  Ever since the Barab\'{a}si-Albert (BA) scale-free network has been proposed,
network modeling has been studied intensively in light of the network growth
and the preferential attachment (PA). However, numerous real systems are
featured with a dynamic evolution including network reduction in addition to
network growth. In this paper, we propose a novel mechanism for evolving
networks from the perspective of vertex degree. We construct a queueing system
to describe the increase and decrease of vertex degree, which drives the
network evolution. In our mechanism, the degree increase rate is regarded as a
function positively correlated to the degree of a vertex, ensuring the
preferential attachment in a new way. Degree distributions are investigated
under two expressions of the degree increase rate, one of which manifests a
``long tail'', and another one varies with different values of parameters. In
simulations, we compare our theoretical distributions with simulation results
and also apply them to real networks, which presents the validity and
applicability of our model.


  The electronic structure and magnetic properties of the graphene/Fe/Ni(111)
system were investigated via combination of the density functional theory
calculations and electron-spectroscopy methods. This system was prepared via
intercalation of thin Fe layer (1 ML) underneath graphene on Ni(111) and its
inert properties were verified by means of photoelectron spectroscopy.
Intercalation of iron in the space between graphene and Ni(111) changes
drastically the magnetic response from the graphene layer that is explained by
the formation of the highly spin-polarized $3d_{z^2}$ quantum-well state in the
thin iron layer.


  We test the relationship between UV-derived star formation rates (SFRs) and
the 7.7 ${\mu}$m polycyclic aromatic hydrocarbon (PAH) luminosities from the
integrated emission of galaxies at z ~ 0 - 2. We utilize multi-band photometry
covering 0.2 - 160 ${\mu}$m from HST, CFHT, JWST, Spitzer, and Herschel for
galaxies in the Cosmic Evolution Early Release Science (CEERS) Survey. We
perform spectral energy distribution (SED) modeling of these data to measure
dust-corrected far-UV (FUV) luminosities, $L_{FUV}$, and UV-derived SFRs. We
then fit SED models to the JWST/MIRI 7.7 - 21 ${\mu}$m CEERS data to derive
rest-frame 7.7 ${\mu}$m luminosities, $L_{770}$, using the average flux density
in the rest-frame MIRI F770W bandpass. We observe a correlation between
$L_{770}$ and $L_{FUV}$, where log $L_{770}$ is proportional to (1.27+/-0.04)
log $L_{FUV}$. $L_{770}$ diverges from this relation for galaxies at lower
metallicities, lower dust obscuration, and for galaxies dominated by evolved
stellar populations. We derive a "single-wavelength" SFR calibration for
$L_{770}$ which has a scatter from model estimated SFRs
(${{\sigma}_{{\Delta}SFR}}$) of 0.24 dex. We derive a "multi-wavelength"
calibration for the linear combination of the observed FUV luminosity
(uncorrected for dust) and the rest-frame 7.7 ${\mu}$m luminosity, which has a
scatter of ${{\sigma}_{{\Delta}SFR}}$ = 0.21 dex. The relatively small decrease
in ${\sigma}$ suggests this is near the systematic accuracy of the total SFRs
using either calibration. These results demonstrate that the rest-frame 7.7
${\mu}$m emission constrained by JWST/MIRI is a tracer of the SFR for distant
galaxies to this accuracy, provided the galaxies are dominated by
star-formation with moderate-to-high levels of attenuation and metallicity.


  The Mu3e experiment aims to find or exclude the lepton flavour violating
decay $\mu \rightarrow eee$ at branching fractions above $10^{-16}$. A first
phase of the experiment using an existing beamline at the Paul Scherrer
Institute (PSI) is designed to reach a single event sensitivity of $2\cdot
10^{-15}$. We present an overview of all aspects of the technical design and
expected performance of the phase~I Mu3e detector. The high rate of up to
$10^{8}$ muon decays per second and the low momenta of the decay electrons and
positrons pose a unique set of challenges, which we tackle using an ultra thin
tracking detector based on high-voltage monolithic active pixel sensors
combined with scintillating fibres and tiles for precise timing measurements.


  To facilitate the understanding and to quantitatively assess the material
transport in fluids, a modern characterisation method has emerged in fluid
dynamics in the last decades footed in dynamical systems theory. It allows to
examine the most influential material lines which are called Lagrangian
Coherent Structures (LCS) and order the material transport into dynamically
distinct regions at large scales which resist diffusion or mixing. LCS reveal
the robust skeleton of material surfaces and are essential to assess material
transport in time-dependent flows quantitatively. Candidates of LCS can be
estimated and visualised from finite-time stretching and folding fields by
calculating the Finite-Time Lyapunov Exponents (FTLE).
  In this contribution, we provide an OpenFOAM function object to compute FTLE
during CFD simulation. This enables the OpenFOAM community to assess the
geometry of the material transport in any flow quantitatively on-the-fly using
principally any OpenFOAM flow solver.


  Chow, Li and Yi in [2] proved that the majority of the unperturbed tori {\it
on sub-manifolds} will persist for standard Hamiltonian systems. Motivated by
their work, in this paper, we study the persistence and tangent frequencies
preservation of lower dimensional invariant tori on smooth sub-manifolds for
real analytic, nearly integrable Hamiltonian systems. The surviving tori might
be elliptic, hyperbolic, or of mixed type.


  The filamentation instability occurring when a non relativistic electron beam
passes through a quantum magnetized plasma is investigated by means of a cold
quantum magnetohydrodynamic model. It is proved that the instability can be
completely suppressed by quantum effects if and only if a finite magnetic field
is present. A dimensionless parameter is identified which measures the strength
of quantum effects. Strong quantum effects allow for a much smaller magnetic
field to suppress the instability than in the classical regime.


  Analogue models of gravity have provided an experimentally realizable test
field for our ideas on quantum field theory in curved spacetimes but they have
also inspired the investigation of possible departures from exact Lorentz
invariance at microscopic scales. In this role they have joined, and sometime
anticipated, several quantum gravity models characterized by Lorentz breaking
phenomenology. A crucial difference between these speculations and other ones
associated to quantum gravity scenarios, is the possibility to carry out
observational and experimental tests which have nowadays led to a broad range
of constraints on departures from Lorentz invariance. We shall review here the
effective field theory approach to Lorentz breaking in the matter sector,
present the constraints provided by the available observations and finally
discuss the implications of the persisting uncertainty on the composition of
the ultra high energy cosmic rays for the constraints on the higher order,
analogue gravity inspired, Lorentz violations.


  We present the result of a near-infrared (J H Ks) survey along the Galactic
plane, -10.5deg < l < +10.5deg and b=+1.0deg, with the IRSF 1.4m telescope and
the SIRIUS camera. Ks vs. H-Ks color-magnitude diagrams reveal a well-defined
population of red clump (RC) stars whose apparent magnitude peak changes
continuously along the Galactic plane, from Ks=13.4 at l=-10deg to Ks=12.2 at
l=+10deg after dereddening. This variation can be explained by the bar-like
structure found in previous studies, but we find an additional inner structure
at |l| < 4deg, where the longitude - apparent magnitude relation is distinct
from the outer bar, and the apparent magnitude peak changes by only 0.1 mag
over the central 8deg. The exact nature of this inner structure is as yet
uncertain.


  We use lateral spin valves with varying interface resistance to measure
non-local Hanle effect in order to extract the spin-diffusion length of the
non-magnetic channel. A general expression that describes spin injection and
transport, taking into account the influence of the interface resistance, is
used to fit our results. Whereas the fitted spin-diffusion length value is in
agreement with the one obtained from standard non-local measurements in the
case of a finite interface resistance, in the case of transparent contacts a
clear disagreement is observed. The use of a corrected expression, recently
proposed to account for the anisotropy of the spin absorption at the
ferromagnetic electrodes, still yields a deviation of the fitted spin-diffusion
length which increases for shorter channel distances. This deviation shows how
sensitive the non-local Hanle fittings are, evidencing the complexity of
obtaining spin transport information from such type of measurements.


  We discuss the present state and planned updates of CosmoLattice, a
cutting-edge code for lattice simulations of non-linear dynamics of
scalar-gauge field theories in an expanding background. We first review current
capabilities of the code, including the simulation of interacting singlet
scalars and of Abelian and non-Abelian scalar-gauge theories. We also comment
on new features recently implemented, such as the simulation of gravitational
waves from scalar and gauge fields. Secondly, we discuss new extensions of
CosmoLattice that we plan to release publicly. On the one hand, we comment on
new physics modules, which include axion-gauge interactions $\phi F
\widetilde{F}$, non-minimal gravitational couplings $\phi^2 R$, creation and
evolution of cosmic defect networks, and magneto-hydro-dynamics (MHD). On the
other hand, we discuss new technical features, including evolvers for
non-canonical interactions, arbitrary initial conditions, simulations in 2+1
dimensions, and higher accuracy spatial derivatives.


  The increasingly sophisticated and growing number of threat actors along with
the sheer speed at which cyber attacks unfold, make timely identification of
attacks imperative to an organisations' security. Consequently, persons
responsible for security employ a large variety of information sources
concerning emerging attacks, attackers' course of actions or indicators of
compromise. However, a vast amount of the needed security information is
available in unstructured textual form, which complicates the automated and
timely extraction of attackers' Tactics, Techniques and Procedures (TTPs). In
order to address this problem we systematically evaluate and compare different
Natural Language Processing (NLP) and machine learning techniques used for
security information extraction in research. Based on our investigations we
propose a data processing pipeline that automatically classifies unstructured
text according to attackers' tactics and techniques derived from a knowledge
base of adversary tactics, techniques and procedures.


  We calculate the local correlation functions of charge and spin for the
one-chain and two-chain Hubbard model using the density matrix renormalization
group method and the recursion technique. Keeping only finite number of states
we get good accuracy for the low energy excitations. We study the charge and
spin gaps, bandwidths and weights of the spectra for various values of the
on-site Coulomb interaction U and the electron filling. In the low energy part,
the local correlation functions are different for the charge and spin. The
bandwidths are proportional to t for the charge and J for the spin,
respectively.


