giant Branch of intermediate mass stars,
or the evolution of massive stars. But how well defined is the boundary between
these categories of objects defined? How would an observer proceed to classify
stars into one or the other category? How do objects near the boundary evolve,
die, and contribute to the chemical evolution of their environment? During this
3-day international workshop, 26 high quality presentations were given by
specialists in the relevant fields of astrophysics, and stimulating discussions
followed. It is technically impossible to provide an exhaustive census of the
results and ideas that emerged. In this brief article, we choose to point to
key elements of the workshop, some of which are now the topic of new
collaborations and will lead to publications elsewhere. For the sake of
brevity, we deliberately cite only the contributors to the workshop and no
external references. Many bibliographic references can be found in the original
presentations, which can be retrieved through:
http://astro.u-strasbg.fr/observatoire/obs/stars2009/stars2009.html The
programme workshop, which includes the titles of the individual contributions,
is provided as an appendix.


  We present the first results study of the effects of the powerful Gamma Ray
Burst GRB 221009A that occurred on October 9, 2022, and was serendipitously
recorded by electron and proton detectors aboard the four spacecraft of the
NASA THEMIS mission. Long-duration gamma-ray bursts (GRBs) are powerful cosmic
explosions, signaling the death of massive stars, and, among them, GRB 221009A
is so far the brightest burst ever observed due to its enormous energy
($E_{\gamma iso}\sim10^{55}$ erg) and proximity (the redshift is $z\sim
0.1505$). The THEMIS mission launched in 2008 was designed to study the plasma
processes in the Earth's magnetosphere and the solar wind. The particle flux
measurements from the two inner magnetosphere THEMIS probes THA and THE and
ARTEMIS spacecraft THB and THC orbiting the Moon captured the dynamics of GRB
221009A with a high-time resolution of more than 20 measurements per second.
This allowed us to resolve the fine structure of the gamma-ray burst and
determine the temporal scales of the two main bursts spiky structure
complementing the results from gamma-ray space telescopes and detectors.


  Structured equations are a standard modeling tool in mathematical biology.
They areintegro-differential equations where the unknown depends on one or
several variables, representing the state or phenotype of individuals. A large
literature has been devoted to many aspects of these equations and in
particular to the study of measure solutions.Here we introduce a transport
distance closely related to the Monge-Kantorovich distance,which appears to be
non-expanding for several (mainly linear) examples of structured equations.


  Recent advances in microscopy enable three-dimensional live imaging at a high
resolution. Long-term live imaging of a multicellular organism requires
immobilization of the organism under stable physiological conditions. Despite
proper immobilization, challenges remain within live imaging data analysis due
to other intrinsic and extrinsic dynamics, which can result in misalignments of
an image series over time. 4Dia, an ImageJ/Fiji macro script, aligns 3D
timelapse images through Z-stacks as well as over time using any user selected
channel. 4Dia can be used for essentially any tissue sample with no limit on
the size of Z-stack or the number of timepoints.


  In this paper, we propose, implement, and test two novel downlink LTE
scheduling algorithms. The implementation and testing of these algorithms were
in Matlab, and they are based on the use of Reinforcement Learning, more
specifically, the Qlearning technique for scheduling two types of users. The
first algorithm is called a Collaborative scheduling algorithm, and the second
algorithm is called a Competitive scheduling algorithm. The first type of the
scheduled users is the Primary Users, and they are the licensed subscribers
that pay for their service. The second type of the scheduled users is the
Secondary Users, and they could be unlicensed subscribers that dont pay for
their service, device to device communications, or sensors. Each user whether
it is a primary or secondary is considered as an agent. In the Collaborative
scheduling algorithm, the primary user agents will collaborate in order to make
a joint scheduling decision about allocating the resource blocks to each one of
them, then the secondary user agents will compete among themselves to use the
remaining resource blocks. In the Competitive scheduling algorithm, the primary
user agents will compete among themselves over the available resources, then
the secondary user agents will compete among themselves over the remaining
resources. Experimental results show that both scheduling algorithms converged
to almost ninety percent utilization of the spectrum, and provided fair shares
of the spectrum among users.


  We study an impartial avoidance game introduced by Anderson and Harary. The
game is played by two players who alternately select previously unselected
elements of a finite group. The first player who cannot select an element
without making the set of jointly-selected elements into a generating set for
the group loses the game. We develop criteria on the maximal subgroups that
determine the nim-numbers of these games and use our criteria to study our game
for several families of groups, including nilpotent, sporadic, and symmetric
groups.


  The behaviour under coarsening functors of simple, entire, or reduced graded
rings, of free graded modules over principal graded rings, of superfluous
monomorphisms and of homological dimensions of graded modules, as well as
adjoints of degree restriction functors, are investigated.


  Spin torque oscillators placed onto a nonmagnetic heavy metal show
synchronized auto-oscillations due to the coupling originating from spin Hall
magnetoresistance effect. Here, we study a system having two spin torque
oscillators under the effect of the spin Hall torque, and show that switching
the external current direction enables us to control the phase difference of
the synchronization between in-phase and antiphase.


  We report on recent measurements of W and Z boson production at CMS. These
include measurements of inclusive and differential W and Z boson production
cross sections at $\sqrt{s}$ = 8 and 13 TeV, measurements of the angular
coefficients of Z boson production, forward-backward asymmetry of
Z/$\gamma^{*}$ events, and W charge asymmetry at $\sqrt{s}$ = 8 TeV. These
measurements can be used to improve PDFs and refine QCD calculations of weak
boson production processes. In addition, a W-like mass measurement using Z
boson events has been performed to probe the experimental uncertainties
expected for a W mass measurement at $\sqrt{s}$ = 7 TeV.


  We present one-shot compression protocols that optimally encode ensembles of
$N$ identically prepared mixed states into $O(\log N)$ qubits. In contrast to
the case of pure-state ensembles, we find that the number of encoding qubits
drops down discontinuously as soon as a nonzero error is tolerated and the
spectrum of the states is known with sufficient precision. For qubit ensembles,
this feature leads to a 25% saving of memory space. Our compression protocols
can be implemented efficiently on a quantum computer.


  It is known that the canonical double cover of any connected nonbipartite
graph have an automorphism group of the form $H \rtimes \mathbb{Z}_2$, where
$H$ is the set of automorphism which preserve bipartite parts. We construct
connected nonbipartite and vertex determining graphs whose canonical double
covers have auromorphisms group isomorphic to any semisimple product of
$\mathbb{Z}_2$ with any abstract group $H$. Later we show, that the canonical
double cover of any asymmetric graph have abelian automorphisms group of odd
order. The above construction provides an example of asymmetric graph for any
such group. By modifying the aforementioned construction we obtain graphs which
have any possible number and type of graphs with isomorphic double covers.


  In this paper, we propose an extension to the multinomial logit (MNL) model,
the Halo MNL, that takes into account the interaction effects among products in
an assortment. In particular, this model incorporates pairwise interactions of
items in an effort to describe positive/negative effects among products that
are present/absent in the assortment. Furthermore, we are interested in
establishing sufficient conditions for identifiability, in order to build
robust estimation methods. Under strict identifiability conditions, we use
maximum likelihood to estimate the model parameters for which we derive closed
formulas. We also perform simulation experiments, in order to numerically
evaluate our method, study the accuracy of the estimators and compare it with
the MNL. Last, we fit our model in the Hotel Chain dataset in Bodea et al., and
we compare it with MNL in terms of efficiency, accuracy and robustness. We
conclude that for rich enough datasets the model that includes interaction
effects performs better in terms of how well it fits the data.


  This article focusses on the analysis of a conforming finite element method
for the time-dependent incompressible Navier-Stokes equations. For
divergence-free approximations, in a semi-discrete formulation, we prove error
estimates for the velocity that hold independently of both pressure and
Reynolds number. Here, a key aspect is the use of the discrete Stokes
projection for the error splitting. Optionally, edge-stabilisation can be
included in the case of dominant convection. Emphasising the importance of
conservation properties, the theoretical results are complemented with
numerical simulations of vortex dynamics and laminar boundary layer flows.


  We present the discovery of 17 low mass white dwarfs (WDs) in short-period
P<1 day binaries. Our sample includes four objects with remarkable log(g)~5
surface gravities and orbital solutions that require them to be double
degenerate binaries. All of the lowest surface gravity WDs have metal lines in
their spectra implying long gravitational settling times or on-going accretion.
Notably, six of the WDs in our sample have binary merger times <10 Gyr. Four
have >=0.9 Msun companions. If the companions are massive WDs, these four
binaries will evolve into stable mass transfer AM CVn systems and possibly
explode as underluminous supernovae. If the companions are neutron stars, then
these may be milli-second pulsar binaries. These discoveries increase the
number of detached, double degenerate binaries in the ELM Survey to 54; 31 of
these binaries will merge within a Hubble time.


