  Disentangling New Physics effects from the Standard Model requires a good
understanding of all pieces that stem from the latter, especially the
uncertainties that might plague the theoretical estimations within the Standard
Model. In the light of recent measurements made in the decay of $B\to
K^*\ell^+\ell^-$, and accompanying possibilities of New Physics effects, we
re-examine the hadronic uncertainties that come about in this exclusive $b \to
s$ transition. We show that it is not trivial to distinguish New Physics
effects from these hadronic uncertainties and we attempt to quantify the latter
in its magnitude and kinematic shape from the recent LHCb measurements of the
angular observables in this decay mode. We also update our fit with the more
recent calculations of the form factors combined with the ones computed with
Lattice QCD.


  A possible way of defining M theory as the CS theory for the supergroup
$OSp(1|32)\times OSp(1|32)$ is investigated, based on the approach by Horava in
hep-th/9712130. In the high energy limit (expansion in M), where only the
highest ($R^5$) terms survive in the action, the supergroup contracts to the
D'Auria-Fre M theory supergroup. Then the contracted equations of motion are
solved by the usual 11d supergravity equations of motion, linearized in
everything but the vielbein. These two facts suggest that the whole nonlinear
11d sugra should be obtainable somehow in the contraction limit. Type IIB also
arises as a contraction of the $OSp(1|32)\times OSp(1|32)$ theory. The presence
of a cosmological constant in 11d constraints the parameter M experimentally to
be of the order of the inverse horizon size, $1/L_0$. Then the 11d Planck mass
$M_{P,11}\sim 10GeV$ (hopefully higher: $>TeV$ due to uncertainties).
Unfortunately, the most naive attempt at cosmological implications for the
theory is excluded experimentally. Interestingly, the low energy expansion
(high M) of the CS theory, truncated to the gravitational sector, gives much
better phenomenology.


  We study logarithmic operators in Coulomb gas models, and show that they
occur when the ``puncture'' operator of the Liouville theory is included in the
model. We also consider WZNW models for $SL(2,R)$, and for SU(2) at level 0, in
which we find logarithmic operators which form Jordan blocks for the current as
well as the Virasoro algebra.


  This is a condensed exposition of the results of math.QA/0601337, based on a
talk of the first author at the Oberwolfach workshop "Deformations and
Contractions in Mathematics and Physics", 15-21 January 2006.


  We calculate angle-dependent magnetoresistance oscillations (AMRO) for
interlayer transport of cuprate superconductors in the presence of ($\pi,\pi$)
order. The order reconstructs the Fermi surface, creating magnetic breakdown
junctions; we show how such magnetic breakdown effects can be incorporated into
calculations of interlayer conductivity for this system. We successfully fit
experimental data with our model, and these fits suggest a connection between
($\pi,\pi$) order and the anisotropic scattering observed in overdoped
cuprates. This work paves the way for the use of AMRO as a tool to distinguish
different kinds of ordered states.


  We study profinite completion of spaces in the model category of profinite
spaces and construct a rigidification of the completion functors of Artin-Mazur
and Sullivan which extends also to non-connected spaces. Another new aspect is
an equivariant profinite completion functor and equivariant fibrant replacement
functor for a profinite group acting on a space. This is crucial for
applications where, for example, Galois groups are involved, or for profinite
Teichmueller theory where equivariant completions are applied. Along the way we
collect and survey the most important known results about profinite completion
of spaces.


  We present results of a search for R-parity-violating decay of the neutralino
chi_1^0, taken to be the Lightest Supersymmetric Particle. It is assumed that
this decay proceeds through one of the lepton-number violating couplings
lambda-prime_2jk (j=1,2; k=1,2,3). This search is based on 77.5 pb-1 of data,
collected by the D0 experiment at the Fermilab Tevatron in ppbar collisions at
a center of mass energy of 1.8 TeV in 1992-1995.


  We define a coalgebra structure for open strings transverse to any framed
codimension 2 submanifold. When the submanifold is a knot in R^3, we show this
structure recovers a specialization of the Ng cord algebra, a non-trivial knot
invariant which is not determined by a number of other knot invariants.


  Canonical correlation analysis is a widely used multivariate statistical
technique for exploring the relation between two sets of variables. This paper
considers the problem of estimating the leading canonical correlation
directions in high-dimensional settings. Recently, under the assumption that
the leading canonical correlation directions are sparse, various procedures
have been proposed for many high-dimensional applications involving massive
data sets. However, there has been few theoretical justification available in
the literature. In this paper, we establish rate-optimal nonasymptotic minimax
estimation with respect to an appropriate loss function for a wide range of
model spaces. Two interesting phenomena are observed. First, the minimax rates
are not affected by the presence of nuisance parameters, namely the covariance
matrices of the two sets of random variables, though they need to be estimated
in the canonical correlation analysis problem. Second, we allow the presence of
the residual canonical correlation directions. However, they do not influence
the minimax rates under a mild condition on eigengap. A generalized sin-theta
theorem and an empirical process bound for Gaussian quadratic forms under rank
constraint are used to establish the minimax upper bounds, which may be of
independent interest.


  The technological advancements of recent years have steadily increased the
complexity of vehicle-internal software systems, and the ongoing development
towards autonomous driving will further aggravate this situation. This is
leading to a level of complexity that is pushing the limits of existing vehicle
software architectures and system designs. By changing the software structure
to a service-based architecture, companies in other domains successfully
managed the rising complexity and created a more agile and future-oriented
development process. This paper presents a case-study investigating the
feasibility and possible effects of changing the software architecture for a
complex driver assistance function to a microservice architecture. The complete
procedure is described, starting with the description of the
software-environment and the corresponding requirements, followed by the
implementation, and the final testing. In addition, this paper provides a
high-level evaluation of the microservice architecture for the automotive
use-case. The results show that microservice architectures can reduce
complexity and time-consuming process steps and makes the automotive software
systems prepared for upcoming challenges as long as the principles of
microservice architectures are carefully followed.


  Non-Newtonian fluids have a viscosity that varies with applied stress.
Elastoviscoplastic fluids, the elastic, viscous and plastic properties of which
are interconnected in a non-trivial way, belong to this category. We have
performed numerical simulations to investigate turbulence in elastoviscoplastic
fluids at very high Reynolds-number values, as found in landslides and lava
flows, focusing on the effect of plasticity. We find that the range of active
scales in the energy spectrum reduces when increasing the fluid plasticity;
when plastic effects dominate, a new scaling range emerges between the inertial
range and the dissipative scales. An extended self-similarity analysis of the
structure functions reveals that intermittency is present and grows with the
fluid plasticity. The enhanced intermittency is caused by the non-Newtonian
dissipation rate, which also exhibits an intermittent behaviour. These findings
have relevance to catastrophic events in natural flows, such as landslides and
lava flows, where the enhanced intermittency results in stronger extreme
events, which are thus more destructive and difficult to predict.


  The Escalator Boxcar Train (EBT) is a numerical method that is widely used in
theoretical biology to investigate the dynamics of physiologically structured
population models, i.e., models in which individuals differ by size or other
physiological characteristics. The method was developed more than two decades
ago, but has so far resisted attempts to give a formal proof of convergence.
Using a modern framework of measure-valued solutions, we investigate the EBT
method and show that the sequence of approximating solution measures generated
by the EBT method converges weakly to the true solution measure under weak
conditions on the growth rate, birth rate, and mortality rate. In rigorously
establishing the convergence of the EBT method, our results pave the way for
wider acceptance of the EBT method beyond theoretical biology and constitutes
an important step towards integration with established numerical schemes.


  We consider the entanglement of closed bosonic strings intersecting the event
horizon of a Rindler spacetime and, by using some simplified (rather
semiclassical) arguments and some elements of the string field theory, we show
the existence of a critical temperature beyond which closed strings
\emph{cannot be in thermal equilibrium}. The order of magnitude of this
critical value coincides with the Hagedorn temperature, which suggests an
interpretation consistent with the fact of having a partition function which is
bad defined for temperatures higher than it. Possible implications of the
present approach on the microscopical structure of stretched horizons are also
pointed out.


  This paper addresses the problem of designing a data-driven feedback
controller for complex nonlinear dynamical systems in the presence of
time-varying disturbances with unknown dynamics. Such disturbances are modeled
as the "unknown" part of the system dynamics. The goal is to achieve
finite-time regulation of system states through direct policy updates while
also generating informative data that can subsequently be used for data-driven
stabilization or system identification. First, we expand upon the notion of
"regularizability" and characterize this system characteristic for a linear
time-varying representation of the nonlinear system with locally-bounded
higher-order terms. "Rapid-regularizability" then gauges the extent by which a
system can be regulated in finite time, in contrast to its asymptotic behavior.
We then propose the Data-Guided Regulation for Adaptive Nonlinear Control (
DG-RAN) algorithm, an online iterative synthesis procedure that utilizes
discrete time-series data from a single trajectory for regulating system states
and identifying disturbance dynamics. The effectiveness of our approach is
demonstrated on a 6-DOF power descent guidance problem in the presence of
adverse environmental disturbances.


  Recent advances in the understanding of Generative Adversarial Networks
(GANs) have led to remarkable progress in visual editing and synthesis tasks,
capitalizing on the rich semantics that are embedded in the latent spaces of
pre-trained GANs. However, existing methods are often tailored to specific GAN
architectures and are limited to either discovering global semantic directions
that do not facilitate localized control, or require some form of supervision
through manually provided regions or segmentation masks. In this light, we
present an architecture-agnostic approach that jointly discovers factors
representing spatial parts and their appearances in an entirely unsupervised
fashion. These factors are obtained by applying a semi-nonnegative tensor
factorization on the feature maps, which in turn enables context-aware local
image editing with pixel-level control. In addition, we show that the
discovered appearance factors correspond to saliency maps that localize
concepts of interest, without using any labels. Experiments on a wide range of
GAN architectures and datasets show that, in comparison to the state of the
art, our method is far more efficient in terms of training time and, most
importantly, provides much more accurate localized control. Our code is
available at: https://github.com/james-oldfield/PandA.