  We report a determination of the complex in-plane dielectric function of
monolayers of four transition metal dichalcogenides: MoS2, MoSe2, WS2 and WSe2,
for photon energies from 1.5 - 3 eV. The results were obtained from reflection
spectra using a Kramers-Kronig constrained variational analysis. From the
dielectric functions, we obtain the absolute absorbance of the monolayers. We
also provide a comparison of the dielectric function for the monolayers with
the corresponding bulk materials.


  Shahriar S. Afshar claimed that his 2007 modified version of the double-slit
experiment violates complementarity [1]. He makes two modifications to the
standard double-slit experiment. First, he adds a wire grid that is placed in
between the slits and the screen at locations of interference minima. The
second modification is to place a converging lens just after the wire grid. The
idea is that the wire grid implies the existence of interference
minima(wave-like behavior), while the lens can simultaneously obtain which-way
information (particle-like behavior). More recently, John G. Cramer [2] argued
that the experiment bolstered the Transactional Interpretation of Quantum
mechanics (TIQM). His argument scrutinizes Bohr's complementarity in favor of
TIQM. We analyze this experiment by simulation using the path integral
formulation of quantum mechanics [3] and find that it agrees with the wave
particle duality relation given by Englert, Greenberg and Yasin (E-G-Y) [4, 5].
We conclude that the use of Afshar's experiment to provide a testbed for
quantum mechanical interpretations is limited.


  We prove that the coinvariant ring of the irreducible Coxeter group of type
H4 has the strong Lefschetz property.


  This paper addresses the challenge of geometric quality assurance in
manufacturing, particularly when human assessment is required. It proposes
using Blender, an open-source simulation tool, to create synthetic datasets for
machine learning (ML) models. The process involves translating expert
information into shape key parameters to simulate deformations, generating
images for both deformed and non-deformed objects. The study explores the
impact of discrepancies between real and simulated environments on ML model
performance and investigates the effect of different simulation backgrounds on
model sensitivity. Additionally, the study aims to enhance the model's
robustness to camera positioning by generating datasets with a variety of
randomized viewpoints. The entire process, from data synthesis to model
training and testing, is implemented using a Python API interfacing with
Blender. An experiment with a soda can object validates the accuracy of the
proposed pipeline.


  This paper presents some of the main aspects of the software library that has
been developed for the reduction of optical and infrared images, an integral
part of the end-to-end survey system being built to support public imaging
surveys at ESO. Some of the highlights of the new library are: unbiased
estimates of the background, critical for deep IR observations; efficient and
accurate astrometric solutions, using multi-resolution techniques; automatic
identification and masking of satellite tracks; weighted co-addition of images;
creation of optical/IR mosaics, and appropriate management of multi-chip
instruments. These various elements have been integrated into a system using
XML technology for setting input parameters, driving the various processes,
producing comprehensive history logs and storing the results, binding them to
the supporting database and to the web. The system has been extensively tested
using deep images as well as images of crowded fields (e.g. globular clusters,
LMC), processing at a rate of 0.5 Mega-pixels per second using a DS20E ALPHA
computer with two processors. The goal of this presentation is to review some
of the main features of this package.


  We study the relativistic Euler equations on the Minkowski spacetime
background. We make assumptions on the equation of state and the initial data
that are relativistic analogs of the well-known physical vacuum boundary
condition, which has played an important role in prior work on the
non-relativistic compressible Euler equations. Our main result is the
derivation, relative to Lagrangian (also known as co-moving) coordinates, of
local-in-time a priori estimates for the solution. The solution features a
fluid-vacuum boundary, transported by the fluid four-velocity, along which the
hyperbolicity of the equations degenerates. In this context, the relativistic
Euler equations are equivalent to a degenerate quasilinear hyperbolic
wave-map-like system that cannot be treated using standard energy methods.


  We present a new perspective on the symmetries that govern the formation of
large-scale structures across the Universe, particularly focusing on the
transition from the seeds of galaxy clusters to the seeds of galaxies
themselves. We address two main features of cosmological fluid dynamics
pertaining to both the linear and non-linear regimes. The linear dynamics of
cosmological perturbations within the Hubble horizon is characterized by the
Jeans length, which separates stable configurations from unstable fluctuations
due to the gravitational effect on sufficiently large (and therefore, massive
enough) overdensities. On the other hand, the non-linear dynamics of the
cosmological fluid is associated with a turbulent behavior once the Reynolds
numbers reach a sufficiently high level. This turbulent regime leads to energy
dissipation across smaller and smaller scales, resulting in a fractal
distribution of eddies throughout physical space. The proposed scenario
suggests that the spatial scale of eddy formation is associated with the Jeans
length of various levels of fragmentation from an original large-scale
structure. By focusing on the fragmentation of galaxy cluster seeds versus
galaxy seeds, we arrived at a phenomenological law that links the ratio of the
two structure densities to the number of galaxies in each cluster and to the
Hausdorff number of the Universe matter distribution. Finally, we introduced a
primordial magnetic field and studied its influence on the Jeans length
dynamics. The resulting anisotropic behavior of the density contrast led us to
infer that the main features of the turbulence could be reduced to a 2D Euler
equation. Numerical simulations showed that the two lowest wavenumbers
contained the major energy contribution of the spectrum.


  If agents cooperate only within small groups of some bounded sizes, is there
a way to partition the population into small groups such that no collection of
agents can do better by forming a new group? This paper revisited f-core in a
transferable utility setting. By providing a new formulation to the problem, we
built up a link between f-core and the transportation theory. Such a link helps
us to establish an exact existence result, and a characterization result of
f-core for a general class of agents, as well as some improvements in computing
the f-core in the finite type case.


  We numerically investigate the aging dynamics of a monatomic Lennard-Jones
glass, focusing on the topology of the potential energy landscape which, to
this aim, has been partitioned in basins of attraction of stationary points
(saddles and minima). The analysis of the stationary points visited during the
aging dynamics shows the existence of two distinct regimes: i) at short times,
t<t_c, the system visits basins of saddles whose energies and orders decrease
with t; ii) at long times, t>t_c, the system mainly lies in basins pertaining
to minima of slowly decreasing energy. The dynamics for t>t_c can be
represented by a simple random walk on a network of minima with a jump
probability proportional to the inverse of the waiting time.


  The Large Hadron Collider has a potential to probe the scale of left-right
symmetry restoration and the associated lepton number violation. Moreover, it
offers hope of measuring the right-handed leptonic mixing matrix. We show how
this, together with constraints from lepton flavor violating processes, can be
used to make predictions for neutrinoless double beta decay. We illustrate this
deep connection in the case of the type-II seesaw.


  It is well known that Gamma-ray Burst spectra often display a break at
energies $\simless 400$ keV, with some exceptions extending to several MeV.\ \
Modeling of a cosmological source population is thus non-trivial when comparing
the catalogs from instruments with different energy windows since this spectral
structure is redshifted across the trigger channels at varying levels of
sensitivity. We here include this important effect in an attempt to reconcile
all the available data sets and show that a model in which bursts have a
``standard'' spectral break at $300$ keV and occur in a population uniformly
distributed in a \qo $=1/2$ universe with no evolution can account very well
for the combined set of observations. We show that the source population cannot
be truncated at a minimum redshift $z_{min}$ beyond $\sim 0.1$, and suggest
that a simple follow-on instrument to BATSE, with the same trigger window, no
directionality and 18 times better sensitivity might be able to distinguish
between a \qo$=0.1$ and a \qo$=0.5$ universe in $3$ years of full sky coverage,
provided the source population has no luminosity evolution.


  Clifford circuits play an important role in quantum computation. Gottesman
and Chuang proposed a gate teleportation protocol so that a quantum circuit can
be implemented by the teleportation circuit with specific ancillary qubits. In
particular, an $n$-qubit Clifford circuit $U$ can be implemented by preparing
an ancillary stabilizer state $(I\otimes U)|\Phi^+\rangle^{\otimes n}$ for
teleportation and doing a Pauli correction conditioned on the measurement. In
this paper, we provide an alternative procedure to implement a Clifford circuit
through Pauli measurements, by preparing $O(1)$ ancillas that are
Calderbank-Shor-Steane (CSS) stabilizer states. That is to say, $O(1)$ CSS
states are sufficient to implement any Clifford circuit. As an application to
fault-tolerant quantum computation, any Clifford circuit can be implemented by
$O(1)$ steps of Steane syndrome extraction if clean CSS stabilizer states are
available.


  Many techniques for measuring neutron star radii rely on absolute flux
measurements in the X-rays. As a result, one of the fundamental uncertainties
in these spectroscopic measurements arises from the absolute flux calibrations
of the detectors being used. Using the stable X-ray burster, GS 1826-238, and
its simultaneous observations by Chandra HETG/ACIS-S and RXTE/PCA as well as by
XMM-Newton EPIC-pn and RXTE/PCA, we quantify the degree of uncertainty in the
flux calibration by assessing the differences between the measured fluxes
during bursts. We find that the RXTE/PCA and the Chandra gratings measurements
agree with each other within their formal uncertainties, increasing our
confidence in these flux measurements. In contrast, XMM-Newton EPIC-pn measures
14.0$\pm$0.3 % less flux than the RXTE/PCA. This is consistent with the
previously reported discrepancy with the flux measurements of EPIC-pn, compared
to EPIC-MOS1, MOS2 and ACIS-S detectors. We also show that any intrinsic time
dependent systematic uncertainty that may exist in the calibration of the
satellites has already been implicity taken into account in the neutron star
radius measurements.


  We consider the problem of variable selection in high-dimensional sparse
additive models. We focus on the case that the components belong to
nonparametric classes of functions. The proposed method is motivated by
geometric considerations in Hilbert spaces and consists of comparing the norms
of the projections of the data onto various additive subspaces. Under minimal
geometric assumptions, we prove concentration inequalities which lead to new
conditions under which consistent variable selection is possible. As an
application, we establish conditions under which a single component can be
estimated with the rate of convergence corresponding to the situation in which
the other components are known.


