  Noise in seismic data arises from numerous sources and is continually
evolving. The use of supervised deep learning procedures for denoising of
seismic datasets often results in poor performance: this is due to the lack of
noise-free field data to act as training targets and the large difference in
characteristics between synthetic and field datasets. Self-supervised,
blind-spot networks typically overcome these limitation by training directly on
the raw, noisy data. However, such networks often rely on a random noise
assumption, and their denoising capabilities quickly decrease in the presence
of even minimally-correlated noise. Extending from blind-spots to blind-masks
can efficiently suppress coherent noise along a specific direction, but it
cannot adapt to the ever-changing properties of noise. To preempt the network's
ability to predict the signal and reduce its opportunity to learn the noise
properties, we propose an initial, supervised training of the network on a
frugally-generated synthetic dataset prior to fine-tuning in a self-supervised
manner on the field dataset of interest. Considering the change in peak
signal-to-noise ratio, as well as the volume of noise reduced and signal
leakage observed, we illustrate the clear benefit in initialising the
self-supervised network with the weights from a supervised base-training. This
is further supported by a test on a field dataset where the fine-tuned network
strikes the best balance between signal preservation and noise reduction.
Finally, the use of the unrealistic, frugally-generated synthetic dataset for
the supervised base-training includes a number of benefits: minimal prior
geological knowledge is required, substantially reduced computational cost for
the dataset generation, and a reduced requirement of re-training the network
should recording conditions change, to name a few.


  We study the problem of routing vehicles with energy constraints through a
network where there are at least some charging nodes. We seek to minimize the
total elapsed time for vehicles to reach their destinations by determining
routes as well as recharging amounts when the vehicles do not have adequate
energy for the entire journey. For a single vehicle, we formulate a
mixed-integer nonlinear programming (MINLP) problem and derive properties of
the optimal solution allowing it to be decomposed into two simpler problems.
For a multi-vehicle problem, where traffic congestion effects are included, we
use a similar approach by grouping vehicles into subflows. We also provide an
alternative flow optimization formulation leading to a computationally simpler
problem solution with minimal loss in accuracy. Numerical results are included
to illustrate these approaches.


  Uncertainty estimation methods are expected to improve the understanding and
quality of computer-assisted methods used in medical applications (e.g.,
neurosurgical interventions, radiotherapy planning), where automated medical
image segmentation is crucial. In supervised machine learning, a common
practice to generate ground truth label data is to merge observer annotations.
However, as many medical image tasks show a high inter-observer variability
resulting from factors such as image quality, different levels of user
expertise and domain knowledge, little is known as to how inter-observer
variability and commonly used fusion methods affect the estimation of
uncertainty of automated image segmentation. In this paper we analyze the
effect of common image label fusion techniques on uncertainty estimation, and
propose to learn the uncertainty among observers. The results highlight the
negative effect of fusion methods applied in deep learning, to obtain reliable
estimates of segmentation uncertainty. Additionally, we show that the learned
observers' uncertainty can be combined with current standard Monte Carlo
dropout Bayesian neural networks to characterize uncertainty of model's
parameters.


  A large number of real-world networks include multiple types of nodes and
edges. Graph Neural Network (GNN) emerged as a deep learning framework to
generate node and graph embeddings for downstream machine learning tasks.
However, popular GNN-based architectures operate on single homogeneous
networks. Enabling them to work on multiple networks brings additional
challenges due to the heterogeneity of the networks and the multiplicity of the
existing associations. In this study, we present a computational approach named
GRAF (Graph Attention-aware Fusion Networks) utilizing GNN-based approaches on
multiple networks with the help of attention mechanisms and network fusion.
Using attention-based neighborhood aggregation, GRAF learns the importance of
each neighbor per node (called node-level attention) followed by the importance
of association (called association-level attention). Then, GRAF processes a
network fusion step weighing each edge according to learned node- and
association-level attentions. Considering that the fused network could be a
highly dense network with many weak edges depending on the given input
networks, we included an edge elimination step with respect to edges' weights.
Finally, GRAF utilizes Graph Convolutional Network (GCN) on the fused network
and incorporates node features on graph-structured data for a node
classification or a similar downstream task. To demonstrate GRAF's
generalizability, we applied it to four datasets from different domains and
observed that GRAF outperformed or was on par with the baselines,
state-of-the-art methods, and its own variations for each node classification
task. Source code for our tool is publicly available at
https://github.com/bozdaglab/GRAF .


  Local density of states (LDOS) in the triangular vortex lattice is
investigated based on the quasi-classical Eilenberger theory. We consider the
case of an isotropic s-wave superconductor with the material parameter
appropriate to NbSe_2. At a weak magnetic field, the spatial variation of the
LDOS shows cylindrical structure around a vortex core. On the other hand, at a
high field where the core regions substantially overlap each other, the LDOS is
sixfold star-shaped structure due to the vortex lattice effect. The orientation
of the star coincides with the experimental data of the scanning tunneling
microscopy. That is, the ray of the star extends toward the nearest-neighbor
(next nearest-neighbor) vortex direction at higher (lower) energy.


  $k$-means and $k$-median clustering are powerful unsupervised machine
learning techniques. However, due to complicated dependences on all the
features, it is challenging to interpret the resulting cluster assignments.
Moshkovitz, Dasgupta, Rashtchian, and Frost [ICML 2020] proposed an elegant
model of explainable $k$-means and $k$-median clustering. In this model, a
decision tree with $k$ leaves provides a straightforward characterization of
the data set into clusters.
  We study two natural algorithmic questions about explainable clustering. (1)
For a given clustering, how to find the "best explanation" by using a decision
tree with $k$ leaves? (2) For a given set of points, how to find a decision
tree with $k$ leaves minimizing the $k$-means/median objective of the resulting
explainable clustering? To address the first question, we introduce a new model
of explainable clustering. Our model, inspired by the notion of outliers in
robust statistics, is the following. We are seeking a small number of points
(outliers) whose removal makes the existing clustering well-explainable. For
addressing the second question, we initiate the study of the model of
Moshkovitz et al. from the perspective of multivariate complexity. Our rigorous
algorithmic analysis sheds some light on the influence of parameters like the
input size, dimension of the data, the number of outliers, the number of
clusters, and the approximation ratio, on the computational complexity of
explainable clustering.


  This research started with an algebra for reasoning about rely/guarantee
concurrency for a shared memory model. The approach taken led to a more
abstract algebra of atomic steps, in which atomic steps synchronise (rather
than interleave) when composed in parallel. The algebra of rely/guarantee
concurrency then becomes an interpretation of the more abstract algebra. Many
of the core properties needed for rely/guarantee reasoning can be shown to hold
in the abstract algebra where their proofs are simpler and hence allow a higher
degree of automation. Moreover, the realisation that the synchronisation
mechanisms of standard process algebras, such as CSP and CCS/SCCS, can be
interpreted in our abstract algebra gives evidence of its unifying power. The
algebra has been encoded in Isabelle/HOL to provide a basis for tool support.


  The universal R-matrix of two-parameter quantum general linear supergroups is
computed explicitly based on the RTT realization of
Faddeev--Reshetikhin--Takhtajan.


  The double plasma resonance (DPR) instability plays a basic role in the
generation of solar radio zebras. In the plasma, consisting of the loss-cone
type distribution of hot electrons and much denser and colder background
plasma, this instability generates the upper-hybrid waves, which are then
transformed into the electromagnetic waves and observed as radio zebras. In the
present paper we numerically study the double plasma resonance instability from
the point of view of the zebra interpretation. We use a 3-dimensional
electromagnetic particle-in-cell (3-D PIC) relativistic model. First using the
multi-mode model, we study details of the double plasma resonance instability.
We show how the distribution function of hot electrons changes during this
instability. Then we show that there is a very good agreement between results
obtained by the multi-mode and specific-mode models, which is caused by a
dominance of the wave with the maximal growth rate. Therefore, for computations
in a broad range of model parameters, we use the specific-mode model. We
compute the maximal growth rates of the double plasma resonance instability.
The results are compared with the analytical ones. We find a very good
agreement between numerical and analytical growth rates. We also compute
saturation energies of the upper-hybrid waves in a very broad range of
parameters. We find that the saturation energies of the upper-hybrid waves show
maxima and minima at almost the same values of
$\omega_\mathrm{UH}/\omega_\mathrm{ce}$ as the growth rates. Furthermore, we
find that the saturation energy of the upper-hybrid waves is proportional to
the density of hot electrons. The maximum saturated energy can be up to one
percent of the kinetic energy of hot electrons. All these findings can be used
in the interpretation of solar radio zebras.


  A (1,1) knot K in a 3-manifold M is a knot that intersects each solid torus
of a genus 1 Heegaard splitting of M in a single trivial arc. Choi and Ko
developed a parameterization of this family of knots by a four-tuple of
integers, which they call Schubert's normal form. This article presents an
algorithm for constructing a doubly-pointed Heegaard diagram compatible with K,
given a Schubert's normal form for K. The construction, coupled with results of
Ozsv\'ath and Szab\'o, provides a practical way to compute knot Floer homology
groups for (1,1) knots. The construction uses train tracks, and its method is
inspired by the work of Goda, Matsuda and Morifuji.


  Transport in topological matter has shown a variety of novel phenomena over
the last decade. Although numerous transport studies have been conducted on
three-dimensional topological insulators (3D-TIs), study of ballistic motion
and thus exploration of potential landscapes on a hundred nanometer scale is
for the prevalent TI materials almost impossible due to their low carrier
mobility. Therefore it is unknown whether helical Dirac electrons in TIs, bound
to interfaces between topologically distinct materials, can be manipulated on
the nanometer scale by local gates or locally etched regions. Here we impose a
submicron periodic potential onto a single surface of Dirac electrons in high
mobility strained mercury telluride (HgTe), which is a strong TI. Pronounced
geometric resistance resonances constitute the first observation of a ballistic
effect in 3D-TIs.


  In 2015, S. Hong and C. Wang proved that none of the elementary symmetric
functions of $1,1/3,\ldots,1/(2n-1)$ is an integer when $n\geq 2$. In 2017, Kh.
Pilehrood, T. Pilehrood and R. Tauraso proved that the multiple harmonic sums
$H_n(s_1,\ldots,s_r)$ are never integers with exceptions of $H_1(s_1)=1$ and
$H_3(1,1)=1$. They also proved that the multiple harmonic star sums are never
integers when $n\geq 2$. In this paper, we consider the odd multiple harmonic
sums and the odd multiple harmonic star sums and show that none of these sums
is an integer with exception of the trivial case. Besides, we give evaluations
of the odd (alternating) multiple harmonic sums with depth one.