  Nowadays, deep neural networks (DNNs) are the core enablers for many emerging
edge AI applications. Conventional approaches to training DNNs are generally
implemented at central servers or cloud centers for centralized learning, which
is typically time-consuming and resource-demanding due to the transmission of a
large amount of data samples from the device to the remote cloud. To overcome
these disadvantages, we consider accelerating the learning process of DNNs on
the Mobile-Edge-Cloud Computing (MECC) paradigm. In this paper, we propose
HierTrain, a hierarchical edge AI learning framework, which efficiently deploys
the DNN training task over the hierarchical MECC architecture. We develop a
novel \textit{hybrid parallelism} method, which is the key to HierTrain, to
adaptively assign the DNN model layers and the data samples across the three
levels of edge device, edge server and cloud center. We then formulate the
problem of scheduling the DNN training tasks at both layer-granularity and
sample-granularity. Solving this optimization problem enables us to achieve the
minimum training time. We further implement a hardware prototype consisting of
an edge device, an edge server and a cloud server, and conduct extensive
experiments on it. Experimental results demonstrate that HierTrain can achieve
up to 6.9x speedup compared to the cloud-based hierarchical training approach.


  We present a general statistical framework for describing the effect of
sample variance in the number counts of virialized objects and examine its
effect on cosmological parameter estimation. Specifically, we consider effects
of sample variance on the power spectrum normalization and properties of dark
energy extracted from current and future local and high-redshift samples of
clusters. We show that for future surveys that probe ever lower cluster masses
and temperatures, sample variance is generally comparable to or greater than
shot noise and thus cannot be neglected in deriving precision cosmological
constraints. For example, sample variance is usually more important than shot
variance in constraints on the equation of state of the dark energy from z < 1
clusters. Although we found that effects of sample variance on the
sigma_8-Omega_m constraints from the current flux and temperature limited X-ray
surveys are not significant, they may be important for future studies utilizing
the shape of the temperature function to break the sigma_8-Omega_m degeneracy.
We also present numerical tests clarifying the definition of cluster mass
employed in cosmological modelling and accurate fitting formula for the
conversion between different definitions of halo mass (e.g., virial vs. fixed
overdensity).


  We will explain how to compute the exact $L^p$ operator norm of a "quadratic
perturbation" of the real part of the Ahlfors--Beurling operator. For the lower
bound estimate we use a new approach of constructing a sequence of laminates
(probability measures for which Jensen's inequality holds, but for rank one
concave functions) to give an almost extremal sequence to approximate the
operator. The upper bound estimate is given by extending the estimates of the
quadratic perturbation of the martingale transform to continuous martingales.
The use of "heat martingales" then allow us to connect the Riesz transforms to
the continuous martingale estimate.


  Compilers for accelerator design languages (ADLs) translate high-level
languages into application-specific hardware. ADL compilers rely on a hardware
control interface to compose hardware units. There are two choices: static
control, which relies on cycle-level timing; or dynamic control, which uses
explicit signalling to avoid depending on timing details. Static control is
efficient but brittle; dynamic control incurs hardware costs to support
compositional reasoning. Piezo is an ADL compiler that unifies static and
dynamic control in a single intermediate language (IL). Its key insight is that
the IL's static fragment is a refinement of its dynamic fragment: static code
admits a subset of the run-time behaviors of the dynamic equivalent. Piezo can
optimize code by combining facts from static and dynamic submodules, and it
opportunistically converts code from dynamic to static control styles. We
implement Piezo as an extension to an existing dynamic ADL compiler, Calyx. We
use Piezo to implement an MLIR frontend, a systolic array generator, and a
packet-scheduling hardware generator to demonstrate its optimizations and the
static-dynamic interactions it enables.


  The acquisition of grammar has been a central question to adjudicate between
theories of language acquisition. In order to conduct faster, more
reproducible, and larger-scale corpus studies on grammaticality in
child-caregiver conversations, tools for automatic annotation can offer an
effective alternative to tedious manual annotation. We propose a coding scheme
for context-dependent grammaticality in child-caregiver conversations and
annotate more than 4,000 utterances from a large corpus of transcribed
conversations. Based on these annotations, we train and evaluate a range of NLP
models. Our results show that fine-tuned Transformer-based models perform best,
achieving human inter-annotation agreement levels.As a first application and
sanity check of this tool, we use the trained models to annotate a corpus
almost two orders of magnitude larger than the manually annotated data and
verify that children's grammaticality shows a steady increase with age.This
work contributes to the growing literature on applying state-of-the-art NLP
methods to help study child language acquisition at scale.


  Cosmic-ray electrons (CREs) originating from the star-forming discs of spiral
galaxies frequently form extended radio haloes that are best observable in
edge-on galaxies. For the present study we selected two nearby edge-on galaxies
from the CHANG-ES survey, NGC 891 and 4565, which differ largely in halo size
and SFR. To figure out how such differences are related to the CRE transport in
disc and halo, we use wide-band 1.5 and 6 GHz VLA observations obtained in the
B, C, and D configurations, and combine the 6 GHz images with Effelsberg
observations to correct for missing short spacings. We study the spatially
resolved non-thermal spectral index distribution in terms of CRE spectral
ageing, compute total magnetic field strengths assuming energy equipartition
between CRs and magnetic fields, and also determine synchrotron scale heights.
Based on the vertical profiles of synchrotron intensity and spectral index, we
create purely advective and purely diffusive CRE transport models by
numerically solving the 1D diffusion-loss equation. In particular, we
investigate for the first time the radial dependence of synchrotron and
magnetic field scale heights, advection speeds and diffusion coefficients in
these two galaxies. We find the spectral index distribution of NGC 891 to be
mostly consistent with continuous CRE injection, while in NGC 4565 the local
synchrotron spectra are more in line with discrete-epoch CRE injection (JP or
KP models). This implies that CRE injection timescales are lower than the
synchrotron cooling timescales. The scale height of NGC 891 increases with
radius, indicating that synchrotron losses are significant. NGC 891 is probably
dominated by advective CRE transport at a velocity of
$\gtrsim150\,\mathrm{km\,s^{-1}}$. In contrast, NGC 4565 is diffusion-dominated
up to $z=1$ kpc or higher, with a diffusion coefficient of
$\geq2\times10^{28}\,\mathrm{cm^2\,s^{-1}}$.


  In this article, we consider a multi-agent path planning problem in a
stochastic environment. The environment, which can be an urban road network, is
represented by a graph where the travel time for selected road segments
(impeded edges) is a random variable because of traffic congestion. An unmanned
ground vehicle (UGV) wishes to travel from a starting location to a destination
while minimizing the arrival time at the destination. UGV can traverse through
an impeded edge but the true travel time is only realized at the end of that
edge. This implies that the UGV can potentially get stuck in an impeded edge
with high travel time. A support vehicle, such as an unmanned aerial vehicle
(UAV) is simultaneously deployed from its starting position to assist the UGV
by inspecting and realizing the true cost of impeded edges. With the updated
information from UAV, UGV can efficiently reroute its path to the destination.
The UGV does not wait at any time until it reaches the destination. The UAV is
permitted to terminate its path at any vertex. The goal is then to develop an
online algorithm to determine efficient paths for the UGV and the UAV based on
the current information so that the UGV reaches the destination in minimum
time. We refer to this problem as Stochastic Assisted Path Planning (SAPP). We
present Dynamic $k$-Shortest Path Planning (D*KSPP) algorithm for the UGV
planning and Rural Postman Problem (RPP) formulation for the UAV planning. Due
to the scalability challenges of RPP, we also present a heuristic based
Priority Assignment Algorithm (PAA) for the UAV planning. Computational results
are presented to corroborate the effectiveness of the proposed algorithm to
solve SAPP.


  Despite their remarkable achievements, modern Large Language Models (LLMs)
face exorbitant computational and memory footprints. Recently, several works
have shown significant success in training-free and data-free compression
(pruning and quantization) of LLMs that achieve 50 - 60% sparsity and reduce
the bit width to 3 or 4 bits per weight, with negligible degradation of
perplexity over the uncompressed baseline. As recent research efforts are
focused on developing increasingly sophisticated compression methods, our work
takes a step back and re-evaluates the effectiveness of existing SoTA
compression methods, which rely on a fairly simple and widely questioned
metric, perplexity (even for dense LLMs). We introduce Knowledge-Intensive
Compressed LLM BenchmarK (LLM-KICK), a collection of carefully curated tasks to
redefine the evaluation protocol for compressed LLMs, which have significant
alignment with their dense counterparts and perplexity fail to capture subtle
change in their true capabilities. LLM-KICK unveils many favorable merits and
unfortunate plights of current SoTA compression methods: all pruning methods
suffer significant performance degradation, sometimes at trivial sparsity
ratios (e.g., 25-30%), and fail for N:M sparsity in knowledge-intensive tasks;
current quantization methods are more successful than pruning; yet, pruned LLMs
even at $\geq 50$% sparsity are robust in-context retrieval and summarization
systems; among others. LLM-KICK is designed to holistically access compressed
LLMs' ability for language understanding, reasoning, generation, in-context
retrieval, in-context summarization, etc. We hope our study can foster the
development of better LLM compression methods. The reproduced codes are
available at https://github.com/VITA-Group/llm-kick.


  We establish the triple integral evaluation \[ \int_{1}^{\infty} \int_{0}^{1}
\int_{0}^{1} \frac{dz \, dy \, dx}{x(x+y)(x+y+z)}
  = \frac{5}{24} \zeta(3), \] as well as the equivalent polylogarithmic double
sum \[ \sum_{k=1}^{\infty} \sum_{j=k}^{\infty} \frac{(-1)^{k-1}}{k^{2}} \,
\frac{1}{j \, 2^{j}}
  = \frac{13}{24} \zeta(3). \] This double sum is related to, but less
approachable than, similar sums studied by Ramanujan. It is also reminiscent of
Euler's formula $\zeta(2,1) = \zeta(3)$, which is the simplest instance of
duality of multiple polylogarithms. We review this duality and apply it to
derive a companion identity. We also discuss approaches based on computer
algebra. All of our approaches ultimately require the introduction of
polylogarithms and nontrivial relations between them. It remains an open
challenge to relate the triple integral or the double sum to $\zeta(3)$
directly.


  Let $f\in\Sigma_{n,2d}$ be a sum of squares. The Gram spectrahedron of $f$ is
a compact, convex set that parametrizes all sum of squares representations of
$f$. Let $F\subseteq\mathrm{Gram}(f)$ be a face of its Gram spectrahedron. We
are interested in upper bounds for the dimension of $F$. We show that this
upper bound can be determined combinatorially. As it turns out, if the degree
is large enough, a face realizing this bound, is a face of a Gram spectrahedron
such that the form $f$ is singular. Thus we are also interested in finding
better bounds whenever the form $f$ is smooth.