  This paper deals with the analysis of a recent reformulation of the
primal-dual hybrid gradient method [Zhu and Chan 2008, Pock, Cremers, Bischof
and Chambolle 2009, Esser, Zhang and Chan 2010, Chambolle and Pock 2011], which
allows to apply it to nonconvex regularizers as first proposed for truncated
quadratic penalization in [Strekalovskiy and Cremers 2014]. Particularly, it
investigates variational problems for which the energy to be minimized can be
written as $G(u) + F(Ku)$, where $G$ is convex, $F$ semiconvex, and $K$ is a
linear operator. We study the method and prove convergence in the case where
the nonconvexity of $F$ is compensated by the strong convexity of the $G$. The
convergence proof yields an interesting requirement for the choice of algorithm
parameters, which we show to not only be sufficient, but necessary.
Additionally, we show boundedness of the iterates under much weaker conditions.
Finally, we demonstrate effectiveness and convergence of the algorithm beyond
the theoretical guarantees in several numerical experiments.


  By integrating external knowledge, Retrieval-Augmented Generation (RAG) has
become an effective strategy for mitigating the hallucination problems that
large language models (LLMs) encounter when dealing with knowledge-intensive
tasks. However, in the process of integrating external non-parametric
supporting evidence with internal parametric knowledge, inevitable knowledge
conflicts may arise, leading to confusion in the model's responses. To enhance
the knowledge selection of LLMs in various contexts, some research has focused
on refining their behavior patterns through instruction-tuning. Nonetheless,
due to the absence of explicit negative signals and comparative objectives,
models fine-tuned in this manner may still exhibit undesirable behaviors in the
intricate and realistic retrieval scenarios. To this end, we propose a
Knowledge-aware Preference Optimization, dubbed KaPO, aimed at achieving
controllable knowledge selection in real retrieval scenarios. Concretely, we
explore and simulate error types across diverse context combinations and learn
how to avoid these negative signals through preference optimization methods.
Simultaneously, by adjusting the balance between response length and the
proportion of preference data representing different behavior patterns, we
enhance the adherence capabilities and noise robustness of LLMs in a balanced
manner. Experimental results show that KaPO outperforms previous methods for
handling knowledge conflicts by over 37%, while also exhibiting robust
generalization across various out-of-distribution datasets.


  Allowing the energy of a gravitational field to serve partially as its own
source allows gravitating bodies to exhibit stronger fields, as if they were
more massive. Depending on degree of compaction of the body, the field could be
one to five times larger than the newtonian field. This is a comfortable range
of increase in field strength and may prove to be of convenience in the study
of velocity curves of spirals, of velocity dispersions in clusters of galaxies
and in interpreting the Tully-Fisher or Faber-Jackson relations in galaxies or
systems of galaxies. The revised gravitation admits of superposition principle
but only approximately in systems whose components are widely separated. The
revised dynamics admits of the equivalence principle in that, the effective
force acting on a test particle is derived from a potential, and could be
eliminated in a freely falling frame of reference


  Quantum Moves is a citizen science game that investigates the ability of
humans to solve complex physics challenges that are intractable for computers.
During the launch of Quantum Moves in April 2016 the game's leaderboard
function broke down resulting in a "no leaderboard" game experience for some
players for a couple of days (though their scores were still displayed). The
subsequent quick fix of an all-time Top 5 leaderboard, and the following
long-term implementation of a personalized relative-position (infinite)
leaderboard provided us with a unique opportunity to compare and investigate
the effect of different leaderboard implementations on player performance in a
points-driven citizen science game.
  All three conditions were live sequentially during the game's initial influx
of more than 150.000 players that stemmed from global press attention on
Quantum Moves due the publication of a Nature paper about the use of Quantum
Moves in solving a specific quantum physics problem. Thus, it has been possible
to compare the three conditions and their influence on the performance (defined
as a player's quality of game play related to a high-score) of over 4500 new
players. These 4500 odd players in our three leaderboard-conditions have a
similar demographic background based upon the time-window over which the
implementations occurred and controlled against Player ID tags. Our results
placed Condition 1 experience over condition 3 and in some cases even over
condition 2 which goes against the general assumption that leaderboards enhance
gameplay and its subsequent overuse as a an oft-relied upon element that
designers slap onto a game to enhance said appeal. Our study thus questions the
use of leaderboards as general performance enhancers in gamification contexts
and brings some empirical rigor to an often under-reported but overused
phenomenon.


  Automated understanding of user interfaces (UIs) from their pixels can
improve accessibility, enable task automation, and facilitate interface design
without relying on developers to comprehensively provide metadata. A first step
is to infer what UI elements exist on a screen, but current approaches are
limited in how they infer how those elements are semantically grouped into
structured interface definitions. In this paper, we motivate the problem of
screen parsing, the task of predicting UI elements and their relationships from
a screenshot. We describe our implementation of screen parsing and provide an
effective training procedure that optimizes its performance. In an evaluation
comparing the accuracy of the generated output, we find that our implementation
significantly outperforms current systems (up to 23%). Finally, we show three
example applications that are facilitated by screen parsing: (i) UI similarity
search, (ii) accessibility enhancement, and (iii) code generation from UI
screenshots.


  Identifying what broken symmetries are present in the cuprates has become a
major area of research. Many authors have reported evidence for so-called "$Q
\sim 0$" order that involves broken inversion, mirror, chiral, or time-reversal
symmetry that is uniform in space. Not all these observations are well
understood and new experimental probes are needed. Here we use resonant soft
x-ray scattering (RSXS) to search for $Q \sim 0$ order in
Bi$_{2.1}$Sr$_{1.9}$CaCu$_2$O$_{8+x}$ (Bi-2212) by measuring the region of a
forbidden Bragg peak, $(0,0,3)$, which is normally extinguished by symmetry but
may become allowed on resonance if valence band order is present. Using
circularly polarized light, we found that this reflection becomes allowed on
the Cu $L_3$ resonance for temperatures $T_c < T < T^\ast$, though remains
absent in linear polarization and at other temperatures. This observation
suggests the existence of spatially uniform valence band order near the
pseudogap temperature. In addition, we observed periodic oscillations in the
specular reflectivity from the sample surface that resemble thin film
interference fringes, though no known film is present. These fringes are highly
resonant, appear in all polarizations, and exhibit a period that depends on the
location where the beam strikes the sample surface. We speculate that these
fringes arise from interaction between some intrinsic valence band instability
and extrinsic structural surface morphologies of the material. Our study
supports the existence of some kind of $Q \sim 0$ broken symmetry state in
Bi-2212 at intermediate temperatures, and calls for further study using a
microfocused beam that could disentangle microscopic effects from macroscopic
heterogeneities.


  A photonic approach for radio-frequency (RF) self-interference cancellation
(SIC) incorporated in an in-band full-duplex radio-over-fiber system is
proposed. A dual-polarization binary phase-shift keying modulator is used for
dual-polarization multiplexing at the central office (CO). A local oscillator
signal and an intermediate-frequency signal carrying the downlink data are
single-sideband modulated on the two polarization directions of the modulator,
respectively. The optical signal is then transmitted to the remote unit, where
the optical signals in the two polarization directions are split into two
parts. One part is detected to generate the up-converted downlink RF signal,
and the other part is re-modulated by the uplink RF signal and the
self-interference, which is then transmitted back to the CO for the signal
down-conversion and SIC via the optical domain signal adjustment and balanced
detection. The functions of SIC, frequency up-conversion, down-conversion, and
fiber transmission with dispersion immunity are all incorporated in the system.
An experiment is performed. Cancellation depths of more than 39 dB for the
single-tone signal and more than 20 dB for the 20-MBaud 16 quadrature amplitude
modulation signal are achieved in the back-to-back case. The performance of the
system does not have a significant decline when a section of 4.1-km optical
fiber is incorporated.


  Users often struggle to program visualizations using complex toolkits like
D3. Before we can design effective code assistants to support them, we must
first understand how D3 users reason about their code. In this work, we explore
users' understanding of D3 using an important gauge of code comprehension in CS
education: code decomposition. We qualitatively analyze 560 D3 programs
published on Observable and identify three distinct strategies to decomposing
D3 programs: segmenting code into layers of functionality, keeping everything
all in one cell, or creating reusable visualization functions. We also observe
how users inherit decomposition methods from copied examples and reorganize
copied code to suit their needs. We corroborate our findings for decomposition
preferences through interviews with D3 and Observable users. Based on our
findings, we suggest strategies for generating more intuitive D3 code
recommendations using decomposition preferences and highlight new research
opportunities for visualization code assistants. All supplemental materials are
available at https://osf.io/sudb8/?view_only=302fc5c8d397412aac35c6e094ae7dd6.


  In this paper, we introduce a novel Distributed Markov Chain Monte Carlo
(MCMC) inference method for the Bayesian Non-Parametric Latent Block Model
(DisNPLBM), employing the Master/Worker architecture. Our non-parametric
co-clustering algorithm divides observations and features into partitions using
latent multivariate Gaussian block distributions. The workload on rows is
evenly distributed among workers, who exclusively communicate with the master
and not among themselves. DisNPLBM demonstrates its impact on cluster labeling
accuracy and execution times through experimental results. Moreover, we present
a real-use case applying our approach to co-cluster gene expression data. The
code source is publicly available at
https://github.com/redakhoufache/Distributed-NPLBM.


  In the past few years, contrastive learning has played a central role for the
success of visual unsupervised representation learning. Around the same time,
high-performance non-contrastive learning methods have been developed as well.
While most of the works utilize only two views, we carefully review the
existing multi-view methods and propose a general multi-view strategy that can
improve learning speed and performance of any contrastive or non-contrastive
method. We first analyze CMC's full-graph paradigm and empirically show that
the learning speed of $K$-views can be increased by $_{K}\mathrm{C}_{2}$ times
for small learning rate and early training. Then, we upgrade CMC's full-graph
by mixing views created by a crop-only augmentation, adopting small-size views
as in SwAV multi-crop, and modifying the negative sampling. The resulting
multi-view strategy is called ECPP (Efficient Combinatorial Positive Pairing).
We investigate the effectiveness of ECPP by applying it to SimCLR and assessing
the linear evaluation performance for CIFAR-10 and ImageNet-100. For each
benchmark, we achieve a state-of-the-art performance. In case of ImageNet-100,
ECPP boosted SimCLR outperforms supervised learning.


