  Single-particle overlap functions and spectroscopic factors are calculated on
the basis of the one-body density matrices (ODM) obtained for the nucleus
$^{16}O$ employing different approaches to account for the effects of
correlations. The calculations use the relationship between the overlap
functions related to bound states of the (A-1)-particle system and the ODM for
the ground state of the A-particle system. The resulting bound-state overlap
functions are compared and tested in the description of the experimental data
from (p,d) reactions for which the shape of the overlap function is important.


  We discuss an amazing prey--predator model with variable coefficients,
analyze its predictions and the accuracy of the variational iteration method
used to solve the nonlinear equations.


  This paper presents novel solutions of the data-based synchronization problem
for continuous-time multiagent systems. We consider the cases of homogeneous
and heterogeneous systems. First, we obtain a data-based representation of the
synchronization error dynamics for homogeneous systems and show how to extend
existing data-based stabilization results to stabilize such error dynamics. The
proposed method relies on the solution of a set of linear matrix inequalities
that are shown to be feasible. Then, we solve the synchronization problem for
heterogeneous systems by means of dynamic controllers. Different from existing
results, we do not require model knowledge for the followers and the leader.
The theoretical results are finally validated using a numerical simulation.


  Model-independent parametrisations of modified gravity have attracted a lot
of attention over the past few years and numerous combinations of experiments
and observables have been suggested to constrain the parameters used in these
models. Galaxy clusters have been mentioned, but not looked at as extensively
in the literature as some other probes. Here we look at adding galaxy clusters
into the mix of observables and examine how they could improve the constraints
on the modified gravity parameters. In particular, we forecast the constraints
from combining Planck satellite Cosmic Microwave Background (CMB) measurements
and Sunyaev-Zeldovich (SZ) cluster catalogue with a DES-like weak lensing
survey. We find that cluster counts significantly improve the constraints over
those derived using CMB and WL. We then look at surveys further into the
future, to see how much better it may be feasible to make the constraints.


  The string theory predicts many light fields called moduli and axions, which
cause a cosmological problem due to the overproduction of their coherent
oscillation after inflation. One of the prominent solutions is an adiabatic
suppression mechanism, which, however, is non-trivial to achieve in the case of
axions because it necessitates a large effective mass term which decreases as a
function of time. The purpose of this paper is twofold. First, we provide an
analytic method to calculate the cosmological abundance of coherent oscillation
in a general situation under the adiabatic suppression mechanism. Secondly, we
apply our method to some concrete examples, including the one where a string
axion acquires a large effective mass due to the Witten effect in the presence
of hidden monopoles.


  Transport in complex systems is characterized by a fractal dimension -- the
walk dimension -- that indicates the diffusive or anomalous nature of the
underlying random walk process. Here we report on the experimental retrieval of
this key quantity, using light waves propagating in disordered media. The
approach is based on measurements of the time-resolved transmission, in
particular on how the lifetime scales with sample size. We show that this
allows one to retrieve the walk dimension and apply the concept to samples with
varying degree of fractal heterogeneity. In addition, the method provides the
first experimental demonstration of anomalous light dynamics in a random
medium.


  Semantic segmentation benefits robotics related applications especially
autonomous driving. Most of the research on semantic segmentation is only on
increasing the accuracy of segmentation models with little attention to
computationally efficient solutions. The few work conducted in this direction
does not provide principled methods to evaluate the different design choices
for segmentation. In this paper, we address this gap by presenting a real-time
semantic segmentation benchmarking framework with a decoupled design for
feature extraction and decoding methods. The framework is comprised of
different network architectures for feature extraction such as VGG16, Resnet18,
MobileNet, and ShuffleNet. It is also comprised of multiple meta-architectures
for segmentation that define the decoding methodology. These include SkipNet,
UNet, and Dilation Frontend. Experimental results are presented on the
Cityscapes dataset for urban scenes. The modular design allows novel
architectures to emerge, that lead to 143x GFLOPs reduction in comparison to
SegNet. This benchmarking framework is publicly available at
"https://github.com/MSiam/TFSegmentation".