  Information visualization is essential in making sense out of large data
sets. Often, high-dimensional data are visualized as a collection of points in
2-dimensional space through dimensionality reduction techniques. However, these
traditional methods often do not capture well the underlying structural
information, clustering, and neighborhoods. In this paper, we describe GMap: a
practical tool for visualizing relational data with geographic-like maps. We
illustrate the effectiveness of this approach with examples from several
domains All the maps referenced in this paper can be found in
http://www.research.att.com/~yifanhu/GMap


  Massive stars generally end their lives as neutron stars (NSs) or black holes
(BHs), with NS formation typically occurring at the low mass end and collapse
to a BH more likely at the high mass end. In an intermediate regime, with a
mass range that depends on the uncertain details of rotation and mass loss
during the star's life, a NS is initially formed which then experiences
fallback accretion and collapse to a BH. The electromagnetic consequence of
such an event is not clear. Depending on the progenitor's structure,
possibilities range from a long gamma-ray burst to a Type II supernova (that
may or may not be jet-powered) to a collapse with a weak electromagnetic
signature. Gravitational waves (GWs) provide the exciting opportunity to peer
through the envelope of a dying massive star and directly probe what is
occurring inside. We explore whether fallback onto young NSs can be detected by
ground-based interferometers. When the incoming material has sufficient angular
momentum to form a disk, the accretion spins up the NS sufficiently to produce
non-axisymmetric instabilities and gravitational radiation at frequencies of
~700-2400 Hz for ~30-3000 s until collapse to a BH occurs. Using a realistic
excess cross-power search algorithm, we show that such events are detectable by
Advanced LIGO out to ~17 Mpc. From the rate of nearby core-collapse supernovae,
we estimate that there will be ~1-2 events each year that are worth checking
for fallback GWs. The observation of these unique GW signatures coincident with
electromagnetic detections would identify the transient events that are
associated with this channel of BH formation, while providing information about
the protoneutron star progenitor.


  Many dynamical systems exhibit abrupt transitions or tipping as the control
parameter is varied. In scenarios where the parameter is varied continuously,
the rate of change of control parameter greatly affects the performance of
early warning signals (EWS) for such critical transitions.We study the impact
of variation of the control parameter with a finite rate on the performance of
\textcolor{black}{EWS for critical transitions} in a thermoacoustic system (a
horizontal Rijke tube) exhibiting subcritical Hopf bifurcation. There is a
growing interest in developing early warning signals for tipping in real
systems. Firstly, we explore the efficacy of early warning signals based on
critical slowing down and fractal characteristics. From this study, lag-1
autocorrelation (AC) and Hurst exponent H are found to be good measures to
predict the transition well-before the tipping point. The warning time,
obtained using AC and $H$, reduces with an increase in the rate of change of
the control parameter following an inverse power law relation. Hence, for very
fast rates, the warning time may be too short to perform any control action.
Furthermore, we report the observation of a hyperexponential scaling relation
between the AC and the variance of fluctuations during such dynamic Hopf
bifurcation. We construct a theoretical model for noisy Hopf bifurcation
wherein the control parameter is continuously varied at different rates to
study the effect of rate of change of parameter on EWS. Similar results,
including the hyperexponential scaling, are observed in the model as well.


  We consider pion-nucleon scattering in heavy-baryon chiral perturbation
theory to third order. All electromagnetic corrections appearing to this order
are included. We thus have a consistent description of strong and
electromagnetic effects, which allows us to isolate the strong part of the
interaction in an unambiguous way. We give pion-nucleon phase shifts up to pion
laboratory momenta of 100 MeV and find sizeable differences for the S-waves of
the elastic channels compared to previous phase shift analyses. The precise
description of the scattering process also allows us to address the question of
isospin violation in the strong interaction. For the usually employed triangle
relation we find an isospin breaking effect of -0.7% in the S-wave, whereas the
P-waves show an effect of -1.5% and -4 to -2.5%, respectively, for pion
laboratory momenta between 25 and 100 MeV.


  We present directed searches for continuous gravitational waves from the
neutron stars in the Cassiopeia A (Cas A) and Vela Jr. supernova remnants. We
carry out the searches in the LIGO data from the first six months of the third
Advanced LIGO and Virgo observing run, using the Weave semi-coherent method,
which sums matched-filter detection-statistic values over many time segments
spanning the observation period. No gravitational wave signal is detected in
the search band of 20--976 Hz for assumed source ages greater than 300 years
for Cas A and greater than 700 years for Vela Jr. Estimates from simulated
continuous wave signals indicate we achieve the most sensitive results to date
across the explored parameter space volume, probing to strain magnitudes as low
as ~$6.3\times10^{-26}$ for Cas A and ~$5.6\times10^{-26}$ for Vela Jr. at
frequencies near 166 Hz at 95% efficiency.


  We show that final state interactions are important in shaping Dalitz plots
for the decay $D^+ \rar K^- \p^+ \p^+$. The theoretical treatment of this
reaction requires a blend of several weak and hadronic processes and hence it
is necessarily involved. In this talk we present results from a calculation
which is still in progress, but has already unveiled the role of important
dynamical mechanisms. We do not consider explicit quark degrees of freedom and
our study is performed within an effective hadronic framework. In spite of the
relatively wide window of energies available in the Dalitz plot for the $D^+$
decay, we depart from $SU(3)\times SU(3)$ chiral perturbation theory and extend
its range by means of unitarization. Our present results, which concentrate on
the vector weak vertex, describe qualitative features of the modulus of the
decay amplitude and agrees well with its phase in the elastic region.


  Resilience and vulnerability of societies to large-scale events such as wars,
climate catastrophes, immigration waves, and institutional collapses is not
well-understood. Some societies prove more resilient, while others collapse.
Diversity has been proposed in the literature as a potential cause of
resilience in areas such as ecology, computer science and biology, and could
also be a potential factor in sociocultural contexts. Using CulSim (Ulloa
2016), a cultural simulator that enables the study of cultural complexity and
diversity based on Axelrod's (1997b) model of local convergence and global
polarization and its extension including institutions (Ulloa et al 2016), the
resilience of diverse societies and monocultural societies to nine different
types of events is compared, while varying event sizes and distributions.
Results show a strong positive relation between cultural diversity and
resilience, in particular for events such as foreign invasions and settlements,
and institutional damage and conversion.


  We consider a facility location problem, where the objective is to
``disperse'' a number of facilities, i.e., select a given number k of locations
from a discrete set of n candidates, such that the average distance between
selected locations is maximized. In particular, we present algorithmic results
for the case where vertices are represented by points in d-dimensional space,
and edge weights correspond to rectilinear distances. Problems of this type
have been considered before, with the best result being an approximation
algorithm with performance ratio 2. For the case where k is fixed, we establish
a linear-time algorithm that finds an optimal solution. For the case where k is
part of the input, we present a polynomial-time approximation scheme.


  We study the effects of the galactic magnetic field on the ultra high energy
cosmic ray propagation. We show that the deflections of the cosmic ray
trajectories can have many important implications such as (de)magnification of
the cosmic ray fluxes by lensing effects (which can modify the spectrum of
individual sources), the formation of multiple images of a source or the
existence of regions of the sky to which the Earth is almost blind. The
appearance of image pairs is related to the existence of critical curves in the
magnification maps, which divide regions in the sky where the images have
opposite parities. The results are pictorially illustrated as the stretching
and folding of a `sheet' describing the sky seen on Earth. Making use of the
most energetic AGASA events we emphasize the need to know the cosmic ray
composition and the structure of the magnetic field when attempting to do
detailed cosmic ray astronomy.


  We show that the Humbert surfaces rationally generate the Picard groups of
Siegel modular threefolds.


  Off-shell Higgs at the high mass tail may shed light on the underlying
mechanism of the electroweak symmetry breaking. Due to the large cancellation
in the standard model (SM) between the box and Higgs-mediated triangle
diagrams, the $gg\to WW(ZZ)$ process in the SM is dominated by the $V_T V_T$
transverse-mode at the high mass tail. The cancellation does not necessarily
hold, when there is a sufficiently large new physics contribution resulting in
$V_LV_L$ longitudinal mode, which is commonly the case when the Higgs sector is
modified. Thus the $V_LV_L$ final states in the high mass tail can be utilized
as a sensitive probe for such models. In the paper we focus on a study of the
$gg \to ZZ$ process in the fully leptonic decay modes, proposing to utilize the
polarization modes of the off-shell Higgs to probe new physics, whose
contribution mainly shows in the longitudinal mode. As examples, we analyze
three different Higgs sector new physics cases (Higgs portal with a light
scalar, a broad-width scalar that mixes with the Higgs, and quantum critical
Higgs models), and demonstrate that the angular information relating to the
polarization serves as very sensitive probe for such new physics.


  Let $D$ be a strongly connected digraph. The average distance
$\bar{\sigma}(v)$ of a vertex $v$ of $D$ is the arithmetic mean of the
distances from $v$ to all other vertices of $D$. The remoteness $\rho(D)$ and
proximity $\pi(D)$ of $D$ are the maximum and the minimum of the average
distances of the vertices of $D$, respectively. We obtain sharp upper and lower
bounds on $\pi(D)$ and $\rho(D)$ as a function of the order $n$ of $D$ and
describe the extreme digraphs for all the bounds. We also obtain such bounds
for strong tournaments. We show that for a strong tournament $T$, we have
$\pi(T)=\rho(T)$ if and only if $T$ is regular. Due to this result, one may
conjecture that every strong digraph $D$ with $\pi(D)=\rho(D)$ is regular. We
present an infinite family of non-regular strong digraphs $D$ such that
$\pi(D)=\rho(D).$ We describe such a family for undirected graphs as well.