  It is known that the formation of a wormhole typically involves a violation
of the Weak Energy Condition (WEC), but the reverse is not necessarily true. In
the context of Brans-Dicke gravity, the $\textit{generalized}$
Campanelli-Lousto solution, which we shall unveil in this paper, demonstrates a
WEC violation that coincides with the appearance of $\textit{unbounded}$ sheets
of spacetime within the "interior" section. The emergence of a wormhole in the
"exterior" section is thus only an indirect consequence of the WEC violation.
Additionally, we use the generalized Campanelli-Lousto solution to construct a
Kruskal-Szekeres diagram, which exhibits a "gulf" sandwiched between the four
quadrants in the diagram, a novel feature in Brans-Dicke gravity. Overall, our
findings shed new light onto a complex interplay between the WEC and wormholes
in the Brans-Dicke theory.


  We have calculated the Wilson coefficients $C_{10}, C_{Q_i}$ (i=1,2) in the
$\bar{MS}$ renormalization scheme in the model III 2HDM. Using the obtained
Wilson coefficients, we have analyzed the CP violation in decays $B^0_q\to
l^+l^-$ (q=d,s) in the model. The CP asymmetry, $A_{CP}$, depends on the
parameters of models and $A_{CP}$ in $B_d\to l^+l^-$ can be as large as 40% and
35% for $l=\tau$ and $l=\mu$ respectively. It can reach 4% for $B^0_s$ decays.
Because in SM CP violation is smaller than or equal to O($10^{-3}$) which is
unobservably small, an observation of CP asymmetry in the decays $B^0_q \to
l^+l^- (q=d,s)$ would unambiguously signal the existence of new physics.


  Measurements of distributions of charged particles produced in proton-proton
collisions with a centre-of-mass energy of 13 TeV are presented. The data were
recorded by the ATLAS detector at the LHC and correspond to an integrated
luminosity of 151 $\mu$b$^{-1}$. The particles are required to have a
transverse momentum greater than 100 MeV and an absolute pseudorapidity less
than 2.5. The charged-particle multiplicity, its dependence on transverse
momentum and pseudorapidity and the dependence of the mean transverse momentum
on multiplicity are measured in events containing at least two charged
particles satisfying the above kinematic criteria. The results are corrected
for detector effects and compared to the predictions from several Monte Carlo
event generators.


  Equations of motion and the lagrangian are derived explicitely for Dual D=10,
N=1 Supergravity considered as a field theory limit of a Fivebrane. It is used
the mass-shell solution of Heterotic String Bianchi Identites obtained in the
2-dimensional $\sigma$-model two-loop approximation and in the tree-level
Heterotic String approximation. As a result the Dual Supergravity lagrangian is
derived in the one-loop Five-Brane approximation and in the lowest
6-dimensional $\sigma$-model approximaton.


  We investigate the birthrate problem for low-mass X-ray binaries (LMXBs) and
millisecond radio pulsars (MRPs) in this paper. We consider intermediate-mass
and low-mss X-ray binaries (I/LMXBs) as the progenitors of MRPs, and calculate
their evolutionary response to the cosmic star formation rate (SFR) both
semi-analytically and numerically. With typical value (~1 Gyr) of the LMXB
lifetime, one may expect comparable birthrates of LMXBs and MRPs, but the
calculated number of LMXBs is an order of magnitude higher than observed in the
Galaxy. Instead, we suggest that the birthrate problem could be solved if most
MRPs have evolved from faint rather bright LMXBs. The former may have a
population of ~ 104 in the Galaxy.


  Numerical software is usually shipped with built-in hyperparameters. By
carefully tuning those hyperparameters, significant performance enhancements
can be achieved for specific applications. We developed MindOpt Tuner, a new
automatic tuning tool that supports a wide range of numerical software,
including optimization and other solvers. MindOpt Tuner uses elastic cloud
resources, features a web-based task management panel and integration with
ipython notebook with both command-line tools and Python APIs. Our experiments
with COIN-OR Cbc, an open-source mixed-integer optimization solver, demonstrate
remarkable improvements with the tuned parameters compared to the default ones
on the MIPLIB2017 test set, resulting in over 100x acceleration on several
problem instances. Additionally, the results demonstrate that Tuner has a
higher tuning efficiency compared to the state-of-the-art automatic tuning tool
SMAC3.


  Literary reading is an important activity for individuals and choosing to
read a book can be a long time commitment, making book choice an important task
for book lovers and public library users. In this paper we present an hybrid
recommendation system to help readers decide which book to read next. We study
book and author recommendation in an hybrid recommendation setting and test our
approach in the LitRec data set. Our hybrid book recommendation approach
purposed combines two item-based collaborative filtering algorithms to predict
books and authors that the user will like. Author predictions are expanded in
to a book list that is subsequently aggregated with the former list generated
through the initial collaborative recommender. Finally, the resulting book list
is used to yield the top-n book recommendations. By means of various
experiments, we demonstrate that author recommendation can improve overall book
recommendation.


  In-silico investigation of skin permeation is an important but also
computationally demanding problem. To resolve all scales involved in full
detail will not only require exascale computing capacities but also suitable
parallel algorithms. This article investigates the applicability of the
time-parallel Parareal algorithm to a brick and mortar setup, a precursory
problem to skin permeation. The C++ library Lib4PrM implementing Parareal is
combined with the UG4 simulation framework, which provides the spatial
discretization and parallelization. The combination's performance is studied
with respect to convergence and speedup. It is confirmed that anisotropies in
the domain and jumps in diffusion coefficients only have a minor impact on
Parareal's convergence. The influence of load imbalances in time due to
differences in number of iterations required by the spatial solver as well as
spatio-temporal weak scaling is discussed.


  In analogy with classical electromagnetic theory, where one determines the
total charge and both electric and magnetic multipole moments of a source from
certain surface integrals of the asymptotic (or far) fields, it has been known
for many years - from the work of Hermann Bondi - that energy and momentum of
gravitational sources could be determined by similar integrals of the
asymptotic Weyl tensor. Recently we observed that there were certain overlooked
structures, {defined at future null infinity,} that allowed one to determine
(or define) further properties of both electromagnetic and gravitating sources.
These structures, families of {complex} `slices' or `cuts' of Penrose's null
infinity, are referred to as Universal Cut Functions, (UCF). In particular, one
can define from these structures a (complex) center of mass (and center of
charge) and its equations of motion - with rather surprising consequences. It
appears as if these asymptotic structures contain in their imaginary part, a
well defined total spin-angular momentum of the source. We apply these ideas to
the type II algebraically special metrics, both twisting and twist-free.


  To improve the efficiency of surgical trajectory segmentation for robot
learning in robot-assisted minimally invasive surgery, this paper presents a
fast unsupervised method using video and kinematic data, followed by a
promoting procedure to address the over-segmentation issue. Unsupervised deep
learning network, stacking convolutional auto-encoder, is employed to extract
more discriminative features from videos in an effective way. To further
improve the accuracy of segmentation, on one hand, wavelet transform is used to
filter out the noises existed in the features from video and kinematic data. On
the other hand, the segmentation result is promoted by identifying the adjacent
segments with no state transition based on the predefined similarity
measurements. Extensive experiments on a public dataset JIGSAWS show that our
method achieves much higher accuracy of segmentation than state-of-the-art
methods in the shorter time.


  We obtained long-slit optical spectroscopy of one transit of WASP-48b with
the Optical System for Imaging and low-Intermediate-Resolution Integrated
Spectroscopy (OSIRIS) spectrograph at the 10.4 m Gran Telescopio Canarias
(GTC). We integrated the spectrum of WASP-48 and one reference star in several
channels with different wavelength ranges, creating numerous color light curves
of the transit. We fit analytic transit curves to the data taking into account
the systematic effects present in the time series in an effort to measure the
change of the planet-to-star radius ratio ($R_p/R_s$) across wavelength. After
removing the transit model and systematic trends to the curves we reached
precisions between 261 ppm and 455-755 ppm for the white and spectroscopic
light curves, respectively. We obtained $R_p/R_s$ uncertainty values between
$0.8 \times 10^{-3}$ and $1.5\times 10^{-3}$ for all the curves analyzed in
this work. The measured transit depth for the curves made by integrating the
wavelength range between 530 nm and 905 nm is in agreement with previous
studies. We report a relatively flat transmission spectrum for WASP-48b with no
statistical significant detection of atmospheric species, although the
theoretical models that fit the data more closely include of TiO and VO.


  A loop $X$ is said to satisfy Moufang's theorem if for every $x,y,z\in X$
such that $x(yz)=(xy)z$ the subloop generated by $x$, $y$, $z$ is a group. We
prove that the variety $V$ of Steiner loops satisfying the identity
$(xz)(((xy)z)(yz)) = ((xz)((xy)z))(yz)$ is not contained in the variety of
Moufang loops, yet every loop in $V$ satisfies Moufang's theorem. This solves a
problem posed by Andrew Rajah.


  Relations between star formation rates along the spiral arms and the
velocities of gas inflow into the arms in grand-design galaxy NGC 628 were
studied. We found that the radial distribution of average star formation rate
in individual star formation regions in regular spiral arms correlates with the
velocity of gas inflow into the spiral arms. Both distributions have maxima at
a galactocentric distance of 4.5-5 kpc. There are no correlations between the
radial distributions of average star formation rate in star formation regions
in spiral arms and outside spiral arms in the main disc. We also did not find a
correlation between the radial distribution of average star formation rate in
star formation regions in spiral arms and HI column density.


  In the modified dynamics (MOND) the inner workings of dwarf satellites can be
greatly affected by their mother galaxy-over and beyond its tidal effects.
Because of MOND's nonlinearity a system's internal dynamics can be altered by
an external field in which it is immersed (even when this field, by itself, is
constant in space). As a result, the size and velocity dispersion of the
satellite vary as the external field varies along its orbit. A notable outcome
of this is a substantial increase in the dwarf's vulnerability to eventual
tidal disruption-rather higher than Newtonian dynamics (with a dark-matter
halo) would lead us to expect for a satellite with given observed parameters.