  We consider the one-dimensional linear free space Schr\"odinger equation on a
bounded interval subject to homogeneous linear boundary conditions. We prove
that, in the case of pseudoperiodic boundary conditions, the solution of the
initial-boundary value problem exhibits the phenomenon of revival at specific
(`rational') times, meaning that it is a linear combination of a certain number
of copies of the initial datum. Equivalently, the fundamental solution at these
times is a finite linear combination of delta functions. At other
(`irrational') times, for suitably rough initial data, e.g., a step or more
general piecewise constant function, the solution exhibits a continuous but
fractal-like profile. Further, we express the solution for general homogenous
linear boundary conditions in terms of numerically computable eigenfunctions.
Alternative solution formulas are derived using the Uniform Transform Method
(UTM), that can prove useful in more general situations. We then investigate
the effects of general linear boundary conditions, including Robin, and find
novel `dissipative' revivals in the case of energy decreasing conditions.


  The classical problem of spherical homologous gravitational collapse with a
polytropic equation of state for pressure is examined in Lagrangian fluid
coordinate, where the position of each initial fluid element {\eta} = r(0) is
followed in time by the evolution function y(t). In this Lagrangian
description, the fluid velocity v = dr/dt = {\eta}dy/dt is not a fluid
variable, contrary to the commonly used Eulerian fluid description. As a
result, the parameter space is one dimensional in {\eta}, in contrast to the
(x, v) two-parameter space of Eulerian formulation. In terms of Lagrangian
coordinate, the evolution function y(t), which is not limited to a linear time
scaling, agrees with the well established parametric form of Mestel (Mestel
1965) for cold cloud collapse. The spatial structure is described by an
equation which corresponds to the one derived by Goldreich and Weber (Goldreich
& Weber 1980). The continuous self-similar density distribution presents a
peaked central core followed by oscillations with decreasing amplitude,
somewhat reminiscent to the expansion-wave inside-out collapse of Shu (Shu
1977). This continuous solution could account for the planetary system of a
protostar. There is also a disconnected density distribution, which could be
relevant to cavity formation between the highly peaked central core and the
external infalling envelope of a magnetar-in-a-cavity pre-supernova
configuration.


  Modern physics experiments often utilize FPGA-based systems for real-time
data acquisition. Integrated analog electronics demand for complex calibration
routines. Furthermore, versatile configuration and control of the whole system
is a key requirement. Beside low-level register interface to the FPGA, also
access to I$^2$C and SPI buses is often needed to configure the complete
system. Calibration through an FPGA is inflexible and yields a complex hardware
implementation. On the contrary, calibration through a remote system is
possible but considerably slower due to repetitive network accesses. By using
SoC-FPGA solutions with a microprocessor, more sophisticated configuration and
calibration solutions, as well as standard remote access protocols, can be
efficiently integrated in software.
  Based on Xilinx Zynq US+ SoC-FPGAs, we implemented a versatile control
framework. This software framework offers a convenient access to the hardware
and a flexible abstraction via remote-procedure calls (RPCs). Based on the open
source RPC library gRPC, functionality with low-latent control flow, complex
algorithms, data conversions and processing, as well as configuration via
external buses can be provided to a client via Ethernet. Furthermore, client
interfaces for various programming languages can be generated automatically
which eases collaboration among different working groups and integration into
existing software. This contribution presents the framework as well as
benchmarks regarding latency and data throughput.


  The properties of the gravitational energy-momentum 3-form and of the
superpotential 2-form are discussed in the covariant teleparallel framework,
where the Weitzenb\"ock connection represents inertial effects related to the
choice of the frame. Due to its odd asymptotic behavior, the contribution of
the inertial effects often yields unphysical (divergent or trivial) results for
the total energy of the system. However, in the covariant teleparallel
approach, the energy is always finite and nontrivial. The teleparallel
connection plays a role of a regularizing tool which subtracts the inertial
effects without distorting the true gravitational contribution. As a crucial
test of the covariant formalism, we reanalyze the computation of the total
energy of the Schwarzschild and the Kerr solutions.


  Let M(v) be the moduli of stable sheaves on K3 surfaces X of Mukai vector v.
If v is primitive, than it is expected that M(v) is deformation equivalent to
some Hilbert scheme and weight two hogde structure can be described by
H^*(X,Z). These are known by Mukai, O'Grady and Huybrechts if rank is 1 or 2,
or the first Chern class is primitive. Under some conditions on the dimension
of M(v), we shall show that these assertion are true. For the proof, we shall
use Huybrechts's results on symplectic manifolds.


  Vacuum condensates of dimension two and their relevance for the dynamical
mass generation for gluons in Yang-Mills theories are discussed


  We introduce the first result of the Clusters Hiding in Plain Sight (CHiPS)
survey, which aims to discover new, nearby, and massive galaxy clusters that
were incorrectly identified as isolated point sources in the ROSAT All-Sky
Survey. We present a Chandra X-ray observation of our first newly discovered
low-redshift (z = 0.223) galaxy cluster with a central X-ray bright point
source, PKS1353-341. After removing the point source contribution to the
cluster core (L_nuc ~ 1.8x10^44 erg/s), we determine various properties of the
cluster. The presence of a relaxed X-ray morphology, a central temperature
drop, and a central cooling time around 400 Myr indicates that it is a strong
cool-core cluster. The central galaxy appears to be forming stars at the rate
of 6.2+\-3.6 Msun/yr, corresponding to ~1% of the classical cooling prediction.
The supermassive black hole in the central galaxy appear to be accreting at
~0.1% of the Eddington rate with a total power output of ~5x10^45 erg/s, split
nearly equally between radiative and mechanical power. We see weak evidence of
localized excess entropy at a radius of 200 kpc which, if true, could imply a
recent (~180 Myr) energetic outburst in the core that has risen buoyantly to a
larger radius. Comparing the cluster's bulk properties with those of other
known clusters (e.g., the total mass M_500 is 6.9(+4.3)(-2.6)x10^14 Msun, and
the bolometric X-ray luminosity L_X is 7x10^44 erg/s), we show that this
cluster, which is massive enough that it was detected (but not confirmed) by
the Planck survey, is also sufficiently luminous that it would have been
identified as a cluster in the ROSAT All-sky Survey if it did not have such a
bright central point source. This discovery demonstrates the potential of the
CHiPS survey to find massive nearby clusters with extreme central properties
that may have been missed or misidentified by previous surveys.


  We present a novel machine learning architecture that uses the exponential of
a single input-dependent matrix as its only nonlinearity. The mathematical
simplicity of this architecture allows a detailed analysis of its behaviour,
providing robustness guarantees via Lipschitz bounds. Despite its simplicity, a
single matrix exponential layer already provides universal approximation
properties and can learn fundamental functions of the input, such as periodic
functions or multivariate polynomials. This architecture outperforms other
general-purpose architectures on benchmark problems, including CIFAR-10, using
substantially fewer parameters.


  In this article, we study the test for independence of two random elements
$X$ and $Y$ lying in an infinite dimensional space ${\cal{H}}$ (specifically, a
real separable Hilbert space equipped with the inner product $\langle .,
.\rangle_{\cal{H}}$). In the course of this study, a measure of association is
proposed based on the sup-norm difference between the joint probability density
function of the bivariate random vector $(\langle l_{1}, X \rangle_{\cal{H}},
\langle l_{2}, Y \rangle_{\cal{H}})$ and the product of marginal probability
density functions of the random variables $\langle l_{1}, X \rangle_{\cal{H}}$
and $\langle l_{2}, Y \rangle_{\cal{H}}$, where $l_{1}\in{\cal{H}}$ and
$l_{2}\in{\cal{H}}$ are two arbitrary elements. It is established that the
proposed measure of association equals zero if and only if the random elements
are independent. In order to carry out the test whether $X$ and $Y$ are
independent or not, the sample version of the proposed measure of association
is considered as the test statistic after appropriate normalization, and the
asymptotic distributions of the test statistic under the null and the local
alternatives are derived. The performance of the new test is investigated for
simulated data sets and the practicability of the test is shown for three real
data sets related to climatology, biological science and chemical science.