  This work examines strategies to handle large shared data objects in
distributed storage systems (DSS), while boosting the number of concurrent
accesses, maintaining strong consistency guarantees, and ensuring good
operation performance. To this respect, we define the notion of fragmented
objects:con-current objects composed of a list of fragments (or blocks) that
allow operations to manipulate each of their fragments individually. As the
fragments belong to the same object, it is not enough that each fragment is
linearizable to have useful consistency guarantees in the composed object.
Hence, we capture the consistency semantic of the whole object with the notion
of fragmented linearizability. Then, considering that a variance of
linearizability, coverability, is more suited for versioned objects like files,
we provide an implementation of a distributed file system, called COBFS, that
utilizes coverable fragmented objects (i.e., files).In COBFS, each file is a
linked-list of coverable block objects. Preliminary emulation of COBFS
demonstrates the potential of our approach in boosting the concurrency of
strongly consistent large objects.


  In view of the recent result from the anti-neutrino run of MiniBooNE, we
suggest to repeat the original Liquid Scintillator Neutrino Detector (LSND)
experiment using Super-Kamiokande, doped with Gadolinium, as detector. Due to
the more than 100 times larger detector mass offered by Super-Kamiokande, the
neutrino source requires a proton beam power of less than 300kW at a proton
energy around a 1 GeV. A one year run of this setup can corroborate or refute
both the LSND and MiniBooNE claims at more than 5 sigma confidence level. If a
signal is observed, the large size of Super-Kamiokande combined with its good
ability to determine the position of an anti-neutrino event allows to establish
the characteristic L/E-dependence of oscillation.


  Belinschi et al. [Adv. Math., 226 (2011), 3677--3698] proved that the normal
distribution is freely infinitely divisible. This paper establishes a certain
monotonicity, real analyticity and asymptotic behavior of the density of the
free L\'{e}vy measure. The monotonicity property strengthens the result in
Hasebe et al. [Int. Math. Res. Not. (2019), 1758--1787] that the normal
distribution is freely selfdecomposable.


  We show that electrons acquire anyonic statistics if a two-dimensional
electron gas is placed in proximity to a charged magnetic membrane. In this
two-layered system, electrons become anyons through electromagnetic field
mediated interactions with a membrane phonon. The statistical parameter is
irrational and depends on the membrane tension and on the electric charge and
magnetic dipolar densities on the membrane. We propose a measurement that
yields the value of the statistical parameter.


  We show that positive absolutely norm attaining operators can be
characterized by a simple property of their spectra. This result clarifies and
simplifies a result of Ramesh. As an application we characterize weighted shift
operators which are absolutely norm attaining.


  Mixture quality plays a crucial role in the physical properties of
multi-component immiscible polymer mixtures including nanocomposites and
polymer blends. Such complex mixtures are often characterized by hierarchical
internal structures, which have not been accounted for by conventional mixture
quantifications. We propose a way to characterize the mixture quality of
complex mixtures with hierarchical structures. Starting from a concentration
field, which can be typically obtained from TEM/SEM images, the distribution of
the coarsegrained concentration is analyzed to obtain the scale-dependent
inhomogeneity of a mixture. The hierarchical nature of a mixture is
characterized by multiple characteristic scales of the scale-dependent
inhomogeneity. We demonstrate how the proposed method works to characterize
sizes and distributions in different dispersions. This method is generally
applicable to various complex mixtures.


  Theoretical expressions for ionization cross sections by electron impact
based on the binary encounter Bethe (BEB) model, valid from ionization
threshold up to relativistic energies, are proposed. The new modified BEB
(MBEB) and its relativistic counterpart (MRBEB) expressions are simpler than
the BEB (nonrelativistic and relativistic) expressions because they require
only one atomic parameter, namely the binding energy of the electrons to be
ionized, and use only one scaling term for the ionization of all sub-shells.
The new models are used to calculate the K-, L- and M-shell ionization cross
sections by electron impact for several atoms with Z from 6 to 83. Comparisons
with all, to the best of our knowledge, available experimental data show that
this model is as good or better than other models, with less complexity.


  The freeze out of the expanding systems, created in relativistic heavy ion
collisions, will be discussed. We combine kinetic freeze out equations with
Bjorken type system expansion into a unified model. Such a model is a more
physical generalization of the earlier simplified non-expanding freeze out
models. We shall see that the basic freeze out features, pointed out in the
earlier works, are not smeared out by the expansion.


  Piecewise deterministic Markov processes (PDMPs) are a type of
continuous-time Markov process that combine deterministic flows with jumps.
Recently, PDMPs have garnered attention within the Monte Carlo community as a
potential alternative to traditional Markov chain Monte Carlo (MCMC) methods.
The Zig-Zag sampler and the Bouncy particle sampler are commonly used examples
of the PDMP methodology which have also yielded impressive theoretical
properties, but little is known about their robustness to extreme dependence or
isotropy of the target density. It turns out that PDMPs may suffer from poor
mixing due to anisotropy and this paper investigates this effect in detail in
the stylised but important Gaussian case. To this end, we employ a multi-scale
analysis framework in this paper. Our results show that when the Gaussian
target distribution has two scales, of order $1$ and $\epsilon$, the
computational cost of the Bouncy particle sampler is of order $\epsilon^{-1}$,
and the computational cost of the Zig-Zag sampler is either $\epsilon^{-1}$ or
$\epsilon^{-2}$, depending on the target distribution. In comparison, the cost
of the traditional MCMC methods such as RWM or MALA is of order
$\epsilon^{-2}$, at least when the dimensionality of the small component is
more than $1$. Therefore, there is a robustness advantage to using PDMPs in
this context.


  Several spatially continuous pedestrian dynamics models have been validated
against empirical data. We try to reproduce the experimental fundamental
diagram (velocity versus density) with simulations. In addition to this
quantitative criterion, we tried to reproduce stop-and-go waves as a
qualitative criterion. Stop-and-go waves are a characteristic phenomenon for
the single file movement. Only one of three investigated models satisfies both
criteria.


  In this paper, we establish an analytic framework for studying set-valued
backward stochastic differential equations (set-valued BSDE), motivated largely
by the current studies of dynamic set-valued risk measures for multi-asset or
network-based financial models. Our framework will make use of the notion of
Hukuhara difference between sets, in order to compensate the lack of "inverse"
operation of the traditional Minkowski addition, whence the vector space
structure in set-valued analysis. While proving the well-posedness of a class
of set-valued BSDEs, we shall also address some fundamental issues regarding
generalized Aumann-It\^o integrals, especially when it is connected to the
martingale representation theorem. In particular, we propose some necessary
extensions of the integral that can be used to represent set-valued martingales
with non-singleton initial values. This extension turns out to be essential for
the study of set-valued BSDEs.


  The ratios of partial widths for the decay of a glueball into two
pseudoscalar mesons are calculated under the assumption that the production of
light quark pairs ($u\bar u,d\bar d,s\bar s$) in soft gluon-\-induced reactions
goes on within universal symmetry breaking. Parameter of the violation of
flavour symmetry is fixed by the central hadron production data in high energy
hadron collisions and/or by the ratios of radiative decay amplitudes $J/\Psi
\to \gamma\eta/\gamma\eta'$ and $J/\Psi \to \gamma \phi \phi/\gamma \omega
\omega$. The ratios of coupling constants $glueball\to\pi\pi,K\bar K,
\eta\eta,\eta\eta'$ which are calculated with this parameter coincide
reasonably with those of $f_0(1500)$, supporting an idea about glueball nature
of $f_0(1500)$.


  3D generation has raised great attention in recent years. With the success of
text-to-image diffusion models, the 2D-lifting technique becomes a promising
route to controllable 3D generation. However, these methods tend to present
inconsistent geometry, which is also known as the Janus problem. We observe
that the problem is caused mainly by two aspects, i.e., viewpoint bias in 2D
diffusion models and overfitting of the optimization objective. To address it,
we propose a two-stage 2D-lifting framework, namely DreamControl, which
optimizes coarse NeRF scenes as 3D self-prior and then generates fine-grained
objects with control-based score distillation. Specifically, adaptive viewpoint
sampling and boundary integrity metric are proposed to ensure the consistency
of generated priors. The priors are then regarded as input conditions to
maintain reasonable geometries, in which conditional LoRA and weighted score
are further proposed to optimize detailed textures. DreamControl can generate
high-quality 3D content in terms of both geometry consistency and texture
fidelity. Moreover, our control-based optimization guidance is applicable to
more downstream tasks, including user-guided generation and 3D animation. The
project page is available at https://github.com/tyhuang0428/DreamControl.


  Arrays of minibeams of protons and $^{12}$C in tissue-like media were modeled
with Geant4 toolkit. A set of beam energies was used in simulations to provide
a Spead-out Bragg peak (SOBP) extended by 6 cm in depth for protons as well as
for $^{12}$C. In both cases, beams of 0.3 mm or 0.5 mm FWHM were arranged at
the entrance to a water phantom either on a rectangular or an hexagonal grid to
compare two kinds of projectiles and different minibeam patterns. Differential
and cumulative dose-volume histograms (DVH) were calculated and compared for
protons and $^{12}$C as dose uniformity metrics. A uniform dose distribution
was easily achieved with protons due to an enhanced lateral scattering of these
projectiles in comparison to $^{12}$C. The cumulative DVHs calculated for 0.3
mm or 0.5 mm minibeams almost coincide in the target volume, but diverge for
different grid patterns. In contrast, cumulative entry DVHs were found similar
for both grid patterns, but different for 0.3 mm and 0.5 mm minibeams.


  We propose a scheme for generating the superposition and the entanglement of
squeezed vacuum states of electromagnetical fields. The scheme involves
single-photon source, single photon detector, and cross Kerr nonlinearity. The
Kerr nonlinearity required for generating the superposition of squeezed vacuum
states is 1/2 of that required for generating the superposition of coherent
states. The proposal can also be extended to generate the entanglement states
between two coherent states and that between one coherent state and one
squeezed vacuum state.


  We study the edge states of twisted bilayer graphene and their topological
origin. We show that the twisted bilayer graphene has special edge states
associated with the moir\'{e} pattern, and the emergence of these moir\'{e}
edge states is linked with the sliding Chern number, which describes
topological charge pumping caused by relative interlayer sliding. When one
layer of the twisted bilayer is relatively slid with respect to the other
layer, the edge states are transferred from a single band to another across the
band gap, and the number of the edge states pumped in a sliding cycle is shown
to be equal to the sliding Chern number of the band gap. The relationship can
be viewed as a manifestation of the bulk-edge correspondence inherent in
moir\'{e} bilayer systems.


