  Bayesian statistical inference has become increasingly important for the
analysis of observations from the Advanced LIGO and Advanced Virgo
gravitational-wave detectors. To this end, iterative simulation techniques, in
particular nested sampling and parallel tempering, have been implemented in the
software library LALInference to sample from the posterior distribution of
waveform parameters of compact binary coalescence events. Nested sampling was
mainly developed to calculate the marginal likelihood of a model but can
produce posterior samples as a by-product. Thermodynamic integration is
employed to calculate the evidence using samples generated by parallel
tempering but has been found to be computationally demanding. Here we propose
the stepping-stone sampling algorithm, originally proposed by Xie et al. (2011)
in phylogenetics and a special case of path sampling, as an alternative to
thermodynamic integration. The stepping-stone sampling algorithm is also based
on samples from the power posteriors of parallel tempering but has superior
performance as fewer temperature steps and thus computational resources are
needed to achieve the same accuracy. We demonstrate its performance and
computational costs in comparison to thermodynamic integration and nested
sampling in a simulation study and a case study of computing the marginal
likelihood of a binary black hole signal model applied to simulated data from
the Advanced LIGO and Advanced Virgo gravitational wave detectors. To deal with
the inadequate methods currently employed to estimate the standard errors of
evidence estimates based on power posterior techniques, we propose a novel
block bootstrap approach and show its potential in our simulation study and
LIGO application.


  We study the structural transition from `B' form of DNA to 'A' form of DNA
using group theoretic methods. The transition is not of the order-disorder type
and hence to construct a Landau kind of theory for the transition we define a
higher symmetry and relevant order parameters. We also discuss the issue of all
the conformations, observed experimentally during the course of transition,
being fundamentally different or not.


  Plasmonic nanocavities enable the confinement of molecules and
electromagnetic fields within nano-metric volumes. As a consequence, the
molecules experience a remarkably strong interaction with the electromagnetic
field, to such an extent that the quantum states of the system become hybrids
between light and matter: polaritons. Here we present a non-perturbative method
to simulate the emerging properties of such polaritons: it combines a
high-level quantum chemical description of the molecule with a quantized
description of the localized surface plasmons in the nanocavity. We apply the
method to molecules of realistic complexity in a typical plasmonic nanocavity,
featuring also a subnanometric asperity (picocavity). Our results disclose the
effects of the mutual polarization and correlation of plasmons and molecular
excitations, disregarded so far. They also quantify to what extent the
molecular charge density can be manipulated by nanocavities, and stand as
benchmarks to guide the development of methods for molecular polaritonics.


  We propose a fully data-driven approach to calibrate local stochastic
volatility (LSV) models, circumventing in particular the ad hoc interpolation
of the volatility surface. To achieve this, we parametrize the leverage
function by a family of feed-forward neural networks and learn their parameters
directly from the available market option prices. This should be seen in the
context of neural SDEs and (causal) generative adversarial networks: we
generate volatility surfaces by specific neural SDEs, whose quality is assessed
by quantifying, possibly in an adversarial manner, distances to market prices.
The minimization of the calibration functional relies strongly on a variance
reduction technique based on hedging and deep hedging, which is interesting in
its own right: it allows the calculation of model prices and model implied
volatilities in an accurate way using only small sets of sample paths. For
numerical illustration we implement a SABR-type LSV model and conduct a
thorough statistical performance analysis on many samples of implied volatility
smiles, showing the accuracy and stability of the method.


  Let $\f$ be a primitive, cuspidal Hilbert modular form of parallel weight. We
investigate the Rankin convolution $L$-values $L(\f,\g,s)$, where $\g$ is a
theta-lift modular form corresponding to a finite-order character. We prove
weak forms of Kato's `false Tate curve' congruences for these values, of the
form predicted by conjectures in non-commmutative Iwasawa theory.


  The Gamma-ray Large Area Space Telescope (GLAST) Science Support Center
(GSSC) is the scientific community's interface with GLAST. The GSSC will
provide data, analysis software and documentation. In addition, the GSSC will
administer the guest investigator program for NASA HQ. Consequently, the GSSC
will provide proposal preparation tools to assist proposers in assessing the
feasibility of observing sources of interest.


  Data are presented on mutual and self-inductance of various inductors used in
multilayered superconductor integrated circuits: microstrips and striplines
with widths of signal traces from 250 nm to a few micrometers, located on the
same circuit layer at various distances from each other (from 250 nm to a few
micrometers) and/or on different layers spaced vertically; effect of long slits
in the ground plane(s) along the inductors on their mutual inductance;
inductance of right-angled bends; inductance of meanders. Simple analytical
expressions for mutual and self-inductance of the basic inductors are given,
describing experimental data with accuracy better than 2% in a very wide range
of parameters. They can be used for superconductor integrated circuit design
and calibration of numerical inductance extractors. Measurements were done
using circuits fabricated in fully planarized fabrication processes with eight
niobium layers and Nb/Al-AlOx/Nb Josephson junctions, known as the SFQ5ee and
SC1 processes developed at MIT Lincoln Laboratory for superconductor
electronics. Mutual inductance decreases exponentially with distance between
striplines and as a second power of the distance between microstrips, strongly
depends on magnetic field penetration depths in superconducting ground planes,
whereas superconducting properties of the signal traces are practically
immaterial. Weak dependence of mutual inductance on the linewidth of
superconducting wires indicates that area of superconducting flux transformers
- the essential component of all digital circuits using ac power,
superconducting qubits, and sensor arrays - scales poorly with the linewidth,
putting a predictable upper limit on the integration scale of such circuits.


  In galaxy cluster collisions, the gas can be separated from dark matter
halos. Abell~56 displays signatures of a dissociative bullet-like merger with a
possible high inclination angle between the plane of orbit and the sky. Our
objective is to provide a comprehensive description of the features observed in
the collision scenario of Abell~56. Additionally, we aim to apply a potential
weak lensing mass bias correction attributed to the merger to evaluate its
impact on our findings. To investigate this, we perform tailored hydrodynamical
$N$-body simulations, varying the impact parameter. We initially identified an
early scenario at $0.12$\,Gyr after the central passage that reproduces some
observational features. However, the mean temperature of $9.7$\,keV exceeded
the observed value. Our best model corresponds to the late scenario at
$0.52$\,Gyr after the pericenter, reproducing observed features of Abell~56,
with an inclination of $58^\circ$. These features include the offset of
$103$\,kpc between the main gas density peak and the south dark matter density
peak, gas morphology, a line of sight relative velocity of $184$\,km\,s$^{-1}$,
and a mean temperature of $6.7$\,keV. This late model provides a plausible
scenario to describe the dynamics of Abell~56. The weak lensing mass bias did
not significantly impact the overall dynamics of this cluster merger.


  [abridged] It has been widely claimed that several lines of observational
evidence point towards a "downsizing" (DS) of the process of galaxy formation
over cosmic time. This behavior is sometimes termed "anti-hierarchical", and
contrasted with the "bottom-up" assembly of the dark matter structures in Cold
Dark Matter models. In this paper we address three different kinds of
observational evidence that have been described as DS: the stellar mass
assembly, star formation rate and the ages of the stellar populations in local
galaxies. We compare a broad compilation of available data-sets with the
predictions of three different semi-analytic models of galaxy formation within
the Lambda-CDM framework. In the data, we see only weak evidence at best of DS
in stellar mass and in star formation rate. We find that, when observational
errors on stellar mass and SFR are taken into account, the models acceptably
reproduce the evolution of massive galaxies, over the entire redshift range
that we consider. However, lower mass galaxies are formed too early in the
models and are too passive at late times. Thus, the models do not correctly
reproduce the DS trend in stellar mass or the archaeological DS, while they
qualitatively reproduce the mass-dependent evolution of the SFR. We demonstrate
that these discrepancies are not solely due to a poor treatment of satellite
galaxies but are mainly connected to the excessively efficient formation of
central galaxies in high-redshift haloes with circular velocities ~100-200
km/s. [abridged]


  Emission from the photosphere in gamma-ray burst (GRB) jets can be
substantially affected by subphotospheric energy dissipation, which is
typically caused by radiation-mediated shocks (RMSs). We study the
observational characteristics of such emission, in particular the spectral
signatures. Relevant shock initial conditions are estimated using a simple
internal collision framework, which then serve as inputs for an RMS model that
generates synthetic photospheric spectra. Within this framework, we find that
if the free fireball acceleration starts at $r_0 \sim 10^{10}~$cm, in agreement
with hydrodynamical simulations, then the typical spectrum consists of a broad,
soft power-law segment with a cutoff at high energies and a hardening in
X-rays. The synthetic spectra are generally well fitted with a standard cutoff
power-law (CPL) function, as the hardening in X-rays is commonly outside the
observable energy range of current detectors. The CPL-fits yield values for the
low-energy index, $\alpha$, and the peak energy, $E_{\rm peak}$, that are
centered around $\sim -0.8$ and $\sim 220~$keV, respectively, similar to
typical observed values. We also identify a non-negligible parameter region for
what we call ``optically shallow shocks'': shocks that do not accumulate enough
scatterings to reach a steady-state spectrum before decoupling and thereby
produce more complex spectra. These occur for optical depths $\tau \lesssim 55
\, u_u^{-2}$, where $u_u = \gamma_u\beta_u$ is the dimensionless specific
momentum of the upstream as measured in the shock rest frame.


  This paper presents measurements of D^{*\pm} production in deep inelastic
scattering from collisions between 27.5 GeV positrons and 820 GeV protons. The
data have been taken with the ZEUS detector at HERA. The decay channel
$D^{*+}\to (D^0 \to K^- \pi^+) \pi^+ $ (+ c.c.) has been used in the study. The
$e^+p$ cross section for inclusive D^{*\pm} production with $5<Q^2<100 GeV^2$
and $y<0.7$ is 5.3 \pms 1.0 \pms 0.8 nb in the kinematic region
{$1.3<p_T(D^{*\pm})<9.0$ GeV and $| \eta(D^{*\pm}) |<1.5$}. Differential cross
sections as functions of p_T(D^{*\pm}), $\eta(D^{*\pm}), W$ and $Q^2$ are
compared with next-to-leading order QCD calculations based on the photon-gluon
fusion production mechanism. After an extrapolation of the cross section to the
full kinematic region in p_T(D^{*\pm}) and $\eta$(D^{*\pm}), the charm
contribution $F_2^{c\bar{c}}(x,Q^2)$ to the proton structure function is
determined for Bjorken $x$ between 2 $\cdot$ 10$^{-4}$ and 5 $\cdot$ 10$^{-3}$.