  We present the global group properties of two samples of galaxy groups
containing 39 high quality X-ray selected systems and 38 optically
(spectroscopically) selected systems in coincident spatial regions at
0.12<z<0.79. Only nine optical systems are associable with X-ray systems. We
discuss the confusion inherent in the matching of both galaxies to extended
X-ray emission and of X-ray emission to already identified optical systems.
Extensive spectroscopy has been obtained and the resultant redshift catalog and
group membership are provided here. X-ray, dynamical, and total stellar masses
of the groups are also derived and presented. We explore the effects of
applying three different kinds of radial cut to our systems: a constant cut of
1 Mpc and two r200 cuts, one based on the velocity dispersion of the system and
the other on the X-ray emission. We find that an X-ray based r200 results in
less scatter in scaling relations and less dynamical complexity as evidenced by
results of the Anderson-Darling and Dressler-Schectman tests, indicating that
this radius tends to isolate the virialized part of the system. The constant
and velocity dispersion based cuts can overestimate membership and can work to
inflate velocity dispersion and dynamical and stellar mass. We find Lx-sigma
and Mstellar-Lx scaling relations for X-ray and optically selected systems are
not dissimilar. The mean fraction of mass found in stars for our systems is
approximately 0.014 with a logarithmic standard deviation of 0.398 dex. We also
define and investigate a sample of groups which are X-ray underluminous given
the total group stellar mass. For these systems the fraction of stellar mass
contributed by the most massive galaxy is typically lower than that found for
the total population of groups implying that there may be less IGM contributed
from the most massive member in these systems. (Abridged)


  A stochastic-gradient-based interior-point algorithm for minimizing a
continuously differentiable objective function (that may be nonconvex) subject
to bound constraints is presented, analyzed, and demonstrated through
experimental results. The algorithm is unique from other interior-point methods
for solving smooth nonconvex optimization problems since the search directions
are computed using stochastic gradient estimates. It is also unique in its use
of inner neighborhoods of the feasible region -- defined by a positive and
vanishing neighborhood-parameter sequence -- in which the iterates are forced
to remain. It is shown that with a careful balance between the barrier,
step-size, and neighborhood sequences, the proposed algorithm satisfies
convergence guarantees in both deterministic and stochastic settings. The
results of numerical experiments show that in both settings the algorithm can
outperform projection-based methods.


  This work studies the robust subspace tracking (ST) problem. Robust ST can be
simply understood as a (slow) time-varying subspace extension of robust PCA. It
assumes that the true data lies in a low-dimensional subspace that is either
fixed or changes slowly with time. The goal is to track the changing subspaces
over time in the presence of additive sparse outliers and to do this quickly
(with a short delay). We introduce a "fast" mini-batch robust ST solution that
is provably correct under mild assumptions. Here "fast" means two things: (i)
the subspace changes can be detected and the subspaces can be tracked with
near-optimal delay, and (ii) the time complexity of doing this is the same as
that of simple (non-robust) PCA. Our main result assumes piecewise constant
subspaces (needed for identifiability), but we also provide a corollary for the
case when there is a little change at each time.
  A second contribution is a novel non-asymptotic guarantee for PCA in linearly
data-dependent noise. An important setting where this is useful is for linearly
data dependent noise that is sparse with support that changes enough over time.
The analysis of the subspace update step of our proposed robust ST solution
uses this result.


  We study Anderson localization of ultracold atoms in weak, one-dimensional
speckle potentials, using perturbation theory beyond Born approximation. We
show the existence of a series of sharp crossovers (effective mobility edges)
between energy regions where localization lengths differ by orders of
magnitude. We also point out that the correction to the Born term explicitly
depends on the sign of the potential. Our results are in agreement with
numerical calculations in a regime relevant for experiments. Finally, we
analyze our findings in the light of a diagrammatic approach.


  The aim of this paper is to define what we shall call open graphic dynamics,
their interactions and the dynamics produced by those interactions. It prepares
the study of "open sub-categorical dynamics" and "open categorical dynamics".


  Despite recent advances in Visual QuestionAnswering (VQA), it remains a
challenge todetermine how much success can be attributedto sound reasoning and
comprehension ability.We seek to investigate this question by propos-ing a new
task ofrationale generation. Es-sentially, we task a VQA model with generat-ing
rationales for the answers it predicts. Weuse data from the Visual Commonsense
Rea-soning (VCR) task, as it contains ground-truthrationales along with visual
questions and an-swers. We first investigate commonsense un-derstanding in one
of the leading VCR mod-els, ViLBERT, by generating rationales frompretrained
weights using a state-of-the-art lan-guage model, GPT-2. Next, we seek to
jointlytrain ViLBERT with GPT-2 in an end-to-endfashion with the dual task of
predicting the an-swer in VQA and generating rationales. Weshow that this kind
of training injects com-monsense understanding in the VQA modelthrough
quantitative and qualitative evaluationmetrics


  We address the problem of video captioning by grounding language generation
on object interactions in the video. Existing work mostly focuses on overall
scene understanding with often limited or no emphasis on object interactions to
address the problem of video understanding. In this paper, we propose
SINet-Caption that learns to generate captions grounded over higher-order
interactions between arbitrary groups of objects for fine-grained video
understanding. We discuss the challenges and benefits of such an approach. We
further demonstrate state-of-the-art results on the ActivityNet Captions
dataset using our model, SINet-Caption based on this approach.