  Recently, Pal and Skar in [arXiv:hep-th/0701266] proposed a mechanism to
arise the warped braneworld models from bulk tachyon matter, which are endowed
with a thin brane and a thick brane. In this framework, we investigate
localization of fermionic fields on these branes. As in the 1/2 spin case, the
field can be localized on both the thin and thick branes with inclusion of
scalar background. In the 3/2 spin extension, the general supergravity action
coupled to chiral supermultiplets is considered to produce the localization on
both the branes as a result.


  The recent preliminary results from central Au+Au collisions at $\sqrt{s_{\rm
NN}} = $ 130 GeV from the STAR experiment at RHIC are presented and discussed
along with the results on the $\Lambda$(1520) production in cental Pb+Pb and
p+p collisions at $\sqrt{s} = $ 17 GeV from the NA49 experiment at the SPS. The
$\Lambda$(1520) is measured with the invariant mass reconstruction of the decay
products in the hadronic channel (K$^{-}$, p). The mean $\Lambda$(1520)
multiplicity scaled by the number of participants decreases from p+p to Pb+Pb
collisions at the same energy of $\sqrt{s}$ = 17 GeV. An upper limit estimate
of the multiplicity from the first measurement at $\sqrt{s_{\rm NN}} = $ 130
GeV shows the same trend. Comparisons with model predictions provides an
indication of possible medium effects on the resonance and their decay
daughters.


  We have theoretically studied the uptake of a non-uniformly charged
biomolecule, suitable to represent a globular protein or a drug, by a charged
hydrogel carrier in the presence of a 1:1 electrolyte. Based on the analysis of
a physical interaction Hamiltonian including monopolar, dipolar and Born
(self-energy) contributions derived from linear electrostatic theory of the
unperturbed homogeneous hydrogel, we have identified five different sorption
states of the system, from complete repulsion of the molecule to its full
sorption deep inside the hydrogel, passing through meta- and stable surface
adsorption states. The results are summarized in state diagrams that also
explore the effects of varying the electrolyte concentration, the sign of the
net electric charge of the biomolecule, and the role of including
excluded-volume (steric) or hydrophobic biomolecule-hydrogel interactions. We
show that the dipole moment of the biomolecule is a key parameter controlling
the spatial distribution of the globules. In particular, biomolecules with a
large dipole moment tend to be adsorbed at the external surface of the
hydrogel, even if like-charged, whereas uniformly charged biomolecules tend to
partition towards the internal core of an oppositely-charged hydrogel.
Hydrophobic attraction shifts the states towards internal sorption of the
biomolecule, whereas steric repulsion promotes surface adsorption for
oppositely-charged biomolecules, or the total exclusion for likely-charged
ones. Our results establish a guidance for the spatial partitioning of proteins
and drugs in hydrogel carriers, tuneable by hydrogel charge, pH and salt
concentration.


  Solidification structures are determined by the interaction between the
interfacial processes and transport processes of heat and solute. In this
paper, we investigate planar instability in directional solidification.
Firstly, the interfacial evolution at the initial growth stage is simulated,
indicating the planar instability is represented by the transition from the
planar to the cellular. Secondly, to represent the history-dependence of
solidification, constant thermal gradient G and varying pulling speed VP are
used in the simulations. The results indicate the cooling rate R ( = G*VP)
dominates the overall propagation speed of the interface, to maintain the local
thermodynamic equilibrium. The solute segregation determines the stability of
the interface, by changing the excess free energy at the interface and
corresponding interface energy. Finally, the simulations of the grains with
different preferred crystallographic orientations are performed, indicating the
surface energy and its anisotropy do not affect the solute diffusion and planar
growth. The results also verify the conclusion that solute segregation
influences the interface energy and results in interface instability. On the
other hand, for the planar-cellular transition, the minimum surface stiffness
rule is more suitable than the maximum surface energy rule. The influence of
the solute concentration on the excess free energy and interface energy can be
applied to other solidification patterns induced by the interface instability,
which will be studied in the future.


  In the present work, a simple strategy is used to thermally oxidize TiN
nanopowder (ca. 20 nm) to an anatase phase of a TiO2:Ti3+:N compound. In
contrast to the rutile phase of such a compound this photocatalyst provides
photocatalytic activity for hydrogen evolution under AM1.5 conditions - this
without the use of any noble metal co-catalyst. Moreover the photocatalyst is
active and stable over extended periods of time (tested for 4 months).
Importantly, to achieve successful conversion to the active anatase polymorph,
sufficiently small starting particles of TiN are needed. The key factor for
catalysis is the stabilization of the co-catalytically active Ti3+ species
against oxidation by nitrogen present in the starting material.


  For non-critical almost Mathieu operators with Diophantine frequency, we
establish exponential asymptotics on the size of spectral gaps, and show that
the spectrum is homogeneous. We also prove the homogeneity of the spectrum for
Sch\"odinger operators with (measure-theoretically) typical quasi-periodic
analytic potentials and fixed strong Diophantine frequency. As applications, we
show the discrete version of Deift's conjecture \cite{Deift, Deift17} for
subcritical analytic quasi-periodic initial data and solve a series of open
problems of Damanik-Goldstein et al \cite{BDGL, DGL1, dgsv, Go} and Kotani
\cite{Kot97}.


  In this paper, we propose a model including four scalar fields coupled with
general gravity theories, which is a generalization of the two-scalar model
proposed in Phys. Rev. D \textbf{103} (2021) no.4, 044055, where it has been
shown that any given spherically symmetric static/time-dependent spacetime can
be realized by using the two-scalar model. We show that by using the
four-scalar model, we can construct a model that realizes any given spacetime
as a solution even if the spacetime does not have a spherical symmetry or any
other symmetry. We also show that by imposing constraints on the scalar fields
by using the Lagrange multiplier fields, the scalar fields become non-dynamical
and they do not propagate. This tells that there does not appear any sound
which is usually generated by the density fluctuation of the fluid. In this
sense, the model with the constraints is a most general extension of the
mimetic theory in JHEP \textbf{11} (2013), 135, where there appears an
effective dark matter. The dark matter is non-dynamical and it does not
collapse even under gravitational force. Our model can be regarded as a general
extension of any kind of fluid besides dark matter. We may consider the case
that the potential of the scalar fields vanishes and the model becomes a
non-linear $\sigma$ model. Then our formulation gives a mapping from the
geometry of the spacetime to the geometry of the target space of the non-linear
$\sigma$ model via gravity theory although the physical meaning has not been
clear. We also consider the application of the model to $f(Q)$ gravity theory,
which is based on a non-metricity tensor and $Q$ is a scalar quantity
constructed from the non-metricity tensor. ...


  The hierarchy of unstable modes when two counter-streaming pair plasmas
interact over a flow-aligned magnetic field has been recently investigated [PoP
\textbf{23}, 062122 (2016)]. The analysis is here extended to the case of an
arbitrarily tilted magnetic field. The two plasma shells are initially cold and
identical. For any angle $\theta \in [0,\pi/2]$ between the field and the
initial flow, the hierarchy of unstable modes is numerically determined in
terms of the initial Lorentz factor of the shells $\gamma_0$, and the field
strength as measured by a parameter denoted $\sigma$. For $\theta=0$, four
different kinds of mode are likely to lead the linear phase. The hierarchy
simplifies for larger $\theta$'s, partly because the Weibel instability can no
longer be cancelled in this regime. For $\theta>0.78$ (44$^\circ$) and in the
relativistic regime, the Weibel instability always govern the interaction. In
the non-relativistic regime, the hierarchy becomes $\theta$-independent because
the interaction turns to be field-independent. As a result, the two-stream
instability becomes the dominant one, regardless of the field obliquity.


  We consider a normal metal - superconductor (N-S) junction in the regime,
when electrons in the normal metal are driven out of equilibrium. We show that
the non-equilibrium fluctuations of the electron density in the N-layer cause
the fluctuations of the phase of the order parameter in the S-layer. As a
result, the density of states in the superconductor deviates from the BCS form,
most notably the density of states in the gap becomes finite. This effect can
be viewed as a result of the time reversal symmetry breaking due to the
non-equilibrium, and can be described in terms of a low energy collective mode
of the junction, which couples normal currents in N-layer and supercurrents.
This mode is analogous to the Schmid-Sch\"{o}n mode. To interpret their
measurements of the tunneling current, Pothier {\em et. al} [Phys. Rev. Lett.
{\bf 79}, 3490 (1997)] had to assume that the energy relaxation rate in the
normal metal is surprisingly high. The broadening of the BCS singularity of the
density of states in the S-layer manifest itself similarly to the broadening of
the distribution function. Mechanism suggested here can be a possible
explanation of this experimental puzzle. We also propose an independent
experiment to test our explanation.


  We consider modal logics of products of neighborhood frames and prove that
for any pair $L$ and $L'$ of logics from set $\{S4, D4, D, T\}$ modal logic of
products of $L$-neighborhood frames and $L'$-neighborhood frames is the fusion
of $L$ and $L'$.


  On directed Barabasi-Albert networks with two and seven neighbours selected
by each added site, the Ising model with spin S=1/2 was seen not to show a
spontaneous magnetisation. Instead, the decay time for flipping of the
magnetisation followed an Arrhenius law for Metropolis and Glauber algorithms,
but for Wolff cluster flipping the magnetisation decayed exponentially with
time. On these networks the
  Ising model spin S=1 is now studied through Monte Carlo simulations.
  However, in this model, the order-disorder phase transition is well defined
in this system. We have obtained a first-order phase transition for values of
connectivity m=2 and m=7 of the directed Barabasi-Albert network.


  In this paper we propose a principal component Liu-type logistic estimator by
combining the principal component logistic regression estimator and Liu-type
logistic estimator to overcome the multicollinearity problem. The superiority
of the new estimator over some related estimators are studied under the
asymptotic mean squared error matrix. A Monte Carlo simulation experiment is
designed to compare the performances of the estimators using mean squared error
criterion. Finally, a conclusion section is presented.


  The vacuum persistence can be written as the Bose-Einstein distribution in
spinor QED and as the Fermi-Dirac distribution in scalar QED exactly in a
constant electric field and approximately in time-varying electric fields. The
inverse temperature is determined by the period of charged particle in the
Euclidean time and the negative chemical potential by the ratio of the
worldline instanton to the inverse temperature. The negativity of chemical
potential is due to the vacuum instability under strong electric fields. The
inversion of spin statistics in the vacuum persistence is a consequence of the
Bogoliubov relations for fermions and bosons.