  We consider a perturbation of an ``integrable'' Hamiltonian and give an
expression for the canonical or unitary transformation which ``simplifies''
this perturbed system. The problem is to invert a functional defined on the
Lie- algebra of observables. We give a bound for the perturbation in order to
solve this inversion. And apply this result to a particular case of the control
theory, as a first example, and to the ``quantum adiabatic transformation'', as
another example.


  The aim of this work is to provide an understanding of detachment at TCV with
emphasis on analysis of the Balmer line emission. A new Divertor Spectroscopy
System has been developed for this purpose. Further development of Balmer line
analysis techniques has allowed detailed information to be extracted from the
three-body recombination contribution to the n=7 Balmer line intensity.
  During density ramps, the plasma at the target detaches as inferred from a
drop in ion current to the target. At the same time the Balmer $6\rightarrow2$
and $7\rightarrow2$ line emission near the target is dominated by
recombination. As the core density increases further, the density and
recombination rate are rising all along the outer leg to the x-point while
remaining highest at the target. Even at the highest core densities accessed
(Greenwald fraction 0.7) the peaks in recombination and density may have moved
not more than a few cm poloidally away from the target which is different to
other, higher density tokamaks, where both the peak in recombination and
density continue to move towards the x-point as the core density is increased.
  The inferred magnitude of recombination is small compared to the target ion
current at the time detachment (particle flux drop) starts at the target.
However, recombination may be having more localized effects (to a flux tube)
which we cannot discern at this time. Later, at the highest densities achieved,
the total recombination does reach levels similar to the particle flux.


  The optical and radiochemical purification of the scintillating liquid, which
will fill the central detector of the JUNO experiment, plays a crucial role in
achieving its scientific goals. Given its gigantic mass and dimensions and an
unprecedented target value of about 3% @ 1 MeV in energy resolution, JUNO has
set severe requirements on the parameters of its scintillator, such as
attenuation length (Lat>20 m at 430 nm), transparency, light yield, and content
of radioactive contaminants (238U,232Th<10-15 g/g). To accomplish these needs,
the scintillator will be processed using several purification methods,
including distillation in partial vacuum and gas stripping, which are performed
in two large scale plants installed at the JUNO site. In this paper, layout,
operating principles, and technical aspects which have driven the design and
construction of the distil- lation and gas stripping plants are reviewed. The
distillation is effective in enhancing the optical properties and removing
heavy radio-impurities (238U,232Th, 40K), while the stripping process exploits
pure water steam and high-purity nitrogen to extract gaseous contaminants
(222Rn, 39Ar, 85Kr, O2) from the scintillator. The plant operating parameters
have been tuned during the recent com- missioning phase at the JUNO site and
several QA/QC measurements and tests have been performed to evaluate the
performances of the plants. Some preliminary results on the efficiency of these
purification processes will be shown.


  We report evidence of magnetic activity associated with the secondary star in
the EXO 0748-676 low mass X-ray binary system. An analysis of a sequence of
five consecutive X-ray eclipses observed during December 2003 with the RXTE
satellite brings out a feature occurring during ingress we interpret as the
X-ray photoelectric absorption shadow, as seen by an observer at Earth, of a
plasma structure suspended above the surface of the secondary star. The light
curve feature consists of an initial drop in count rate to near zero (the
absorption shadow) with a very short rebound to a significant fraction of the
pre-ingress count rate and then a final plunge to totality over a total time
scale of ~25 s. The ingress feature persists for at least 5 consecutive orbital
periods (a total of ~19 hr), and possibly up to 5 days in our data. Our data
also show significant post-egress dipping during this eclipse sequence, unusual
for this source, indicating possible secondary star mass ejection during this
episode.


  Friendship formation is important to online social network sites and to
society, but can suffer from informational friction. In this study, we
demonstrate that social networks may effectively use an IT-facilitated
intervention -- displaying things in common (TIC) between users (mutual
hometown, interest, education, work, city) -- to encourage friendship
formation. Displaying TIC updates an individual's belief about the shared
similarity with another and reduces information friction that may be hard to
overcome in offline communication. In collaboration with an online social
network, we conduct a randomized field experiment that randomly varies the
prominence of different things in common when a user is browsing a non-friend's
profile. The dyad-level exogenous variation, orthogonal to any (un)observed
structural factors in viewer-profile's network, allows us to cleanly isolate
the role of preferences for TIC in driving network formation and homophily. We
find that displaying TICs to viewers can significantly increase their
probability of sending a friend requests and forming friendships, and is
especially effective for pairs of people who have little in common. We also
find that displaying TIC can improve friendship formation for a wide range of
viewers with different demographics and is more effective when the TICs are
more surprising to the viewer.


  Convolutional Neural Network (CNN)-based accurate prediction typically
requires large-scale annotated training data. In Medical Imaging, however, both
obtaining medical data and annotating them by expert physicians are
challenging; to overcome this lack of data, Data Augmentation (DA) using
Generative Adversarial Networks (GANs) is essential, since they can synthesize
additional annotated training data to handle small and fragmented medical
images from various scanners--those generated images, realistic but completely
novel, can further fill the real image distribution uncovered by the original
dataset. As a tutorial, this paper introduces GAN-based Medical Image
Augmentation, along with tricks to boost classification/object
detection/segmentation performance using them, based on our experience and
related work. Moreover, we show our first GAN-based DA work using automatic
bounding box annotation, for robust CNN-based brain metastases detection on 256
x 256 MR images; GAN-based DA can boost 10% sensitivity in diagnosis with a
clinically acceptable number of additional False Positives, even with
highly-rough and inconsistent bounding boxes.


  In this paper, we propose a novel concept for engineered molecular
communication (MC) systems inspired by animal olfaction. We focus on a
multi-user scenario where several transmitters wish to communicate with a
central receiver. We assume that each transmitter employs a unique mixture of
different types of signaling molecules to represent its message and the
receiver is equipped with an array comprising $R$ different types of receptors
in order to detect the emitted molecule mixtures. The design of an MC system
based on \textit{orthogonal} molecule-receptor pairs implies that the hardware
complexity of the receiver linearly scales with the number of signaling
molecule types $Q$ (i.e., $R=Q$). Natural olfaction systems avoid such high
complexity by employing arrays of \textit{cross-reactive} receptors, where each
type of molecule activates multiple types of receptors and each type of
receptor is predominantly activated by multiple types of molecules albeit with
different activation strengths. For instance, the human olfactory system is
believed to discriminate several thousands of chemicals using only a few
hundred receptor types, i.e., $Q\gg R$. Motivated by this observation, we first
develop an end-to-end MC channel model that accounts for the key properties of
olfaction. Subsequently, we present the proposed transmitter and receiver
designs. In particular, given a set of signaling molecules, we develop
algorithms that allocate molecules to different transmitters and optimize the
mixture alphabet for communication. Moreover, we formulate the molecule mixture
recovery as a convex compressive sensing problem which can be efficiently
solved via available numerical solvers.


  We study a field--theoretical analogue of the Aharonov--Bohm effect in the
Abelian Higgs Model: the corresponding topological interaction is proportional
to the linking number of the Abrikosov--Nielsen--Olesen string world sheets and
the particle world trajectory. The creation operators of the strings are
explicitly constructed in the path integral and in the Hamiltonian formulation
of the theory. We show that the Aharonov--Bohm effect gives rise to several
nontrivial commutation relations. We also study the Aharonov--Bohm effect in
the lattice formulation of the Abelian Higgs Model. It occurs that this effect
gives rise to a nontrivial interaction of tested charged particles.


  In order to study the "problem of time", Rovelli proposed a model of a two
harmonic oscillator system where one of the oscillators can be thought of as a
'clock' for the other oscillator. In this paper we examine a model where the
Hamiltonian is a difference between two harmonic oscillators, and we consider
one of them which has the minus sign as a 'clock'. Klauder's projection
operator approach to generalized coherent states is used to define physical
states and operators. The resolution of unity is derived in terms of a gauge
invariant coordinate. We investigate the 'quantum clock' and show that the
evolution described by it is identical to the classical motion when the energy
becomes large.


  The aim of this work is to show existence, uniqueness and regularity
properties of nonlinear fractional Schr\"{o}dinger equation with fractional
time derivative of order $\alpha\in (0,1)$ and with a Hartree-type nonlinear
term.