  SAP is the market leader in enterprise software offering an end-to-end suite
of applications and services to enable their customers worldwide to operate
their business. Especially, retail customers of SAP deal with millions of sales
transactions for their day-to-day business. Transactions are created during
retail sales at the point of sale (POS) terminals and then sent to some central
servers for validations and other business operations. A considerable
proportion of the retail transactions may have inconsistencies due to many
technical and human errors. SAP provides an automated process for error
detection but still requires a manual process by dedicated employees using
workbench software for correction. However, manual corrections of these errors
are time-consuming, labor-intensive, and may lead to further errors due to
incorrect modifications. This is not only a performance overhead on the
customers' business workflow but it also incurs high operational costs. Thus,
automated detection and correction of transaction errors are very important
regarding their potential business values and the improvement in the business
workflow. In this paper, we present an industrial case study where we apply
machine learning (ML) to automatically detect transaction errors and propose
corrections. We identify and discuss the challenges that we faced during this
collaborative research and development project, from three distinct
perspectives: Software Engineering, Machine Learning, and industry-academia
collaboration. We report on our experience and insights from the project with
guidelines for the identified challenges. We believe that our findings and
recommendations can help researchers and practitioners embarking into similar
endeavors.


  A randomly chosen star in today's Universe is most likely to live in a galaxy
with a stellar mass between that of the Milky Way and Andromeda. Yet it remains
uncertain how the structural evolution of these bulge-disk systems proceeded.
Most of the unobscured star formation we observe building Andromdeda
progenitors at 0.7<z<1.5 occurs in disks, but >90% of their star formation is
reprocessed by dust and remains unaccounted for. Here we map 500micron dust
continuum emission in an Andromeda progenitor at z=1.25 to probe where it is
growing through dust-obscured star formation. Combining resolved dust
measurements from the NOEMA interferometer with Hubble Space Telescope Halpha
maps and multicolor imaging (including new UV data from the HDUV survey), we
find a bulge growing by dust-obscured star formation: while the unobscured star
formation is centrally suppressed, the dust continuum is centrally
concentrated, filling in the ring-like structures evident in the Halpha and UV
emission. Reflecting this, the dust emission is more compact than the
optical/UV tracers of star formation with r_e(dust)=3.4kpc,
r_e(Halpha)/r_e(dust)=1.4, and r_e(UV)/r_e(dust)=1.8. Crucially, however, the
bulge and disk of this galaxy are building simultaneously; although the dust
emission is more compact than the rest-optical emission
(r_e(optical)/r_e(dust)=1.4), it is somewhat less compact than the stellar mass
(r_e(M_*)/r_e(dust)=0.9). Taking the 500micron emission as a tracer of star
formation, the expected structural evolution of this galaxy can be accounted
for by star formation: it will grow in size by Delta(r_e)/Delta(M_*)~0.3 and
central surface density by Delta(Sigma_cen)/Delta(M_*)~0.9. Finally, our
observations are consistent with a picture in which merging and disk
instabilities drive gas to the center of galaxies, boosting global star
formation rates above the main sequence and building bulges.


  We develop a nanoscale dynamical mean-field theory (nano-DMFT) to deal with
strong Coulomb interaction effects in physical systems that are intermediate in
size between atoms and bulk materials, taking into account the tunneling into
nearby electrodes. Focusing on a simplified treelike geometry, the usual DMFT
loop simply stops when the finite lattice is fully covered, starting with an
initial seed provided by the electronic environment at the boundary. To
illustrate this nano-DMFT, we investigate the disappearance of the
quasiparticle weight in a correlated nano object near the Mott transition. In
contrast to thermally driven classical phase transitions, quantum effects lead
to unexpected oscillations of the order parameter, related to the interference
of coherent renormalized quasiparticles. This behavior also implies a spatially
inhomogeneous Mott localization process at the nanoscale.


  Brain-mapping techniques have proven to be vital in understanding the
molecular, cellular, and functional mechanisms of the brain. Normal anatomical
imaging can provide structural information on certain abnormalities in the
brain. However there are many neurological disorders for which only structure
studies are not sufficient. In such cases it is required to investigate the
functional organization of the brain. Further it is necessary to study the
brain functions under normal as well as diseased conditions. Brain mapping
techniques can help in deriving useful and important information on these
issues. Brain functions and brain area responsible for the particular
activities like motor, sensory speech and memory process could be investigated.
The authors provide an overview of various Brain Mapping techniques and fMRI
signal processing methods.


  We show that by requiring positivity of the longitudinal pressure it is
possible to constrain the initial conditions one can use in 2nd-order viscous
hydrodynamical simulations of ultrarelativistic heavy-ion collisions. We
demonstrate this explicitly for 0+1 dimensional viscous hydrodynamics and
discuss how the constraint extends to higher dimensions. Additionally, we
present an analytic approximation to the solution of 0+1 dimensional 2nd-order
viscous hydrodynamical evolution equations appropriate to describe the
evolution of matter in an ultrarelativistic heavy-ion collision.


  Colored solar cells suffer from lower efficiency due to reflection and
absorption losses by coatings. By studying different types of coatings on solar
cells, the spectrum parameters impacting the solar cell efficiency were
identified. A collection of color coatings was fabricated and characterized
using spectrophotometry and colorimetric photography. The coatings include
commercial absorption filters, commercial distributed bragg reflectors,
lab-made interference coatings, and cellulose nanocrystal coatings. Commercial
single junction and multijunction solar cells were used to measure the impact
of the color coatings on solar cell performance. Structural colors were found
to result in the highest brightness to color loss ratio. Structural colors do
not fade provided that the structure is not compromised. Color loss in single
junction solar cells is a result of the proportion of reflected light in the
absorption range of the material. Multijunction solar cells were strongly
affected by current mismatch losses, where narrow reflection peaks resulted in
high efficiency losses. Structural color coatings made using cellulose
nanocrystals exhibited low and broad reflection peaks that produced bright
colors and maintained high performance of single junction and multijunction
solar cells, retaining up to 83 % of the reference power obtained in the
absence of a color coating.


  In this article we study fine regularity properties for mappings of finite
distortion. Our main theorems yield strongly localized regularity results in
the borderline case in the class of maps of exponentially integrable
distortion. Analogues of such results were known earlier in the case of
quasiconformal mappings. Moreover, we study regularity for maps whose
distortion has higher exponential integrability.


  Iwasawa theory of modular forms over anticyclotomic $\mathbb{Z}_p$-extensions
of imaginary quadratic fields has been studied by several authors, starting
from the works of Bertolini-Darmon and Iovita-Spiess, under the crucial
assumption that the prime $p$ is unramified in $K$. We start in this article
the systematic study of anticyclotomic $p$-adic $L$-functions when $p$ is
ramified in $K$. In particular, when $f$ is a weight $2$ modular form attached
to an elliptic curve $E/\mathbb{Q}$ having multiplicative reduction at $p$, and
$p$ is ramified in $K$, we show an analogue of the exceptional zeroes
phenomenon investigated by Bertolini-Darmon in the setting when $p$ is inert in
$K$. More precisely, we consider situations in which the $p$-adic $L$-function
$L_p(E/K)$ of $E$ over the anticyclotomic $\mathbb{Z}_p$-extension of $K$ does
not vanish identically but, by sign reasons, has a zero at certain characters
$\chi$ of the Hilbert class field of $K$. In this case we show that the value
at $\chi$ of the first derivative of $L_p(E/K)$ is equal to the formal group
logarithm of the specialization at $p$ of a global point on the elliptic curve
(actually, this global point is a twisted sum of Heegner points). This
generalizes similar results of Bertolini-Darmon, available when $p$ is inert in
$K$ and $\chi$ is the trivial character.


  Kontar et al. (2004) have shown how to recover mean source electron spectra
in solar flares through a physical constraint regularization analysis of the
bremsstrahlung photon spectra that they produce. They emphasize the use of
non-square inversion techniques, and preconditioning combined with physical
properties of the spectra to achieve the most meaningful solution to the
problem. Higher-order regularization techniques may be used to generate
${overline F}(E)$ forms with certain desirable properties (e.g., higher order
derivatives). They further note that such analyses may be used to infer
properties of the electron energy spectra at energies well above the maximum
photon energy observed. In this paper we apply these techniques to data from a
solar flare observed by RHESSI on 26 February, 2002. Results using different
orders of regularization are presented and compared for various time intervals.
Clear evidence is presented for a change in the value of the high-energy cutoff
in the mean source electron spectrum with time. We also show how the
construction of the injected (accelerated) electron spectrum $F_0(E_0)$
(assuming that Coulomb collisions in a cold target dominate the electron
energetics) is facilitated by the use of higher-order regularization methods.


  Motivated by a recent experiment in an antiferromagnetic spin-1 Bose-Einstein
condensate of ${}^{23} \textrm{Na}$ atoms, we study the energetical stability
of a singly quantum vortex injected into the center of a quasi-two-dimensional
gas with zero total spin against dissocation into a pair of half-quantum
vortices. We find that the critical dissociation point of this
confinement-deconfinement type phase transition can be expressed in terms of
the ratio of density-density ($c_0$) and spin-spin ($c_2$) coupling constants.
The transition of bound to unbound vortices, in particular, sensitively depends
on (1) the ratio of system size ($R$) to density healing length ($\xi_d$), and
(2) the trap potential. Specifically, the critical ratio $(c_2 /
c_0)_{\textrm{cr}}$ increases when $R / \xi_d$ decreases, and is relatively
larger in a harmonic trap than in a box trap. Dissociation is energetically
generally favored for $c_2 / c_0 < (c_2 / c_0)_{\textrm{cr}}$, which as a
corollary implies that vortex dissociation is observed as well for negative
$c_2 < 0$, e.g., in a rubidium spin-1 BEC, whereas in a sodium spin-1 BEC
($c_2>0$) it is energetically blocked above the critical ratio $(c_2 /
c_0)_{\textrm{cr}}$. Tuning the coupling ratio $c_2/c_0$ by using microwave
control techniques, the dependence of the deconfinement phase transition on
coupling parameters, density, and system size we predict, can be verified in
experiments with ultracold spinor gases.