  For standard leptogenesis from the decay of singlet right-handed neutrinos,
we derive source terms for the lepton asymmetry that are present in a finite
density background but absent in the vacuum. These arise from cuts through the
vertex correction to the decay asymmetry, where in the loop either the Higgs
boson and the right-handed neutrino or the left-handed lepton and the
right-handed neutrino are simultaneously on shell. We evaluate the source terms
numerically and use them to calculate the lepton asymmetry for illustrative
points in parameter space, where we consider only two right-handed neutrinos
for simplicity. Compared to calculations where only the standard cut through
the propagators of left-handed lepton and Higgs boson is included, sizable
corrections arise when the masses of the right-handed neutrinos are of the same
order, but the new sources are found to be most relevant when the decaying
right-handed neutrino is heavier than the one in the loop. In that situation,
they can yield the dominant contribution to the lepton asymmetry.


  We report results of spectroscopic observations of V382 Vel (Nova Vel 1999)
carried out at La Silla between 5 and 498 days after maximum light (23 May
1999, V(max) $\sim 2.3\pm 0.1$). The analysis of the photometric and
spectroscopic evolution shows this object to be a {\sl fast nova} belonging to
the Fe II {\sl broad} spectroscopic class. A distance of 1.7 kpc ($\pm 20%$) is
derived from the maximum magnitude vs. rate of decline relationship after
correcting for the small reddening toward the nova, E(B--V)$\lsim 0.10$. From
the measured H$\alpha$ flux and the associated rate of expansion we derive an
approximate mass for the ejected shell, M$_{env}\lsim 10^{-5}$ M$_\odot$. We
have also observed during the early decline a broad, short-lived ($\lsim$ 10
days) feature at 6705-6715 \AA for which several identifications are possible,
one of which is the lithium doublet at 6708 \AA and which could place an
empirical limit on the lithium production that might occur during the outburst
of a {\sl fast nova}. The high luminosity at maximum, M$_v=-8.9$, and the
relatively small height above the galactic plane ($z\lsim 160$pc) suggest that
V382 Vel originated from a massive white dwarf, likely in the mass range
1.1--1.2 M$_\odot$.


  We apply the relativistic precession (RP) model with its variants and the
resonance epicyclic model with its variants, based on the frequencies of the
geodesic epicyclic motion in the field of a Kerr black hole, to put limits on
the mass of the black hole in the ultraluminous X-ray source M82 X-1
demonstrating twin high-frequency quasi-periodic oscillations (HF QPOs) with
the frequency ratio near 3:2. The mass limits implied by the geodesic HF QPO
models are compared to those obtained due to the model of string loop
oscillations around a stable equilibrium position. Assuming the whole range of
the black hole dimensionless spin, 0 < a < 1, the restrictions on the black
hole mass related to the twin HF QPOs are widely extended and strongly model
dependent; nevertheless, they give the lower limit M_{M82 X-1} > 130 M_{sun}
confirming existence of an intermediate black hole in the M82 X-1 source. The
upper limit given by one of the variants of the geodesic twin HF QPO models
goes up to M_{M82 X-1}<1500 M_{sun}. The range 37-210 mHz of the low-frequency
QPOs observed in the M82 X-1 source introduces additional restrictive limits on
the black hole mass, if we model the low-frequency QPOs by nodal precession of
the epicyclic motion. The nodal precession model restrictions combined with
those implied by the geodesic models of the twin HF QPOs give allowed ranges of
the M82 X-1 black hole parameters, namely 140 M_{sun}<M_{M82 X-1}<660 M_{sun}
for the mass parameter and 0.05<a_{M82 X-1}<0.6 for the spin parameter.


  Halo samples that have no kinematic bias have been successfully isolated by
photometric observations. We show that the near-UV (NUV) magnitude of the GALEX
All-Sky Survey can be used, together with Johnson BV magnitudes in a (NUV-V)_0
vs. (B-V)_0 plot, to distinguish blue horizontal branch (BHB) from other A
stars of the same B-V color for 12<V<18. In addition, we use SDSS gr magnitudes
in a (NUV - r)_0 vs. (g-r)_0 plot for 14<r<18. The faint limit will be extended
by ~3 magnitudes for the GALEX Medium-Deep Survey. Attempts to use NUV in
conjunction with 2MASS magnitudes and ROTSE m_r magnitudes did not prove
useful. The (NUV - V)_0 vs. (B-V)_0 plot was used to examine BHB star
candidates of varying quality near the South Galactic Pole. We conclude that
the addition of the GALEX NUV significantly adds to the reliabilty with which
these stars can be identified.


  In Chaos, a minor divergence between two initial conditions exhibits
exponential amplification over time, leading to far-away outcomes, known as the
butterfly effect. Thus, the distant future is full of uncertainty and hard to
forecast. We introduce Group Reservoir Transformer to predict long-term events
more accurately and robustly by overcoming two challenges in Chaos: (1) the
extensive historical sequences and (2) the sensitivity to initial conditions. A
reservoir is attached to a Transformer to efficiently handle arbitrarily long
historical lengths, with an extension of a group of reservoirs to reduce the
sensitivity to the initialization variations. Our architecture consistently
outperforms state-of-the-art models in multivariate time series, including
TimeLLM, GPT2TS, PatchTST, DLinear, TimeNet, and the baseline Transformer, with
an error reduction of up to -59\% in various fields such as ETTh, ETTm, and air
quality, demonstrating that an ensemble of butterfly learning can improve the
adequacy and certainty of event prediction, despite of the traveling time to
the unknown future.


  Entanglement is known to be a relative notion, defined with respect to the
choice of physical observables to be measured (i.e., the measurement setup
used). This implies that, in general, the same state can be both separable and
entangled for different measurement setups, but this does not exclude the
existence of states which are separable (or entangled) for all possible setups.
We show that for systems of bosonic particles there indeed exist such
universally separable states: they are i.i.d. pure states. In contrast, there
is no such state for fermionic systems with a few exceptional cases. We also
find that none of the fermionic and bosonic systems admits universally
entangled states.


  A problem of optimally allocating partially effective ammunition $x$ to be
used on randomly arriving enemies in order to maximize an aircraft's
probability of surviving for time~$t$, known as the Bomber Problem, was first
posed by \citet{Klinger68}. They conjectured a set of apparently obvious
monotonicity properties of the optimal allocation function $K(x,t)$. Although
some of these conjectures, and versions thereof, have been proved or disproved
by other authors since then, the remaining central question, that $K(x,t)$ is
nondecreasing in~$x$, remains unsettled. After reviewing the problem and
summarizing the state of these conjectures, in the setting where $x$ is
continuous we prove the existence of a ``spend-it-all'' region in which
$K(x,t)=x$ and find its boundary, inside of which the long-standing, unproven
conjecture of monotonicity of~$K(\cdot,t)$ holds. A new approach is then taken
of directly estimating~$K(x,t)$ for small~$t$, providing a complete small-$t$
asymptotic description of~$K(x,t)$ and the optimal probability of survival.


  Spallation source dedicated for neutron scattering experiments, as well as
multi-purpose facilities serving several applications call for pulsed mode
operation of a high intensity proton linac. There is general agreement on the
superconducting technology for the high-energy part, which offers some
advantages, like higher gradient capabilities or operational costs reduction,
as compared to room-temperatures accelerating structures. This mode of
operation however could spoil the energy stability of the proton beam and needs
thus to be carefully studied. First, transient beam-loading effects, arising
from the large beam phase slippage along a multi-cell cavity and associated
with the finite RF energy propagation, can induce significant energy modulation
with a too small cell-to-cell coupling or a too large number of cells. Second,
due to beam phase slippage effects along the linac, energy spread exhibits a
larger sensitivity to cavity fields fluctuations than relativistic particles. A
computer code, initially developed for electron beams has been extended to
proton beams. It solves the 6xN coupled differential equations, needed to
describe cavity fields and beam-cavity interactions of a high-energy linac
composed of N cavities. Simulation examples on a typical pulsed accelerator are
given with various error sources, like Lorentz forces or microphonics detuning,
beam injection energy offsets, intensity jitters ...


  We present an alternative method for computing primary decomposition of
zero-dimensional ideals over finite fields. Based upon the further
decomposition of the invariant subspace of the Frobenius map acting on the
quotient algebra in the algorithm given by S. Gao, D. Wan and M. Wang in 2008,
we get an alternative approach to compute all the primary components at once.
As one example of our method, an improvement of Berlekamp's algorithm by
theoretical considerations which computes the factorization of univariate
polynomials over finite fields is also obtained.


  In this paper we present a comprehensive study of magnetic dynamics in the
rare-earth orthoferrite YbFeO$_3$ at temperatures below and above the
spin-reorientation (SR) transition $T_{\mathrm{SR}}=7.6$ K, in magnetic fields
applied along the $a, b$ and $c$ axes. Using single-crystal inelastic neutron
scattering, we observed that the spectrum of magnetic excitations consists of
two collective modes well separated in energy: 3D gapped magnons with a
bandwidth of $\sim$60 meV, associated with the antiferromagnetically (AFM)
ordered Fe subsystem, and quasi-1D AFM fluctuations of $\sim$1 meV within the
Yb subsystem, with no hybridization of those modes. The spin dynamics of the Fe
subsystem changes very little through the SR transition and could be well
described in the frame of semiclassical linear spin-wave theory. On the other
hand, the rotation of the net moment of the Fe subsystem at $T_{\mathrm{SR}}$
drastically changes the excitation spectrum of the Yb subsystem, inducing the
transition between two regimes with magnon and spinon-like fluctuations. At $T
< T_{\mathrm{SR}}$, the Yb spin chains have a well defined field-induced
ferromagnetic (FM) ground state, and the spectrum consists of a sharp
single-magnon mode, a two-magnon bound state, and a two-magnon continuum,
whereas at $T > T_{\mathrm{SR}}$ only a gapped broad spinon-like continuum
dominates the spectrum. In this work we show that a weak quasi-1D coupling
within the Yb subsystem $J_\text{Yb-Yb}$, mainly neglected in previous studies,
creates unusual quantum spin dynamics on the low energy scales. The results of
our work may stimulate further experimental search for similar compounds with
several magnetic subsystems and energy scales, where low-energy fluctuations
and underlying physics could be "hidden" by a dominating interaction.