  Adopting the MPI-AMRVAC code, we present a 2.5-dimensional
magnetohydrodynamic (MHD) simulation, which includes thermal conduction and
radiative cooling, to investigate the formation and evolution of the coronal
rain phenomenon. We perform the simulation in initially linear force-free
magnetic fields which host chromospheric, transition region, and coronal
plasma, with turbulent heating localized on their footpoints. Due to thermal
instability, condensations start to occur at the loop top, and rebound shocks
are generated by the siphon inflows. Condensations fragment into smaller blobs
moving downwards and as they hit the lower atmosphere, concurrent upflows are
triggered. Larger clumps show us clear "coronal rain showers" as dark
structures in synthetic EUV hot channels and bright blobs with cool cores in
the 304 {\AA} channel, well resembling real observations. Following coronal
rain dynamics for more than 10 hours, we carry out a statistical study of all
coronal rain blobs to quantify their widths, lengths, areas, velocity
distributions, and other properties. The coronal rain shows us continuous
heating-condensation cycles, as well as cycles in EUV emissions. Compared to
previous studies adopting steady heating, the rain happens faster and in more
erratic cycles. Although most blobs are falling downward, upward-moving blobs
exist at basically every moment. We also track the movement of individual blobs
to study their dynamics and the forces driving their movements. The blobs have
a prominence-corona transition-region-like structure surrounding them, and
their movements are dominated by the pressure evolution in the very dynamic
loop system.


  Humans and machines interact more frequently than ever and our societies are
becoming increasingly hybrid. A consequence of this hybridisation is the
degradation of societal trust due to the prevalence of AI-enabled deception.
Yet, despite our understanding of the role of trust in AI in the recent years,
we still do not have a computational theory to be able to fully understand and
explain the role deception plays in this context. This is a problem because
while our ability to explain deception in hybrid societies is delayed, the
design of AI agents may keep advancing towards fully autonomous deceptive
machines, which would pose new challenges to dealing with deception. In this
paper we build a timely and meaningful interdisciplinary perspective on
deceptive AI and reinforce a 20 year old socio-cognitive perspective on trust
and deception, by proposing the development of DAMAS -- a holistic Multi-Agent
Systems (MAS) framework for the socio-cognitive modelling and analysis of
deception. In a nutshell this paper covers the topic of modelling and
explaining deception using AI approaches from the perspectives of Computer
Science, Philosophy, Psychology, Ethics, and Intelligence Analysis.


  We construct characteristic classes of smooth (Hamiltonian) fibrations as as
fiber integrals of products of Pontriagin (or Chern) classes of vertical vector
bundles over the total space of the universal fibration. We give explicit
formulae of these fiber integrals for toric manifolds and get estimates of the
dimension of the cohomology groups of classifying spaces.


  We study the influence of the meson cloud of the nucleon on predictions of
the Monte Carlo Glauber model for the charged particle multiplicity density at
mid-rapidity in $AA$ collisions. We find that for central $AA$ collisions the
meson cloud can increase the multiplicity density by $\sim 16-18$\%. The
meson-baryon Fock component reduces the required fraction of the binary
collisions by a factor of $\sim 2$ for Au+Au collisions at $\sqrt{s}=0.2$ TeV
and $\sim 1.5$ for Pb+Pb collisions at $\sqrt{s}=2.76$ TeV.


  One of the current key challenges in Explainable AI is in correctly
interpreting activations of hidden neurons. It seems evident that accurate
interpretations thereof would provide insights into the question what a deep
learning system has internally \emph{detected} as relevant on the input, thus
lifting some of the black box character of deep learning systems.
  The state of the art on this front indicates that hidden node activations
appear to be interpretable in a way that makes sense to humans, at least in
some cases. Yet, systematic automated methods that would be able to first
hypothesize an interpretation of hidden neuron activations, and then verify it,
are mostly missing.
  In this paper, we provide such a method and demonstrate that it provides
meaningful interpretations. It is based on using large-scale background
knowledge -- a class hierarchy of approx. 2 million classes curated from the
Wikipedia Concept Hierarchy -- together with a symbolic reasoning approach
called \emph{concept induction} based on description logics that was originally
developed for applications in the Semantic Web field.
  Our results show that we can automatically attach meaningful labels from the
background knowledge to individual neurons in the dense layer of a
Convolutional Neural Network through a hypothesis and verification process.


  The emission from the accreting black holes (BHs) in low-mass X-ray binaries
(LMXBs) covers a broad energy band from radio to X-rays. Studying the
correlations between emission in different energy bands during outbursts can
provide valuable information about the accretion process. We analyse the
simultaneous optical, ultraviolet (UV) and X-ray data of the BH-LMXB Swift
J1753.5-0127 during its $\sim$ 12-year long outburst with the {\it Neil Gehrels
Swift Observatory}. We find that the UV/optical and X-ray emission are strongly
correlated during the hard states of the outburst. We fit the relation with a
power-law function $F_{UV/optical} \propto F_{X}^{\beta}$ and find that the
power-law index $\beta$ increases from $\sim$ 0.24 to $\sim$ 0.33 as the
UV/optical wavelength decreases from $\sim$ 5400 \r{A} (V) to $\sim$ 2030 \r{A}
(UVW2). We explore the possible reasons for this and suggest that in Swift
J1753.5-0127 the UV/optical emission is dominated by a viscously heated
accretion disc at large radii. We find that the data that deviate from the
correlation correspond to the low-intensity peaks appeared in the X-ray band
during the outburst, and suggest that these deviations are driven by the
emission from the inner part of the accretion disc.


  Recently, Accattoli introduced the Exponential Substitution Calculus (ESC)
given by untyped proof terms for Intuitionistic Multiplicative Exponential
Linear Logic (IMELL), endowed with rewriting rules at-a-distance for cut
elimination. He also introduced a new cut elimination strategy, dubbed the good
strategy, and showed that its number of steps is a time cost model with
polynomial overhead for the ESC/IMELL, and the first such one.
  Here, we refine Accattoli's result by introducing an abstract machine for ESC
and proving that it implements the good strategy and computes cut-free
terms/proofs within a linear overhead.


  As data have become more prevalent in academia, industry, and daily life, it
is imperative that undergraduate students are equipped with the skills needed
to analyze data in the modern environment. In recent years there has been a lot
of work innovating introductory statistics courses and developing introductory
data science courses; however, there has been less work beyond the first
course. This paper describes innovations to Regression Analysis taught at Duke
University, a course focused on application that serves a diverse undergraduate
student population of statistics and data science majors along with non-majors.
Three principles guiding the modernization of the course are presented with
details about how these principles align with the necessary skills of practice
outlined in recent statistics and data science curriculum guidelines. The paper
includes pedagogical strategies, motivated by the innovations in introductory
courses, that make it feasible to implement skills for the practice of modern
statistics and data science alongside fundamental statistical concepts. The
paper concludes with the impact of these changes, challenges, and next steps
for the course. Portions of in-class activities and assignments are included in
the paper, with full sample assignments and resources for finding data in the
supplemental materials.


  This paper describes an alignment-based model for interpreting natural
language instructions in context. We approach instruction following as a search
over plans, scoring sequences of actions conditioned on structured observations
of text and the environment. By explicitly modeling both the low-level
compositional structure of individual actions and the high-level structure of
full plans, we are able to learn both grounded representations of sentence
meaning and pragmatic constraints on interpretation. To demonstrate the model's
flexibility, we apply it to a diverse set of benchmark tasks. On every task, we
outperform strong task-specific baselines, and achieve several new
state-of-the-art results.


  This chapter presents an overview of the main observational results obtained
to date about Blue Straggler Stars (BSSs) in Galactic Globular Clusters (GCs).
The BSS specific frequency, radial distribution, chemical composition and
rotational properties are presented and discussed in the framework of using
this stellar population as probe of GC internal dynamics. In particular, the
shape of the BSS radial distribution has been found to be a powerful tracer of
the dynamical age of stellar systems, thus allowing the definition of the first
empirical "dynamical clock".


  A graph is called $t$-perfect if its stable set polytope is fully described
by non-negativity, edge and odd-cycle constraints. We characterise $P_5$-free
$t$-perfect graphs in terms of forbidden $t$-minors. Moreover, we show that
$P_5$-free $t$-perfect graphs can always be coloured with three colours, and
that they can be recognised in polynomial time.


  We investigate the consequences of the hybrid quantization approach for
primordial perturbations in loop quantum cosmology, obtaining predictions for
the cosmic microwave background and comparing them with data collected by the
Planck mission. In this work, we complete previous studies about the scalar
perturbations and incorporate tensor modes. We compute their power spectrum for
a variety of vacuum states. We then analyze the tensor-to-scalar ratio and the
consistency relation between this quantity and the spectral index of the tensor
power spectrum. We also compute the temperature-temperature, electric-electric,
temperature-electric, and magnetic-magnetic correlation functions. Finally, we
discuss the effects of the quantum geometry in these correlation functions and
confront them with observations.