  In the context of upcoming large-scale structure surveys such as Euclid, it
is of prime importance to quantify the effect of peculiar velocities on
geometric probes. Hence the formalism to compute in redshift space the
geometrical and topological one-point statistics of mildly non-Gaussian 2D and
3D cosmic fields is developed. Leveraging the partial isotropy of the target
statistics, the Gram-Charlier expansion of the joint probability distribution
of the field and its derivatives is reformulated in terms of the corresponding
anisotropic variables. In particular, the cosmic non-linear evolution of the
Minkowski functionals, together with the statistics of extrema are investigated
in turn for 3D catalogues and 2D slabs. The amplitude of the non-Gaussian
redshift distortion correction is estimated for these geometric probes. In 3D,
gravitational perturbation theory is implemented in redshift space to predict
the cosmic evolution of all relevant Gram-Charlier coefficients. Applications
to the estimation of the cosmic parameters sigma(z) and beta=f/b1 from upcoming
surveys is discussed. Such statistics are of interest for anisotropic fields
beyond cosmology.


  We prove an optimal error estimate for the flux variable for a stabilized
unfitted Nitsche finite element method applied to an elliptic interface problem
with discontinuous constant coefficients. Our result shows explicitly that this
error estimate is totally independent of the diffusion coefficients


  We consider the problem of determining the granular temperatures of the
components of a homogeneous binary heated mixture of inelastic hard spheres, in
the framework of Enskog kinetic theory. Equations are derived for the
temperatures of each species and their ratio, which is different from unity, as
may be expected since the system is out of equilibrium. We focus on the
particular heating mechanism where the inelastic energy loss is compensated by
an injection through a random external force (``stochastic thermostat''). The
influence of various parameters and their possible experimental relevance is
discussed.


  We demonstrate a new technique for calculating proton-proton inelastic
cross-section, which allows one by application of the Laplace' method replace
the integrand in the integral for the scattering amplitude in the vicinity of
the maximum point by expression of Gaussian type. This in turn, allows one to
overcome the computational difficulties for the calculation of the integrals
expressing the cross section to sufficiently large numbers of particles. We
have managed to overcome these problems in calculating the proton-proton
inelastic cross-section for production (n \le 8) number of secondary particles
in within the framework of \phi^3 model. As the result the obtained dependence
of inelastic cross-section and total scattering cross-section on the energy
\sqrt{s} are qualitative agrees with the experimental data. Such description of
total cross-section behavior differs considerably from existing now
description, where reggeons exchange with the intercept greater than unity is
considered.


  Large Language Models (LLMs) are typically trained in two phases:
pre-training on large internet-scale datasets, and fine-tuning for downstream
tasks. Given the higher computational demand of pre-training, it's intuitive to
assume that fine-tuning adds less new information to the model, and is thus
more compressible. We explore this assumption by decomposing the weights of
fine-tuned models into their pre-trained components and an additional delta. We
introduce a simple method, BitDelta, which successfully quantizes this delta
down to 1 bit without compromising performance. This interesting finding not
only highlights the potential redundancy of information added during
fine-tuning, but also has significant implications for the multi-tenant serving
and multi-tenant storage of fine-tuned models. By enabling the use of a single
high-precision base model accompanied by multiple 1-bit deltas, BitDelta
dramatically reduces GPU memory requirements by more than 10x, which can also
be translated to enhanced generation latency in multi-tenant settings. We
validate BitDelta through experiments across Llama-2 and Mistral model
families, and on models up to 70B parameters, showcasing minimal performance
degradation over all tested settings.


  In this paper, we give a direct proof of the twisted Poincar\'{e} lemma by
using the integrations over regularized paths. This method tells us a concrete
description of the \v{C}ech-de Rham isomorphism.