  We present a preliminary measurement of the composition of inclusive
semileptonic B meson decays using 9.4 fb^{-1} of e^+e^- data taken with the
CLEO detector at the Upsilon(4S) resonance. In addition to measuring the
charged lepton kinematics, the neutrino four-vector is inferred using the
hermeticity of the detector. We perform a maximum likelihood fit over the full
three-dimensional differential decay distribution for the fractional
contributions from the B->X_c l nu processes with X_c = D, D^*, D^**, and
non-resonant X_c, and the process B -> X_u l nu. From the fit results we
extract <M_X2 - M_D[Bar]^2> = (0.456 +- 0.014 +- 0.045 +- 0.109) GeV^2/c^4 with
minimum lepton energy of 1.0 GeV and <M_X2 - M_D[Bar]^2> (0.293 +- 0.012 +-
0.033 +- 0.048) GeV^2/c^4 with minimum lepton energy of 1.5 GeV. The
uncertainties are from statistics, detector systematic effects, and model
dependence, respectively.


  We study coherence of graph products and Coxeter groups and obtain many
results in this direction.


  In this paper we explore the effects of negative sampling in dual encoder
models used to retrieve passages for automatic question answering. We explore
four negative sampling strategies that complement the straightforward random
sampling of negatives, typically used to train dual encoder models. Out of the
four strategies, three are based on retrieval and one on heuristics. Our
retrieval-based strategies are based on the semantic similarity and the lexical
overlap between questions and passages. We train the dual encoder models in two
stages: pre-training with synthetic data and fine tuning with domain-specific
data. We apply negative sampling to both stages. The approach is evaluated in
two passage retrieval tasks. Even though it is not evident that there is one
single sampling strategy that works best in all the tasks, it is clear that our
strategies contribute to improving the contrast between the response and all
the other passages. Furthermore, mixing the negatives from different strategies
achieve performance on par with the best performing strategy in all tasks. Our
results establish a new state-of-the-art level of performance on two of the
open-domain question answering datasets that we evaluated.


  We have found correlations between properties of the equation of state for
stellar matter with a phase transition at supernuclear densities and two
characteristic features of a "phase diagram" for rotating compact stars in the
angular velocity - baryon number plane: 1) the critical dividing line between
mono- and two-phase star configurations and 2) the maximum mass line. The
second line corresponds to the minimum mass function for black hole candidates
whereas the first one is observable by a population statistics, e.g. for
Z-sources in low-mass X-ray binaries. The observation of a population gap in
the mass distribution for the latter is suggested as an astrophysical
verification of the existence of a first order phase transition in QCD at high
densities such as the deconfinement.


  Many real-world problems can be represented as graph-based learning problems.
In this paper, we propose a novel framework for learning spatial and
attentional convolution neural networks on arbitrary graphs. Different from
previous convolutional neural networks on graphs, we first design a
motif-matching guided subgraph normalization method to capture neighborhood
information. Then we implement subgraph-level self-attentional layers to learn
different importances from different subgraphs to solve graph classification
problems. Analogous to image-based attentional convolution networks that
operate on locally connected and weighted regions of the input, we also extend
graph normalization from one-dimensional node sequence to two-dimensional node
grid by leveraging motif-matching, and design self-attentional layers without
requiring any kinds of cost depending on prior knowledge of the graph
structure. Our results on both bioinformatics and social network datasets show
that we can significantly improve graph classification benchmarks over
traditional graph kernel and existing deep models.


  The controlled preparation of the excited state in a quantum emitter is a
prerequisite for its usage as single-photon sources - a key building block for
quantum technologies. In this paper we propose a coherent excitation scheme
using off-resonant pulses. In the usual Rabi scheme, these pulses would not
lead to a significant occupation. This is overcome by using a frequency
modulated pulse to swing up the excited state population. The same effect can
be obtained using two pulses with different strong detunings of the same sign.
We theoretically analyze the applicability of the scheme to a semiconductor
quantum dot. In this case the excitation is several meV below the band gap,
i.e., far away from the detection frequency allowing for easy spectral
filtering, and does not rely on any auxiliary particles such as phonons. Our
scheme has the potential to lead to the generation of close-to-ideal photons.


  Theorists and advocates of "remixing" have suggested that appropriation can
act as a pathway for learning. We test this theory quantitatively using data
from more than 2.4 million multimedia programming projects shared by more than
1 million users in the Scratch online community. First, we show that users who
remix more often have larger repertoires of programming commands even after
controlling for the numbers of projects and amount of code shared. Second, we
show that exposure to computational thinking concepts through remixing is
associated with increased likelihood of using those concepts. Our results
support theories that young people learn through remixing, and have important
implications for designers of social computing systems.


  The viscosity of Graphene nano-sheet suspensions (GNS)and its behavior with
temperature and concentration have been experimentally determined. A physical
mechanism for the enhanced viscosity over the base fluids has been proposed for
the poly-dispersed GNSs. Experimental data reveals that enhancement of
viscosity for GNSs lie in between that of Carbon Nanotube Suspensions (CNTSs)
and nano Alumina suspensions (nAS) , indicating the hybrid mechanism of
percolation (like CNTs) and Brownian motion assisted sheet dynamics (like
Alumina particles). Sheet dynamics and percolation, along with a proposed
percolation Network Dynamicity Factor; have been used to determine a
dimensionally consistent analytical model to accurately determine and explain
the viscosity of poly-dispersed GNSs. It has been hypothesized that the dynamic
sheets behave qualitatively analogous to gas molecules. The model also provides
insight into the mechanisms of viscous behavior of different dilute
nanoparticle suspensions. The model has been found to be in agreement with the
GNS experimental data, and even for CNT and nano Alumina suspensions.


  We present ultraviolet (UV) spectroscopy and photometry of four Type Ia
supernovae (SNe 2004dt, 2004ef, 2005M, and 2005cf) obtained with the UV prism
of the Advanced Camera for Surveys on the Hubble Space Telescope. This dataset
provides unique spectral time series down to 2000 Angstrom. Significant
diversity is seen in the near maximum-light spectra (~ 2000--3500 Angstrom) for
this small sample. The corresponding photometric data, together with archival
data from Swift Ultraviolet/Optical Telescope observations, provide further
evidence of increased dispersion in the UV emission with respect to the
optical. The peak luminosities measured in uvw1/F250W are found to correlate
with the B-band light-curve shape parameter dm15(B), but with much larger
scatter relative to the correlation in the broad-band B band (e.g., ~0.4 mag
versus ~0.2 mag for those with 0.8 < dm15 < 1.7 mag). SN 2004dt is found as an
outlier of this correlation (at > 3 sigma), being brighter than normal SNe Ia
such as SN 2005cf by ~0.9 mag and ~2.0 mag in the uvw1/F250W and uvm2/F220W
filters, respectively. We show that different progenitor metallicity or
line-expansion velocities alone cannot explain such a large discrepancy.
Viewing-angle effects, such as due to an asymmetric explosion, may have a
significant influence on the flux emitted in the UV region. Detailed modeling
is needed to disentangle and quantify the above effects.


  The newest results from the ATLAS Collaboration for the production of a
top-quark pair in association with a $Z$ or $W$ boson, and for the production
of four top quarks, are summarised in these proceedings. The measurements were
performed with 36.1 fb$^{-1}$ of proton-proton collision data from the Large
Hadron Collider at a centre-of-mass energy of 13 TeV.


  Colleting the data through a survey in the Northern region of Malaysia;
Kedah, Perlis, Penang and Perak, this study investigates intergenerational
social mobility in Malaysia. We measure and analyzed the factors that influence
social-economic mobility by using binary choice model (logit model). Social
mobility can be measured in several ways, by income, education, occupation or
social class. More often, economic research has focused on some measure of
income. Social mobility variable is measured using the difference between
educational achievement between a father and son. If there is a change of at
least of two educational levels between a father and son, then this study will
assign the value one which means that social mobility has occurred.


  The problem of scheduling sensor transmissions for the detection of
correlated random fields using spatially deployed sensors is considered. Using
the large deviations principle, a closed-form expression for the error exponent
of the miss probability is given as a function of the sensor spacing and
signal-to-noise ratio (SNR). It is shown that the error exponent has a distinct
characteristic: at high SNR, the error exponent is monotonically increasing
with respect to sensor spacing, while at low SNR there is an optimal spacing
for scheduled sensors.


  The optimization of MRI data sampling and image reconstruction methods has
been a priority for the MRI community since the very early days of the field.
Designing an "optimal" method requires the definition of an optimality metric
(i.e., a quantitative evaluation of the "goodness" of different competing
approaches that allows an objective comparison between them). However, a key
challenge is that there are many different possible ways of quantitatively
evaluating the "goodness" of a data sampling scheme or a reconstruction result,
and there are no acquisition or reconstruction methods that are known to be
universally optimal with respect to all of these possible metrics
simultaneously. Thus, optimization of MRI methods requires a subjective choice
about what aspects of quality matter most in the context of a given MRI
experiment, and subsequently the subjective choice of an optimality metric that
hopefully does a reasonable job of quantifying those aspects of quality. Once
these choices are made, the optimization problem becomes well-defined, and it
remains to choose an algorithm that can identify data sampling or image
reconstruction methods that are optimal with respect to the chosen metric. All
of these choices are generally nontrivial.
  In this presentation, we will discuss optimal sampling and reconstruction
designs from multiple different perspectives, including ideas from information
and estimation theory and various practical perspectives.


  Ensuring the correctness of distributed system implementations remains a
challenging and largely unaddressed problem. In this paper we present a
protocol that can be used to certify the safety of consensus implementations.
Our proposed protocol is efficient both in terms of the number of additional
messages sent and their size, and is designed to operate correctly in the
presence of $n-1$ nodes failing in an $n$ node distributed system (assuming
fail-stop failures). We also comment on how our construction might be
generalized to certify other protocols and invariants.


  In this talk I present the current status of a precise first-principles
calculation of the quark connected, quark disconnected, and leading QED and
strong isospin-breaking contributions to the leading-order hadronic vacuum
polarization by the RBC and UKQCD collaborations. The lattice data is also
combined with experimental $e^+ e^-$ scattering data, consistency between the
two datasets is checked, and a combined result with smaller error than the
lattice data and $e^+ e^-$ scattering data individually is presented.