  We study a simple extension of the standard model where scalar singlets that
mix with the Higgs doublet are added. This modification to the standard model
could have a significant impact on Higgs searches at the LHC. The Higgs doublet
is not a mass eigenstate and therefore the expected nice peak of the standard
model Higgs disappears. We analyze this scenario finding the required
properties of the singlets in order to make the Higgs "invisible" at the LHC.
In some part of the parameter space even one singlet could make the discovery
of the SM Higgs problematic. In other parts, the Higgs can be discovered even
in the presence of many singlets.


  We study the solid-on-solid interface model above a horizontal wall in three
dimensional space, with an attractive interaction when the interface is in
contact with the wall, at low temperatures. There is no bulk external field.
The system presents a sequence of layering transitions, whose levels increase
with the temperature, before reaching the wetting transition.


  I present the latest calculations of total and differential cross sections
for top-antitop pair production and single top quark production via all main
partonic channels. Higher-order corrections from the resummation of soft gluons
are added through NNLL accuracy. Detailed numerical results are presented for
approximate NNLO cross sections and top quark transverse momentum distributions
at the Tevatron and LHC colliders.


  We use detailed Lyalpha radiative transfer calculations to further test the
claim of Rauch et al. (2008) that they have detected spatially extended faint
Lyalpha emission from the elusive host population of Damped Lyalpha Absorption
systems (DLAs) in their recent ultra-deep spectroscopic survey. We investigate
the spatial and spectral distribution of Lyalpha emission due to star-formation
at the centre of DLAs, and its dependence on the spatial and velocity structure
of the gas. Our model simultaneously reproduces the observed properties of DLAs
and the faint Lyalpha emitters, including the velocity width and column density
distribution of DLAs and the large spatial extent of the emission of the faint
emitters. Our modelling confirms previous suggestions that DLAs are
predominately hosted by Dark Matter (DM) halos in the mass range
10^{9.5}-10^{12} M_sun, and are thus of significantly lower mass than those
inferred for L_* Lyman Break Galaxies (LBGs). Our modelling suggests that DM
halos hosting DLAs retain up to 20% of the cosmic baryon fraction in the form
of neutral hydrogen, and that star formation at the centre of the halos is
responsible for the faint Lyalpha emission. The scattering of a significant
fraction of the Lyalpha emission to the observed radii, which can be as large
as 50 kpc or more, requires the amplitude of the bulk motions of the gas at the
centre of the halos to be moderate. The observed space density and size
distribution of the emitters together with the incidence rate of DLAs suggests
that the Lyalpha emission due to star formation has a duty cycle of ~ 25%.


  In this talk I present recent studies on vacuum polarization energies and
energy densities induced by QED flux tubes. I focus on comparing three and four
dimensional scenarios and the discussion of various approximation schemes in
view of the exact treatment.


  Microstrip patch antennas (MPAs) are rapidly gaining more attention due to
the proliferation of communication devices and systems with frequencies
becoming more suitable for the size and performance of this type of antenna.
Due to recent advancements in semiconductor technology, high dielectric
constant materials are used to achieve additional size reduction which has made
MPAs very useful and popular in the design of mobile devices and wireless
systems. However, MPAs suffer from problems associated with narrow bandwidth
and low gain. Techniques employed for improving the performance of MPA hinge on
tweaking features such as the patch size, substrate height, ground plane size
and feeding method. In view of this, this research designs and analyzes the
performance of an X-band MPA for wireless systems using CST Microwave Studio.
Including the ground plane, the proposed design has a low profile structure of
17 mm x 17 mm x 1.6 mm which is suitable for wireless systems. The proposed
design also resonates at a frequency of 10 GHz with an omnidirectional
radiation pattern exhibiting a gain of 7.2 dBi. Return Loss, VSWR, Gain and
Radiation Pattern are the performance indicators employed in this research. The
proposed MPA design demonstrates marked performance improvement when
benchmarked with a similar MPA designed for 5G applications.


  We study the spatial decay of electron coherence due to electron-electron
interaction in a finite-length disorder-free quantum wire. Based on the
Luttinger liquid theory, we demonstrate that the coherence length
characterizing the exponential decay of the coherence can vary from region to
region, and that the coherence can even revive after the decay. This
counterintuitive behavior, which is in clear contrast to the conventional
exponential decay with single coherence length, is due to the fractionalization
of an electron and the finite-size-induced recombination of the fractions.


  The article is devoted to one infinite parametric class of continuous
functions with complicated local structure. In the article differential,
integral, self-affine and other properties of functions, that their argument is
represented by the alternating Cantor series are investigated. The functional
equations systems, that investigating functions are unique solution of these
systems in the class of determined and bounded on $[0;1]$ functions are
indicated.
  The investigation was represented in seminar on fractal analysis of Institute
of Mathematics of the National Academy of Sciences of Ukraine on, October 16,
2014 (http://www.imath.kiev.ua/events/index.php?seminarId=21&archiv=1).
  The following investigations in the list of references in the article one can
to find by the corresponding links: [6]
(http://fmi.npu.edu.ua/images/files/publications/naukchasopys1/NZ2013_15.pdf )
[7]
(http://fmi.npu.edu.ua/images/files/publications/naukchasopys1/NZ2013_14.pdf)
[8]
(http://fmi.npu.edu.ua/images/files/publications/naukchasopys1/NZ2012_13_2.pdf)
[9](http://www.ekmair.ukma.edu.ua/bitstream/handle/123456789/7409/Serbeniuk_Funktsii_oznacheni_systemamy.pdf)


  Part of the European Near Earth Asteroids Research (EURONEAR) project, in
2014 we started a survey to observe light curves of Near Earth Asteroids (NEAs)
using the available telescopes of this network. This is the first paper
presenting light-curves and physical properties of 17 NEAs observed by two
amateur astronomers owning small facilities located in good sites, namely a
0.36 m telescope at Isaac Aznar Observatory (Aras de los Olmos, Spain) and a
0.61 m telescope at Blue Mountain Observatory (Leura, Australia). We confirm
most recent or older results and find new ones.


  Large Language Models (LLMs) have become pivotal in advancing natural
language processing, yet their potential to perpetuate biases poses significant
concerns. This paper introduces a new framework employing Direct Preference
Optimization (DPO) to mitigate gender, racial, and religious biases in
LLM-generated English text. By developing a loss function that favors less
biased over biased completions, our approach cultivates a preference for
respectful and non-discriminatory language in LLMs. We also contribute a
manually designed dataset for training LLMs to recognize and correct biases.
This dataset encompasses a diverse range of prompts paired with both biased and
unbiased completions. Implementing this approach on the Microsoft Phi-2 model,
we demonstrate substantial reductions in biased outputs as our model
outperforms the baseline model on almost all bias benchmarks. Our model also
achieves better performance compared to other open-source models on most
benchmarks. By reducing biases in the language generated by the model, our
study marks a significant step towards developing more ethical and socially
responsible LLMs. We publicly release BiasDPO dataset on HuggingFace.


  Anomaly detection is the task of identifying abnormal behavior of a system.
Anomaly detection in computational workflows is of special interest because of
its wide implications in various domains such as cybersecurity, finance, and
social networks. However, anomaly detection in computational workflows~(often
modeled as graphs) is a relatively unexplored problem and poses distinct
challenges. For instance, when anomaly detection is performed on graph data,
the complex interdependency of nodes and edges, the heterogeneity of node
attributes, and edge types must be accounted for. Although the use of graph
neural networks can help capture complex inter-dependencies, the scarcity of
labeled anomalous examples from workflow executions is still a significant
challenge. To address this problem, we introduce an autoencoder-driven
self-supervised learning~(SSL) approach that learns a summary statistic from
unlabeled workflow data and estimates the normal behavior of the computational
workflow in the latent space. In this approach, we combine generative and
contrastive learning objectives to detect outliers in the summary statistics.
We demonstrate that by estimating the distribution of normal behavior in the
latent space, we can outperform state-of-the-art anomaly detection methods on
our benchmark datasets.


  In this paper, we introduce the nonstandard vector space in which the concept
of additive inverse element will not be taken into account. We also consider a
metric defined on this nonstandard vector space. Under these settings, the
conventional intuitive properties for the open and closed balls will not hold
true. Therefore, four kinds of open and closed sets are proposed. Furthermore,
the topologies generated by these different concepts of open and closed sets
are investigated.