  Electronic Fabry-P{\'e}rot interferometry is a powerful method to probe
quasiparticle charge and anyonic braiding statistics in the fractional quantum
Hall regime. We extend this technique to the hierarchy $\nu = 2/5$ fractional
quantum Hall state, possessing two edge modes that in our device can be
interfered independently. The outer edge mode exhibits interference similar to
the behavior observed at the $\nu = 1/3$ state, indicating that the outer edge
mode at $\nu = 2/5$ has properties similar to the single mode at $\nu = 1/3$.
The inner mode shows an oscillation pattern with a series of discrete phase
jumps indicative of distinct anyonic braiding statistics. After taking into
account the impact of bulk-edge coupling, we extract an interfering
quasiparticle charge ${e^*} = 0.17 \pm 0.02$ and anyonic braiding phase $\theta
_a = (-0.43 \pm 0.05)\times 2\pi$, which serve as experimental verification of
the theoretically predicted values of $e^* = \frac{1}{5}$ and $\theta _a =
-\frac{4\pi}{5}$.


  Functionalizing graphene was recently shown to have a dramatic effect on the
electronic properties of this material. Here we investigate spatial ordering of
adatoms driven by the RKKY-type interactions. In the ordered state, which
arises via a Peierls-instability-type mechanism, the adatoms reside mainly on
one of the two graphene sublattices. Bragg scattering of electron waves induced
by sublattice symmetry breaking results in a band gap opening, whereby Dirac
fermions acquire a finite mass. The band gap is found to be immune to the
adatoms' positional disorder, with only an exponentially small number of
localized states residing in the gap. The gapped state is stabilized in a wide
range of electron doping. Our findings show that controlled adsorption of
adatoms or molecules provides a route to engineering a tunable band gap in
graphene.


  Weakly supervised object detection (WSup-OD) increases the usefulness and
interpretability of image classification algorithms without requiring
additional supervision. The successes of multiple instance learning in this
task for natural images, however, do not translate well to medical images due
to the very different characteristics of their objects (i.e. pathologies). In
this work, we propose Weakly Supervised ROI Proposal Networks (WSRPN), a new
method for generating bounding box proposals on the fly using a specialized
region of interest-attention (ROI-attention) module. WSRPN integrates well with
classic backbone-head classification algorithms and is end-to-end trainable
with only image-label supervision. We experimentally demonstrate that our new
method outperforms existing methods in the challenging task of disease
localization in chest X-ray images. Code:
https://github.com/philip-mueller/wsrpn


  We consider toral extensions of hyperbolic dynamical systems. We prove that
its quantitative recurrence (also with respect to given observables) and
hitting time scale behavior depend on the arithmetical properties of the
extension. By this we show that those systems have a polynomial decay of
correlations with respect to $C^{r}$ observables, and give estimations for its
exponent, which depend on $r$ and on the arithmetical properties of the system.
We also show examples of systems of this kind having not the shrinking target
property, and having a trivial limit distribution of return time statistics.


  This paper proposes OCR++, an open-source framework designed for a variety of
information extraction tasks from scholarly articles including metadata (title,
author names, affiliation and e-mail), structure (section headings and body
text, table and figure headings, URLs and footnotes) and bibliography (citation
instances and references). We analyze a diverse set of scientific articles
written in English language to understand generic writing patterns and
formulate rules to develop this hybrid framework. Extensive evaluations show
that the proposed framework outperforms the existing state-of-the-art tools
with huge margin in structural information extraction along with improved
performance in metadata and bibliography extraction tasks, both in terms of
accuracy (around 50% improvement) and processing time (around 52% improvement).
A user experience study conducted with the help of 30 researchers reveals that
the researchers found this system to be very helpful. As an additional
objective, we discuss two novel use cases including automatically extracting
links to public datasets from the proceedings, which would further accelerate
the advancement in digital libraries. The result of the framework can be
exported as a whole into structured TEI-encoded documents. Our framework is
accessible online at http://cnergres.iitkgp.ac.in/OCR++/home/.


  We derive and solve kinetic equations for leptogenesis within the Closed Time
Path (CTP) formalism. It is particularly emphasised how the procedure of real
intermediate state subtraction familiar from the Boltzmann approach is realised
within the CTP framework; and we show how in time-independent situations, no
lepton asymmetry emerges, in accordance with the CPT-theorem. The CTP approach
provides new quantum statistical corrections from evaluating the loop
integrals. These lead to an enhancement of the asymmetry that is originating
from the Bose statistics of the Higgs particles. To quantify this effect, we
define and evaluate an effective CP-violating parameter. We also solve the
kinetic equations and show explicitly that the new quantum statistical
corrections can be neglected in the strong washout regime, while, depending on
initial conditions, they can be very sizable for weak washout.


  Though appropriate for core Internet infrastructure, the Internet Protocol is
unsuited to routing within and between emerging ad-hoc edge networks due to its
dependence on hierarchical, administratively assigned addresses. Existing
ad-hoc routing protocols address the management problem but do not scale to
Internet-wide networks. The promise of ubiquitous network computing cannot be
fulfilled until we develop an Unmanaged Internet Protocol (UIP), a scalable
routing protocol that manages itself automatically. UIP must route within and
between constantly changing edge networks potentially containing millions or
billions of nodes, and must still function within edge networks disconnected
from the main Internet, all without imposing the administrative burden of
hierarchical address assignment. Such a protocol appears challenging but
feasible. We propose an architecture based on self-certifying, cryptographic
node identities and a routing algorithm adapted from distributed hash tables.


  Statistical analysis and node clustering in hypergraphs constitute an
emerging topic suffering from a lack of standardization. In contrast to the
case of graphs, the concept of nodes' community in hypergraphs is not unique
and encompasses various distinct situations. In this work, we conducted a
comparative analysis of the performance of modularity-based methods for
clustering nodes in binary hypergraphs. To address this, we begin by
presenting, within a unified framework, the various hypergraph modularity
criteria proposed in the literature, emphasizing their differences and
respective focuses. Subsequently, we provide an overview of the
state-of-the-art codes available to maximize hypergraph modularities for
detecting node communities in binary hypergraphs. Through exploration of
various simulation settings with controlled ground truth clustering, we offer a
comparison of these methods using different quality measures, including true
clustering recovery, running time, (local) maximization of the objective, and
the number of clusters detected. Our contribution marks the first attempt to
clarify the advantages and drawbacks of these newly available methods. This
effort lays the foundation for a better understanding of the primary objectives
of modularity-based node clustering methods for binary hypergraphs.


  Suppose we are asked to preprocess a string \(s [1..n]\) such that later,
given a substring's endpoints, we can quickly count how many distinct
characters it contains. In this paper we give a data structure for this problem
that takes \(n H_0 (s) + \Oh{n} + \oh{n H_0 (s)}\) bits, where \(H_0 (s)\) is
the 0th-order empirical entropy of $s$, and answers queries in $\Oh{\log^{1 +
\epsilon} n}$ time for any constant \(\epsilon > 0\). We also show how our data
structure can be made partially dynamic.


  Iteratively reweighted L1 (IRL1) algorithm is a common algorithm for solving
sparse optimization problems with nonconvex and nonsmooth regularization. The
development of its acceleration algorithm, often employing Nesterov
acceleration, has sparked significant interest. Nevertheless, the convergence
and complexity analysis of these acceleration algorithms consistently poses
substantial challenges. Recently, Anderson acceleration has gained prominence
owing to its exceptional performance for speeding up fixed-point iteration,
with numerous recent studies applying it to gradient-based algorithms.
Motivated by the powerful impact of Anderson acceleration, we propose an
Anderson-accelerated IRL1 algorithm and establish its local linear convergence
rate. We extend this convergence result, typically observed in smooth settings,
to a nonsmooth scenario. Importantly, our theoretical results do not depend on
the Kurdyka-Lojasiewicz condition, a necessary condition in existing Nesterov
acceleration-based algorithms. Furthermore, to ensure global convergence, we
introduce a globally convergent Anderson accelerated IRL1 algorithm by
incorporating a classical nonmonotone line search condition. Experimental
results indicate that our algorithm outperforms existing Nesterov
acceleration-based algorithms.


  The Fine interior $\Delta^{\text{FI}}$ of a $d$-dimensional lattice polytope
$\Delta$ is a rational subpolytope of $\Delta$ which is important for
constructing minimal birational models of non-degenerate hypersurfaces defined
by Laurent polynomials with Newton polytope $\Delta$. This paper presents some
computational results on the Fine interior of all $674,\!688$ three-dimensional
canonical Fano polytopes.


  Centrality-dependent double-differential transverse momentum spectra of
negatively charged particles ($\pi^-$, $K^-$ and $\bar p$) at
mid-(pseudo)rapidity interval in nuclear collisions are analyzed by the
standard distribution in terms of multi-component. The experimental data
measured in gold-gold (Au-Au) collisions by the PHENIX Collaboration at the
Relativistic Heavy Ion Collider (RHIC) and in lead-lead (Pb-Pb) collisions by
the ALICE Collaboration at the Large Hadron Collider (LHC) are studied. The
effective temperature, initial temperature, kinetic freeze-out temperature,
transverse flow velocity and kinetic freeze-out volume are extracted from the
fitting to transverse momentum spectra. We observed, that the mentioned five
quantities increase with the increase of event centrality due to the fact that
the average transverse momentum increases with the increase of event
centrality. This renders that larger momentum (energy) transfer and further
multiple-scattering had happened in central centrality.


  It has been speculated that quantum gravity might induce a "foamy" space-time
structure at small scales, randomly perturbing the propagation phases of
free-streaming particles (such as kaons, neutrons, or neutrinos). Particle
interferometry might then reveal non-standard decoherence effects, in addition
to standard ones (due to, e.g., finite source size and detector resolution.) In
this work we discuss the phenomenology of such non-standard effects in the
propagation of electron neutrinos in the Sun and in the long-baseline reactor
experiment KamLAND, which jointly provide us with the best available probes of
decoherence at neutrino energies E ~ few MeV. In the solar neutrino case, by
means of a perturbative approach, decoherence is shown to modify the standard
(adiabatic) propagation in matter through a calculable damping factor. By
assuming a power-law dependence of decoherence effects in the energy domain
(E^n with n = 0,+/-1,+/-2), theoretical predictions for two-family neutrino
mixing are compared with the data and discussed. We find that neither solar nor
KamLAND data show evidence in favor of non-standard decoherence effects, whose
characteristic parameter gamma_0 can thus be significantly constrained. In the
"Lorentz-invariant" case n=-1, we obtain the upper limit gamma_0<0.78 x 10^-26
GeV at 95% C.L. In the specific case n=-2, the constraints can also be
interpreted as bounds on possible matter density fluctuations in the Sun, which
we improve by a factor of ~ 2 with respect to previous analyses.