  For scalar fully nonlinear partial differential equations depending on the
Hessian andspatial coordinates, we present a general theory for obtaining
comparison principles and well posedness for the associated Dirichlet problem
with continuous boundary data. In particular, we treat admissible viscosity
solutions of elliptic branches of the equation, where the nonlinearity need not
be monotone on all of the space of symmetric N by N matrices. An elliptic
branch (in the sense of Krylov, 1995) of the equation is encoded by a set
valued map from the coordinate domain into the elliptic subsets of the
symmetric matrices (an elliptic map). The nonlinearity will be monotone along
this map and the degenerate elliptic PDE is replaced by the a differential
inclusion. Weak solutions to such differential inclusions are defined by using
the notion given by Harvey-Lawson (2009) in a pointwise manner. If the elliptic
map is uniformly upper semicontinuous, we show that the comparison principle
holds for these weak solutions and that Perron's method yields a unique
continuous solution to the associated abstract Dirichlet problem provided that
the boundary is suitably convex with respect to the elliptic mapand its dual in
the sense of Harvey and Lawson. When the map encodes an elliptic branch of a
given PDE, these soluitions are shown to be admissible viscosity solutions of
the PDE problem. Various applications are described in terms of structural
conditions which ensure the existence of the needed elliptic map. Examples
include non-totally degenerate equations and equations involving the
eigenvalues of the Hessian and their perturbations. In certain situations, the
methods employed here will be shown to operate freely, while classical
viscosity approaches may not.


  Knot contact homology is an invariant of knots derived from Legendrian
contact homology which has numerous connections to the knot group. We use basic
properties of knot groups to prove that knot contact homology detects every
torus knot. Further, if the knot contact homology of a knot is isomorphic to
that of a cable (respectively composite) knot, then the knot is a cable
(respectively composite).


  These notes, based on the remarks made at the 23 Solvay Conference, collect
several speculative ideas concerning gauge/ strings duality, de Sitter spaces,
dimensionality and the cosmological constant.


  We show how the Dubinin isotherm and its extensions can be related to the
isotherms derived from the general BrouersSotolongo isotherm. We compare them
using benzene vapor adsorbed on activated carbon data from one of the original
Dubinin paper. We use the same procedure to analyze data from the thesis of
MarquezMontesino on the adsorption on activated carbon prepared from pinus
caribaea saw dust. We conclude by proposing a simple methodology to determine
the macroscopic information given by genuine statistical isotherms.


  Ab-initio theory is developed for energies of J=1 particle-hole states of
neutral neon and for oscillator strengths of transitions from such states to
the J=0 ground state. Hole energies of low-Z neonlike ions are evaluated.


  Jellium correction on the fissionability parameter is estimated within a
Liquid Drop Model of the charged metallic cluster. This correction modifies the
critical condition of fission and, it becomes relevant for small multicharged
clusters.


  In the extended NJL model the total cross sections of the processes $e^+e^-
\to (\eta, \eta', \eta(1295), \eta(1405))\gamma$ at energies up to 2 GeV are
calculated. The intermediate vector mesons $\rho (770)$, $\omega(782)$, $\phi
(1020)$, $\rho' (1450)$, $\omega' (1420)$ and $\phi' (1680)$ are taken into
account. The latter three mesons are treated as the first radial excited
states. They are incorporated into the NJL model by means of polynomial form
factors. The calculation results are in satisfactory agreement with the
experimental data obtained with the SND detector at the VEPP-2M, Novosibirsk.
The predictions given for the process $e^+e^- \to (\eta',\eta(1295),
\eta(1405)) \gamma$ have not been experimentally tested yet.


  Future power grids are fundamentally different from current ones, both in
size and in complexity; this trend imposes challenges for situation awareness
(SA) based on classical indicators, which are usually model-based and
deterministic. As an alternative, this paper proposes a statistical indicator
system based on linear eigenvalue statistics (LESs) of large random matrices:
1) from a data modeling viewpoint, we build, starting from power flows
equations, the random matrix models (RMMs) only using the real-time data flow
in a statistical manner; 2) for a data analysis that is fully driven from RMMs,
we put forward the high-dimensional indicators, called LESs that have some
unique statistical features such as Gaussian properties; and 3) we develop a
three-dimensional (3D) power-map to visualize the system, respectively, from a
high-dimensional viewpoint and a low-dimensional one. Therefore, a statistical
methodology of SA is employed; it conducts SA with a model-free and data-driven
procedure, requiring no knowledge of system topologies, units operation/control
models, causal relationship, etc. This methodology has numerous advantages,
such as sensitivity, universality, speed, and flexibility. In particular, its
robustness against bad data is highlighted, with potential advantages in cyber
security. The theory of big data based stability for on-line operations may
prove feasible along with this line of work, although this critical development
will be reported elsewhere.


  We show that excited baryons in large N_c QCD form multiplets, within which
masses are first split at O(1/N_c). The dominant couplings of resonances to
various mesons are highly constrained: The N(1535) decays at leading 1/N_c
order exclusively to eta-N rather than pi-N, and vice versa for the N(1650).
This multiplet structure is reproduced by a simple large N_c quark model, well
studied in the literature, that describes resonances as single-quark
excitations.


  We construct an Euler system for the adjoint Galois representation of a
modular form, using motivic cohomology classes arising from Hilbert modular
surfaces. We use this Euler system to give an upper bound for the Selmer group
of the adjoint representation over the cyclotomic Zp-extension, which agrees
with the predictions of the Iwasawa main conjecture up to powers of p and the
augmentation ideal.


  This paper explores optimization of paging and registration policies in
cellular networks. Motion is modeled as a discrete-time Markov process, and
minimization of the discounted, infinite-horizon average cost is addressed. The
structure of jointly optimal paging and registration policies is investigated
through the use of dynamic programming for partially observed Markov processes.
It is shown that there exist policies with a certain simple form that are
jointly optimal, though the dynamic programming approach does not directly
provide an efficient method to find the policies.
  An iterative algorithm for policies with the simple form is proposed and
investigated. The algorithm alternates between paging policy optimization and
registration policy optimization. It finds a pair of individually optimal
policies, but an example is given showing that the policies need not be jointly
optimal. Majorization theory and Riesz's rearrangement inequality are used to
show that jointly optimal paging and registration policies are given for
symmetric or Gaussian random walk models by the nearest-location-first paging
policy and distance threshold registration policies.


  The motion of classical spinning test particles in the equatorial plane of a
Kerr black hole is considered for the case where the particle spin is
perpendicular to the equatorial plane. We review some results of our recent
research of the innermost stable circular orbits (ISCO) [P.I. Jefremov, O.Yu.
Tsupko and G.S. Bisnovatyi-Kogan, Phys.Rev. D 91 124030 (2015)] and present
some new calculations. The ISCO radius, total angular momentum, energy, and
orbital angular frequency are considered. We calculate the ISCO parameters
numerically for different values of the Kerr parameter $a$ and investigate
their dependence on both black hole and test particle spins. Then we describe
in details how to calculate analytically small-spin corrections to the ISCO
parameters for an arbitrary values of $a$. The cases of Schwarzschild, slowly
rotating Kerr and extreme Kerr black hole are considered. The use of the
orbital angular momentum is discussed. We also consider the ISCO binding
energy. It is shown that the efficiency of accretion onto an extreme Kerr black
hole can be larger than the maximum known efficiency (42 %) if the test body
has a spin.


  Different regularizations are studied in localization of path integrals. We
discuss the effect of the choice of regularization by evaluating the partition
functions for the harmonic oscillator and the Weyl character for SU(2). In
particular, we solve the Weyl shift problem that arises in path integral
evaluation of the Weyl character by using the Atiyah-Patodi-Singer
$\eta$-invariant and the Borel-Weil theory.


  We propose the model of $D-$dimensional massless particle whose Lagrangian is
given by the $N-$th extrinsic curvature of world-line. The system has $N+1$
gauge degrees of freedom constituting $W-$like algebra; the classical
trajectories of the model are space-like curves which obey the conditions
$k_{N+a}=k_{N-a}$, $k_{2N}=0$, $a=1,...,N-1$, $N\leq[(D-2)/2]$, while the first
$N$ curvatures $k_i$ remain arbitrary. We show that the model admits consistent
formulation on the anti-De Sitter space. The solutions of the system are the
massless irreducible representations of Poincar\'e group with $N$ nonzero
helicities, which are equal to each other.


  La-doped ASnO3 (A = Ba, Sr) have great potential as advanced transparent
oxide semiconductors due to their large optical bandgap and relatively high
electron mobility. The bandgap of Ba1-xSrxSnO3 solid solution increases from
3.2 eV (BaSnO3) to 4.6 eV (SrSnO3) with x. However, the increase in the bandgap
is accompanied by reductions in the electrical conductivity. The versatility in
the changes in the electrical properties are not trivial, and the property
optimization has been challenging. Here we propose a simple metric for
quantifying the transport properties of ASnO3. We investigated the
electron/thermal transport properties of Ba1-xSrxSnO3 solid solution films and
their relationship with the lattice distortion. The results suggest that the
all transport properties of Ba1-xSrxSnO3 are dominated by the lattice
distortion. This phenomenon is attributed to the distortions in the SnO6
octahedron, which consists the conduction band.


  We provide a joint numerical-analytical study of the physics of a flowing
atomic Bose-Einstein condensate in the combined presence of an external trap
and a step potential which accelerates the atoms out of the condensate creating
a pair of neighbouring black- and white- hole horizons. In particular, we focus
on the rapidly growing density modulation pattern that appears in the
supersonic region, an experimentally observed feature that was related to
black-hole lasing phenomena. A direct assessment of the role of interactions in
this process suggests an interpretation of the experimental data in terms of
linear interference of atomic waves rather than collective effects. Our
conclusions are further supported by an analytical solution of the Schrodinger
equation in terms of Airy wavefunctions.


  In this dissertation, we study the well-posedness of the three-dimensional
Lagrangian averaged Navier-Stokes (LANS-$\alpha$) equations. There are two
types of LANS-$\alpha$ equations: the anisotropic version in which the
fluctuation tensor is a dynamic variable that is coupled with the evolution
equations for the mean velocity, and the isotropic version in which the
covariance tensor is assumed to be a constant multiple of the identity matrix.
We prove the global-in-time existence and uniqueness of weak solutions to the
isotropic LANS-$\alpha$ equations for the case of no-slip boundary conditions.
When the anisotropic LANS-$\alpha$ equations are written with the Stokes
projector viscosity term, we show the local-in-time well-posedness of the
anisotropic equations in the periodic box. We numerically compute strong
solutions to the anisotropic equations in the laminar channel and pipe by
considering steady fluid flow solutions to the Navier-Stokes equations.