  Graph transformer has been proven as an effective graph learning method for
its adoption of attention mechanism that is capable of capturing expressive
representations from complex topological and feature information of graphs.
Graph transformer conventionally performs dense attention (or global attention)
for every pair of nodes to learn node representation vectors, resulting in
quadratic computational costs that are unaffordable for large-scale graph data.
Therefore, mini-batch training for graph transformers is a promising direction,
but limited samples in each mini-batch can not support effective dense
attention to encode informative representations. Facing this bottleneck, (1) we
start by assigning each node a token list that is sampled by personalized
PageRank (PPR) and then apply standard multi-head self-attention only on this
list to compute its node representations. This PPR tokenization method
decouples model training from complex graph topological information and makes
heavy feature engineering offline and independent, such that mini-batch
training of graph transformers is possible by loading each node's token list in
batches. We further prove this PPR tokenization is viable as a graph
convolution network with a fixed polynomial filter and jumping knowledge.
However, only using personalized PageRank may limit information carried by a
token list, which could not support different graph inductive biases for model
training. To this end, (2) we rewire graphs by introducing multiple types of
virtual connections through structure- and content-based super nodes that
enable PPR tokenization to encode local and global contexts, long-range
interaction, and heterophilous information into each node's token list, and
then formalize our Virtual Connection Ranking based Graph Transformer
(VCR-Graphormer).


  Universal quantifiers occur frequently in proof obligations produced by
program verifiers, for instance, to axiomatize uninterpreted functions and to
express properties of arrays. SMT-based verifiers typically reason about them
via E-matching, an SMT algorithm that requires syntactic matching patterns to
guide the quantifier instantiations. Devising good matching patterns is
challenging. In particular, overly restrictive patterns may lead to spurious
verification errors if the quantifiers needed for a proof are not instantiated;
they may also conceal unsoundness caused by inconsistent axiomatizations. In
this paper, we present the first technique that identifies and helps the users
remedy the effects of overly restrictive matching patterns. We designed a novel
algorithm to synthesize missing triggering terms required to complete a proof.
Tool developers can use this information to refine their matching patterns and
prevent similar verification errors, or to fix a detected unsoundness.


  We study the dynamics of polymers and elastic manifolds in non potential
static random flows. We find that barriers are generated from combined effects
of elasticity, disorder and thermal fluctuations. This leads to glassy trapping
even in pure barrier-free divergenceless flows $v {f \to 0}{\sim} f^\phi$
($\phi > 1$). The physics is described by a new RG fixed point at finite
temperature. We compute the anomalous roughness $R \sim L^\zeta$ and dynamical
$t\sim L^z$ exponents for directed and isotropic manifolds.


  The question of optimal spanwise-periodic modification for the stabilisation
of spanwise-invariant flows is addressed. A 2nd-order sensitivity analysis is
conducted for the linear temporal stability of parallel flows U0 subject to
small-amplitude spanwise-periodic modification e*U1, e<<1. Spanwise-periodic
modifications have a quadratic effect on stability, i.e. the 1st-order
eigenvalue variation is zero. A 2nd-order sensitivity operator is computed from
a 1D calculation, allowing one to predict how eigenvalues are affected by any
U1, without actually solving for modified eigenvalues/eigenmodes. Comparisons
with full 2D stability calculations in a plane channel flow and in a mixing
layer show excellent agreement. Next, optimisation is performed on the
2nd-order sensitivity operator: for each eigenmode streamwise wavenumber and
base flow modification spanwise wavenumber b, the most stabilising profiles U1
are computed, together with lower bounds for the variation in leading
eigenvalue. These bounds increase like b^-2 as b goes to 0, yielding a large
stabilising potential. However, 3D modes with wavenumbers |b0|=b and b/2 are
destabilised, thus larger control wavenumbers should be preferred. The
modification U1 optimised for the most unstable streamwise wavenumber has a
stabilising effect on other streamwise wavenumbers too. Finally, the potential
of transient growth to amplify perturbations and stabilise the flow is
assessed. Combined optimal perturbations that achieve the best balance between
transient linear amplification and flow stabilisation are determined. In the
mixing layer with b<1.5, these combined optimal perturbations appear similar to
transient growth-only optimal perturbations, and achieve a more efficient
overall stabilisation than optimal 1D and 2D modifications computed for
stabilisation only. This is consistent with the efficiency of streak-based
control strategies.


  We consider de Branges-Rovnyak spaces of a considerably large class of
reproducing kernel Hilbert spaces and find a characterization for them to be
complete Nevanlinna-Pick spaces. This extends as well as recovers earlier
characterizations obtained for the Hardy space over the unit disc (\cite{Chu})
as well as for the Drury-Arveson space over the unit ball (\cite{Jesse}). Our
characterization takes a complete form for the particular cases of the Hardy
space over the polydisc and the Bergman space over the disc. We show that a
non-trivial de Branges-Rovnyak space, associated to a contractive multiplier,
of the Hardy space over the bidisc or the Bergman space over the unit disc is a
complete Nevanlinna-Pick space if and only if it is isometrically isomorphic to
the Hardy space over the unit disc. On the contrary, it is shown that
non-trivial de Branges-Rovnyak spaces of the Hardy space over the $n$-disc with
$n\ge 3$ are never complete Nevanlinna-Pick spaces.


  Evolution gave rise to creatures that are arguably more sophisticated than
the greatest human-designed systems. This feat has inspired computer scientists
since the advent of computing and led to optimization tools that can evolve
complex neural networks for machines -- an approach known as "neuroevolution".
After a few successes in designing evolvable representations for
high-dimensional artifacts, the field has been recently revitalized by going
beyond optimization: to many, the wonder of evolution is less in the perfect
optimization of each species than in the creativity of such a simple iterative
process, that is, in the diversity of species. This modern view of artificial
evolution is moving the field away from microevolution, following a fitness
gradient in a niche, to macroevolution, filling many niches with highly
different species. It already opened promising applications, like evolving gait
repertoires, video game levels for different tastes, and diverse designs for
aerodynamic bikes.


  Drifting is a complicated task for autonomous vehicle control. Most
traditional methods in this area are based on motion equations derived by the
understanding of vehicle dynamics, which is difficult to be modeled precisely.
We propose a robust drift controller without explicit motion equations, which
is based on the latest model-free deep reinforcement learning algorithm soft
actor-critic. The drift control problem is formulated as a trajectory following
task, where the errorbased state and reward are designed. After being trained
on tracks with different levels of difficulty, our controller is capable of
making the vehicle drift through various sharp corners quickly and stably in
the unseen map. The proposed controller is further shown to have excellent
generalization ability, which can directly handle unseen vehicle types with
different physical properties, such as mass, tire friction, etc.


  We continue to study Lax (L-A, U-V) pairs (LP) joint covariance with respect
to Darboux transformations (DT) as a classification principle. The scheme is
based on a comparison of general expressions for the transformed coefficients
of LP and its Frechet derivative. We use the compact expressions of the DT via
some version of nonabelian Bell polynomials. It is shown that one more version
of Bell polynomials, so-called binary ones, form a convenient basis for the
invariant subspaces specification. Some non-autonomous generalization of KdV
and Boussinesq equations are discussed in the context.
  Trying to pick up restrictions at minimal operator level we consider
Zakharov-Shabat - like problem . The subclasses that allow a DT symmetry
(covariance at the LP level) are considered from a point of view of dressing
chain equations. The case of classic DT and binary combinations of elementary
DT are considered with possible reduction constraints of Mikhailov type
(generated by an automorphism). Examples of Liuville - von Neumann equation for
density matrix are referred as illustrations .


  This work focuses on the convergence analysis of adaptive distributed
beamforming schemes that can be reformulated as local random search algorithms
via a random search framework. Once reformulated as local random search
algorithms, it is proved that under two sufficient conditions: a) the objective
function of the algorithm is continuous and all its local maxima are global
maxima, and b) the origin is an interior point within the range of the
considered transformation of the random perturbation, the corresponding
adaptive distributed beamforming schemes converge both in probability and in
mean. This proof of convergence is general since it can be applied to analyze
randomized adaptive distributed beamforming schemes with any type of objective
functions and probability measures as long as both the sufficient conditions
are satisfied. Further, this framework can be generalized to analyze an
asynchronous scheme where distributed transmitters can only update their
beamforming coefficients asynchronously. Simulation results are also provided
to validate our analyses.


  Text generation system has made massive promising progress contributed by
deep learning techniques and has been widely applied in our life. However,
existing end-to-end neural models suffer from the problem of tending to
generate uninformative and generic text because they cannot ground input
context with background knowledge. In order to solve this problem, many
researchers begin to consider combining external knowledge in text generation
systems, namely knowledge-enhanced text generation. The challenges of knowledge
enhanced text generation including how to select the appropriate knowledge from
large-scale knowledge bases, how to read and understand extracted knowledge,
and how to integrate knowledge into generation process. This survey gives a
comprehensive review of knowledge-enhanced text generation systems, summarizes
research progress to solving these challenges and proposes some open issues and
research directions.


  We prove the numerical Hodge standard conjecture for the square of a simple
abelian variety of prime dimension, and also in some related cases.


  Quantum aspects, such as electron tunneling between closely separated
metallic nanoparticles, are crucial for understanding the plasmonic response of
nanoscale systems. We explore quantum effects on the response of the
conductively coupled metallic nanoparticle dimer. This is realized by
stretching a nanorod, which leads to the formation of a narrowing atomic
contact between the two nanorod ends. Based on first-principles time-dependent
density-functional-theory calculations, we find a discontinuous evolution of
the plasmonic response as the nanorod is stretched. This is especially
pronounced for the intensity of the main charge-transfer plasmon mode. We show
the correlation between the observed discontinuities and the discrete nature of
the conduction channels supported by the formed atomic-sized junction.


  The control of solute fluxes through either microscopic phoresis or
hydrodynamic advection is a fundamental way to transport molecules, which are
ubiquitously present in nature and technology. We study the transport of large
solute such as DNA driven by a time-dependent thermal field in a polymer
solution. Heat propagation of a single heat spot moving back and forth gives
rise to the molecular focusing of DNA with frequency-tunable control. We
developed a theoretical model, where heat conduction, viscoelastic expansion of
walls, and the viscosity gradient of a smaller solute are coupled, and that can
explain the underlying hydrodynamic focusing and its interplay with phoretic
transports. This cross effect may allow one to design a unique miniaturized
pump in microfluidics.