  Higher-derivative generalization of the supersymmetric quantum mechanics is
proposed. It is formally based on the standard superalgebra but supercharges
involve differential operators of the order $n$. As a result, their
anticommutator entails polynomial of a Hamiltonian. The Witten index does not
characterize spontaneous supersymmetry breaking in such models.


  We explore cosmological perturbations in a modified Gauss-Bonnet f(G)
gravity, using a 1+3 covariant formalism. In such a formalism, we define
gradient variables to get perturbed linear evolution equations. We transform
these linear evolution equations into ordinary differential equations using a
spherical harmonic decomposition method. The obtained ordinary differential
equations are time-dependent and then transformed into redshift dependent.
After these transformations, we analyze energy-density perturbations for
two-fluid systems, namely for a Gauss-Bonnet field-dust system and for a
Gaus-Bonnet field-radiation system for three different pedagogical f(G) models:
trigonometric, exponential, and logarithmic. For the Gauss-Bonnet field-dust
system, energy-density perturbations decay with an increase in redshift for all
three models. For the Gauss-Bonnet field-radiation system, the energy-density
perturbations decay with an increase in redshift for all of the three f(G)
models for long-wavelength modes whereas for short-wavelength modes, the
energy-density perturbations decay with increasing redshift for the logarithmic
and exponential f(G) models and oscillate with decreasing amplitude for the
trigonometric f(G) model.


  We present a detailed spectral analysis of the recent 1.5\,Ms XMM-Newton
observing campaign on the narrow line Seyfert 1 galaxy IRAS~13224$-$3809, taken
simultaneously with 500\,ks of NuSTAR data. The X-ray lightcurve shows three
flux peaks, registering at about 100 times the minimum flux seen during the
campaign, and rapid variability with a time scale of kiloseconds. The spectra
are well fit with a primary powerlaw continuum, two relativistic-blurred
reflection components from the inner accretion disk with very high iron
abundance, and a simple blackbody-shaped model for the remaining soft excess.
The spectral variability is dominated by the power law continuum from a corona
region within a few gravitational radii from the black hole. Additionally,
blueshifted Ne \textsc{x}, Mg \textsc{xii}, Si \textsc{xiv} and S \textsc{xvi}
absorption lines are identified in the stacked low-flux spectrum, confirming
the presence of a highly ionized outflow with velocity up to $v= 0.267$ and
$0.225$\,c. We fit the absorption features with \texttt{xstar} models and find
a relatively constant velocity outflow through the whole observation. Finally,
we replace the \texttt{bbody} and supersolar abundance reflection models by
fitting the soft excess successfully with the extended reflection model
\texttt{relxillD}, which allows for higher densities than the standard
\texttt{relxill} model. This returns a disk electron density $n_{\rm
e}>10^{18.7}$\,cm$^{-3}$ and lowers the iron abundance from $Z_{\rm
Fe}=24^{+3}_{-4}Z_\odot$ with $n_{\rm e}\equiv10^{15}$\,cm$^{-3}$ to $Z_{\rm
Fe}=6.6^{+0.8}_{-2.1}Z_\odot$.


  New sources of CP violation beyond the Standard Model are crucial to explain
the baryon asymmetry in the Universe. We discuss the impact of new CP violating
interactions in theories where a dark matter candidate is predicted by the
cancellation of gauge anomalies. In these theories, the constraint on the dark
matter relic density implies an upper bound on the new symmetry breaking scale
from which all new states acquire their masses. We investigate in detail the
predictions for electric dipole moments and show that if the relevant
CP-violating phase is large, experiments such as the ACME collaboration will be
able to fully probe the theory.


  This paper develops a new distributed power control scheme for a power
splitting-based interference channel (IFC) with simultaneous wireless
information and power transfer (SWIPT). The considered IFC consists of multiple
source-destination pairs. Each destination splits its received signal into two
parts for information decoding and energy harvesting (EH), respectively. Each
pair adjusts its transmit power and power splitting ratio to meet both the
signal-to-interference-plus-noise ratio (SINR) and EH constraints at its
corresponding destination. To characterize rational behaviors of
source-destination pairs, we formulate a non-cooperative game for the
considered system, where each pair is modeled as a strategic player who aims to
minimize its own transmit power under both SINR and EH constraints at the
destination. We derive a sufficient and necessary condition for the existence
and uniqueness of the Nash equilibrium (NE) of the formulated game. The best
response strategy of each player is derived and then the NE can be achieved
iteratively. Numerical results show that the proposed game-theoretic approach
can achieve a near-optimal performance under various SINR and EH constraints.


  For vanilla derivatives that constitute the bulk of investment banks' hedging
portfolios, central clearing through central counterparties (CCPs) has become
hegemonic. A key mandate of a CCP is to provide an efficient and proper
clearing member default resolution procedure. When a clearing member defaults,
the CCP can hedge and auction or liquidate its positions. The counterparty
credit risk cost of auctioning has been analyzed in terms of XVA metrics in
Bastide, Cr{\'e}pey, Drapeau, and Tadese (2023). In this work we assess the
costs of hedging or liquidating. This is done by comparing pre- and
post-default market equilibria, using a Radner equilibrium approach for
portfolio allocation and price discovery in each case. We show that the Radner
equilibria uniquely exist and we provide both analytical and numerical
solutions for the latter in elliptically distributed markets. Using such tools,
a CCP could decide rationally on which market to hedge and auction or liquidate
defaulted portfolios.


  This paper evaluates the energy performance of a new daylighting system,
patented by the author, in a regular closed office space. The advantage of this
new system as opposed to conventional venetian blinds is its rotating
capability, which improves the energy efficiency of the space. Computer
simulation method has been conducted to examine the performance of this new
system on the south aperture of a closed-office space with 30% Window to Wall
ratio (WWR) in three cities in Iran with different climate zones based on
ASHRAE: Tehran (3B), Tabriz (4B), and Yazd (2B). The simulation has been
implemented in Honeybee platform with EnergyPlus engine to simulate the
combined total load consisting of heating, cooling, and lighting loads. To
control lighting, a dimming control is applied to the space. The results of the
study represent the benefits of the reversible daylighting system (RDS) over
the state of the art venetian blinds to improve the energy efficiency of the
space through just changing the location of the blind during heating/cooling
demand time of the year.


  The second order N-dimensional Schrodinger equation with Mie-type potentials
is reduced to a first order differential equation by using the Laplace
transformation. Exact bound state solutions are obtained using convolution or
Faltungs theorem. The Ladder operators are also constructed for the Mie-type
potentials in N- dimensions. Lie algebra associated with these operators are
studied and it is found that they satisfy the commutation relations for the
SU(1,1) group.


  Invertible image representation methods (transforms) are routinely employed
as low-level image processing operations based on which feature extraction and
recognition algorithms are developed. Most transforms in current use (e.g.
Fourier, Wavelet, etc.) are linear transforms, and, by themselves, are unable
to substantially simplify the representation of image classes for
classification. Here we describe a nonlinear, invertible, low-level image
processing transform based on combining the well known Radon transform for
image data, and the 1D Cumulative Distribution Transform proposed earlier. We
describe a few of the properties of this new transform, and with both
theoretical and experimental results show that it can often render certain
problems linearly separable in transform space.


  We propose a generalized formulation of the Huber loss. We show that with a
suitable function of choice, specifically the log-exp transform; we can achieve
a loss function which combines the desirable properties of both the absolute
and the quadratic loss. We provide an algorithm to find the minimizer of such
loss functions and show that finding a centralizing metric is not that much
harder than the traditional mean and median.


  Inputs to signaling pathways can have complex statistics that depend on the
environment and on the behavioral response to previous stimuli. Such behavioral
feedback is particularly important in navigation. Successful navigation relies
on proper coupling between sensors, which gather information during motion, and
actuators, which control behavior. Because reorientation conditions future
inputs, behavioral feedback can place sensors and actuators in an operational
regime different from the resting state. How then can organisms maintain proper
information transfer through the pathway while navigating diverse environments?
In bacterial chemotaxis, robust performance is often attributed to the zero
integral feedback control of the sensor, which guarantees that activity returns
to resting state when the input remains constant. While this property provides
sensitivity over a wide range of signal intensities, it remains unclear how
other parameters affect chemotactic performance, especially when considering
that the swimming behavior of the cell determines the input signal. Using
analytical models and simulations that incorporate recent experimental
evidences about behavioral feedback and flagellar motor adaptation we identify
an operational regime of the pathway that maximizes drift velocity for various
environments and sensor adaptation rates. This optimal regime is outside the
dynamic range of the motor response, but maximizes the contrast between run
duration up and down gradients. In steep gradients, the feedback from
chemotactic drift can push the system through a bifurcation. This creates a
non-chemotactic state that traps cells unless the motor is allowed to adapt.
Although motor adaptation helps, we find that as the strength of the feedback
increases individual phenotypes cannot maintain the optimal operational regime
in all environments, suggesting that diversity could be beneficial.


  We report ALMA and VLA continuum observations that potentially identify the
four youngest protostars in the Orion Molecular Clouds taken as part of the
Orion VANDAM program. These are distinguished by bright, extended, irregular
emission at 0.87 mm and 8 mm and are optically thick at 0.87 mm. These
structures are distinct from the disk or point-like morphologies seen toward
the other Orion protostars. The 0.87 mm emission implies temperatures of 41-170
K, requiring internal heating. The bright 8 mm emission implies masses of 0.5
to 1.2 M_sun assuming standard dust opacity models. One source has a Class 0
companion, while another exhibits substructure indicating a
companion-candidate. Three compact outflows are detected, two of which may be
driven by companions, with dynamical times of ~300 to ~400 years. The slowest
outflow may be driven by a first hydrostatic core. These protostars appear to
trace an early phase when the centers of collapsing fragments become optically
thick to their own radiation and compression raises the gas temperature. This
phase is thought to accompany the formation of hydrostatic cores. A key
question is whether these structures are evolving on free fall times of ~100
years, or whether they are evolving on Kelvin-Helmholtz times of several
thousand years. The number of these sources imply a lifetime of ~6000 years, in
closer agreement with the Kelvin-Helmholtz time. In this case, rotational
and/or magnetic support could be slowing the collapse.