  We study the 2D Navier-Stokes equations linearized around the Couette flow
$(y,0)^t$ in the periodic channel $\mathbb T \times [-1,1]$ with no-slip
boundary conditions in the vanishing viscosity $\nu \to 0$ limit. We split the
vorticity evolution into the free evolution (without a boundary) and a boundary
corrector that is exponentially localized to at most an $O(\nu^{1/3})$ boundary
layer. If the initial vorticity perturbation is supported away from the
boundary, we show inviscid damping of both the velocity and the vorticity
associated to the boundary layer. For example, our $L^2_t L^1_y$ estimate of
the boundary layer vorticity is independent of $\nu$, provided the initial data
is $H^1$. For $L^2$ data, the loss is only logarithmic in $\nu$. Note both such
estimates are false for the vorticity in the interior. To the authors'
knowledge, this inviscid decay of the boundary layer vorticity seems to be a
new observation not previously isolated in the literature. Both velocity and
vorticity satisfy the expected $O(\exp(-\delta\nu^{1/3}\alpha^{2/3}t))$
enhanced dissipation in addition to the inviscid damping. Similar, but slightly
weaker, results are obtained also for $H^1$ data that is against the boundary
initially. For $L^2$ data against the boundary, we at least obtain the boundary
layer localization and enhanced dissipation.


  Production of even-parity charmed mesons in hadronic B decays is studied.
Specifically, we focus on the Cabibbo-allowed decays $\bar B\to D^{**}\pi$ and
$\bar D^{**}_sD^{(*)}$, where $D^{**}$ denotes generically a p-wave charmed
meson. While the measured color-allowed decays $\bar B^0\to D^{**+}\pi^-$ are
consistent with the theoretical expectation, the experimental observation of
$B^-\to D^{**0}\pi^-$ for the broad $D^{**}$ states is astonishing as it
requires that the color-suppressed contribution dominates over the
color-allowed one, even though the former is $1/m_b$ suppressed in the heavy
quark limit. In order to accommodate the data of $\bar B\to D^{**}\pi^-$, it is
found that $a_2/a_1\approx -0.5$ with a sign opposite to that in $\bar B\to
D\pi$ decays, where $a_1$ and $a_2$ are the effective Wilson coefficients for
color-allowed and color-suppressed decay amplitudes, respectively. The decay
constants and form factors for $D^{**}$ and the Isgur-Wise functions
$\tau_{1/2}(\omega)$ and $\tau_{3/2}(\omega)$ are extracted from the data of
$B\to D^{**}\pi$ decays. The Isgur-Wise functions calculated in the covariant
light-front quark model are in good agreement with experiment. The neutral
modes $\bar B^0\to D^{**0}\pi^0$ for $D^{**}=D^*_0(2400),D'_1(2430)$ and $\bar
B^0\to D'^0_1(2430)\omega$ are predicted to have branching ratios of order
$10^{-4}$ which are also supported by isospin argument. The decay constants of
$D_{s0}^*(2317)$ and $D'_{s1}(2460)$ are inferred from the measurements of
$\bar B\to D_s^{**-}D$ to be $58\sim 86$ MeV and $130\sim 200$ MeV,
respectively. Contrary to the decay constants $f_{D_0^*}$ and $f_{D'_1}$ which
are similar in size, the large disparity between $f_{D_{s0}^*}$ and
$f_{D'_{s1}}$ is surprising and unexpected.


  Recent studies of elasto-capillary phenomena have triggered interest in a
basic variant of the classical Young-Laplace-Dupr\'e (YLD) problem: The
capillary interaction between a liquid drop and a thin solid sheet of low
bending stiffness. Here, we consider a two-dimensional model where the sheet is
subjected to an external tensile load and the drop is characterized by a
well-defined Young's contact angle $\theta_Y$. Using a combination of
numerical, variational, and asymptotic techniques, we discuss wetting as a
function of the applied tension. We find that, for wettable surfaces with
$0<\theta_Y<\pi/2$, complete wetting is possible below a critical applied
tension thanks to the deformation of the sheet in contrast with rigid
substrates requiring $\theta_Y=0$. Conversely, for very large applied tensions,
the sheet becomes flat and the classical YLD situation of partial wetting is
recovered. At intermediate tensions, a vesicle forms in the sheet, which
encloses most of the fluid and we provide an accurate asymptotic description of
this wetting state in the limit of small bending stiffness. We show that
bending stiffness, however small, affects the entire shape of the vesicle. Rich
bifurcation diagrams involving partial wetting and ``vesicle'' solution are
found. For moderately small bending stiffnesses, partial wetting can coexist
both with the vesicle solution and complete wetting. Finally, we identify a
tension-dependent bendo-capillary length, $\lambda_\text{BC}$, and find that
the shape of the drop is determined by the ratio $A/\lambda_\text{BC}^2$, where
$A$ is the area of the drop.


  The Laser Interferometer Space Antenna (LISA) will detect gravitational-wave
(GW) signals from merging supermassive black holes (BHs) with masses below
$10^7$~M$_{\odot}$. It is thus of paramount importance to understand the
orbital dynamics of these relatively light central BHs, which typically reside
in disc-dominated galaxies, in order to produce reliable forecasts of merger
rates. To this aim, realistic simulations probing BH dynamics in unequal-mass
disc galaxy mergers, into and beyond the binary hardening stage, are performed
by combining smooth particle hydrodynamics and direct $N$-body codes. The
structural properties and orbits of the galaxies are chosen to be consistent
with the results of galaxy formation simulations. Stellar and dark matter
distributions are triaxial down to the central 100 pc of merger remnant. In all
cases, a BH binary forms and hardens on time-scales of at most 100~Myr,
coalescing on another few hundred Myr time-scale, depending on the
characteristic density and orbital eccentricity. Overall, the sinking of the BH
binary takes no more than $\sim$0.5~Gyr after the merger of the two galaxies is
completed, but can be much faster for very plunging orbits. Comparing with
previous numerical simulations following the decay of BHs in massive early-type
galaxies at $z \sim 3$, we confirm that the characteristic density is the most
crucial parameter determining the overall BH merging time-scale, despite the
structural diversity of the host galaxies. Our results lay down the basis for
robust forecasts of LISA event rates in the case of merging BHs.


  The amount of emitted prompt neutrons from the fission fragments increases as
a function of excitation energy. Yet it is not fully understood whether the
increase in \nu(A) as a function of E_{n} is mass dependent. The share of
excitation energies among the fragments is still under debate, but there are
reasons to believe that the excess in neutron emission originates only from the
heavy fragments, leaving \nu_{light}(A) almost unchanged. In this work we
investigated the consequences of a mass-dependent increase in \nu(A) on the
final mass and energy distributions. The assumptions on \nu(A) are essential
when analysing measurements based on the 2E-technique. This choice showed to be
significant on the measured observables. For example, the post-neutron emission
mass yield distribution revealed changes up to 10-30%. The outcome of this work
pinpoint the urgent need to determine \nu(A) experimentally, and in particular,
how \nu(A) changes as a function of incident-neutron energy. Until then, many
fission yields in the data libraries could be largely affected, since they were
analysed based on another assumption on the neutron emission.


  We consider Monge-Amp\'ere equations with the right hand side function close
to a constant and from a function class that is larger than any H\"older class
and smaller than the Dini-continuous class. We establish an upper bound for the
modulus of continuity of the solution's second derivatives. This bound depends
exponentially on a quantity similar to but larger than the Dini semi-norm. We
establish explicit control on the shape of the sequence of shrinking sections,
hence revealing the nature of such exponential dependence.


  We compute the effective black hole potential V of the most general N=2, d=4
(local) special Kaehler geometry with quantum perturbative corrections,
consistent with axion-shift Peccei-Quinn symmetry and with cubic leading order
behavior. We determine the charge configurations supporting axion-free
attractors, and explain the differences among various configurations in
relations to the presence of ``flat'' directions of V at its critical points.
Furthermore, we elucidate the role of the sectional curvature at the
non-supersymmetric critical points of V, and compute the Riemann tensor (and
related quantities), as well as the so-called E-tensor. The latter expresses
the non-symmetricity of the considered quantum perturbative special Kaehler
geometry.


  A number of geometric problems, including affine hyperbolic spheres, Hilbert
metrics and Minkowski type problems, are reduced to a singular Monge-Amp\`ere
equation which can be written locally as a class of Monge-Amp\`ere equations
with singularity at boundary. We estimate the boundary derivatives of all
orders for the solutions to the class of singular equations as possible as
optimal and prove that the solution to the equation is globally analytic if the
dimension of the space is even. As a corollary, we obtain the global
analyticity of affine hyperbolic spheres in the even dimensional space.


  In [arXiv:1902.04063] we generalize the original definition of weighted
surface algebras in [arXiv:1703.02346] by allowing the possibility that arrows
might not be part of the Gabriel quiver, which gives a much larger class of
algebras. This means that the zero relations need modification, to make sure
that the algebras are symmetric, and of the appropriate dimension. We found
recently that we had missed one necessary modification for the zero relations.
Here we give the correct definition, and revise the parts of [arXiv:1902.04063]
which are affected by this modification.


  The effect of Ni-doping on the magnetism and superconductivity in
Eu0.5K0.5Fe2As2 has been studied through a systematic investigation of magnetic
and superconducting properties of Eu0.5K0.5(Fe1-xNix)2As2 (x = 0, 0.03, 0.05,
0.08 and 0.12) compounds by means of dc and ac magnetic susceptibilities,
electrical resistivity and specific heat measurements. Eu0.5K0.5Fe2As2 is known
to exhibit superconductivity with superconducting transition temperature Tc as
high as 33 K. The Ni-doping leads to a rapid decrease in Tc; Tc is reduced to
23 K with 3% Ni-doping, and 8% Ni-doping suppresses the superconductivity to
below 1.8 K. In 3% Ni-doped sample Eu0.5K0.5(Fe0.97Ni0.03)2As2
superconductivity coexists with short range ordering of Eu2+ magnetic moments
at Tm ~ 6 K. The suppression of superconductivity with Ni-doping is accompanied
with the emergence of a long range antiferromagnetic ordering with TN = 8.5 K
and 7 K for Eu0.5K0.5(Fe0.92Ni0.08)2As2 and Eu0.5K0.5(Fe0.88Ni0.12)2As2,
respectively. The temperature and field dependent magnetic measurements for x =
0.08 and 0.12 samples reflect the possibility of a helical magnetic ordering of
Eu2 moments. We suspect that the helimagnetism of Eu spins could be responsible
for the destruction of superconductivity as has been observed in Co-doped
EuFe2As2. The most striking feature seen in the resistivity data for x = 0.08
is the reappearance of the anomaly presumably due to spin density wave
transition at around 60 K. This could be attributed to the compensation of
holes (K-doping at Eu-site) by the electrons (Ni-doping at Fe site). The
anomaly associated with spin density wave further shifts to 200 K for x = 0.12
for which the electron doping has almost compensated the holes in the system.