  Financial markets are often driven by latent factors which traders cannot
observe. Here, we address an algorithmic trading problem with collections of
heterogeneous agents who aim to perform optimal execution or statistical
arbitrage, where all agents filter the latent states of the world, and their
trading actions have permanent and temporary price impact. This leads to a
large stochastic game with heterogeneous agents. We solve the stochastic game
by investigating its mean-field game (MFG) limit, with sub-populations of
heterogeneous agents, and, using a convex analysis approach, we show that the
solution is characterized by a vector-valued forward-backward stochastic
differential equation (FBSDE). We demonstrate that the FBSDE admits a unique
solution, obtain it in closed-form, and characterize the optimal behaviour of
the agents in the MFG equilibrium. Moreover, we prove the MFG equilibrium
provides an $\epsilon$-Nash equilibrium for the finite player game. We conclude
by illustrating the behaviour of agents using the optimal MFG strategy through
simulated examples.


  Fault-tolerance techniques depend on replication to enhance availability,
albeit at the cost of increased infrastructure costs. This results in a
fundamental trade-off: Fault-tolerant services must satisfy given availability
and performance constraints while minimising the number of replicated
resources. These constraints pose capacity planning challenges for the service
operators to minimise replication costs without negatively impacting
availability.
  To this end, we present PCRAFT, a system to enable capacity planning of
dependable services. PCRAFT's capacity planning is based on a hybrid approach
that combines empirical performance measurements with probabilistic modelling
of availability based on fault injection. In particular, we integrate
traditional service-level availability mechanisms (active route anywhere and
passive failover) and deployment schemes (cloud and on-premises) to quantify
the number of nodes needed to satisfy the given availability and performance
constraints. Our evaluation based on real-world applications shows that cloud
deployment requires fewer nodes than on-premises deployments. Additionally,
when considering on-premises deployments, we show how passive failover requires
fewer nodes than active route anywhere. Furthermore, our evaluation quantify
the quality enhancement given by additional integrity mechanisms and how this
affects the number of nodes needed.


  I briefly report on the work conducted to probe the gravitational potential
of active and non-active disk galaxies using two-dimensional gas and stellar
kinematics, first emphasizing the need to make a distinction between ''fuelling
the nucleus'' and ''building a gas reservoir''.


  We have studied the nearby old pulsar PSR B1929+10 and its surrounding
interstellar medium utilizing the sub-arcsecond angular resolution of the
Chandra X-ray Observatory. The Chandra data are found to be fully consistent
with the results obtained from deep XMM-Newton observations as far as the
pulsar is concerned. We confirm the non-thermal emission nature of the pulsar's
X-radiation. In addition to the X-ray trail already seen in previous
observations by the ROSAT and XMM-Newton X-ray observatories, we discovered an
arc-like nebula surrounding the pulsar. We interpret the feature as a bow-shock
nebula and discuss its energetics in the context of standard shock theory.


  The interest of the machine learning community in image synthesis has grown
significantly in recent years, with the introduction of a wide range of deep
generative models and means for training them. In this work, we propose a
general model-agnostic technique for improving the image quality and the
distribution fidelity of generated images obtained by any generative model. Our
method, termed BIGRoC (Boosting Image Generation via a Robust Classifier), is
based on a post-processing procedure via the guidance of a given robust
classifier and without a need for additional training of the generative model.
Given a synthesized image, we propose to update it through projected gradient
steps over the robust classifier to refine its recognition. We demonstrate this
post-processing algorithm on various image synthesis methods and show a
significant quantitative and qualitative improvement on CIFAR-10 and ImageNet.
Surprisingly, although BIGRoC is the first model agnostic among refinement
approaches and requires much less information, it outperforms competitive
methods. Specifically, BIGRoC improves the image synthesis best performing
diffusion model on ImageNet 128x128 by 14.81%, attaining an FID score of 2.53,
and on 256x256 by 7.87%, achieving an FID of 3.63. Moreover, we conduct an
opinion survey, according to which humans significantly prefer our method's
outputs.


  We introduce a cosmological invisible decay of the sterile neutrino with the
eV-scale mass indicated by short-baseline neutrino oscillation experiments in
order to allow its full thermalization in the early Universe. We show that the
fit of the cosmological data is practically as good as the fit obtained with a
stable sterile neutrino without mass constraints, which has been recently
considered by several authors for the explanation of the observed suppression
of small-scale matter density fluctuations and for a solution of the tension
between the Planck and BICEP2 measurements of the tensor to scalar ratio of
large-scale fluctuations. Moreover, the extra relativistic degree of freedom
corresponding to a fully thermalized sterile neutrino is correlated with a
larger value of the Hubble constant, which is in agreement with local
measurements.


  High-resolution mass spectra of helium droplets doped with gold and ionized
by electrons reveal He$_n$Au$^+$ cluster ions. Additional doping with heavy
noble gases results in NenAu+, Ar$_n$Au$^+$, Kr$_n$Au$^+$, and Xe$_n$Au$^+$
cluster ions. The high stability predicted for covalently bonded Ar$_2$Au$^+$,
Kr$_2$Au$^+$, and Xe$_2$Au$^+$ is reflected in their relatively high abundance.
Surprisingly, the abundance of Ne$_2$Au$^+$ which is predicted to have zero
covalent bonding character and no enhanced stability features a local maximum,
too. The predicted size and structure of complete solvation shells surrounding
ions with essentially non-directional bonding depends primarily on the ratio
$\sigma$* of the ion-ligand $versus$ the ligand-ligand distance. For Au$^+$
solvated in helium and neon the ratio $\sigma$* is slightly below 1, favoring
icosahedral packing in agreement with a maximum observed in the corresponding
abundance distributions at $n$ = 12. He$_n$Au$^+$ appears to adopt two
additional solvation shells of $I_h$ symmetry, containing 20 and 12 atoms,
respectively. For Ar$_n$Au$^+$, with $\sigma$* $\approx$ 0.67, one would expect
a solvation shell of octahedral symmetry, in agreement with an enhanced ion
abundance at $n$ = 6. Another anomaly in the ion abundance at Ar$_9$Au$^+$
matches a local maximum in its computed dissociation energy.


  We propose to explain the recent observations of GRB early X-ray afterglows
with SWIFT by the dissipation of energy in the reverse shock which crosses the
ejecta as it is decelerated by the burst environment. We compute the evolution
of the dissipated power and discuss the possibility that a fraction of it can
be radiated in the X-ray range. We show that this reverse shock contribution
behaves in a way very similar to the observed X-ray afterglows if the following
two conditions are satisfied: (i) the Lorentz factor of the material which is
ejected during the late stages of source activity decreases to small values
Gamma < 10 and (ii) a large part of the shock dissipated energy is transferred
to a small fraction (zeta < 0.1) of the electron population. We also discuss
how our results may help to solve some puzzling problems raised by
multiwavelength early afterglow observations such as the presence of chromatic
breaks.


  We explore the behavior of micron-scale autophoretic Janus (Au/Pt) rods,
having various Au/Pt length ratios, swimming near a wall in an imposed
background flow. We find that their ability to robustly orient and move
upstream, i.e. to rheotax, depends strongly on the Au/Pt ratio, which is easily
tunable in synthesis. Numerical simulations of swimming rods actuated by a
surface slip show a similar rheotactic tunability when varying the location of
the surface slip versus surface drag. Slip location determines whether swimmers
are Pushers (rear-actuated), Pullers (front-actuated), or in between. Our
simulations and modeling show that Pullers rheotax most robustly due to their
larger tilt angle to the wall, which makes them responsive to flow gradients.
Thus, rheotactic response infers the nature of difficult to measure flow-fields
of an active particle, establishes its dependence on swimmer type, and shows
how Janus rods can be tuned for flow responsiveness. We demonstrate the
effectiveness of a simple geometric sieve for rheotactic ability.


  Young stellar populations provide a record of past star formation, and by
establishing their members' dynamics and ages, it is possible to reconstruct
the full history of star formation events. Gaia has greatly expanded the number
of accessible stellar populations, with one of the most notable
recently-discovered associations being Cepheus Far North (CFN), a population
containing hundreds of members spanning over 100 pc. With its proximity (d
$\lesssim$ 200 pc), apparent substructure, and relatively small population, CFN
represents a manageable population to study in depth, with enough evidence of
internal complexity to produce a compelling star formation story. Using Gaia
astrometry and photometry combined with additional spectroscopic observations,
we identify over 500 candidate CFN members spread across 7 subgroups. Combining
ages from isochrones, asteroseismology, dynamics, and lithium depletion, we
produce well-constrained ages for all seven subgroups, revealing a largely
continuous 10 Myr star formation history in the association. By tracing back
the present-day populations to the time of their formation, we identify two
spatially and dynamically distinct nodes in which stars form, one associated
with $\beta$ Cephei which shows mostly co-spatial formation, and one associated
with EE Draconis with a more dispersed star formation history. This detailed
view of star formation demonstrates the complexity of the star formation
process, even in the smallest of regions.


  We present broad-band mid-resolution X-Shooter/VLT spectra for four brown
dwarfs of the TW Hya association. Our targets comprise substellar analogs
representing the different evolutionary phases in young stellar evolution: For
the two diskless brown dwarfs, TWA-26 and TWA-29, we determine the stellar
parameters and we study their chromospheric emission line spectrum. For the two
accreting brown dwarfs, TWA-27 and TWA-28, we estimate the mass accretion rates
from empirical correlations between emission line luminosities and the
accretion luminosity.


  Large language models are playing an increasingly significant role in
molecular research, yet existing models often generate erroneous information,
posing challenges to accurate molecular comprehension. Traditional evaluation
metrics for generated content fail to assess a model's accuracy in molecular
understanding. To rectify the absence of factual evaluation, we present
MoleculeQA, a novel question answering (QA) dataset which possesses 62K QA
pairs over 23K molecules. Each QA pair, composed of a manual question, a
positive option and three negative options, has consistent semantics with a
molecular description from authoritative molecular corpus. MoleculeQA is not
only the first benchmark for molecular factual bias evaluation but also the
largest QA dataset for molecular research. A comprehensive evaluation on
MoleculeQA for existing molecular LLMs exposes their deficiencies in specific
areas and pinpoints several particularly crucial factors for molecular
understanding.