  We employ a quantum theory of the nonlinear optical response from an actual
solid-state material possessing an intrinsic bulk contribution to the
third-order nonlinear susceptibility (Kerr-type nonlinearity), which can be
arbitrarily nanostructured to achieve diffraction-limited electromagnetic field
confinement. By calculating the zero-time delay second-order correlation of the
cavity field, we set the conditions for using semiconductor or insulating
materials with near-infrared energy gaps as efficient means to obtain
single-photon nonlinear behavior in prospective solid-state integrated devices,
alternative to ideal sources of quantum radiation such as, e.g., single
two-level emitters.


  We investigate the motion of test particles in the gravitational field of a
static naked singularity generated by a mass distribution with quadrupole
moment. We use the quadrupole-metric ($q-$metric) which is the simplest
generalization of the Schwarzschild metric with a quadrupole parameter. We
study the influence of the quadrupole on the motion of massive test particles
and photons and show that the behavior of the geodesics can drastically depend
on the values of the quadrupole parameter. In particular, we prove explicitly
that the perihelion distance depends on the value of the quadrupole. Moreover,
we show that an accretion disk on the equatorial plane of the quadrupole source
can be either continuous or discrete, depending on the value of the quadrupole.
The inner radius of the disk can be used in certain cases to determine the
value of the quadrupole parameter. The case of a discrete accretion is
interpreted as due to the presence of repulsive gravity generated by the naked
singularity. Radial geodesics are also investigated and compared with the
Schwarzschild counterparts.


  For p = 3 and p = 5, we exhibit a finite nonsolvable extension of the
rational numbers which is ramified only at p via explicit computations with
Hilbert modular forms.


  We study cascading failures in a system comprising interdependent
networks/systems, in which nodes rely on other nodes both in the same system
and in other systems to perform their function. The (inter-)dependence among
nodes is modeled using a dependence graph, where the degree vector of a node
determines the number of other nodes it can potentially cause to fail in each
system through aforementioned dependency. In particular, we examine the impact
of the variability and dependence properties of node degrees on the probability
of cascading failures. We show that larger variability in node degrees hampers
widespread failures in the system, starting with random failures. Similarly,
positive correlations in node degrees make it harder to set off an epidemic of
failures, thereby rendering the system more robust against random failures.


  In our earlier publication we introduced the Spectrally Integrated Voigt
Function (SIVF) as an alternative to the traditional Voigt function for the
HITRAN-based applications [Quine & Abrarov, JQSRT 2013]. It was shown that
application of the SIVF enables us to reduce spectral resolution without loss
of accuracy in computation of the spectral radiance. As a further development,
in this study we present more efficient SIVF approximations derived by using a
new sampling method based on incomplete cosine expansion of the sinc function
[Abrarov & Quine, Appl. Math. Comput. 2015]. Since the SIVF mathematically
represents the mean value integral of the Voigt function, this method accounts
for area under the curve of the Voigt function. Consequently, the total band
radiance, defined as the integrated spectral radiance within a given spectral
region, can also retain its accuracy even at low spectral resolution. Our
numerical results demonstrate that application of the SIVF may be promising for
more rapid line-by-line computation in atmospheric models utilizing the HITRAN
molecular spectroscopic database. Such an approach may be particularly
efficient to implement a retrieval algorithm for the greenhouse gases from the
NIR space data collected by Earth-orbiting micro-spectrometers like Argus 1000
for their operation in a real-time mode. The real-time mode operation of the
micro-spectrometers can be advantageous for instant decision making during
flight for more efficient data collection from space.


  The expansion of renewable energy could help realizing the goals of peaking
carbon dioxide emissions and carbon neutralization. Some existing grid
dispatching methods integrating short-term renewable energy prediction and
reinforcement learning (RL) have been proved to alleviate the adverse impact of
energy fluctuations risk. However, these methods omit the long-term output
prediction, which leads to stability and security problems on the optimal power
flow. This paper proposes a confidence estimation Transformer for long-term
renewable energy forecasting in reinforcement learning-based power grid
dispatching (Conformer-RLpatching). Conformer-RLpatching predicts long-term
active output of each renewable energy generator with an enhanced Transformer
to boost the performance of hybrid energy grid dispatching. Furthermore, a
confidence estimation method is proposed to reduce the prediction error of
renewable energy. Meanwhile, a dispatching necessity evaluation mechanism is
put forward to decide whether the active output of a generator needs to be
adjusted. Experiments carried out on the SG-126 power grid simulator show that
Conformer-RLpatching achieves great improvement over the second best algorithm
DDPG in security score by 25.8% and achieves a better total reward compared
with the golden medal team in the power grid dispatching competition sponsored
by State Grid Corporation of China under the same simulation environment. Codes
are outsourced in https://github.com/buptlxh/Conformer-RLpatching.


  We consider optimization of generalized performance metrics for binary
classification by means of surrogate losses. We focus on a class of metrics,
which are linear-fractional functions of the false positive and false negative
rates (examples of which include $F_{\beta}$-measure, Jaccard similarity
coefficient, AM measure, and many others). Our analysis concerns the following
two-step procedure. First, a real-valued function $f$ is learned by minimizing
a surrogate loss for binary classification on the training sample. It is
assumed that the surrogate loss is a strongly proper composite loss function
(examples of which include logistic loss, squared-error loss, exponential loss,
etc.). Then, given $f$, a threshold $\widehat{\theta}$ is tuned on a separate
validation sample, by direct optimization of the target performance metric. We
show that the regret of the resulting classifier (obtained from thresholding
$f$ on $\widehat{\theta}$) measured with respect to the target metric is
upperbounded by the regret of $f$ measured with respect to the surrogate loss.
We also extend our results to cover multilabel classification and provide
regret bounds for micro- and macro-averaging measures. Our findings are further
analyzed in a computational study on both synthetic and real data sets.


  Using a self-consistent quark model for nuclear matter we investigate
variations of the masses of the non-strange vector mesons, the hyperons and the
nucleon in dense nuclear matter (up to four times the normal nuclear density).
We find that the changes in the hadron masses can be described in terms of the
value of the scalar mean-field in matter. The model is then used to calculate
the density dependence of the quark condensate in-medium, which turns out to be
well approximated by a linear function of the nuclear density. Some relations
among the hadron properties and the in-medium quark condensate are discussed.


  $N$-body simulations have unveiled several apparently universal properties of
dark matter halos, including a cusped density profile, a power-law pseudo
phase-space density $\rho/\sigma_r^3$, and a linear $\beta-\gamma$ relation
between the density slope and the velocity anisotropy. We present a family of
self-consistent phase-space distribution functions $F(E,L)$, based on the
Dehnen-McLaughlin Jeans models, that incorporate these universal properties
very accurately. These distribution functions, derived using a quadratic
programming technique, are analytical, positive and smooth over the entire
phase space and are able to generate four-parameter velocity anisotropy
profiles $\beta(r)$ with arbitrary asymptotic values $\beta_0$ and
$\beta_\infty$. We discuss the orbital structure of six radially anisotropic
systems in detail and argue that, apart from its use for generating initial
conditions for $N$-body studies, our dynamical modeling provides a valuable
complementary approach to understand the processes involved in the formation of
dark matter halos.


  Motion control of droplets has generated much attention for its applications
to microfluidics, where precise control of small fluid volumes is an imperative
requirement. Mechanical vibrations have been shown to be effective at inducing
controllable depinning, and activation of different drop motion regimes.
However, existing vibration-based strategies involve establishing homogeneous
rigid-body dynamics on the substrate, and therefore lack any form of spatial
heterogeneity and tuning. Addressing this limitation, metamaterials provide an
ideal platform to achieve spectrally and spatially selective drop motion
control, which leverages their ability to attenuate vibrations in selected
frequency bands and in selected regions of a substrate. In this work, we
illustrate the potential of metamaterials-based drop control by experimentally
demonstrating a variety of drop motion capabilities on the surface of
metaplates endowed with locally resonant stubs. The experiments leverage the
design versatility of a LEGO component-enabled reconfigurable design platform
and laser vibrometry measurements with high spatial resolution.