  Mergers of binary neutron stars and black hole-neutron star binaries are one
of the most promising sources for the ground-based gravitational-wave (GW)
detectors and also a high-energy astrophysical phenomenon as illustrated by the
observations of gravitational waves and electromagnetic (EM) waves in the event
of GW170817. Mergers of these neutron-star binaries are also the most promising
site for r-process nucleosynthesis. Numerical simulation in full general
relativity (numerical relativity) is a unique approach to the theoretical
prediction of the merger process, GWs emitted, mass ejection process, and
resulting EM emission. We summarize our current understanding for the processes
of neutron star mergers and subsequent mass ejection based on the results of
the latest numerical-relativity simulations. We emphasize that the predictions
of the numerical-relativity simulations agrees broadly with the optical and
infrared observations of GW170817.


  This paper proposes a novel image contrast enhancement method based on both a
noise aware shadow-up function and Retinex (retina and cortex) decomposition.
Under low light conditions, images taken by digital cameras have low contrast
in dark or bright regions. This is due to a limited dynamic range that imaging
sensors have. For this reason, various contrast enhancement methods have been
proposed. Our proposed method can enhance the contrast of images without not
only over-enhancement but also noise amplification. In the proposed method, an
image is decomposed into illumination layer and reflectance layer based on the
retinex theory, and lightness information of the illumination layer is
adjusted. A shadow-up function is used for preventing over-enhancement. The
proposed mapping function, designed by using a noise aware histogram, allows
not only to enhance contrast of dark region, but also to avoid amplifying
noise, even under strong noise environments.


  A Hecke action on the space of periods of cusp forms, which is compatible
with that on the space of cusp forms, was first computed using continued
fraction and an explicit algebraic formula of Hecke operators acting on the
space of period functions of modular forms was derived by studying the rational
period functions. As an application an elementary proof of the Eichler-Selberg
trace formula was derived. Similar modification has been applied to period
space of Maass cusp forms with spectral parameter $s$. In this paper we study
the space of period functions of Jacobi forms by means of Jacobi integral and
give an explicit description of Hecke operator acting on this space. a Jacobi
Eisenstein series $E_{2,1}({\tau},z)$ of weight 2 and index 1 is discussed as
an example. Periods of Jacobi integrals are already appeared as a disguised
form in the work of Zwegers to study Mordell integral coming from Lerch sums
and mock Jacobi forms are typical example of Jacobi integral.


  For any prime $p$, $\lambda$-constacyclic codes of length $p^s$ over ${\cal
R}=\mathbb{F}_{p^m} + u\mathbb{F}_{p^m}$ are precisely the ideals of the local
ring ${\cal R}_{\lambda}=\frac{{\cal R}[x]}{\left\langle x^{p^s}-\lambda
\right\rangle}$, where $u^2=0$. In this paper, we first investigate the Hamming
distances of cyclic codes of length $p^s$ over ${\cal R}$. The minimum Hamming
distances of all cyclic codes of length $p^s$ over ${\cal R}$ are determined.
Moreover, an isometry between cyclic and $\alpha$-constacyclic codes of length
$p^s$ over ${\cal R}$ is established, where $\alpha$ is a nonzero element of
$\mathbb{F}_{p^m}$, which carries over the results regarding cyclic codes
corresponding to $\alpha$-constacyclic codes of length $p^s$ over ${\cal R}$.


  A quantizable worldsheet action is constructed for the superstring in a
supersymmetric plane wave background with Ramond-Ramond flux. The action is
manifestly invariant under all isometries of the background and is an exact
worldsheet conformal field theory.


  Using Godement mean on the Fourier-Stieltjes algebra of a locally compact
quantum group we obtain strong separation results for quantum positive-definite
functions associated to a subclass of representations, strengthening for
example the known relationship between amenability of a discrete quantum group
and existence of a net of finitely supported quantum positive-definite
functions converging pointwise to $I$. We apply these results to show that von
Neumann algebras of unimodular discrete quantum groups enjoy a strong form of
non-$w^*$-CPAP, which we call the matrix $\epsilon$-separation property.


  We investigated the crystal-electric field ground state of the 4$f$ manifold
in the strongly correlated topological insulator SmB$_6$ using core level
non-resonant inelastic x-ray scattering (NIXS). The directional dependence of
the scattering function that arises from higher multipole transitions
establishes unambiguously that the $\Gamma_8$ quartet state of the Sm $f^5$
$J$=$5/2$ configuration governs the ground-state symmetry and hence the
topological properties of SmB$_6$. Our findings contradict the results of
density functional calculations reported so far.


  During the last few years, intensive research efforts are being done in the
field of brain interfaces to extract neuro-information from the signals
representing neuronal activities in the human brain. Recent development of
brain-to-computer interfaces support direct communication between animals'
brains, enabling direct brain-to-brain communication. Although these results
are based on binary communication with relaxed requirements of latency and
throughput, the fast development in neuro-science technologies indicates
potential new scenarios for wireless communications between brains. In this
paper we highlight technologies that are being used today to enable
brain-to-brain communication and propose potential wireless communication
architectures and requirements for future scenarios.


  We discuss the problem of hidden variables and the motivation for
introducting them in quantum mechanics. These include determinism, and the
problem of meassurement and incompleteness. We first discuss Von-Neumann's
imposisbility proof and then analyse it's weakness in terms of Bell's explicit
hidden variable model of spin one-half particles. We next discuss Gleason's
theorem and Kochen-Specker theorem and bring out the troublems with non
contextual hidden variable theories. An important role is played by Einstein
locality in the discussion of hidden variable theories as was first brought out
by Einstein, Podolsky and Rosen. We elaborate it's various implications such as
Bell's theorem in terms of Bell's inequalities as well as later work in which
Bell's theorem follows without using inequalities.


  Let A_E be the canonical AF subalgebra of a graph C*-algebra C*(E) associated
with a locally finite directed graph E. For Brown-Voiculescu's topological
entropy ht(\Phi_E) of the canonical completely positive map \Phi_E on C*(E),
ht(\Phi_E)=ht(\Phi_E|_{A_E})=h_l(E)=h_b(E) is known to hold for a finite graph
E, where h_l(E) is the loop entropy of Gurevic and h_b(E) is the block entropy
of Salama. For an irreducible infinite graph E, the inequality h_l(E)\leq
ht(\Phi_E|_{A_E}) has been known recently. It is shown in this paper that
ht(\Phi_E|_{A_E})\leq max{h_b(E), h_b(tE)}, where tE is the graph E with the
direction of the edges reversed. Some irreducible infinite graphs E_p(p>1) with
ht(\Phi_E|_{A_{E_p}})=log p are also examined.


  We prove a uniqueness result for limit cycles of the second order ODE $\ddot
x + \dot x \phi(x,\dot x) + g(x) = 0$. Under mild additional conditions, we
show that such a limit cycle attracts every non-constant solution. As a special
case, we prove limit cycle's uniqueness for an ODE studied in \cite{ETA} as a
model of pedestrians' walk. This paper is an extension to equations with a
non-linear $g(x)$ of the results presented in \cite{S}.


  With this technical report, we provide mathematical and implementational
details of cross-validated Bayesian model selection (cvBMS) and averaging
(cvBMA) that could not be communicated in the corresponding peer-reviewed
journal articles. This will allow statisticians and developers to comprehend
internal functionalities of cvBMS and cvBMA for further development of these
techniques.


  With the rapid development of the multimedia,the secure of the multimedia is
get more concerned. as far as we know , Digital watermarking is an effective
way to protect copyright. The watermark must be generally hidden does not
affect the quality of the original image. In this paper,a novel way based on
discrete cosine transform(DCT) and singular value decomposition(SVD) .In the
proposed way,we decomposition the image into 8*8 blocks, next we use the DCT to
get the transformed block,then we choose the diagonal to embed the information,
after we do this, we recover the image and then we decomposition the image to
8*8 blocks,we use the SVD way to get the diagonal matrix and embed the
information in the matrix. next we extract the information use both inverse of
DCT and SVD, as we all know,after we embed the information seconded time , the
information we first information we embed must be changed, we choose a measure
way called Peak Signal to Noise Ratio(PSNR) to estimate the similarity of the
two image, and set a threshold to ensure whether the information is same or
not.


  Perturbation-based explanation methods such as LIME and SHAP are commonly
applied to text classification. This work focuses on their extension to
generative language models. To address the challenges of text as output and
long text inputs, we propose a general framework called MExGen that can be
instantiated with different attribution algorithms. To handle text output, we
introduce the notion of scalarizers for mapping text to real numbers and
investigate multiple possibilities. To handle long inputs, we take a
multi-level approach, proceeding from coarser levels of granularity to finer
ones, and focus on algorithms with linear scaling in model queries. We conduct
a systematic evaluation, both automated and human, of perturbation-based
attribution methods for summarization and context-grounded question answering.
The results show that our framework can provide more locally faithful
explanations of generated outputs.


  Hierarchical clustering is a common algorithm in data analysis. It is unique
among many clustering algorithms in that it draws dendrograms based on the
distance of data under a certain metric, and group them. It is widely used in
all areas of astronomical research, covering various scales from asteroids and
molecular clouds, to galaxies and galaxy cluster. This paper systematically
reviews the history and current status of the development of hierarchical
clustering methods in various branches of astronomy. These applications can be
grouped into two broad categories, one revealing the intrinsic hierarchical
structure of celestial systems and the other classifying large samples of
celestial objects automatically. By reviewing these applications, we can
clarify the conditions and limitations of the hierarchical clustering
algorithm, and make more reasonable and reliable astronomical discoveries.


  We show that almost every entry in the character table of $S_N$ is divisible
by any fixed prime as $N\to\infty$. This proves a conjecture of Miller.


  We present the Spitzer/IRS mid-infrared spectrum of the infrared-luminous
(L_{IR}=4e11 L_sun) brightest cluster galaxy (BCG) in the X-ray-luminous
cluster Z3146 (z=0.29). The spectrum shows strong aromatic emission features,
indicating that the dominant source of the infrared luminosity is star
formation. The most striking feature of the spectrum, however, is the
exceptionally strong molecular hydrogen (H2) emission lines, which seem to be
shock-excited. The line luminosities and inferred warm H2 gas mass (~1e10
M_sun) are 6 times larger than those of NGC 6240, the most H2-luminous galaxy
at z <~ 0.1. Together with the large amount of cold H2 detected previously
(~1e11 M_sun), this indicates that the Z3146 BCG contains disproportionately
large amounts of both warm and cold H2 gas for its infrared luminosity, which
may be related to the intracluster gas cooling process in the cluster core.