  It was recently observed in [1], that in index coding, learning the coding
matrix used by the server can pose privacy concerns: curious clients can
extract information about the requests and side information of other clients.
One approach to mitigate such concerns is the use of $k$-limited-access schemes
[1], that restrict each client to learn only part of the index coding matrix,
and in particular, at most $k$ rows. These schemes transform a linear index
coding matrix of rank $T$ to an alternate one, such that each client needs to
learn at most $k$ of the coding matrix rows to decode its requested message.
This paper analyzes $k$-limited-access schemes. First, a worst-case scenario,
where the total number of clients $n$ is $2^T-1$ is studied. For this case, a
novel construction of the coding matrix is provided and shown to be
order-optimal in the number of transmissions. Then, the case of a general $n$
is considered and two different schemes are designed and analytically and
numerically assessed in their performance. It is shown that these schemes
perform better than the one designed for the case $n=2^T-1$.


  A sequence $A$ of elements an additive group $G$ is {\it incomplete} if there
exists a group element that {\it can not} be expressed as a sum of elements
from $A$. The study of incomplete sequences is a popular topic in combinatorial
number theory. However, the structure of incomplete sequences is still far from
being understood, even in basic groups. The main goal of this paper is to give
a characterization of incomplete sequences in the vector space $F_p^d$, where
$d$ is a fixed integer and $p$ is a large prime. As an application, we give a
new proof for a recent result by Gao-Ruzsa-Thangadurai on the Olson's constant
of $\F_p^2$ and partially answer their conjecture concerning $F_p^3$.


  In a recent paper by Guglielmi and Hairer (SIADS 2015), an analysis in the
$\varepsilon\to 0$ limit was proposed of regularized discontinuous ODEs in
codimension-2 switching domains; this was obtained by studying a certain
2-dimensional system describing the so-called hidden dynamics. In particular,
the existence of a unique limit solution was not proved in all cases, a few of
which were labeled as ambiguous, and it was not clear whether or not the
ambiguity could be resolved. In this paper, we show that it cannot be resolved
in general. A first contribution of this paper is an illustration of the
dependence of the limit solution on the form of the switching function.
Considering the parameter dependence in the ambiguous class of discontinuous
systems, a second contribution is a bifurcation analysis, revealing a range of
possible behaviors. Finally, we investigate the sensitivity of solutions in the
transition from codimension-2 domains to codimension-3 when there is a limit
cycle in the hidden dynamics.


  We link the spontaneous breakdown of chiral symmetry in Euclidean QCD to the
collision of spectral shock waves in the vicinity of zero eigenvalue of Dirac
operator. The mechanism, originating from complex Burger's-like equation for
viscid, pressureless, one-dimensional flow of eigenvalues, is similar to
recently observed weak-strong coupling phase transition in large $N_c$
Yang-Mills theory. The spectral viscosity is proportional to the inverse of the
size of the random matrix that replaces the Dirac operator in the universal
(ergodic) regime. We obtain the exact scaling function and critical exponents
of the chiral phase transition for the averaged characteristic polynomial for
$N_c \ge3$ QCD. We reinterpret our results in terms of known properties of
chiral random matrix models and lattice data.


  Aerial vehicles have recently attracted significant attention in a variety of
commercial and civilian applications due to their high mobility, flexible
deployment and cost-effectiveness. To leverage these promising features, the
aerial users have to satisfy two critical requirements: First, they have to
maintain a reliable communication link to the ground base stations (GBSs)
throughout their flights, to support command and control data flows. Second,
the aerial vehicles have to minimize their propulsion power consumption to
remain functional until the end of their mission. In this paper, we study the
trajectory optimization problem for an aerial user flying over an area
including a set of GBSs. The objective of this problem is to find the
trajectory of the aerial user so that the total propulsion-related power
consumption of the aerial user is minimized while a cellular-connectivity
constraint is satisfied. This problem is a non-convex mixed integer non-linear
problem and hence, it is challenging to find the solution. To deal with, first,
the problem is relaxed and reformulated to a more mathematically tractable
form. Then, using successive convex approximation (SCA) technique, an iterative
algorithm is proposed to convert the problem into a sequence of convex problems
which can be solved efficiently.


  This paper presents the design, analysis, and performance evaluation of
RicMonk, a novel three-link brachiation robot equipped with passive hook-shaped
grippers. Brachiation, an agile and energy-efficient mode of locomotion
observed in primates, has inspired the development of RicMonk to explore
versatile locomotion and maneuvers on ladder-like structures. The robot's
anatomical resemblance to gibbons and the integration of a tail mechanism for
energy injection contribute to its unique capabilities. The paper discusses the
use of the Direct Collocation methodology for optimizing trajectories for the
robot's dynamic behaviors and stabilization of these trajectories using a
Time-varying Linear Quadratic Regulator. With RicMonk we demonstrate
bidirectional brachiation, and provide comparative analysis with its
predecessor, AcroMonk - a two-link brachiation robot, to demonstrate that the
presence of a passive tail helps improve energy efficiency. The system design,
controllers, and software implementation are publicly available on GitHub and
the video demonstration of the experiments can be viewed YouTube.


  Objectivity constitutes one of the main features of the macroscopic classical
world. An important aspect of the quantum-to-classical transition issue is to
explain how such a property arises from the microscopic quantum world.
Recently, within the framework of open quantum systems, there has been proposed
such a mechanism in terms of the, so-called, Spectrum Broadcast Structures.
These are multipartite quantum states of the system of interest and a part of
its environment, assumed to be under an observation. This approach requires a
departure from the standard open quantum systems methods, as the environment
cannot be completely neglected. In the present work we study the emergence of
such a state-structures in one of the canonical models of the condensed matter
theory: Spin-boson model, describing the dynamics of a two-level system coupled
to an environment made up by a large number of harmonic oscillators. We pay
much attention to the behavior of the model in the non-Markovian regime, in
order to provide a testbed to analyze how the non-Markovian nature of the
evolution affects the surfacing of a spectrum broadcast structure.


  We consider the algebras $M_p$ of Fourier multipliers and show that every
bounded continuous function $f$ on $\mathbb R^d$ can be transformed by an
appropriate homeomorphic change of variable into a function that belongs to
$M_p(\mathbb R^d)$ for all $p$, $1<p<\infty$. Moreover, under certain
assumptions on a family $K$ of continuous functions, one change of variable
will suffice for all $f\in K$. A similar result holds for functions on the
torus $\mathbb T^d$. This may be contrasted with the known result on the Wiener
algebra, related to Luzin's rearrangement problem.


  Gravitational microlensing is a key probe of the nature of dark matter and
its distribution on the smallest scales. For many practical purposes,
confronting theory to observation requires to model the probability that a
light source is highly amplified by many-lens systems. This article reviews
four simple analytic models of the amplification probability distribution,
based on different approximations: (i) the strongest-lens model; (ii) the
multiplicative model, where the total amplification is assumed to be the
product of all the lenses' individual amplifications; (iii) a hybrid version of
the previous two; and (iv) an empirical fitting function. In particular, a new
derivation of the multiplicative amplification distribution is proposed,
thereby correcting errors in the literature. Finally, the accuracy of these
models is tested against ray-shooting simulations. They all produce excellent
results as long as lenses are light and rare (low optical depth); however, for
larger optical depths, none of them succeeds in capturing the relevant features
of the amplification distribution. This conclusion emphasizes the crucial role
of lens-lens coupling at large optical depths.


  We study cold fermionic atoms using the holographic principle. We note that
current atomic experiments with massive fermions trapped in a harmonic
potential in the unitarity limit behave as massless fermions thanks to the
Thomas-Fermi approximation. We map the thermodynamics of strongly correlated
massless fermion to that of the charged black hole and study the thermodynamics
and transport properties of cold fermions at strong coupling at finite
temperature and density. In cold limit, the specific heat of charged black hole
is linear in $T$ independent of the dimensionality, which is reminiscent of
Fermi liquids. The shear viscosity per particle is shown to be finite as a
consequence of the non-vanishing of the entropy. We show that our holographic
results compare favorably with most of the current atomic data.


  We construct $R$-matrices (with a multidimensional spectral parameter) that
include additive as well as non-additive parameters. They satisfy the colored
Yang-Baxter equation. The solutions depend on a set of commuting operators.
They change with the representation of the latter. The associated Yang-Baxter
algebra and the spectrum of the transfer matrix are also studied.


  New expansionary and rotational quadratic forms are constructed for
$E^n$-endomorphisms. Relations amongst the various eigenvalues, eigendirections
and matrix invariants are established, including propositions on complexity and
geometric multiplicity. The underlying construction involves a novel,
almost-orthogonal expansion based on two-plane rotations. The development is
strongly geometric in flavour and has application to the theory of connections,
of which the Frenet case on $E^3$ is given as a model.


  In this paper we present in-situ satellite data, theory and laboratory
validation that show how small scale collisionless shocks and
mini-magnetospheres can form on the electron inertial scale length. The
resulting retardation and deflection of the solar wind ions could be
responsible for the unusual "lunar swirl" patterns seen on the surface of the
Moon.


  Principal component analysis (PCA) and related techniques have been
successfully employed in natural language processing. Text mining applications
in the age of the online social media (OSM) face new challenges due to
properties specific to these use cases (e.g. spelling issues specific to texts
posted by users, the presence of spammers and bots, service announcements,
etc.). In this paper, we employ a Robust PCA technique to separate typical
outliers and highly localized topics from the low-dimensional structure present
in language use in online social networks. Our focus is on identifying
geospatial features among the messages posted by the users of the Twitter
microblogging service. Using a dataset which consists of over 200 million
geolocated tweets collected over the course of a year, we investigate whether
the information present in word usage frequencies can be used to identify
regional features of language use and topics of interest. Using the PCA pursuit
method, we are able to identify important low-dimensional features, which
constitute smoothly varying functions of the geographic location.


  A small fraction of fast radio bursts (FRBs) have been observed with multiple
bursts, whereas most Galactic sources emitting radio pulses are known to
repeat. Here we present the results of follow-up observations of two FRBs and
four rotating radio transients (RRATs). Among these, only one RRAT has been
observed with repeating pulses, with an estimated period of around 1.297047 s.
For comparison, we reanalysed the Parkes archival follow-up observations in
CSIRO's data archive for all apparently one-off sources discovered by the
Parkes telescopes, including 13 RRATs and 29 FRBs. In total, 3 RRATs are
suggested to be repeaters, but no repeating signals were detected from the
other sources. Reporting details of the non-detection observations for the
apparently one-off sources would help investigate their origins, and
catastrophic scenarios are worth proposing for both extragalactic and Galactic
sources.


  Well-known and newly developed renormalization schemes for $\tan\beta$ are
analyzed in view of three desirable properties: gauge independence, process
independence, and numerical stability in perturbation theory. Arguments are
provided that no scheme can meet all three requirements, and as an
illustration, a ``No-Go-Theorem'' for the renormalization of $\tan\beta$ is
established. Nevertheless, two particularly attractive schemes emerge. A
discussion about which scheme might be the best compromise in practice is
given.