  An increasing number of works in natural language processing have addressed
the effect of bias on the predicted outcomes, introducing mitigation techniques
that act on different parts of the standard NLP pipeline (data and models).
However, these works have been conducted in isolation, without a unifying
framework to organize efforts within the field. This leads to repetitive
approaches, and puts an undue focus on the effects of bias, rather than on
their origins. Research focused on bias symptoms rather than the underlying
origins could limit the development of effective countermeasures. In this
paper, we propose a unifying conceptualization: the predictive bias framework
for NLP. We summarize the NLP literature and propose a general mathematical
definition of predictive bias in NLP along with a conceptual framework,
differentiating four main origins of biases: label bias, selection bias, model
overamplification, and semantic bias. We discuss how past work has countered
each bias origin. Our framework serves to guide an introductory overview of
predictive bias in NLP, integrating existing work into a single structure and
opening avenues for future research.


  In the context of the Cobb-Douglas productivity model we consider the $N
\times N$ input-output linkage matrix $W$ for a network of $N$ firms $f_1, f_2,
\cdots, f_N$. The associated influence vector $v_w$ of $W$ is defined in terms
of the Leontief inverse $L_W$ of $W$ as $v_W = \frac{\alpha}{N} L_W
\vec{\mathbf{1}}$ where $L_W = (I - (1-\alpha) W')^{-1}$, $W'$ denotes the
transpose of $W$ and $I$ is the identity matrix. Here $\vec{\mathbf{1}}$ is the
$N \times 1$ vector whose entries are all one. The influence vector is a metric
of the importance for the firms in the production network. Under the realistic
assumption that the data to compute the influence vector is incomplete, we
prove bounds on the worst-case error for the influence vector that are sharp up
to a constant factor. We also consider the situation where the missing data is
binomially distributed and contextualize the bound on the influence vector
accordingly. We also investigate how far off the influence vector can be when
we only have data on nodes and connections that are within distance $k$ of some
source node. A comparison of our results is juxtaposed against PageRank
analogues. We close with a discussion on a possible extension beyond
Cobb-Douglas to the Constant Elasticity of Substitution model, as well as the
possibility of considering other probability distributions for missing data.


  This paper is concerned with the blowup phenomena for initial value problem
of semilinear wave equation with critical time-dependent damping term (DW). The
result is the sharp upper bound of lifespan of solution with respect to the
small parameter $\ep$ when $p_F(N)\leq p\leq p_0(N+\mu)$, where $p_F(N)$
denotes the Fujita exponent for the nonlinear heat equations and $p_0(n)$
denotes the Strauss exponent for nonlinear wave equation in $n$-dimension with
$\mu=0$. Consequently, by connecting the result of D'Abbicco--Lucente--Reissig
2015, our result clarifies the threshold exponent $p_0(N+\mu)$ for dividing
blowup phenomena and global existence of small solutions when $N=3$. The
crucial idea is to construct suitable test functions satisfying the conjugate
linear equation $\pa_t^2\Phi-\Delta \Phi-\pa_t(\frac{\mu}{1+t}\Phi)=0$ of (DW)
including the Gauss hypergeometric functions; note that the construction of
test functions is different from Zhou--Han in 2014.


  Cell image classification methods are currently being used in numerous
applications in cell biology and medicine. Applications include understanding
the effects of genes and drugs in screening experiments, understanding the role
and subcellular localization of different proteins, as well as diagnosis and
prognosis of cancer from images acquired using cytological and histological
techniques. We review three different approaches for cell image classification:
numerical feature extraction, end to end classification with neural networks,
and transport-based morphometry. In addition, we provide comparisons on four
different cell imaging datasets to highlight the relative strength of each
method.


  We design an algorithm writing down presentations of graph braid groups.
Generators are represented in terms of actual motions of robots moving without
collisions on a given graph. A key ingredient is a new motion planning
algorithm whose complexity is linear in the number of edges and quadratic in
the number of robots. The computing algorithm implies that 2-point braid groups
of all light planar graphs have presentations where all relators are
commutators.


  When moving from native to light activated bacteriorhodopsin, modification of
charge transport consisting of an increase of conductance is correlated to the
protein conformational change. A theoretical model based on a map of the
protein tertiary structure into a resistor network is implemented to account
for a sequential tunneling mechanism of charge transfer through neighbouring
amino acids. The model is validated by comparison with current-voltage
experiments. The predictability of the model is further tested on bovine
rhodopsin, a G-protein coupled receptor (GPCR) also sensitive to light. In this
case, results show an opposite behaviour with a decrease of conductance in the
presence of light.


  Simflowny is an open platform which automatically generates efficient
parallel code of scientific dynamical models for different simulation
frameworks. Here we present major upgrades on this software to support
simultaneously a quite generic family of partial differential equations. These
equations can be discretized using: (i) standard finite-difference for systems
with derivatives up to any order, (ii) High-Resolution-Shock-Capturing methods
to deal with shocks and discontinuities of balance law equations, and (iii)
particle-based methods. We have improved the adaptive-mesh-refinement
algorithms to preserve the convergence order of the numerical methods, which is
a requirement for improving scalability. Finally, we have also extended our
graphical user interface (GUI) to accommodate these and future families of
equations. This paper summarizes the formal representation and implementation
of these new families, providing several validation results.


  Motivated by ongoing experimental analyses, we report on the calculation of
next-to-leading order QCD corrections to the production of top anti-top pairs
in association with two hard b-jets at the Fermilab TeVatron. Besides the total
cross section and its scale dependence, a few differential distributions
applicable for Higgs boson searches at the TeVaron are given. The QCD
corrections with respect to leading order are negative and small. For our main
setup they amount to 2%, and remain reasonably stable against changes of cuts.
This proves that an integrated next-to-leading order K-factor does not
necessarily need to be applied in the background estimation for the top
anti-top H -> top anti-top bottom anti-bottom signal process. The distributions
show similarly small corrections. The shape of kinematic distributions is
distorted at most by about 20% in some corners of the phase space. Even though
it is not the main purpose of this paper, we also evaluated the
forward-backward asymmetry of the top quark at next-to-leading order.


  Significant reservoirs of cool gas are observed in the circumgalactic medium
(CGM) surrounding galaxies. The CGM is also found to contain substantial
amounts of metals and dust, which require some transport mechanism. We consider
AGN (active galactic nucleus) feedback-driven outflows based on radiation
pressure on dust. Dusty gas is ejected when the central luminosity exceeds the
effective Eddington luminosity for dust. We obtain that a higher dust-to-gas
ratio leads to a lower critical luminosity, implying that the more dusty gas is
more easily expelled. Dusty outflows can reach large radii with a range of
velocities (depending on the outflowing shell configuration and the ambient
density distribution) and may account for the observed CGM gas. In our picture,
dust is required in order to drive AGN feedback, and the preferential expulsion
of dusty gas in the outflows may naturally explain the presence of dust in the
CGM. On the other hand, the most powerful AGN outflow events can potentially
drive gas out of the local galaxy group. We further discuss the effects of
radiation pressure of the central AGN on satellite galaxies. AGN radiative
feedback may therefore have a significant impact on the evolution of the whole
surrounding environment.


  The attempt to equate operator quantum error correction (quant-ph/0504189v1)
with the quantum computer condition (quant-ph/0507141) in version two of
quant-ph/0504189 is shown to be invalid.


  Feedbacks that can destabilize the climates of synchronously-rotating rocky
planets may arise on planets with strong day-night surface temperature
contrasts. Earth-like habitable-zone (HZ) planets maintain stable surface
liquid water over geological time. This requires equilibrium between the
temperature-dependent rate of greenhouse-gas consumption by weathering,and
greenhouse-gas resupply by other processes. Detected small-radius exoplanets,
and anticipated M-dwarf HZ rocky planets, are expected to be tidally locked. We
investigate two feedbacks that can destabilize climate on tidally-locked
planets. (1) If small changes in pressure alter the temperature distribution
across a planet's surface such that the weathering rate increases when the
pressure decreases, a positive feedback occurs involving increasing weathering
rate near the substellar point, decreasing pressure, and increasing substellar
surface temperature. (2) When decreases in pressure increase the surface area
above the melting point (through reduced advective cooling of the substellar
point), and the corresponding increase in volume of liquid causes net
dissolution of the atmosphere, a further decrease in pressure occurs. We use an
idealized energy balance model to map out the conditions under which these
instabilities may occur. The weathering runaway can shrink the habitable zone,
and cause geologically rapid 10^3-fold pressure shifts within the HZ. Mars may
have undergone a weathering runaway in the past. Substellar dissolution is
usually a negative feedback or weak positive feedback on changes in pressure.
Both instabilities are suppressed if the atmosphere has a high radiative
efficiency. Our results are most relevant for atmospheres that are thin and
have low greenhouse-gas radiative efficiency. These results identify a new
pathway by which HZ planets can undergo rapid climate shifts and become
uninhabitable.