  A simplified model of articulatory synthesis involving four stages is
presented. The planning of articulatory gestures is based on syllable graphs
with arcs and nodes that are implemented in a complex representation. This was
first motivated by a reduction in the many-to-one relationship between
articulatory parameters and formant space. This allows for consistent
trajectory planning and computation of articulation dynamics with coordination
and selection operators. The flow of articulatory parameters is derived from
these graphs with four equations. Many assertions of Articulatory Phonology
have been abandoned. This framework is adapted to synthesis using VLAM (a
Maeda's model) and simulations are performed with syllables including main
vowels and the plosives /b,d,g/ only. The model is able to describe
consonant-vowel coarticulation, articulation of consonant clusters, and verbal
transformations are seen as transitions of the syllable graph structure.


  Given a curve in quantum spin state space, we inquire what is the relation
between its geometry and the geometric phase accumulated along it. Motivated by
Mukunda and Simon's result that geodesics (in the standard Fubini-Study metric)
do not accumulate geometric phase, we find a general expression for the
derivatives (of various orders) of the geometric phase in terms of the
covariant derivatives of the curve. As an application of our results, we put
forward the brachistophase problem: given a quantum state, find the
(appropriately normalized) hamiltonian that maximizes the accumulated geometric
phase after time $\tau$ - we find an analytical solution for all spin values,
valid for small $\tau$. For example, the optimal evolution of a spin coherent
state consists of a single Majorana star separating from the rest and tracing
out a circle on the Majorana sphere.


  Larval settlement in wave-dominated, nearshore environments is the most
critical life stage for a vast array of marine invertebrates, yet it is poorly
understood and virtually impossible to observe in situ. Using a custom-built
flume tank that mimics the oscillatory fluid flow over a shallow coral reef, we
show that millimeter-scale benthic topography increases the settlement of
slow-swimming coral larvae by an order of magnitude relative to flat
substrates. Particle tracking velocimetry of flow fields revealed that
millimeter-scale ridges introduced regions of flow recirculation that
redirected larvae toward the substrate surface and decreased the local fluid
speed, effectively increasing the window of time for larvae to settle. In
agreement with experiments, computational fluid dynamics modeling and
agent-based larval simulations also showed significantly higher settlement on
ridged substrates. These findings highlight how physics-based substrate design
can create new opportunities to increase larval recruitment for ecosystem
restoration.


  Nonlinear lens distortion rectification is a common first step in image
processing applications where the assumption of a linear camera model is
essential. For rectifying the lens distortion, forward distortion model needs
to be known. However, many self-calibration methods estimate the inverse
distortion model. In the literature, the inverse of the estimated model is
approximated for image rectification, which introduces additional error to the
system. We propose a novel distortion rectification method that uses the
inverse distortion model directly. The method starts by mapping the distorted
pixels to the rectified image using the inverse distortion model. The resulting
set of points with subpixel locations are triangulated. The pixel values of the
rectified image are linearly interpolated based on this triangulation. The
method is applicable to all camera calibration methods that estimate the
inverse distortion model and performs well across a large range of parameters.


  This paper deals with the study of the zeros of the big $q$-Bessel functions.
In particular, we prove a new orthogonality relations for this functions
similar to the one for the classical Bessel functions. Also we give some
applications related to the sampling theory.


  Multiplex networks describe a large number of complex social, biological and
transportation networks where a set of nodes is connected by links of different
nature and connotation. Here we uncover the rich community structure of
multiplex networks by associating a community to each multilink where the
multilinks characterize the connections existing between any two nodes of the
multiplex network. Our community detection method reveals the rich interplay
between the mesoscale structure of the multiplex networks and their
multiplexity. For instance some nodes can belong to many layers and few
communities while others can belong to few layers but many communities.
Moreover the multilink communities can be formed by a different number of
relevant layers. These results point out that mesoscopically there can be large
differences in the compressibility of multiplex networks.


  We find new and universal relations for the properties of dark matter
particles consistent with standard relic abundances. Analysis is based on first
characterizing the $s$-channel resonant annihilation process in great detail,
keeping track of all velocity-dependence, the presence of multiple scales and
treating each physical regime above, below, and close to thresholds separately.
The resonant regime as well as extension to include non-resonant processes are
then reduced to analytic formulas and inequalities that describe the full range
of multi-dimensional numerical work. These results eliminate the need to
recompute relic abundance model by model, and reduce calculations to verifying
certain scale and parameter combinations are consistent. Remarkably simple
formulas describe the relation between the total width of an $s$-channel
intermediate particle, the masses and the couplings involved. Eliminating the
width in terms of the mass produces new consistency relations between dark
matter masses and the intermediate masses. The formulas are general enough to
test directly whether new particles can be identified as dark matter. Resonance
mass and total width are quantities directly observable at accelerators such as
the LHC, and will be sufficient to establish whether new discoveries are
consistent with the cosmological bounds on dark matter.


  We investigate the morphology of quasi-free-standing monolayer graphene
(QFMLG) formed at several temperatures by hydrogen intercalation and discuss
its relationship with transport properties. Features corresponding to
incomplete hydrogen intercalation at the graphene-substrate interface are
observed by scanning tunneling microscopy on QFMLG formed at 600 and
800{\deg}C. They contribute to carrier scattering as charged impurities. Voids
in the SiC substrate and wrinkling of graphene appear at 1000{\deg}C, and they
decrease the carrier mobility significantly.


  We exhibit a Probabilistic Cellular Automaton (PCA) on the integers with an
alphabet and a neighborhood of size 2 which is non-ergodic although it has a
unique invariant measure. This answers by the negative an old open question on
whether uniqueness of the invariant measure implies ergodicity for a PCA.


  Hierarchical beam search in mmWave communications incurs substantial training
overhead, necessitating deep learning-enabled beam predictions to effectively
leverage channel priors and mitigate this overhead. In this study, we introduce
a comprehensive probabilistic model of power distribution in beamspace, and
formulate the joint optimization problem of probing beam selection and
probabilistic beam prediction as an entropy minimization problem. Then, we
propose a greedy scheme to iteratively and alternately solve this problem,
where a transformer-based beam predictor is trained to estimate the conditional
power distribution based on the probing beams and user location within each
iteration, and the trained predictor selects an unmeasured beam that minimizes
the entropy of remaining beams. To further reduce the number of interactions
and the computational complexity of the iterative scheme, we propose a
two-stage probing beam selection scheme. Firstly, probing beams are selected
from a location-specific codebook designed by an entropy-based criterion, and
predictions are made with corresponding feedback. Secondly, the optimal beam is
identified using additional probing beams with the highest predicted power
values. Simulation results demonstrate the superiority of the proposed schemes
compared to hierarchical beam search and beam prediction with uniform probing
beams.


  We provide a non-perturbative expression for the hadron production in
electron-positron annihilation at zero temperature in a strongly coupled,
large-Nc SU(Nc) field theory with Nf << Nc quark flavors. The resulting
expressions are valid to leading order in the electromagnetic coupling constant
but non-perturbatively in the SU(Nc) interactions and the mass of the quark. We
obtain this quantity by computing the imaginary part of the hadronic vacuum
polarization function Pi_q using holographic techniques, providing an
alternative to the known method that uses the spectrum of infinitely stable
mesons determined by the normalizable modes of the appropriated fields in the
bulk. Our result exhibits a structure of poles localized at specific real
values of q^2, which coincide with the ones found using the normalizable modes,
and extends it offering the unique analytic continuation of this distribution
to a function defined for values of q^2 over the complex plane. This analytic
continuation permits to include a finite decay width for the mesons. By
comparison with experimental data we find qualitatively good agreement on the
shape of the first pole, when using the rho meson parameters and choosing a
proper normalization factor. We then estimate the contribution to the anomalous
magnetic moment of the muon finding an agreement within 25%, for this choice of
parameters.


  While observations in the radio band are providing essential information on
the innermost structures of relativistic jets in active galactic nuclei (AGN),
the recent detection by Fermi of gamma-ray emission from many hundreds of
blazars shows that the maximum jet power is emitted at high energies.
Multi-wavelength monitoring observations further allow variability studies of
the AGN spectral energy distributions over 13 orders of magnitude in frequency.
The Joint Discussion offered the possibility for a comprehensive discussion of
advances in the observational domain and stimulated theoretical discussion
about our current understanding of jet physics.


  Due to the fragility of quantum mechanical effects, real quantum computers
are plagued by frequent noise effects that cause errors during computations.
Quantum error-correcting codes address this problem by providing means to
identify and correct corresponding errors. However, most of the research on
quantum error correction is theoretical or has been evaluated for specific
hardware models only. Moreover, the development of corresponding codes and the
evaluation of whether they indeed solve the problem for a particular hardware
model, still often rests on tedious trial-and-error thus far. In this work, we
propose an open-source framework that supports engineers and researchers in
these tasks by automatically applying error-correcting codes for a given
application followed by an automatic noise-aware quantum circuit simulation.
Case studies showcase that this allows for a substantially more efficient
implementation and evaluation of error-correcting codes.


  We derive an equation that is analogous to a well-known symmetric function
identity: $\sum_{i=0}^n(-1)^ie_ih_{n-i}=0$. Here the elementary symmetric
function $e_i$ is the Frobenius characteristic of the representation of
$\mathcal{S}_i$ on the top homology of the subset lattice $B_i$, whereas our
identity involves the representation of $\mathcal{S}_n\times \mathcal{S}_n$ on
the Segre product of $B_n$ with itself. We then obtain a q-analogue of a
polynomial identity given by Carlitz, Scoville and Vaughan through examining
the Segre product of the subspace lattice $B_n(q)$ with itself. We recognize
the connection between the Euler characteristic of the Segre product of
$B_n(q)$ with itself and the representation on the Segre product of $B_n$ with
itself by recovering our polynomial identity from specializing the identity on
the representation of $\mathcal{S}_i\times \mathcal{S}_i$.