  We introduce the class of split Lie-Rinehart algebras as the natural
extension of the one of split Lie algebras. We show that if $L$ is a tight
split Lie-Rinehart algebra over an associative and commutative algebra $A,$
then $L$ and $A$ decompose as the orthogonal direct sums $L = \bigoplus_{i \in
I}L_i$, $A = \bigoplus_{j \in J}A_j$, where any $L_i$ is a nonzero ideal of
$L$, any $A_j$ is a nonzero ideal of $A$, and both decompositions satisfy that
for any $i \in I$ there exists a unique $\tilde{i} \in J$ such that
$A_{\tilde{i}}L_i \neq 0$. Furthermore any $L_i$ is a split Lie-Rinehart
algebra over $A_{\tilde{i}}$. Also, under mild conditions, it is shown that the
above decompositions of $L$ and $A$ are by means of the family of their,
respective, simple ideals.


  The ALICE experiment at CERN LHC is specifically designed for investigating
heavy ion collisions. The upgraded ALICE accommodates a tenfold increase in
PbPb luminosity and a two-order of magnitude surge in minimum bias events. To
address the challenges of high detector occupancy and event pile-ups, advanced
multidimensional data analysis techniques, including machine learning (ML), are
indispensable. Despite ML popularity, the complexity of its models presents
interpretation challenges, and oversimplification in analysis often leads to
inaccuracies.
  Our objective was to develop RootInteractive, a tool for multidimensional
statistical analysis. This tool simplifies data analysis across dimensions,
visualizes functions with uncertainties, and validates assumptions and
approximations. In RootInteractive, it is crucial to easily define the
functional composition of analytical parametric and non-parametric functions,
exploit symmetries, and define multidimensional invariant functions and
corresponding alarms.
  RootInteractive adopts a declarative programming paradigm, ensuring
userfriendliness for experts, students, and educators. It facilitates
interactive visualization, n-dimensional histogramming/projection, and
information extraction on both Python,C++ server and client. Data compression,
datasets with O(10 to 7) entries and O(25) attributes can be interactively
analyzed in a browser with O(0.500-1 GB) size. Representative downsampling and
reweighting/pre-aggregation enable the effective analysis of one year of ALICE
data for various purposes.


  We evaluate the mass polarization term of the kinetic-energy operator for
different three-body nuclear $AAB$ systems by employing the method of Faddeev
equations in configuration space. For a three-boson system this term is
determined by the difference of the doubled binding energy of the $AB$
subsystem $2E_{2}$ and the three-body binding energy $E_{3}(V_{AA}=0)$ when the
interaction between the identical particles is omitted. In this case:
$\left\vert E_{3}(V_{AA}=0)\right\vert >2\left\vert E_{2}\right\vert$. In the
case of a system complicated by isospins(spins), such as the kaonic clusters $
K^{-}K^{-}p$ and $ppK^{-}$, the similar evaluation impossible. For these
systems it is found that $\left\vert E_{3}(V_{AA}=0)\right\vert <2\left\vert
E_{2}\right\vert$. A model with an $AB$ potential averaged over spin(isospin)
variables transforms the later case to the first one. The mass polarization
effect calculated within this model is essential for the kaonic clusters.
Besides we have obtained the relation $|E_3|\le |2E_2|$ for the binding energy
of the kaonic clusters.


  Using unreliable or noisy components for reliable communication requires
error correction. But which noise processes can support information
transmission, and which are too destructive? For classical systems any channel
whose output depends on its input has the capacity for communication, but the
situation is substantially more complicated in the quantum setting. We find a
generic test for incapacity based on any suitable forbidden transformation---a
protocol for communication with a channel passing our test would also allow us
to implement the associated forbidden transformation. Our approach includes
both known quantum incapacity tests---positive partial transposition (PPT) and
antidegradability (no cloning)---as special cases, putting them both on the
same footing. We also find a physical principle explaining the
nondistillability of PPT states: Any protocol for distilling entanglement from
such a state would also give a protocol for implementing the forbidden
time-reversal operation.


  This paper introduces GLOBE, a high-quality English corpus with worldwide
accents, specifically designed to address the limitations of current zero-shot
speaker adaptive Text-to-Speech (TTS) systems that exhibit poor
generalizability in adapting to speakers with accents. Compared to commonly
used English corpora, such as LibriTTS and VCTK, GLOBE is unique in its
inclusion of utterances from 23,519 speakers and covers 164 accents worldwide,
along with detailed metadata for these speakers. Compared to its original
corpus, i.e., Common Voice, GLOBE significantly improves the quality of the
speech data through rigorous filtering and enhancement processes, while also
populating all missing speaker metadata. The final curated GLOBE corpus
includes 535 hours of speech data at a 24 kHz sampling rate. Our benchmark
results indicate that the speaker adaptive TTS model trained on the GLOBE
corpus can synthesize speech with better speaker similarity and comparable
naturalness than that trained on other popular corpora. We will release GLOBE
publicly after acceptance. The GLOBE dataset is available at
https://globecorpus.github.io/.


  It is shown how the theory of classical $W$--algebras can be formulated on a
higher genus Riemann surface in the spirit of Krichever and Novikov. An
intriguing relation between the theory of $A_1$ embeddings into simple Lie
algebras and the holomorphic geometry of Riemann surfaces is exihibited.


  This paper develops a modified version of the Boltzmann equation for
micro-scale particulate flow with capture and diffusion that describes the
colloidal-suspension-nano transport in porous media. An equivalent sink term is
introduced into the kinetic equation instead of non-zero initial data,
resulting in the solution of an operator equation in the Fourier space and an
exact homogenization. The upper scale equation is obtained in closed form
together with explicit formulae for the large-scale model coefficients in terms
of the micro-scale parameters. The upscaling reveals the delay in particle
transport if compared with the carrier water velocity, which is a collective
effect of the particle capture and diffusion. The derived governing equation
generalizes the current models for suspension-colloidal-nano transport in
porous media.


  Let $f$ be an invertible transitive subshift of finite type over a bilateral
symbol space $X$, let $\mu$ be a Gibbs measure for $f$ determined by a H\"older
continuous potential on $X$, and let $A$ be an invertible continuous linear
cocycle over $f$ acting on a continuous $\R^d$-bundle $E$ over $X$ with
Lyapunov exponents $\lambda_k < \lambda_{k-1} < \ldots < \lambda_1$ such that
$A^{-1}$ is continuous as well. We prove that if the Oseledets flags $F_j(x) =
E_j(x) \oplus E_{j-1}(x) \oplus \cdots \oplus E_1(x)$ depend upper
semi-continuously on $x \in X$, then there exists a Pesin set with
exponentially small tails for $\mu$.


  We investigate the amount of scatter in the Tully-Fisher relation (TFR) when
using optical long-slit H-alpha rotation curves to determine the velocity
widths of spiral galaxies. We study a sample of 25 galaxies in the Coma region
of the sky which were shown in Bernstein et al. (1994) to exhibit an
extraordinarily low scatter of 0.10 mag RMS in the I magnitude vs 21-cm width
TFR. Using the same I magnitudes with new widths derived from high-quality
H-alpha rotation curves, we measure an RMS scatter of 0.14 mag in the TFR. This
suggests that measurement errors and ``astrophysical errors'' (such as
non-circular gas motion) on the H-alpha velocity widths are below 6%, and
optical widths are nearly as good for TFR studies as 21-cm widths. The scatter
and form of the TFR are found to be robust under choice of velocity
width-extraction algorithm, as long as the central portions of the optical
rotation curve are ignored and low-S/N points are not weighted too heavily. In
this small sample there is no evidence that rotation curve shapes vary
systematically with rotation velocity, nor that rotation curve shape can be
used to reduce the scatter in the TFR.


  I argue that scattering theory for massless particles in Minkowski space
should be reformulated as a mapping between past and future representations of
an algebra of densities on the conformal boundary. These densities are best
thought of as living on the momentum space light cone dual to null infinity,
which describes the simultaneous eigenstates of the BMS generators. The
currents describe the flow of other quantum numbers through the holographic
screen at infinity. They are operator valued measures on the momentum light
cone, with non-zero support at $P = 0$, which is necessary to describe finite
flows of total momentum, with zero energy-momentum density, on the asymptotic
holographic screen. Jet states, the closest approximation to the conventional
notion of asymptotic particle state, have finite momentum flowing out through
spherical caps of finite opening angle, with the zero momentum currents
vanishing in annuli surrounding these caps. Although these notions are valid
both in field theory and quantum gravity, I'll argue that they form the basis
for understanding the holographic/covariant entropy principle in the latter
framework, where the densities form a complete set of operators. The variables
on a finite area holographic screen are restrictions of those at infinity. The
restriction is implemented by a cutoff on the Euclidean Dirac spectrum on the
screen, which is a generalized UV/IR correspondence.


  We consider the secure transmission in ergodic fast-Rayleigh fading
multiple-input single-output single-antennaeavesdropper (MISOSE) wiretap
channels. We assume that the statistics of both the legitimate and eavesdropper
channels is the only available channel state information at the transmitter
(CSIT). By introducing a new secrecy capacity upper bound, we prove that the
secrecy capacity is achieved by Gaussian input without prefixing. To attain
this, we form another MISOSE channel for upper-bounding, and tighten the bound
by finding the worst correlations between the legitimate and eavesdropper
channel coefficients. The resulting upper bound is tighter than the others in
the literature which are based on modifying the correlation between the noises
at the legitimate receiver and eavesdropper. Next, we fully characterize the
ergodic secrecy capacity by showing that the optimal channel input covariance
matrix is a scaled identity matrix, with the transmit power allocated uniformly
among the antennas. The key to solve such a complicated stochastic optimization
problem is by exploiting the completely monotone property of the ergodic
secrecy capacity to use the stochastic ordering theory. Finally, our simulation
results show that for the considered channel setting, the secrecy capacity is
bounded in both the high signal-to-noise ratio and large number of transmit
antenna regimes.


  A rank-select index for a sequence $B=(b_1,\ldots,b_n)$ of $n$ bits is a data
structure that, if provided with an operation to access $\Theta(\log n)$
arbitrary consecutive bits of $B$ in constant time (thus $B$ is stored outside
of the data structure), can compute $\mathit{rank}_B(j)=\sum_{i=1}^j b_i$ for
given $j\in\{0,\ldots,n\}$ and
$\mathit{select}_B(k)=\min\{j:\mathit{rank}_B(j)\ge k\}$ for given
$k\in\{1,\ldots,\sum_{i=1}^n b_i\}$. We describe a new rank-select index that,
like previous rank-select indices, occupies $O(n\log\log n/\log n)$ bits and
executes $\mathit{rank}$ and $\mathit{select}$ queries in constant time. Its
derivation is intended to be particularly easy to follow and largely free of
tedious low-level detail, its operations are given by straight-line code, and
we show that it can be constructed in $O(n/\log n)$ time.