  We propose a new version of generalized probabilistic propositional logic,
namely, discrete-continuous logic (DCL) in which every generalized proposition
(GP) is represented as 2x2 nondiagonal positive matrix with unit trace. We
demonstrate that on the set of propositions of this kind one can define both
the discrete logical operations (connectives) such as negation and strong
logical disjunction and in addition one parameter group of continuous
operations (logical rotations). We prove that an arbitrary classical
proposition (which in this logic is represented by the purely diagonal matrix)
can be considered as the result of strong disjunction of two identical GP. This
fact gives one a good reason to presume the DCL as a prime logical substructure
underlying to ordinary propositional logic, which is recorded by our
consciousness. We believe that proposed version of DCL will find many
applications both in physics (quantum logic) and also in cognitive sciences
(mental imagery) for better understanding of the pecular nature of mental brain
operations.


  In this paper the quantum direct scattering problem is solved for the
Sine-Gordon model. Correlators of the Jost functions are derived by the angular
quantization method.


  The Lieb-Schultz-Mattis theorem and its higher dimensional generalizations by
Oshikawa and Hastings require that translationally invariant 2D spin systems
with a half-integer spin per unit cell must either have a continuum of low
energy excitations, spontaneously break some symmetries, or exhibit topological
order with anyonic excitations. We establish a connection between these
constraints and a remarkably similar set of constraints at the surface of a 3D
interacting topological insulator. This, combined with recent work on
symmetry-enriched topological phases (SETs) with on-site unitary symmetries,
enables us to develop a framework for understanding the structure of SETs with
both translational and on-site unitary symmetries, including the effective
theory of symmetry defects. This framework places stringent constraints on the
possible types of symmetry fractionalization that can occur in 2D systems whose
unit cell contains fractional spin, fractional charge, or a projective
representation of the symmetry group. As a concrete application, we determine
when a topological phase must possess a "spinon" excitation, even in cases when
spin rotational invariance is broken down to a discrete subgroup by the crystal
structure. We also describe the phenomena of "anyonic spin-orbit coupling",
which may arise from the interplay of translational and on-site symmetries.
These include the possibility of on-site symmetry defect branch lines carrying
topological charge per unit length and lattice dislocations inducing on-site
symmetry protected degeneracies.


  For the first time, we have identified NeVIII absorption lines in far-UV
spectra of the hottest known (Teff>150,000 K) hydrogen-deficient (pre-) white
dwarfs of spectral type PG1159. They are of photospheric origin and can be
matched by synthetic non-LTE line profiles. We also show that a number of UV
and optical emission lines in these stars can be explained as being
photospheric NeVIII features and not, as hitherto suspected, as ultrahigh
ionised OVIII lines created along shock-zones in the stellar wind.
Consequently, we argue that the long-standing identification of the same
emission lines in hot [WR]-type central stars as being due to ultrahigh-ionised
species (OVII-VIII, CV-VI) must be revised. These lines can be entirely
attributed to thermally excited species (NeVII-VIII, NV, OVI). Photospheric
NeVIII lines are also identified in the hottest known He-rich white dwarf
KPD0005+5106 some of which were also attributed to OVIII previously. This is a
surprise because it must be concluded that KPD0005+5106 is much hotter
(Teff=200,000 K) than hitherto assumed (Teff=120,000 K). This is confirmed by a
re-assessment of the HeII line spectrum. We speculate that the temperature is
high enough to explain the mysterious, hard X-ray emission (1 keV) as being of
photospheric origin.


  The almost simultaneous detection of gravitational waves and a short
gamma-ray burst from a neutron star merger has put a tight constraint on the
difference between the speed of gravity and light. In the four-dimensional
scalar-tensor theory with second order equations of motion, the Horndeski
theory, this translates into a significant reduction of the viable parameter
space of the theory. Recently, extensions of Horndeski theory, which are free
from Ostrogradsky ghosts despite the presence of higher order derivatives in
the equations of motion, have been identified and classified exploiting the
degeneracy criterium. In these new theories, the fifth force mediated by the
scalar field must be suppressed in order to evade the stringent Solar System
constraints. We study the Vainshtein mechanism in the most general degenerate
higher order scalar-tensor theory in which light and gravity propagate at the
same speed. We find that the Vainshtein mechanism generally works outside a
matter source but it is broken inside matter, similarly to beyond Horndeski
theories. This leaves interesting possibilities to test these theories that are
compatible with gravitational wave observations using astrophysical objects.


  The most concentrated application of lower-limb rehabilitation exoskeleton
(LLE) robot is that it can help paraplegics "re-walk". However, "walking" in
daily life is more than just walking on flat ground with fixed gait. This paper
focuses on variable gaits generation for LLE robot to adapt complex walking
environment. Different from traditional gaits generator for biped robot, the
generated gaits for LLEs should be comfortable to patients. Inspired by the
pose graph optimization algorithm in SLAM, we propose a graph-based gait
generation algorithm called gait graph optimization (GGO) to generate variable,
functional and comfortable gaits from one base gait collected from healthy
individuals to adapt the walking environment. Variants of walking problem,
e.g., stride adjustment, obstacle avoidance, and stair ascent and descent, help
verify the proposed approach in simulation and experimentation. We open source
our implementation.


  As an emerging technology and evolution that goes beyond massive multi-input
multi-output (MIMO), large intelligent surface (LIS) has gained much interest
recently. LIS acts as an electromagnetic surface and can transmit, redirect,
and receive radiating signals across its entire contiguous surface. It allows
for unprecedented energy-focusing, data-transmission and terminal-positioning,
and can fulfill the most grand visions for future communication systems.
Earlier proposed LISs are in two-dimensional (2D), i.e., planar shapes. In this
paper, we extend LIS to be three-dimensional (3D) and deployed as spherical
surfaces. Compared to 2D shapes, spherical LISs have advantages of wide
coverage, simple positioning techniques, and flexible deployments as
reflectors.


  This note tackles the problem of the rotation of Io with the 4-degrees of
freedom Poincar\'e-Hough model. Io is modeled as a 2-layer body, i.e. a
triaxial fluid core and a rigid outer layer. We show that the longitudinal
librations should have an amplitude of about 30 arcseconds, independent of the
composition of the core. We also estimate the tidal instability of the core,
and show that should be slowly unstable.


  The last unknown neutrino mixing angle $\theta_{13}$ is one of the
fundamental parameters of nature; it is also a crucial parameter for
determining the sensitivity of future long-baseline experiments aimed to study
CP violation in the neutrino sector. Daya Bay is a reactor neutrino oscillation
experiment designed to achieve a sensitivity on the value of
$sin^2(2\theta_{13})$ to better than 0.01 at 90% CL. The experiment consists of
multiple identical detectors placed underground at different baselines to
minimize systematic errors and suppress cosmogenic backgrounds. With the
baseline design, the expected anti-neutrino signal at the far site is about 360
events per day and at each of the near sites is about 1500 events per day. An
overview and current status of the experiment will be presented.


  We study a combinatorial market design problem, where a collection of
indivisible objects is to be priced and sold to potential buyers subject to
equilibrium constraints.The classic solution concept for such problems is
Walrasian Equilibrium (WE), which provides a simple and transparent pricing
structure that achieves optimal social welfare. The main weakness of the WE
notion is that it exists only in very restrictive cases. To overcome this
limitation, we introduce the notion of a Combinatorial Walrasian equilibium
(CWE), a natural relaxation of WE. The difference between a CWE and a
(non-combinatorial) WE is that the seller can package the items into
indivisible bundles prior to sale, and the market does not necessarily clear.
  We show that every valuation profile admits a CWE that obtains at least half
of the optimal (unconstrained) social welfare. Moreover, we devise a poly-time
algorithm that, given an arbitrary allocation X, computes a CWE that achieves
at least half of the welfare of X. Thus, the economic problem of finding a CWE
with high social welfare reduces to the algorithmic problem of social-welfare
approximation. In addition, we show that every valuation profile admits a CWE
that extracts a logarithmic fraction of the optimal welfare as revenue.
Finally, these results are complemented by strong lower bounds when the seller
is restricted to using item prices only, which motivates the use of bundles.
The strength of our results derives partly from their generality - our results
hold for arbitrary valuations that may exhibit complex combinations of
substitutes and complements.