  Rankings of people and items has been highly used in selection-making,
match-making, and recommendation algorithms that have been deployed on ranging
of platforms from employment websites to searching tools. The ranking position
of a candidate affects the amount of opportunities received by the ranked
candidate. It has been observed in several works that the ranking of candidates
based on their score can be biased for candidates belonging to the minority
community. In recent works, the fairness-aware representative ranking was
proposed for computing fairness-aware re-ranking of results. The proposed
algorithm achieves the desired distribution of top-ranked results with respect
to one or more protected attributes. In this work, we highlight the bias in
fairness-aware representative ranking for an individual as well as for a group
if the group is sub-active on the platform. We define individual unfairness and
group unfairness and propose methods to generate ideal individual and group
fair representative ranking if the universal representation ratio is known or
unknown. The simulation results show the quantified analysis of fairness in the
proposed solutions. The paper is concluded with open challenges and further
directions.


  We discuss unbiased estimation equations in a class of objective function
using a monotonically increasing function $f$ and Bregman divergence. The
choice of the function $f$ gives desirable properties such as robustness
against outliers. In order to obtain unbiased estimation equations,
analytically intractable integrals are generally required as bias correction
terms. In this study, we clarify the combination of Bregman divergence,
statistical model, and function $f$ in which the bias correction term vanishes.
Focusing on Mahalanobis and Itakura-Saito distances, we provide a
generalization of fundamental existing results and characterize a class of
distributions of positive reals with a scale parameter, which includes the
gamma distribution as a special case. We discuss the possibility of latent bias
minimization when the proportion of outliers is large, which is induced by the
extinction of the bias correction term.


  We present the results of studies for magnetogyration (MG) effect in
non-centro-symmetric, non-polar Bi12GeO20 crystals performed with the
small-angular polarimetric mapping technique. The magnitude of MG rotation
obtained with the small-angular mapping is close to the corresponding values
obtained recently on the basis of single-ray polarimetry. Our results
demonstrate that multiple reflections of light play a key role in the studies
of MG effect in Bi12GeO20 crystals. They lead to the error, which is at least
two times as large as the expected value of the MG rotation.


  We derived atmospheric parameters and spectroscopic abundances for C and O
for a large sample of stars located in the Hertzsprung gap in the
Hertzsprung-Russell Diagram in order to detect chemical peculiarities and get a
comprehensive overview of the population of stars in this evolutionary state.
We have observed and analyzed high resolution spectra (R = 60 000) of 188 stars
in the mass range 2 - 5 Msun with the 2.7 m Harlan J. Smith Telescope at the
McDonald Observatory including 28 stars previously identified as Am/Ap stars.
We find that the C and O abundances of the majority of stars in the Hertzsprung
gap are in accordance with abundances derived for local lower mass dwarfs but
detect expected peculiarities for the Am/Ap stars. The C and O abundances of
stars with Teff < 6500 K are slightly lower than for the hotter objects but the
C/O ratio is constant in the analyzed temperature domain. No indication of an
alteration of the C and O abundances of the stars by mixing during the
evolution across the Hertzsprung gap could be found before the homogenization
of their atmospheres by the first dredge-up.


  Consistent Lagrangian description of lightlike p-branes (LL-branes) is
presented in two equivalent forms - a Polyakov-type formulation and a dual to
it Nambu-Goto-type formulation. An important characteristic feature of the
LL-branes is that the brane tension appears as a non-trivial additional
dynamical degree of freedom. Next, properties of p=2 LL-brane dynamics (as a
test brane) in D=4 Kerr or Kerr-Newman gravitational backgrounds are discussed
in some detail. It is shown that the LL-brane automatically positions itself on
the horizon and rotates along with the same angular velocity. Finally, a
Misner-Wheeler-type of Reissner-Nordstroem wormhole is constructed in a
self-consistent electrically sourceless Einstein-Maxwell system in the D=4 bulk
interacting with a LL-brane. The pertinent wormhole throat is located precisely
at the LL-brane sitting on the outer Reissner-Nordstroem horizon with the
Reissner-Nordstroem mass and charge being functions of the dynamical LL-brane
tension.


  The proposed electron-proton collider LHeC is a unique facility where
electroweak interactions can be studied with a very high precision in a largely
unexplored kinematic regime of spacelike momentum transfer. We have simulated
inclusive neutral- and charged-current deep-inelastic lepton proton scattering
cross section data at center-of-mass energies of 1.2 and 1.3 TeV including
their systematic uncertainties. Based on simultaneous fits of electroweak
physics parameters and parton distribution functions, we estimate the
uncertainties of Standard Model parameters as well as a number of parameters
describing physics beyond the Standard Model, for instance the oblique
parameters $S$, $T$, and $U$. An unprecedented precision at the sub-percent
level is expected for the measurement of the weak neutral-current couplings of
the light-quarks to the $Z$ boson, $g_{A/V}^{u/d}$, improving their present
precision by more than an order of magnitude. The weak mixing angle can be
determined with a precision of about $\Delta \sin^2\theta_\textrm{W} = \pm
0.00015$, and its scale dependence can be studied in the range between about 25
and 700 GeV. An indirect determination of the $W$-boson mass in the on-shell
scheme is possible with an experimental uncertainty down to $\Delta
m_{W}=\pm6\,\textrm{MeV}$. We discuss how the uncertainties of such
measurements in deep-inelastic scattering compare with those from measurements
in the timelike domain, e.g. at the $Z$-pole, and which aspects of the
electroweak interaction are unique to measurements at the LHeC, for instance
electroweak parameters in charged-current interactions. We conclude that the
LHeC will determine electroweak physics parameters, in the spacelike region,
with unprecedented precision leading to thorough tests of the Standard Model
and possibly beyond.


  The Logical Execution Time (LET) model has been gaining industrial attention
because of its timing and data-flow deterministic characteristics, which
simplify the computation of end-to-end latencies of multi-rate cause-effect
chains at the cost of pessimistic latencies. In this paper, we propose a novel
method to reduce the pessimism in the latencies introduced by LET, while
maintaining its determinism. We propose a schedule-aware LET model that
shortens the lengths and repositions LET's communication intervals resulting in
less pessimistic end-to-end latencies. By adding dependencies between specific
task instances, the method can further reduce the pessimism in the latency
calculations of the LET model. If needed, e.g., for legacy reasons, our method
can be applied to a subset of tasks only. We evaluate our work based on real
world automotive benchmarks and randomly generated synthetic task sets. We
compare our results with previous work and the LET model. The experiments show
significant reductions of worst-case data age and worst-case reaction latency
values.


  When semiconducting transition metal dichalcogenides heterostructures are
stacked the twist angle and lattice mismatch leads to a periodic moir\'e
potential. As the angle between the layers changes, so do the electronic
properties. As the angle approaches 0- or 60-degrees interesting
characteristics and properties such as modulations in the band edges, flat
bands, and confinement are predicted to occur. Here we report scanning
tunneling microscopy and spectroscopy measurements on the band gaps and band
modulations in MoSe2/WSe2 heterostructures with near 0 degree rotation (R-type)
and near 60 degree rotation (H-type). We find a modulation of the band gap for
both stacking configurations with a larger modulation for R-type than for
H-type as predicted by theory. Furthermore, local density of states images show
that electrons are localized differently at the valence band and conduction
band edges.


  Following the tracks of Malbet, Yu, & Shao (1995} on dark hole algorithms, we
present analytical methods to measure and correct the speckle noise behind an
ideal coronagraph. We show that, in a low aberration regime, wavefront sensing
can be accomplished with only three images, the next image being fully
corrected (no iterative process needed). The only hardware required is the
coronagraph deformable mirror and an imaging detector in the focal plane, thus
there are no non-common path errors to correct. Our first method, speckle field
nulling, is a fast FFT-based algorithm requiring the deformable mirror
influence functions to have identical shapes. Our second method, speckle energy
minimization is more general and based on matrix inversion. Numerical
simulations show that these methods can improve the contrast by several orders
of magnitude.


  Augmented sports videos, which combine visualizations and video effects to
present data in actual scenes, can communicate insights engagingly and thus
have been increasingly popular for sports enthusiasts around the world. Yet,
creating augmented sports videos remains a challenging task, requiring
considerable time and video editing skills. On the other hand, sports insights
are often communicated using natural language, such as in commentaries, oral
presentations, and articles, but usually lack visual cues. Thus, this work aims
to facilitate the creation of augmented sports videos by enabling analysts to
directly create visualizations embedded in videos using insights expressed in
natural language. To achieve this goal, we propose a three-step approach - 1)
detecting visualizable entities in the text, 2) mapping these entities into
visualizations, and 3) scheduling these visualizations to play with the video -
and analyzed 155 sports video clips and the accompanying commentaries for
accomplishing these steps. Informed by our analysis, we have designed and
implemented Sporthesia, a proof-of-concept system that takes racket-based
sports videos and textual commentaries as the input and outputs augmented
videos. We demonstrate Sporthesia's applicability in two exemplar scenarios,
i.e., authoring augmented sports videos using text and augmenting historical
sports videos based on auditory comments. A technical evaluation shows that
Sporthesia achieves high accuracy (F1-score of 0.9) in detecting visualizable
entities in the text. An expert evaluation with eight sports analysts suggests
high utility, effectiveness, and satisfaction with our language-driven
authoring method and provides insights for future improvement and
opportunities.


  Blockchain brings various advantages to online transactions. However, the
total transparency of these transactions may leakage users' sensitive
information. Requirements on both cooperation and anonymity for
companies/organizations become necessary. In this paper, we propose a
Multi-center Anonymous Blockchain-based (MAB) system, with joint management for
the consortium and privacy protection for the participants. To achieve that, we
formalize the syntax used by the MAB system and present a general construction
based on a modular design. By applying cryptographic primitives to each module,
we instantiate our scheme with anonymity and decentralization. Furthermore, we
carry out a comprehensive formal analysis of the proposed solution. The results
demonstrate our constructed scheme is secure and efficient.