  A new calorimeter for measurements of the AC heat capacity and magnetocaloric
effect of small samples in pulsed magnetic fields is discussed for the
exploration of thermal and thermodynamic properties at temperatures down to 2
K. We tested the method up to \mu 0H = 50 Tesla, but it could be extended to
higher fields. For these measurements we used carefully calibrated bare chip
Cernox\textregistered and RuO2 thermometers, and we present a comparison of
their performance. The monotonic temperature and magnetic field dependences of
the magneto resistance of RuO2 allow us to carry on precise thermometry with a
precision as good as \pm 1mK at T = 2 K. To test the performance of our
calorimeter, AC heat capacity and magnetocaloric effect for the spin-dimer
compound Sr3Cr2O8 and the triangular lattice antiferromagnet RbFe(MoO4)2 are
presented.


  One essential problem in skeleton-based action recognition is how to extract
discriminative features over all skeleton joints. However, the complexity of
the State-Of-The-Art (SOTA) models of this task tends to be exceedingly
sophisticated and over-parameterized, where the low efficiency in model
training and inference has obstructed the development in the field, especially
for large-scale action datasets. In this work, we propose an efficient but
strong baseline based on Graph Convolutional Network (GCN), where three main
improvements are aggregated, i.e., early fused Multiple Input Branches (MIB),
Residual GCN (ResGCN) with bottleneck structure and Part-wise Attention
(PartAtt) block. Firstly, an MIB is designed to enrich informative skeleton
features and remain compact representations at an early fusion stage. Then,
inspired by the success of the ResNet architecture in Convolutional Neural
Network (CNN), a ResGCN module is introduced in GCN to alleviate computational
costs and reduce learning difficulties in model training while maintain the
model accuracy. Finally, a PartAtt block is proposed to discover the most
essential body parts over a whole action sequence and obtain more explainable
representations for different skeleton action sequences. Extensive experiments
on two large-scale datasets, i.e., NTU RGB+D 60 and 120, validate that the
proposed baseline slightly outperforms other SOTA models and meanwhile requires
much fewer parameters during training and inference procedures, e.g., at most
34 times less than DGNN, which is one of the best SOTA methods.


  An autoencoder-based codec employs quantization to turn its bottleneck layer
activation into bitstrings, a process that hinders information flow between the
encoder and decoder parts. To circumvent this issue, we employ additional skip
connections between the corresponding pair of encoder-decoder layers. The
assumption is that, in a mirrored autoencoder topology, a decoder layer
reconstructs the intermediate feature representation of its corresponding
encoder layer. Hence, any additional information directly propagated from the
corresponding encoder layer helps the reconstruction. We implement this kind of
skip connections in the form of additional autoencoders, each of which is a
small codec that compresses the massive data transfer between the paired
encoder-decoder layers. We empirically verify that the proposed
hyper-autoencoded architecture improves perceptual audio quality compared to an
ordinary autoencoder baseline.


  The planetary system of TRAPPIST-1, discovered in 2016-2017, is a
treasure-trove of information. Thanks to a combination of observational
techniques, we have estimates of the radii and masses of the seven planets of
this very exotic system. With three planets within the traditional Habitable
Zone limits, it is one of the best constrained system of astrobiological
interest. I will review here the theoretical constraints we can put on this
system by trying to reconstruct its history: its atmospheric evolution which
depends on the luminosity evolution of the dwarf star, and its tidal dynamical
evolution. These constraints can then be used as hypotheses to assess the
habitability of the outer planets of the system with a Global Climate Model.


  In this second paper, I construct a limit space of a Cauchy sequence of
globally hyperbolic spacetimes. In the second section, I work gradually towards
a construction of the limit space. I prove the limit space is unique up to
isometry. I als show that, in general, the limit space has quite complicated
causal behaviour. This work prepares the final paper in which I shall study in
more detail properties of the limit space and the moduli space of (compact)
globally hyperbolic spacetimes (cobordisms). As a fait divers, I give in this
paper a suitable definition of dimension of a Lorentz space in agreement with
the one given by Gromov in the Riemannian case.


  A generalized theory unifying gravity with electromagnetism was proposed by
Einstein in 1945. He considered a Hermitian metric on a real space-time. In
this work we review Einstein's idea and generalize it further to consider
gravity in a complex Hermitian space-time.


  To study the properties of the interstellar medium in the prototypical
merging system of the Antennae galaxies (NGC 4038 and NGC 4039), we have
obtained CO(1-0), (2-1) and (3-2) line maps, as well as a map of the 870 micron
continuum emission. Our results are analysed in conjunction with data from
X-ray to radio wavelengths. In order to distinguish between exact coincidence
and merely close correspondence of emission features, we compare the
morphological structure of the different emission components at the highest
available angular resolution. To constrain the physical state of the molecular
gas, we apply models of photon dominated regions (PDRs) that allow us to fit CO
and [CII] data, as well as other indicators of widespread PDRs in the Antennae
system, particularly within the super giant molecular cloud (SGMC) complexes of
the interaction region (IAR) between the two galaxies. The modeled clouds have
cores with moderately high gas densities up to 4 10^4 / cm^3 and rather low
kinetic temperatures <=25K). At present, all these clouds, including those near
the galactic nuclei, show no signs of intense starburst activity. Thermal radio
or mid-infrared emission are all observed to peak slightly offset from the
molecular peaks. The total molecular gas mass of the Antennae system adds up to
\~10^10 M_sun. In the vicinity of each galactic nucleus, the moleculargas mass,
1-2 10^9 M_sun, exceeds that of the Galactic centre region by a factorof almost
100. Furthermore, the gas does not seem to deviate much from the N_{H_2}/I_CO
ratio typical of the disk of our Galaxy rather than our Galactic centre.


  As a top-down holographic approach, the D4/D8 model is expected to be the
holographic version of QCD since it almost includes all the elementary features
of QCD based on string theory. In this manuscript, we review the fundamental
properties of the D4/D8 model with respect to the D4-brane background,
embedding of flavor branes and holographic quark, gluon, meson, baryon and
glueball with various symmetries, then we also take a look at some interesting
applications and developments based on this model.


  In this paper, we confirm the Fino-Vezzoni Conjecture for unimodular Lie
algebras which contain abelian ideals of codimension two, a natural
generalization to the class of almost abelian Lie algebras. This provides new
evidence towards the validity of the conjecture on a very special type of
$3$-step solvmanifolds.


  We show that AdS/QCD generates predictions for the rate of diffractive rho
meson electroproduction that are in agreement with data collected at the HERA
electron-proton collider.


  Edema is a common symptom of kidney disease, and quantitative measurement of
edema is desired. This paper presents a method to estimate the degree of edema
from facial images taken before and after dialysis of renal failure patients.
As tasks to estimate the degree of edema, we perform pre- and post-dialysis
classification and body weight prediction. We develop a multi-patient
pre-training framework for acquiring knowledge of edema and transfer the
pre-trained model to a model for each patient. For effective pre-training, we
propose a novel contrastive representation learning, called weight-aware
supervised momentum contrast (WeightSupMoCo). WeightSupMoCo aims to make
feature representations of facial images closer in similarity of patient weight
when the pre- and post-dialysis labels are the same. Experimental results show
that our pre-training approach improves the accuracy of pre- and post-dialysis
classification by 15.1% and reduces the mean absolute error of weight
prediction by 0.243 kg compared with training from scratch. The proposed method
accurately estimate the degree of edema from facial images; our edema
estimation system could thus be beneficial to dialysis patients.


  For high throughput applications, turbo-like iterative decoders are
implemented with parallel architectures. However, to be efficient parallel
architectures require to avoid collision accesses i.e. concurrent read/write
accesses should not target the same memory block. This consideration applies to
the two main classes of turbo-like codes which are Low Density Parity Check
(LDPC) and Turbo-Codes. In this paper we propose a methodology which finds a
collision-free mapping of the variables in the memory banks and which optimizes
the resulting interleaving architecture. Finally, we show through a pedagogical
example the interest of our approach compared to state-of-the-art techniques.


  We consider an arbitrary representation of the additive group over a field of
characteristic zero and give an explicit description of a finite separating set
in the corresponding ring of invariants.


  The Fe1+y Te1-x Sex compounds belong to the family of iron-based high
temperature superconductors, in which superconductivity often appears upon
doping antiferromagnetic parent compounds. Unlike other Fe-based
superconductors (in which the antiferromagnetic order is at the Fermi surface
nesting wavevector [1/2,1/2,1]), the Fe1+y Te1-x Sex parent compound Fe1+y Te
orders at a different wavevector, [1/2, 0, 1/2]. Furthermore, the ordering
wavevector depends on y, the occupation of interstitial sites with excess iron;
the origin of this behavior is controversial. Using inelastic neutron
scattering on Fe1.08 Te, we find incommensurate magnetic fluctuations above the
Neel temperature, even though the ordered state is bicollinear and commensurate
with gapped spin waves. This behavior can be understood in terms of a
competition between commensurate and incommensurate order, which we explain as
a lock-in transition caused by the magnetic anisotropy.


  Multi-layer Ti3C2Tx coatings have demonstrated an outstanding wear
performance with excellent durability due to beneficial tribo-layers formed.
However, the involved formation processes dependent on the tribological
conditions and coating thickness are yet to be fully explored. Therefore, we
spray-coated Ti3C2Tx multi-layer particles onto stainless steel substrates to
create coatings with two different thicknesses and tested their solid
lubrication performance with different normal loads (100 and 200 mN) and
sliding frequencies (1 and 2.4 Hz) using linear-reciprocating ball-on-disk
tribometry. We demonstrate that MXenes' tribological performance depends on
their initial state (delaminated few-layer vs. multi-layer particles), coating
thickness, applied load and sliding frequency. Specifically, the best behavior
is observed for thinner multi-layer coatings tested at the lower frequency. In
contrast, coatings made of delaminated few-layer MXene are not as effective as
their multi-layer counterparts. Our high-resolution interface characterization
by transmission electron microscopy revealed unambiguous differences regarding
the uniformity and chemistry of the formed tribo-layers as well as the degree
of tribo-induced MXenes' exfoliation. Atomistic insights into the exfoliation
process and molecular dynamic simulations quantitatively backed up our
experimental results regarding coating thickness and velocity dependency. This
ultimately demonstrates that MXenes' tribological performance is governed by
the underlying tribo-chemistry and their exfoliation ability during rubbing.