  The new round of experiments, MEG II, COMET/Mu2e, and Mu3e, would soon start
to push the $\mu \to e\gamma$, $\mu N \to eN$ conversion, and $\mu \to 3e$
frontier, while Belle II would probe $\tau \to \mu\gamma$ and $\tau \to 3\mu$.
In the general two Higgs doublet model with extra Yukawa couplings, we show
that all these processes probe the lepton flavor violating (LFV) dipole
transition that arises from the two loop mechanism, with scalar-induced contact
terms subdominant. This is because existing data suggest the extra Yukawa
couplings $\rho_{\mu e},\, \rho_{ee} \lesssim \lambda_e$, while
$\rho_{\tau\mu},\, \rho_{\tau\tau} \lesssim \lambda_\tau$ and $\rho_{tt}
\lesssim \lambda_t$, with $\lambda_i$ the usual Yukawa coupling of the Standard
Model (SM), where $\rho_{\mu e}\rho_{tt}$ and $\rho_{\tau\mu}\rho_{tt}$ enter
the $\mu e\gamma$ and $\tau\mu\gamma$ two loop amplitudes, respectively. With
the $B_s \to \mu\mu$ decay rate basically consistent with SM expectation,
together with the $B_s$ mixing constraint, we show that $B_s \to \tau\tau$
would also be consistent with SM, while $B_s \to \tau\mu$ and $B \to K\tau\mu$
decays would be out of reach of projected sensitivities, in strong contrast
with some models motivated by the B anomalies.


  The amplitude for ordinary muon capture on the proton is evaluated, through
the first four orders in the expansion parameter, in a manifestly Lorentz
invariant form of baryon chiral perturbation theory. Expressions for the low
energy constants in terms of physical quantities are obtained in each of the
several renormalization schemes which have been proposed for forcing the
relativistic approach to obey the same counting rules as obtained in heavy
baryon chiral perturbation theory. The advantages and disadvantages of these
schemes are discussed, using the muon capture results as an example, with the
aim of gaining insight as to which scheme is preferable for practical
calculations.


  Summarizing basic facts from abstract topological modules over Colombeau
generalized complex numbers we discuss duality of Colombeau algebras. In
particular, we focus on generalized delta functionals and operator kernels as
elements of dual spaces. A large class of examples is provided by
pseudodifferential operators acting on Colombeau algebras. By a refinement of
symbol calculus we review a new characterization of the wave front set for
generalized functions with applications to microlocal analysis.


  Pearson's chi-squared test, from 1900, is the standard statistical tool for
"hypothesis testing on distributions": namely, given samples from an unknown
distribution $Q$ that may or may not equal a hypothesis distribution $P$, we
want to return "yes" if $P=Q$ and "no" if $P$ is far from $Q$. While the
chi-squared test is easy to use, it has been known for a while that it is not
"data efficient", it does not make the best use of its data. Precisely, for
accuracy $\epsilon$ and confidence $\delta$, and given $n$ samples from the
unknown distribution $Q$, a tester should return "yes" with probability
$>1-\delta$ when $P=Q$, and "no" with probability $>1-\delta$ when
$|P-Q|>\epsilon$. The challenge is to find a tester with the \emph{best}
tradeoff between $\epsilon$, $\delta$, and $n$. We introduce a new tester,
efficiently computable and easy to use, which we hope will replace the
chi-squared tester in practical use. Our tester is found via a new non-convex
optimization framework that essentially seeks to "find the tester whose
Chernoff bounds on its performance are as good as possible". This tester is
$1+o(1)$ optimal, in that the number of samples $n$ needed by the tester is
within $1+o(1)$ factor of the samples needed by \emph{any} tester, even
non-linear testers (for the setting: accuracy $\epsilon$, confidence $\delta$,
and hypothesis $P$). We complement this algorithmic framework with matching
lower bounds saying, essentially, that "our tester is instance-optimal, even to
$1+o(1)$ factors, to the degree that Chernoff bounds are tight". Our overall
non-convex optimization framework extends well beyond the current problem and
is of independent interest.


  We present a pedagogical review of the fundamental concepts in thermodynamics
of information, by focusing on the second law of thermodynamics and the entropy
production. Especially, we discuss the relationship among thermodynamic
reversibility, logical reversibility, and heat emission in the context of the
Landauer principle and clarify that these three concepts are fundamentally
distinct to each other. We also discuss thermodynamics of measurement and
feedback control by Maxwell's demon. We clarify that the demon and the second
law are indeed consistent in the measurement and the feedback processes
individually, by including the mutual information to the entropy production.


  In this work, we study the inverse problem of recovering a potential
coefficient in the subdiffusion model, which involves a Djrbashian-Caputo
derivative of order $\alpha\in(0,1)$ in time, from the terminal data. We prove
that the inverse problem is locally Lipschitz for small terminal time, under
certain conditions on the initial data. This result extends the result in
Choulli and Yamamoto (1997) for the standard parabolic case to the fractional
case. The analysis relies on refined properties of two-parameter Mittag-Leffler
functions, e.g., complete monotonicity and asymptotics. Further, we develop an
efficient and easy-to-implement algorithm for numerically recovering the
coefficient based on (preconditioned) fixed point iteration and Anderson
acceleration. The efficiency and accuracy of the algorithm is illustrated with
several numerical examples.


  We present a simple and effective image super-resolution algorithm that
imposes an image formation constraint on the deep neural networks via pixel
substitution. The proposed algorithm first uses a deep neural network to
estimate intermediate high-resolution images, blurs the intermediate images
using known blur kernels, and then substitutes values of the pixels at the
un-decimated positions with those of the corresponding pixels from the
low-resolution images. The output of the pixel substitution process strictly
satisfies the image formation model and is further refined by the same deep
neural network in a cascaded manner. The proposed framework is trained in an
end-to-end fashion and can work with existing feed-forward deep neural networks
for super-resolution and converges fast in practice. Extensive experimental
results show that the proposed algorithm performs favorably against
state-of-the-art methods.


  In this paper, we present an analytical framework to explore the interplay of
signal interference and transmission queue management, and their impacts on the
performance of unmanned aerial vehicles (UAVs) when operating in the unlicensed
spectrum bands. In particular, we develop a comprehensive framework to
investigate the impact of other interference links on the UAV as it
communicates with the ground users. To this end, we provide closed-form
expressions for packet drop probabilities in the queue due to buffer overflow
or large queuing delay, which are expressed in terms of a transmission policy
as a function of the channel fading threshold $\beta$. The overall packet loss
caused either by interference signals or queuing packet drop is obtained,
which, in turn, yields in obtaining the expected throughput performance.
Through extensive numerical results, we investigate the impact of the channel
fading threshold $\beta$, which plays an important role in balancing the
trade-offs between packet loss due to queue drop or transmission error due to
large interference levels.


  We consider the problem of a particular kind of quantum correlation that
arises in some two-party games. In these games, one player is presented with a
question they must answer, yielding an outcome of either 'win' or 'lose'.
Molina and Watrous (arXiv:1104.1140) studied such a game that exhibited a
perfect form of hedging, where the risk of losing a first game can completely
offset the corresponding risk for a second game. This is a non-classical
quantum phenomenon, and establishes the impossibility of performing strong
error-reduction for quantum interactive proof systems by parallel repetition,
unlike for classical interactive proof systems. We take a step in this article
towards a better understanding of the hedging phenomenon by giving a complete
characterization of when perfect hedging is possible for a natural
generalization of the game in arXiv:1104.1140. Exploring in a different
direction the subject of quantum hedging, and motivated by implementation
concerns regarding loss-tolerance, we also consider a variation of the protocol
where the player who receives the question can choose to restart the game
rather than return an answer. We show that in this setting there is no possible
hedging for any game played with state spaces corresponding to
finite-dimensional complex Euclidean spaces.


  A {\it $k$-involution} is an involution with a fixed point set of codimension
$k$. The conjugacy class of such an involution, denoted $S_k$, generates
$\text{M\"ob}(n)$-the the group of isometries of hyperbolic $n$-space-if $k$ is
odd, and its orientation preserving subgroup if $k$ is even. In this paper, we
supply effective lower and upper bounds for the $S_k$ word length of
$\text{M\"ob}(n)$ if $k$ is odd, and the $S_k$ word length of
$\text{M\"ob}^+(n)$, if $k$ is even. As a consequence, for a fixed codimension
$k$ the length of $\text{M\"ob}^{+}(n)$ with respect to $S_k$, $k$ even, grows
linearly with $n$ with the same statement holding in the odd case. Moreover,
the percentage of involution conjugacy classes for which $\text{M\"ob}^{+}(n)$
has length two approaches zero, as $n$ approaches infinity.


  The surging global mobile data traffic challenges the economic viability of
cellular networks and calls for innovative solutions to reduce the network
congestion and improve user experience. In this context, user-provided networks
(UPNs), where mobile users share their Internet access by exploiting their
diverse network resources and needs, turn out to be very promising.
Heterogeneous users with advanced handheld devices can form connections in a
distributed fashion and unleash dormant network resources at the network edge.
However, the success of such services heavily depends on users' willingness to
contribute their resources, such as network access and device battery energy.
In this paper, we introduce a general framework for UPN services and design a
bargaining-based distributed incentive mechanism to ensure users participation.
The proposed mechanism determines the resources that each user should
contribute in order to maximise the aggregate data rate in UPN, and fairly
allocate the benefit among the users. The numerical results verify that the
service can always improve performance, and such improvement increases with the
diversity of the users' resources. Quantitatively, it can reach an average 30%
increase of the total served traffic for a typical scenario even with only 6
mobile users.


  This paper examines two methods for finding whether long-range correlations
exist in DNA: a fractal measure and a mutual information technique. We evaluate
the performance and implications of these methods in detail. In particular we
explore their use comparing DNA sequences from a variety of sources. Using
software for performing in silico mutations, we also consider evolutionary
events leading to long range correlations and analyse these correlations using
the techniques presented. Comparisons are made between these virtual sequences,
randomly generated sequences, and real sequences. We also explore correlations
in chromosomes from different species.


  The specializations of the motivic elliptic polylog are called motivic
Eisenstein classes. For applications to special values of L-Functions, it is
important to compute the realizations of these classes. In this paper, we prove
that the syntomic realization of the motivic Eisenstein classes, restricted to
the ordinary locus of the modular curve, may be expressed using p-adic
Eisenstein-Kronecker series. These p-adic modular forms are defined using the
two-variable p-adic measure with values in p-adic modular forms constructed by
Katz.