  We investigate the ground-state properties of two-component Bose gases
confined in one-dimensional harmonic traps in the scheme of density-functional
theory. The density-functional calculations employ a Bethe-ansatz-based
local-density approximation for the correlation energy, which accounts for the
correlation effect properly in the full physical regime. For the binary Bose
mixture with spin-independent interaction, the homogeneous reference system is
exactly solvable by the Bethe-ansatz method. Within the local-density
approximation, we determine the density distribution of each component and
study its evolution from Bose distributions to Fermi-like distribution with the
increase in interaction. For the binary mixture of Tonks-Girardeau gases with a
tunable inter-species repulsion, with a generalized Bose-Fermi transformation
we show that the Bose mixture can be mapped into a two-component Fermi gas,
which corresponds to exact soluble Yang-Gaudin model for the homogeneous
system. Based on the ground-state energy function of the Yang-Gaudin model, the
ground-state density distributions are calculated for various inter-species
interactions. It is shown that with the increase in inter-species interaction,
the system exhibits composite-fermionization crossover.


  We consider answering queries where the underlying data is available only
over limited interfaces which provide lookup access to the tuples matching a
given binding, but possibly restricting the number of output tuples returned.
Interfaces imposing such "result bounds" are common in accessing data via the
web. Given a query over a set of relations as well as some integrity
constraints that relate the queried relations to the data sources, we examine
the problem of deciding if the query is answerable over the interfaces; that
is, whether there exists a plan that returns all answers to the query, assuming
the source data satisfies the integrity constraints.
  The first component of our analysis of answerability is a reduction to a
query containment problem with constraints. The second component is a set of
"schema simplification" theorems capturing limitations on how interfaces with
result bounds can be useful to obtain complete answers to queries. These
results also help to show decidability for the containment problem that
captures answerability, for many classes of constraints. The final component in
our analysis of answerability is a "linearization" method, showing that query
containment with certain guarded dependencies -- including those that emerge
from answerability problems -- can be reduced to query containment for a
well-behaved class of linear dependencies. Putting these components together,
we get a detailed picture of how to check answerability over result-bounded
services.


  Multidimensional optical signals are commonly recorded by varying the delays
between time ordered pulses. These control the evolution of the density matrix
and are described by ladder diagrams. We propose a new non-time-ordered
protocol based on following the time evolution of the wavefunction and
described by loop diagrams. The time variables in this protocol allow to
observe different types of resonances and reveal information about intraband
dephasing not readily available by time ordered techniques. The time variables
involved in this protocol become coupled when using entangled light, which
provides high selectivity and background free measurement of the various
resonances. Entangled light can resolve certain states even when strong
background due to fast dephasing suppresses the resonant features when probed
by classical light.


  We study the affine solutions of the equations of plane oscillations of cold
plasma, which, under the assumption of electrostaticity, correspond to the
Euler-Poisson equations in the repulsive case. It is proved that the zero
equilibrium state of the cold plasma equations, both with and without the
assumption of electrostaticity, is unstable in the class of all affine
solutions. It is also shown that an arbitrary perturbation of an axially
symmetric electrostatic solution leads to a finite time blow-up.


  We present the first comprehensive derivation of the intrinsic electronic
phase diagram of the iron-oxypnictide superconductors in the normal state based
on the analysis of the electrical resistivity $\rho$ of both
LaFeAsO$_{1-x}$F$_x$ and SmFeAsO$_{1-x}$F$_x$ for a wide range of doping. Our
data give clear-cut evidence for unusual normal state properties in these new
materials. In particular, the emergence of superconductivity at low doping
levels is accompanied by distinct anomalous transport behavior in $\rho$ of the
normal state which is reminiscent of the spin density wave (SDW) signature in
the parent material. At higher doping levels $\rho$ of LaFeAsO$_{1-x}$F$_x$
shows a clear transition from this pseudogap-like behavior to Fermi liquid-like
behavior, mimicking the phase diagram of the cuprates. Moreover, our data
reveal a correlation between the strength of the anomalous features and the
stability of the superconducting phase. The pseudogap-like features become
stronger in SmFeAsO$_{1-x}$F$_x$ where superconductivity is enhanced and vanish
when superconductivity is reduced in the doping region with Fermi liquid-like
behavior.


  We study multiplicative statistics for the eigenvalues of unitarily-invariant
Hermitian random matrix models. We consider one-cut regular polynomial
potentials and a large class of multiplicative statistics. We show that in the
large matrix limit several associated quantities converge to limits which are
universal in both the potential and the family of multiplicative statistics
considered. In turn, such universal limits are described by the
integro-differential Painlev\'e II equation, and in particular they connect the
random matrix models considered with the narrow wedge solution to the KPZ
equation at any finite time.


  We prove a Berry-Esseen type inequality for approximating expectations of
sufficiently smooth functions $f$, like $f=|\cdot|^3$, with respect to
standardized convolutions of laws $P_1,\ldots, P_n$ on the real line by
corresponding expectations based on symmetric two-point laws $Q_1,\ldots,Q_n$
isoscedastic to the $P_i$. Equality is attained for every possible
constellation of the Lipschitz constant $\|f"\|^{}_{\mathrm{L}}$ and the
variances and the third centred absolute moments of the $P_i$. The error bound
is strictly smaller than $\frac 16$ times the Lyapunov ratio times
$\|f"\|^{}_{\mathrm{L}}$, and tends to zero also if $n$ is fixed and the third
standardized absolute moments of the $P_i$ tend to one.
  In the homoscedastic case of equal variances of the $P_i$, and hence in
particular in the i.i.d. case, the approximating law is a standardized
symmetric binomial one.
  The inequality is strong enough to yield for some constellations, in
particular in the i.i.d. case with $n$ large enough given the standardized
third absolute moment of $P_1$, an improvement of a more classical and already
optimal Berry-Esseen type inequality of Tyurin (2009).
  Auxiliary results presented include some inequalities either purely
analytical or concerning Zolotarev's $\zeta$-metrics, and some binomial moment
calculations.


  Laser cooling of solids keeps attracting attention owing to abroad range of
its applications that extends from cm-sized all-optical cryocoolers for
airborne and space-based applications to cooling on nanoparticles for
biological and mesoscopic physics. Laser cooling of nanoparticles is a
challenging task. We propose to use Mie resonances to enhance anti-Stokes
fluorescence laser cooling in rare-earth (RE) doped nanoparticles made of
low-phonon glasses or crystals. As an example, we consider an Yb3+:YAG
nanosphere pumped at the long wavelength tail of the Yb3+ absorption spectrum
at 1030 nm. We show that if the radius of the nanosphere is adjusted to the
pump wavelength in such a manner that the pump excites some of its Mie resonant
modes, the cooling power density generated in the sample is considerably
enhanced and the temperature of the sample is consequently considerably (~ 63%)
decreased. This concept can be extended to nanoparticles of different shapes
and made from different low-phonon RE doped materials suitable for laser
cooling by anti-Stokes fluorescence.


  Recently Greg Martin derived an interesting formula for the least common
multiple of {1,2,...,n}. Here, we give an exposition of a concise proof in
terms of the sine function.


  In modern Commercial Off-The-Shelf (COTS) multicore systems, each core can
generate many parallel memory requests at a time. The processing of these
parallel requests in the DRAM controller greatly affects the memory
interference delay experienced by running tasks on the platform. In this paper,
we model a modern COTS multicore system which has a nonblocking last-level
cache (LLC) and a DRAM controller that prioritizes reads over writes. To
minimize interference, we focus on LLC and DRAM bank partitioned systems. Based
on the model, we propose an analysis that computes a safe upper bound for the
worst-case memory interference delay. We validated our analysis on a real COTS
multicore platform with a set of carefully designed synthetic benchmarks as
well as SPEC2006 benchmarks. Evaluation results show that our analysis is more
accurately capture the worst-case memory interference delay and provides safer
upper bounds compared to a recently proposed analysis which significantly
under-estimate the delay.


  We have used whole genome paired-end Illumina sequence data to identify
tandem duplications in 20 isofemale lines of D. yakuba, and 20 isofemale lines
of D. simulans and performed genome wide validation with PacBio long molecule
sequencing. We identify 1,415 tandem duplications that are segregating in D.
yakuba as well as 975 duplications in D. simulans, indicating greater variation
in D. yakuba. Additionally, we observe high rates of secondary deletions at
duplicated sites, with 8% of duplicated sites in D. simulans and 17% of sites
in D. yakuba modified with deletions. These secondary deletions are consistent
with the action of the large loop mismatch repair system acting to remove
polymorphic tandem duplication, resulting in rapid dynamics of gain and loss in
duplicated alleles and a richer substrate of genetic novelty than has been
previously reported. Most duplications are present in only single strains,
suggesting deleterious impacts are common. D. simulans shows larger numbers of
whole gene duplications in comparison to larger proportions of gene fragments
in D. yakuba. D. simulans displays an excess of high frequency variants on the
X chromosome, consistent with adaptive evolution through duplications on the D.
simulans X or demographic forces driving duplicates to high frequency. We
identify 78 chimeric genes in D. yakuba and 38 chimeric genes in D. simulans,
as well as 143 cases of recruited non-coding sequence in D. yakuba and 96 in D.
simulans, in agreement with rates of chimeric gene origination in D.
melanogaster. Together, these results suggest that tandem duplications often
result in complex variation beyond whole gene duplications that offers a rich
substrate of standing variation that is likely to contribute both to
detrimental phenotypes and disease, as well as to adaptive evolutionary change.


  The possibility to avoid the cosmic initial singularity as a consequence of
nonlinear effects on the Maxwell eletromagnetic theory is discussed. For a flat
FRW geometry we derive the general nonsingular solution supported by a magnetic
field plus a cosmic fluid and a nonvanishing vacuum energy density. The
nonsingular behavior of solutions with a time-dependent $\Lambda(t)$-term are
also examined. As a general result, it is found that the functional dependence
of $\Lambda(t)$ can uniquely be determined only if the magnetic field remains
constant. All these models are examples of bouncing universes which may exhibit
an inflationary dynamics driven by the nonlinear corrections of the magnetic
field.