  We have designed honeycomb lattices for microwave photons with a frequency
imbalance between the two sites in the unit cell. This imbalance is the
equivalent of a mass term that breaks the lattice inversion symmetry. At the
interface between two lattices with opposite imbalance, we observe topological
valley edge states. By imaging the spatial dependence of the modes along the
interface, we obtain their dispersion relation that we compare to the
predictions of an ab initio tight-binding model describing our microwave
photonic lattices.


  In the paper, frameworks for electronic shopping of composite (modular)
products are described: (a) multicriteria selection (product is considered as a
whole system, it is a traditional approach), (b) combinatorial synthesis
(composition) of the product from its components, (c) aggregation of the
product from several selected products/prototypes. The following product model
is examined: (i) general tree-like structure, (ii) set of system
parts/components (leaf nodes), (iii) design alternatives (DAs) for each
component, (iv) ordinal priorities for DAs, and (v) estimates of compatibility
between DAs for different components. The combinatorial synthesis is realized
as morphological design of a composite (modular) product or an extended
composite product (e.g., product and support services as financial
instruments). Here the solving process is based on Hierarchical Morphological
Multicriteria Design (HMMD): (i) multicriteria selection of alternatives for
system parts, (ii) composing the selected alternatives into a resultant
combination (while taking into account ordinal quality of the alternatives
above and their compatibility). The aggregation framework is based on
consideration of aggregation procedures, for example: (i) addition procedure:
design of a products substructure or an extended substructure ('kernel') and
addition of elements, and (ii) design procedure: design of the composite
solution based on all elements of product superstructure. Applied numerical
examples (e.g., composite product, extended composite product, product repair
plan, and product trajectory) illustrate the proposed approaches.


  The central idea of this work is the concept of prespace, a hypothetical
structure that is postulated to underlie the fabric of space or space-time. I
consider how such a structure could relate to space and space-time, and the
implications of the existence of this structure for quantum theory. I compare
space and space-time to other spaces used in physics, such as configuration
space, phase space, and Hilbert space. I support the 'property view' of space,
opposing both the traditional views of space and space-time, substantivalism
and relationism. I argue that configuration space has a special status in the
microscopic world similar to the status of position space in the macroscopic
world. The prespace structure is compared with a computational system, in
particular to a cellular automaton, in which space and all physical quantities
are broken into discrete units. One way open for a prespace metaphysics can be
found if physics is made fully discrete. I suggest as a heuristic principle
that the physical laws of our world are such that the computational cost of
implementing those laws on an arbitrary computational system is minimized. I
discuss the 'measurement problem' of quantum mechanics. Considering how quantum
theory could be made fully discrete leads naturally to a suggestion of how
standard linear quantum mechanics could be modified to give a solution to the
measurement problem, calling this model Critical Complexity Quantum Mechanics
(CCQM). I compare CCQM with some other proposed solutions to the measurement
problem, in particular, the spontaneous localization model of Ghirardi, Rimini,
and Weber. Finally, I argue that the measure of the complexity of quantum
mechanical states introduced in CCQM also provides a new definition of entropy
for quantum mechanics, and suggests an objective foundation for statistical
mechanics, thermodynamics, and the arrow of time.


  Crilin (Crystal Calorimeter with Longitudinal Information) is a
semi-homogeneous, longitudinally segmented electromagnetic calorimeter based on
high-$Z$, ultra-fast crystals with UV-extended SiPM readout. The Crilin design
has been proposed as a candidate solution for both a future Muon Collider
barrel ECAL and for the Small Angle Calorimeter of the HIKE experiment. As a
part of the Crilin development program, we have carried out beam tests of small
($10\times10\times40$~mm$^3$) lead fluoride (PbF$_2$) and ultra-fast lead
tungstate (PbWO$_4$, PWO) crystals with 120~GeV electrons at the CERN SPS to
study the light yield, timing response, and systematics of light collection
with a proposed readout scheme. For a single crystal of PbF$_2$, corresponding
to a single Crilin cell, a time resolution of better than 25~ps is obtained for
$>$3 GeV of deposited energy. For a single cell of \pwo, a time resolution of
better than 45~ps is obtained for the same range of deposited energy. This
timing performance fully satisfies the design requirements for the Muon
Collider and HIKE experiments. Further optimizations of the readout scheme and
crystal surface preparation are expected to bring further improvements.


  Let $a$ be a real euclidean vector space of finite dimension and $\Sigma$ a
root system in $a$ with a basis $\Delta$. Let $\Theta \subset \Delta$ and $M =
M_{\Theta}$ be a standard Levi of a reductive group $G$ such that $a_\Theta =
a_M / a_G$. Let us denote $d$ the dimension of $a_\Theta$, i.e the cardinal of
$\Delta - \Theta$ and $\Sigma_{\Theta}$ the set of all non-trivial projections
of roots in $\Sigma$. We obtain conditions on $\Theta$ such that
$\Sigma_\Theta$ contains a root system of rank $d$.


  Let $S$ be a set of arbitrary objects, and let $s\mapsto s'$ be a permutation
of $S$ such that $s"=(s')'=s$ and $s'\neq s$. Let $S^d=\{v_1...v_d\colon v_i\in
S\}$. Two words $v,w\in S^d$ are dichotomous if $v_i=w'_i$ for some $i\in [d]$,
and they form a twin pair if $v_i'=w_i$ and $v_j=w_j$ for every $j\in
[d]\setminus \{i\}$. A polybox code is a set $V\subset S^d$ in which every two
words are dichotomous. A polybox code $V$ is a cube tiling code if $|V|=2^d$. A
$2$-periodic cube tiling of $\mathbb{R}^d$ and a cube tiling of flat torus
$\mathbb{T}^d$ can be encoded in a form of a cube tiling code. A twin pair
$v,w$ in which $v_i=w_i'$ is glue (at the $i$th position) if the pair $v,w$ is
replaced by one word $u$ such that $u_j=v_j=w_j$ for every $j\in [d]\setminus
\{i\}$ and $u_i=*$, where $*\not\in S$ is some extra fixed symbol. A word $u$
with $u_i=*$ is cut (at the $i$th position) if $u$ is replaced by a twin pair
$q,t$ such that $q_i=t_i'$ and $u_j=q_j=t_j$ for every $j\in [d]\setminus
\{i\}$. If $V,W\subset S^d$ are two cube tiling codes and there is a sequence
of twin pairs which can be interchangeably gluing and cutting in a way which
allows us to pass from $V$ to $W$, then we say that $W$ is obtained from $V$ by
gluing and cutting. In the paper it is shown that for every two cube tiling
codes in dimension six one can be obtained from the other by gluing and
cutting.


  We consider the optimal control of singular nonlinear partial differential
equation which is the distributional formulation of the multiphase Stefan type
free boundary problem for the general second order parabolic equation. Boundary
heat flux is the control parameter, and the optimality criteria consist of the
minimization of the $L_2$-norm declination of the trace of the solution to the
PDE problem at the final moment from the given measurement. Sequence of
finite-dimensional optimal control problems is introduced through finite
differences. We establish existence of the optimal control and prove the
convergence of the sequence of discrete optimal control problems to the
original problem both with respect to functional and control. Proofs rely on
establishing a uniform $L_{\infty}$ bound, and $W_2^{1,1}$-energy estimate for
the discrete nonlinear PDE problem with discontinuous coefficient.


  Magnetic Resonance Imaging (MRI) is a widely used medical imaging technique,
but its long acquisition time can be a limiting factor in clinical settings. To
address this issue, researchers have been exploring ways to reduce the
acquisition time while maintaining the reconstruction quality. Previous works
have focused on finding either sparse samplers with a fixed reconstructor or
finding reconstructors with a fixed sampler. However, these approaches do not
fully utilize the potential of joint learning of samplers and reconstructors.
In this paper, we propose an alternating training framework for jointly
learning a good pair of samplers and reconstructors via deep reinforcement
learning (RL). In particular, we consider the process of MRI sampling as a
sampling trajectory controlled by a sampler, and introduce a novel
sparse-reward Partially Observed Markov Decision Process (POMDP) to formulate
the MRI sampling trajectory. Compared to the dense-reward POMDP used in
existing works, the proposed sparse-reward POMDP is more computationally
efficient and has a provable advantage. Moreover, the proposed framework,
called L2SR (Learning to Sample and Reconstruct), overcomes the training
mismatch problem that arises in previous methods that use dense-reward POMDP.
By alternately updating samplers and reconstructors, L2SR learns a pair of
samplers and reconstructors that achieve state-of-the-art reconstruction
performances on the fastMRI dataset. Codes are available at
\url{https://github.com/yangpuPKU/L2SR-Learning-to-Sample-and-Reconstruct}.


  Pre-trained language models have recently emerged as a powerful tool for
fine-tuning a variety of language tasks. Ideally, when models are pre-trained
on large amount of data, they are expected to gain implicit knowledge. In this
paper, we investigate the ability of pre-trained language models to generalize
to different non-language tasks. In particular, we test them on tasks from
different domains such as computer vision, reasoning on hierarchical data, and
protein fold prediction. The four pre-trained models that we used, T5, BART,
BERT, and GPT-2 achieve outstanding results. They all have similar performance
and they outperform transformers that are trained from scratch by a large
margin. For instance, pre-trained language models perform better on the Listops
dataset, with an average accuracy of 58.7\%, compared to transformers trained
from scratch, which have an average accuracy of 29.0\%. The significant
improvement demonstrated across three types of datasets suggests that
pre-training on language helps the models to acquire general knowledge,
bringing us a step closer to general AI. We also showed that reducing the
number of parameters in pre-trained language models does not have a great
impact as the performance drops slightly when using T5-Small instead of
T5-Base. In fact, when using only 2\% of the parameters, we achieved a great
improvement compared to training from scratch. Finally, in contrast to prior
work, we find out that using pre-trained embeddings for the input layer is
necessary to achieve the desired results.