  Existing deepfake speech detection systems lack generalizability to unseen
attacks (i.e., samples generated by generative algorithms not seen during
training). Recent studies have explored the use of universal speech
representations to tackle this issue and have obtained inspiring results. These
works, however, have focused on innovating downstream classifiers while leaving
the representation itself untouched. In this study, we argue that
characterizing the long-term temporal dynamics of these representations is
crucial for generalizability and propose a new method to assess representation
dynamics. Indeed, we show that different generative models generate similar
representation dynamics patterns with our proposed method. Experiments on the
ASVspoof 2019 and 2021 datasets validate the benefits of the proposed method to
detect deepfakes from methods unseen during training, significantly improving
on several benchmark methods.


  Researchers in the biological sciences nowadays often encounter the curse of
high-dimensionality, which many previously developed statistical models fail to
overcome. To tackle this problem, sufficient dimension reduction aims to
estimate the central subspace (CS), in which all the necessary information
supplied by the covariates regarding the response of interest is contained.
Subsequent statistical analysis can then be made in a lower-dimensional space
while preserving relevant information. Oftentimes studies are interested in a
certain transformation of the response (the induced response), instead of the
original one, whose corresponding CS may vary. When estimating the CS of the
induced response, existing dimension reduction methods may, however, suffer the
problem of inefficiency. In this article, we propose a more efficient two-stage
estimation procedure to estimate the CS of an induced response. This approach
is further extended to the case of censored responses. An application for
combining multiple biomarkers is also illustrated. Simulation studies and two
data examples provide further evidence of the usefulness of the proposed
method.


  Magnetic resonance imaging (MRI) acquisition, reconstruction, and
segmentation are usually processed independently in the conventional practice
of MRI workflow. It is easy to notice that there are significant relevances
among these tasks and this procedure artificially cuts off these potential
connections, which may lead to losing clinically important information for the
final diagnosis. To involve these potential relations for further performance
improvement, a sequential multi-task joint learning network model is proposed
to train a combined end-to-end pipeline in a differentiable way, aiming at
exploring the mutual influence among those tasks simultaneously. Our design
consists of three cascaded modules: 1) deep sampling pattern learning module
optimizes the $k$-space sampling pattern with predetermined sampling rate; 2)
deep reconstruction module is dedicated to reconstructing MR images from the
undersampled data using the learned sampling pattern; 3) deep segmentation
module encodes MR images reconstructed from the previous module to segment the
interested tissues. The proposed model retrieves the latently interactive and
cyclic relations among those tasks, from which each task will be mutually
beneficial. The proposed framework is verified on MRB dataset, which achieves
superior performance on other SOTA methods in terms of both reconstruction and
segmentation.


  Like medicine, psychology, or education, data science is fundamentally an
applied discipline, with most students who receive advanced degrees in the
field going on to work on practical problems. Unlike these disciplines,
however, data science education remains heavily focused on theory and methods,
and practical coursework typically revolves around cleaned or simplified data
sets that have little analog in professional applications. We believe that the
environment in which new data scientists are trained should more accurately
reflect that in which they will eventually practice and propose here a data
science master's degree program that takes inspiration from the residency model
used in medicine. Students in the suggested program would spend three years
working on a practical problem with an industry, government, or nonprofit
partner, supplemented with coursework in data science methods and theory. We
also discuss how this program can also be implemented in shorter formats to
augment existing professional masters programs in different disciplines. This
approach to learning by doing is designed to fill gaps in our current approach
to data science education and ensure that students develop the skills they need
to practice data science in a professional context and under the many
constraints imposed by that context.


  We prove that for a non-amenable, locally finite, connected, transitive,
planar graph with one end, any automorphism invariant site percolation on the
graph does not have exactly 1 infinite 1-cluster and exactly 1 infinite
0-cluster a.s. If we further assume that the site percolation is
insertion-tolerant and a.s.~there exists a unique infinite 0-cluster, then
a.s.~there are no infinite 1-clusters. The proof is based on the analysis of a
class of delicately constructed interfaces between clusters and contours.
Applied to the case of i.i.d.~Bernoulli site percolation on infinite,
connected, locally finite, transitive, planar graphs, these results solve two
conjectures of Benjamini and Schramm (Conjectures 7 and 8 in \cite{bs96}) in
1996.


  In order to alleviate the inefficiencies caused by the interaction of the
logic and functional sides, integrated languages may take advantage of
\emph{demand} information -- i.e. knowing in advance which computations are
needed and, to which extent, in a particular context. This work studies
\emph{demand analysis} -- which is closely related to \emph{backwards
strictness analysis} -- in a semantic framework of \emph{partial predicates},
which in turn are constructive realizations of ideals in a domain. This will
allow us to give a concise, unified presentation of demand analysis, to relate
it to other analyses based on abstract interpretation or strictness logics,
some hints for the implementation, and, more important, to prove the soundness
of our analysis based on \emph{demand equations}. There are also some
innovative results. One of them is that a set constraint-based analysis has
been derived in a stepwise manner using ideas taken from the area of program
transformation. The other one is the possibility of using program
transformation itself to perform the analysis, specially in those domains of
properties where algorithms based on constraint solving are too weak.


  Bayesian integral functional measure of entropy-uncertainty (EF) on
trajectories of Markov multi-dimensional diffusion process is cutting off by
interactive impulses (controls). Each cutoff minimax of EF superimposes and
entangles conjugated fractions in microprocess, enclosing the captured entropy
fractions as source of an information unit. The impulse step-up action launches
the unit formation and step-down action finishes it and brings energy from the
interactive jump. This finite jump transfers the entangled entropy from
uncertain Yes-logic to the certain-information No-logic information unit whose
measuring at end of the cut kills final entropy-uncertainty and limits unit.
The Yes-No logic holds Bit Participator creating elementary information
observer without physical pre-law. Cooperating two units in doublet and an
opposite directional information unit in triplet forms minimal stable
structure. Information path functional (IPF) integrates multiple hidden
information contributions along the cutting process correlations in information
units of cooperating doublets-triplets, bound by free information, and enfolds
the sequence of enclosing triplet structures in the information network (IN)
that sequentially decreases the entropy and maximizes information. The IN bound
triplets release free information rising information forces enable attracting
new information unit and ordering it. While IPF collects the information units,
the IN performs logical computing using doublet-triplet code. The IN different
levels unite logic of quantum micro- and macro- information processes,
composing quantum and/or classical computation.


  We calculate the advection/diffusion of the large-scale magnetic field
threading an ADAF, and find that the magnetic field can be dragged inward by
the accretion flow efficiently, if the magnetic Prandtl number P~1. This is due
to the large radial velocity of the ADAF. It is found that the magnetic
pressure can be as high as ~50% of the gas pressure in the inner region of the
ADAF close to the black hole horizon, even if the external imposed vertical
field strength is <5% of the gas pressure at the outer radius of the ADAF,
which is caused by the gas plunging rapidly to the black hole within the
marginal stable circular orbit. In the inner region of the ADAF, the flow is
significantly pressured in the vertical direction by the magnetic field, and
therefore its gas pressure can be two orders of magnitude higher than that in
the ADAF without magnetic fields. This means that the magnetic field strength
near the black hole is underestimated by assuming equipartition between
magnetic and gas pressure with the conventional ADAF model. Our results show
that the magnetic field strength of the flow near the black hole horizon can be
more than one order of magnitude higher than that in the ADAF at 6GM/c^2, which
implies the Blandford-Znajek mechanism could be more important than the
Blandford-Payne mechanism for ADAFs. We find that the accretion flow is
decelerated near the black hole by the magnetic field when the external imposed
field is strong enough or the gas pressure of the flow is low at the outer
radius, or both. This corresponds to a critical accretion rate, below which the
accretion flow will be arrested by the magnetic field near the black hole for a
given external imposed field. In this case, the gas may accrete as magnetically
confined blobs diffusing through field lines in the region very close to the
black hole horizon, which is similar to those in compact stars.


  (abridged) We investigate the properties of feedback-driven shocks in 8
nearby starburst galaxies using narrow-band imaging data from the Hubble Space
Telescope (HST). We identify the shock--ionized component via the line
diagnostic diagram \oiii/\hb vs. \sii (or \nii)/\ha, applied to resolved
regions 3--15 pc in size. We divide our sample into three sub-samples:
sub-solar (Holmberg II, NGC 1569, NGC 4214, NGC 4449, and NGC 5253), solar (He
2-10, NGC 3077) and super-solar (NGC 5236) for consistent shock measurements.
For the sub-solar sub-sample, we derive three scaling relations: (1) $L_{shock}
\propto {SFR}^{~0.62}$, (2) $L_{shock} \propto {\Sigma_{SFR,HL}}^{~0.92}$, and
(3) $L_{shock}/L_{tot} \propto {(L_H/L_{\odot,H})}^{-0.65}$, where $L_{shock}$
is the \ha luminosity from shock--ionized gas, ${\Sigma_{SFR,HL}}$ the SFR per
unit half-light area, $L_{tot}$ the total \ha luminosity, and $L_H/L_{\odot,H}$
the absolute H-band luminosity from 2MASS normalized to solar luminosity. The
other two sub--samples do not have enough number statistics, but appear to
follow the first scaling relation. The energy recovered indicates that the
shocks from stellar feedback in our sample galaxies are fully radiative. If the
scaling relations are applicable in general to stellar feedback, our results
are similar to those by Hopkins et al. (2012) for galactic super winds. This
similarity should, however, be taken with caution at this point, as the
underlying physics that enables the transition from radiative shocks to gas
outflows in galaxies is still poorly understood.


  We describe how to compute estimates of the power spectrum C_l from Cosmic
Microwave Background (CMB) maps that not only retain all the cosmological
information, but also have uncorrelated error bars and well-behaved window
functions. We apply this technique to the 4-year COBE/DMR data, and tabulate
eight uncorrelated band-powers.


  Kidney transplants are sharply overdemanded in the United States. A recent
innovation to address organ shortages is a kidney exchange, in which willing
but medically incompatible patient-donor pairs swap donors so that two
successful transplants occur. Proposed rules for matching such pairs include
static fair matching rules, which improve matching for a particular group, such
as highly-sensitized patients. However, in dynamic environments, it seems
intuitively fair to prioritize time-critical pairs. We consider the tradeoff
between established sensitization fairness and time fairness in dynamic
environments. We design two algorithms, SENS and TIME, and study their patient
loss. We show that the there is a theoretical advantage to prioritizing
time-critical patients (around 9.18% tradeoff on U.S. data) rather than
sensitized patients. Our results suggest that time fairness needs to be
considered in kidney exchange. We then propose a batching algorithm for current
branch-and-price solvers that balances both fairness needs.