  The quantum phase transition in iron-based superconductors with 'half-Dirac'
node at the electron Fermi surface as a $T=0$ structural phase transition
described in terms of nematic order is discussed. An effective low energy
theory that describes half-Dirac nodal Fermions and their coupling to Ising
nematic order that describes the phase transition is derived and analyzed using
renormalization group (RG) study of the large-$N_f$ version of the theory. The
inherent absence of Lorentz invariance of the theory leads to RG flow structure
where the velocities $v_F$ and $v_\Delta$ at the paired half-Dirac nodes
($1\overline{1}$ and $2\overline{2}$) in general flow differently under RG,
implying that the nodal electron gap is deformed and the $C_4$ symmetry is
broken, explaining the structural (orthogonal to orthorhombic) phase transition
at the quantum critical point (QCP). The theory is found to have Gaussian fixed
point $\lambda^*=0, (v_{\Delta}/v_F)^*=0$ with stable flow lines toward it,
suggesting a second order nematic phase transition. Interpreting the
fermion-Ising nematic boson interaction as a decay process of nematic Ising
order parameter scalar field fluctuations into half-Dirac nodal fermions, I
find that the theory surprisingly behaves as systems with dynamical critical
exponent $z = 1$, reflecting undamped quantum critical dynamics and emergent
fully relativistic field theory arising from the non(fully)-relativistic field
theory and is direct consequence of $(v_{\Delta}/v_F)^*=0$ fixed point. The
nematic critical fluctuations lead to remarkable change to the spectral
function peak where at a critical point $\lambda_c$, directly related to
nematic QCP, the central spectral peak collapses and splits into satellite
spectral peaks around nodal point. The vanishing of the zero modes density of
states leads to the undamped $z=1$ quantum critical dynamics.


  Deep learning has revolutionized industries like computer vision, natural
language processing, and speech recognition. However, back propagation, the
main method for training deep neural networks, faces challenges like
computational overhead and vanishing gradients. In this paper, we propose a
novel instant parameter update methodology that eliminates the need for
computing gradients at each layer. Our approach accelerates learning, avoids
the vanishing gradient problem, and outperforms state-of-the-art methods on
benchmark data sets. This research presents a promising direction for efficient
and effective deep neural network training.


  Context. One of the most fundamental scaling relations in galaxies is
observed between metallicity and stellar mass -- the mass-metallicity relation
(MZR) -- although recently a stronger dependence of the gas-phase metallicity
with the galactic gravitational potential ($\Phi \rm ZR$) has been reported.
Further dependences of metallicity on other galaxy properties have been
revealed, with the star formation rate (SFR) being one of the most studied and
debated secondary parameters in the relation (the so-called fundamental
metallicity relation). Aims. In this work we explore the dependence of the
gas-phase metallicity residuals from the MZR and $\Phi \rm ZR$ on different
galaxy properties in the search for the most fundamental scaling relation in
galaxies. Methods. We applied a random forest regressor algorithm on a sample
of 3430 nearby star-forming galaxies from the SDSS-IV MaNGA survey. Using this
technique, we explored the effect of 147 additional parameters on the global
oxygen abundance residuals obtained after subtracting the MZR. Alternatively,
we followed a similar approach with the metallicity residuals from the $\Phi
\rm ZR$. Results. The stellar metallicity of the galaxy is revealed as the
secondary parameter in both the MZR and the $\Phi \rm ZR$, ahead of the SFR.
This parameter reduces the scatter in the relations $\sim 10-15\%$. We find the
3D relation between gravitational potential, gas metallicity, and stellar
metallicity to be the most fundamental metallicity relation observed in
galaxies.


  We present the results from our seven-year long broad-band X-ray observing
campaign of SN\,2014C with \emph{Chandra} and \emph{NuSTAR}. These coordinated
observations represent the first look at the evolution of a young extragalactic
SN in the 0.3-80 keV energy range in the years after core collapse. We find
that the spectroscopic metamorphosis of SN\,2014C from an ordinary type Ib SN
into an interacting SN with copious hydrogen emission is accompanied by
luminous X-rays reaching $L_x\approx 5.6\times10^{40}\, \rm{erg\,s^{-1}}$
(0.3--100 keV) at $\sim 1000$ days post explosion and declining as $L_x\propto
t^{-1}$ afterwards. The broad-band X-ray spectrum is of thermal origin and
shows clear evidence for cooling after peak, with $T(t)\approx 20 \,{\rm
keV}(t/t_{\rm pk})^{-0.5}$. Soft X-rays of sub-keV energy suffer from large
photoelectric absorption originating from the local SN environment with
$NH_{\rm int}(t)\approx3\times 10^{22}(t/400
\,\rm{days})^{-1.4}\,\rm{cm^{-2}}$. We interpret these findings as the result
of the interaction of the SN shock with a dense ($n\approx
10^{5}-10^{6}\,\rm{cm^{-3}}$), H-rich disk-like circumstellar medium (CSM) with
inner radius $\sim2\times 10^{16}$ cm and extending to $\sim 10^{17}$ cm. Based
on the declining $NH_{\rm int}(t)$ and X-ray luminosity evolution, we infer a
CSM mass of $\sim(1.2\,f$--2.0$\sqrt{f}) \rm{M_{\odot}}$, where $f$ is the
volume filling factor. Finally, we place SN\,2014C in the context of 119
core-collapse SNe with evidence for strong shock interaction with a thick
circumstellar medium and we highlight the challenges that the current mass-loss
theories (including wave-driven mass loss, binary interaction and line-driven
winds) face when interpreting the wide dynamic ranges of CSM parameters
inferred from observations.


  We define the spectrum of a tensor triangulated category $K$ as the set of
so-called prime ideals, endowed with a suitable topology. In this very
generality, the spectrum is the universal space in which one can define
supports for objects of $K$. This construction is functorial with respect to
all tensor triangulated functors. Several elementary properties of schemes hold
for such spaces, e.g. the existence of generic points and some
quasi-compactness. Locally trivial morphisms are proved to be nilpotent. We
establish in complete generality a classification of thick tensor-ideal
subcategories in terms of arbitrary unions of closed subsets with quasi-compact
complements (Thomason's theorem for schemes, mutatis mutandis). We also equip
this spectrum with a sheaf of rings, turning it into a locally ringed space. We
compute examples and show that our spectrum unifies the schemes of algebraic
geometry and the support varieties of modular representation theory.


  Reply to "Comment on 'Fickian non-Gaussian diffusion in glass-forming
liquids' ".
  In [ArXiv:2210.07119v1], Berthier et al. questioned the findings of our
letter [Phys. Rev. Lett. 128, 168001 (2022)], concerning the existence and the
features of Fickian non-Gaussian diffusion in glass-forming liquids. Here we
demonstrate that their arguments are either wrong, or not meaningful to our
scope. Thus, we fully confirm the validity and novelty of our results.


  Exponential families and mixture families are parametric probability models
that can be geometrically studied as smooth statistical manifolds with respect
to any statistical divergence like the Kullback-Leibler (KL) divergence or the
Hellinger divergence. When equipping a statistical manifold with the KL
divergence, the induced manifold structure is dually flat, and the KL
divergence between distributions amounts to an equivalent Bregman divergence on
their corresponding parameters. In practice, the corresponding Bregman
generators of mixture/exponential families require to perform definite integral
calculus that can either be too time-consuming (for exponentially large
discrete support case) or even do not admit closed-form formula (for continuous
support case). In these cases, the dually flat construction remains theoretical
and cannot be used by information-geometric algorithms. To bypass this problem,
we consider performing stochastic Monte Carlo (MC) estimation of those
integral-based mixture/exponential family Bregman generators. We show that,
under natural assumptions, these MC generators are almost surely Bregman
generators. We define a series of dually flat information geometries, termed
Monte Carlo Information Geometries, that increasingly-finely approximate the
untractable geometry. The advantage of this MCIG is that it allows a practical
use of the Bregman algorithmic toolbox on a wide range of probability
distribution families. We demonstrate our approach with a clustering task on a
mixture family manifold.


  We construct a Schwinger-Keldysh effective field theory for relativistic
hydrodynamics for charged matter in a thermal background using a superspace
formalism. Superspace allows us to efficiently impose the symmetries of the
problem and to obtain a simple expression for the effective action. We show
that the theory we obtain is compatible with the Kubo-Martin-Schwinger
condition, which in turn implies that Green's functions obey the
fluctuation-dissipation theorem. Our approach complements and extends existing
formulations found in the literature.


  This paper surveys basic properties of finite presentation in groups, Lie
algebras and rings. It includes some new results and also new, more elementary
proofs, of some results that are already in the literature. In particular, we
discuss examples of Stallings and of Roos on coherence by using a purely
algebraic, nonhomological, approach.


  We have investigated the spectra of light-heavy quarkonia with the use of a
quantum-chromodynamic potential model which is similar to that used earlier for
the heavy quarkonia. An essential feature of our treatment is the inclusion of
the one-loop radiative corrections to the quark-antiquark potential, which
contribute significantly to the spin-splittings among the quarkonium energy
levels. Unlike $c\bar{c}$ and $b\bar{b}$, the potential for a light-heavy
system has a complicated dependence on the light and heavy quark masses $m$ and
$M$, and it contains a spin-orbit mixing term. We have obtained excellent
results for the observed energy levels of $D^0$, $D_s$, $B^0$, and $B_s$, and
we are able to provide predicted results for many unobserved energy levels. Our
potential parameters for different quarkonia satisfy the constraints of quantum
chromodynamics.
  We have also used our investigation to test the accuracy of the heavy quark
effective theory. We find that the heavy quark expansion yields generally good
results for the $B^0$ and $B_s$ energy levels provided that $M^{-1}$ and
$M^{-1}\ln M$ corrections are taken into account in the quark-antiquark
interactions. It does not, however, provide equally good results for the energy
levels of $D^0$ and $D_s$, which indicates that the effective theory can be
applied more accurately to the $b$ quark than the $c$ quark.


  Pd is one of the metals suitable for inducing low-temperature crystallization
in Ge. However, it is not clear how residual Pd atoms are integrated into the
Ge lattice. Therefore, time-differential perturbed angular correlations (TDPAC)
technique using the 100Pd(100Rh) nuclear probe produced by recoil implantation
has been applied to study the hyperfine interactions of this probe in
single-crystalline undoped Ge. A Pd-vacancy complex aligned along the <111>
crystallographic direction with a unique interaction frequency of 8.4(5) Mrad/s
has been identified. This complex was measured to have a maximum relative
fraction of about 76(4)% following annealing at 350 oC. Further annealing at
higher temperatures reduced this fraction, possibly via dissociation of the
complex. Calculations suggest dissociation energy of 1.94(5) eV for the
complex. DFT calculations performed in this work are in reasonable good
agreement with the experimental values for the electric-field gradient of the
defect complex in Ge. The calculations predict a split-vacancy configuration
with the Pd on a bond-centred interstitial site having a nearest-neighbour
semi-vacancy on both sides (V-PdBI-V).


  We prove pairwise disjointness of representations T_{z,w} of the
infinite-dimensional unitary group. These representations provide a natural
generalization of the regular representation for the case of "big" group
U(\infty). They were introduced and studied by G.Olshanski and A.Borodin.
  Disjointness of the representations can be reduced to disjointness of certain
probability measures on the space of paths in the Gelfand-Tsetlin graph. We
prove the latter disjointness using probabilistic and combinatorial methods.


  We present energy-resolved photoelectron momentum maps for orbital tomography
that have been collected with a novel and efficient time-of-flight momentum
microscopy setup. This setup is combined with a 0.5 MHz table-top femtosecond
extreme-ultraviolet light source, which enables unprecedented speed in data
collection and paves the way towards time-resolved orbital imaging experiments
in the future. Moreover, we take a significant step forward in the data
analysis procedure for orbital imaging, and present a sparsity-driven approach
to the required phase retrieval problem, which uses only the number of non-zero
pixels in the orbital. Here, no knowledge of the object support is required,
and the sparsity number can easily be determined from the measured data. Used
in the relaxed averaged alternating reflections algorithm, this sparsity
constraint enables fast and reliable phase retrieval for our experimental as
well as noise-free and noisy simulated photoelectron momentum map data.


  We introduce the category of structures and interpretations which allows us
to discuss some issues of Grothendieck's anabelian geometry in model-theory
terms. Our main result is a formulation in terms of pure stability theory of a
problem closely related to Grothendieck's section conjecture


  The stable and efficient operation of the transmission network is fundamental
to the power system's ability to deliver electricity reliably and cheaply. As
average temperatures continue to rise, the ability of the transmission network
to meet demand is diminished. Higher temperatures lead to congestion by
reducing thermal limits of lines while simultaneously reducing generation
potential. Due to prohibitive costs and limited real estate for building new
lines, it is necessary to consider capacity expansion as well to improve the
functioning and efficiency of the grid. Optimal control, however, requires many
discrete choices, rendering fully accurate models intractable. Furthermore,
temperature changes will impact different regions and climate differently. As
such, it is necessary to model both temperature changes and transmission flows
with high spatial resolution. This work proposes a case study of the
transmission grid centered in Arizona, using a DC optimal power flow
mathematical formulation to plan for future transmission expansion and capacity
expansion to efficiently meet demand. The effects of rising temperatures on
transmission and generation are modeled at the regional level. Several classes
of valid inequalities are employed to speed up the solution process. Multiple
experiments considering different temperature and demand trends are considered
which include each of the above technologies.


  We revisit the online dynamic acknowledgment problem. In the problem, a
sequence of requests arrive over time to be acknowledged, and all outstanding
requests can be satisfied simultaneously by one acknowledgement. The goal of
the problem is to minimize the total request delay plus acknowledgement cost.
This elegant model studies the trade-off between acknowledgement cost and
waiting experienced by requests. The problem has been well studied and the
tight competitive ratios have been determined. For this well-studied problem,
we focus on how to effectively use machine-learned predictions to have better
performance.
  We develop algorithms that perform arbitrarily close to the optimum with
accurate predictions while concurrently having the guarantees arbitrarily close
to what the best online algorithms can offer without access to predictions,
thereby achieving simultaneous optimum consistency and robustness. This new
result is enabled by our novel prediction error measure. No error measure was
defined for the problem prior to our work, and natural measures failed due to
the challenge that requests with different arrival times have different effects
on the objective. We hope our ideas can be used for other online problems with
temporal aspects that have been resisting proper error measures.


  We show that dynamic exchange is a dominant effect in strong field ionization
of molecules. In $CO_2$ it fixes the peak ionization yield at the
experimentally observed angle of $45^\circ$ between polarization direction and
the molecular axis. In $N_2$ it changes the alignment dependence of yields by
up to a factor of 2. The effect appears on the Hartree-Fock level as well as in
full {\it ab initio} solutions of the Schr\"odinger equation.


  In PrBa_2Cu_3O_{7-y} (Pr123) single crystals grown by the flux method the
kink in the magnetic susceptibility chi_{ab}(T), connected with AFM ordering of
Pr, disappears after field cooling (FC) in a field H||ab-plane whereas the kink
in chi_c(T) remains unchanged after FC in H||c-axis. This seems to be connected
with the coupling between the Pr and Cu(2) sublattices. The Curie constant C
determined from the data reported for superconducting Pr123 crystals grown by
traveling-solvent floating zone (TSFZ) method (Zou et al, Phys. Rev. Lett., 80,
1074 (1998)) is about one half of that for our flux crystals. Thus, the
concentration of Pr in TSFZ crystal seems to be about one half of the nominal
for Pr123. Therefore, superconductivity in TSFZ samples is connected most
probably with the partial substitution of Pr by nonmagnetic Ba.


  A cycle of length $t$ in a hypergraph is an alternating sequence
$v_1,e_1,v_2\dots,v_t,e_t$ of distinct vertices $v_i$ and distinct edges $e_i$
so that $\{v_i,v_{i+1}\}\subseteq e_i$ (with $v_{t+1}:=v_1$). Let $\lambda
K_n^h$ be the $\lambda$-fold $n$-vertex complete $h$-graph. Let $\mathcal
G=(V,E)$ be a hypergraph all of whose edges are of size at least $h$, and
$2\leq c_1\leq \dots\leq c_k\leq |V|$. In order to partition the edge set of
$\mathcal G$ into cycles of specified lengths $c_1, \dots, c_k$, an obvious
necessary condition is that $\sum_{i=1}^k c_i=|E|$. We show that this condition
is sufficient in the following cases:
  (i) $h\geq \max\{c_k, \lceil n/2 \rceil+1\}$;
  (ii) $\mathcal G=\lambda K_n^h$, $h\geq \lceil n/2 \rceil+2$;
  (iii) $\mathcal G=K_n^h$, $c_1= \dots=c_k:=c$, $c|n(n-1), n\geq 85$.
  In (ii), we guarantee that each cycle is almost regular. In (iii), we also
solve the case where a "small" subset $L$ of edges of $K_n^h$ is removed.


  The U.S. Virtual Astronomical Observatory was a software infrastructure and
development project designed both to begin the establishment of an operational
Virtual Observatory (VO) and to provide the U.S. coordination with the
international VO effort. The concept of the VO is to provide the means by which
an astronomer is able to discover, access, and process data seamlessly,
regardless of its physical location. This paper describes the origins of the
VAO, including the predecessor efforts within the U.S. National Virtual
Observatory, and summarizes its main accomplishments. These accomplishments
include the development of both scripting toolkits that allow scientists to
incorporate VO data directly into their reduction and analysis environments and
high-level science applications for data discovery, integration, analysis, and
catalog cross-comparison. Working with the international community, and based
on the experience from the software development, the VAO was a major
contributor to international standards within the International Virtual
Observatory Alliance. The VAO also demonstrated how an operational virtual
observatory could be deployed, providing a robust operational environment in
which VO services worldwide were routinely checked for aliveness and compliance
with international standards. Finally, the VAO engaged in community outreach,
developing a comprehensive web site with on-line tutorials, announcements,
links to both U.S. and internationally developed tools and services, and
exhibits and hands-on training .... All digital products of the VAO Project,
including software, documentation, and tutorials, are stored in a repository
for community access. The enduring legacy of the VAO is an increasing
expectation that new telescopes and facilities incorporate VO capabilities
during the design of their data management systems.


  This paper presents an online learning with regularized kernel based
one-class extreme learning machine (ELM) classifier and is referred as online
RK-OC-ELM. The baseline kernel hyperplane model considers whole data in a
single chunk with regularized ELM approach for offline learning in case of
one-class classification (OCC). Further, the basic hyper plane model is adapted
in an online fashion from stream of training samples in this paper. Two
frameworks viz., boundary and reconstruction are presented to detect the target
class in online RKOC-ELM. Boundary framework based one-class classifier
consists of single node output architecture and classifier endeavors to
approximate all data to any real number. However, one-class classifier based on
reconstruction framework is an autoencoder architecture, where output nodes are
identical to input nodes and classifier endeavor to reconstruct input layer at
the output layer. Both these frameworks employ regularized kernel ELM based
online learning and consistency based model selection has been employed to
select learning algorithm parameters. The performance of online RK-OC-ELM has
been evaluated on standard benchmark datasets as well as on artificial datasets
and the results are compared with existing state-of-the art one-class
classifiers. The results indicate that the online learning one-class classifier
is slightly better or same as batch learning based approaches. As, base
classifier used for the proposed classifiers are based on the ELM, hence,
proposed classifiers would also inherit the benefit of the base classifier i.e.
it will perform faster computation compared to traditional autoencoder based
one-class classifier.


  We survey a variety of possible explications of the term "Individual Risk."
These in turn are based on a variety of interpretations of "Probability,"
including Classical, Enumerative, Frequency, Formal, Metaphysical, Personal,
Propensity, Chance and Logical conceptions of Probability, which we review and
compare. We distinguish between "groupist" and "individualist" understandings
of Probability, and explore both "group to individual" (G2i) and "individual to
group" (i2G) approaches to characterising Individual Risk. Although in the end
that concept remains subtle and elusive, some pragmatic suggestions for
progress are made.


  We investigate an N-state spin model called quantum relativistic Toda chain
and based on the unitary finite dimensional representations of the Weyl algebra
with q being N-th primitive root of unity. Parameters of the finite dimensional
representation of the local Weyl algebra form the classical discrete integrable
system. Nontrivial dynamics of the classical counterpart corresponds to
isospectral transformations of the spin system. Similarity operators are
constructed with the help of modified Baxter's Q-operators. The classical
counterpart of the modified Q-operator for the initial homogeneous spin chain
is a Baecklund transformation. This transformation creates an extra Hirota-type
soliton in a parameterization of the chain structure. Special choice of values
of solitonic amplitudes yields a degeneration of spin eigenstates, leading to
the quantum separation of variables, or the functional Bethe ansatz. A
projector to the separated eigenstates is constructed explicitly as a product
of modified Q-operators.


  In recent years machine learning algorithms, and more specifically deep
learning algorithms, have been widely used in many fields, including cyber
security. However, machine learning systems are vulnerable to adversarial
attacks, and this limits the application of machine learning, especially in
non-stationary, adversarial environments, such as the cyber security domain,
where actual adversaries (e.g., malware developers) exist. This paper
comprehensively summarizes the latest research on adversarial attacks against
security solutions based on machine learning techniques and illuminates the
risks they pose. First, the adversarial attack methods are characterized based
on their stage of occurrence, and the attacker's goals and capabilities. Then,
we categorize the applications of adversarial attack and defense methods in the
cyber security domain. Finally, we highlight some characteristics identified in
recent research and discuss the impact of recent advancements in other
adversarial learning domains on future research directions in the cyber
security domain. This paper is the first to discuss the unique challenges of
implementing end-to-end adversarial attacks in the cyber security domain, map
them in a unified taxonomy, and use the taxonomy to highlight future research
directions.