  The problem of $\textit{visual metamerism}$ is defined as finding a family of
perceptually indistinguishable, yet physically different images. In this paper,
we propose our NeuroFovea metamer model, a foveated generative model that is
based on a mixture of peripheral representations and style transfer
forward-pass algorithms. Our gradient-descent free model is parametrized by a
foveated VGG19 encoder-decoder which allows us to encode images in high
dimensional space and interpolate between the content and texture information
with adaptive instance normalization anywhere in the visual field. Our
contributions include: 1) A framework for computing metamers that resembles a
noisy communication system via a foveated feed-forward encoder-decoder network
-- We observe that metamerism arises as a byproduct of noisy perturbations that
partially lie in the perceptual null space; 2) A perceptual optimization scheme
as a solution to the hyperparametric nature of our metamer model that requires
tuning of the image-texture tradeoff coefficients everywhere in the visual
field which are a consequence of internal noise; 3) An ABX psychophysical
evaluation of our metamers where we also find that the rate of growth of the
receptive fields in our model match V1 for reference metamers and V2 between
synthesized samples. Our model also renders metamers at roughly a second,
presenting a $\times1000$ speed-up compared to the previous work, which allows
for tractable data-driven metamer experiments.


  We present the new open source C++-based Python library CosTuuM that can be
used to generate infrared absorption and emission coefficients for arbitrary
mixtures of spheroidal dust grains that are (partially) aligned with a magnetic
field. We outline the algorithms underlying the software, demonstrate the
accuracy of our results using benchmarks from literature, and use our tool to
investigate some commonly used approximative recipes. We find that the linear
polarization fraction for a partially aligned dust grain mixture can be
accurately represented by an appropriate linear combination of perfectly
aligned grains and grains that are randomly oriented, but that the commonly
used picket fence alignment breaks down for short wavelengths. We also find
that for a fixed dust grain size, the absorption coefficients and linear
polarization fraction for a realistic mixture of grains with various shapes
cannot both be accurately represented by a single representative grain with a
fixed shape, but that instead an average over an appropriate shape distribution
should be used. Insufficient knowledge of an appropriate shape distribution is
the main obstacle in obtaining accurate optical properties. CosTuuM is
available as a standalone Python library and can be used to generate optical
properties to be used in radiative transfer applications.


  Machine learning models of materials$^{1-5}$ accelerate discovery compared to
ab initio methods: deep learning models now reproduce density functional theory
(DFT)-calculated results at one hundred thousandths of the cost of DFT$^{6}$.
To provide guidance in experimental materials synthesis, these need to be
coupled with an accurate yet effective search algorithm and training data
consistent with experimental observations. Here we report an evolutionary
algorithm powered search which uses machine-learned surrogate models trained on
high-throughput hybrid functional DFT data benchmarked against experimental
bandgaps: Deep Adaptive Regressive Weighted Intelligent Network (DARWIN). The
strategy enables efficient search over the materials space of ~10$^8$ ternaries
and 10$^{11}$ quaternaries$^{7}$ for candidates with target properties. It
provides interpretable design rules, such as our finding that the difference in
the electronegativity between the halide and B-site cation being a strong
predictor of ternary structural stability. As an example, when we seek UV
emission, DARWIN predicts K$_2$CuX$_3$ (X = Cl, Br) as a promising materials
family, based on its electronegativity difference. We synthesized and found
these materials to be stable, direct bandgap UV emitters. The approach also
allows knowledge distillation for use by humans.


  This paper details a number of indoor localization techniques developed for
real-time monitoring of older adults. These were developed within the framework
of the i-Light research project that was funded by the European Union. The
project targeted the development and initial evaluation of a configurable and
cost-effective cyber-physical system for monitoring the safety of older adults
who are living in their own homes. Localization hardware consists of a number
of custom-developed devices that replace existing luminaires. In addition to
lighting capabilities, they measure the strength of a Bluetooth Low Energy
signal emitted by a wearable device on the user. Readings are recorded in real
time and sent to a software server for analysis. We present a comparative
evaluation of the accuracy achieved by several server-side algorithms,
including Kalman filtering, a look-back heuristic as well as a neural
network-based approach. It is known that approaches based on measuring signal
strength are sensitive to the placement of walls, construction materials used,
the presence of doors as well as existing furniture. As such, we evaluate the
proposed approaches in two separate locations having distinct building
characteristics. We show that the proposed techniques improve the accuracy of
localization. As the final step, we evaluate our results against comparable
existing approaches.


  Most of the information is stored as text, so text mining is regarded as
having high commercial potential. Aiming at the semantic constraint problem of
classification methods based on sparse representation, we propose a weighted
recurrent neural network (W-RNN), which can fully extract text serialization
semantic information. For the problem that the feature high dimensionality and
unclear semantic relationship in text data representation, we first utilize the
word vector to represent the vocabulary in the text and use Recurrent Neural
Network (RNN) to extract features of the serialized text data. The word vector
is then automatically weighted and summed using the intermediate output of the
word vector to form the text representation vector. Finally, the neural network
is used for classification. W-RNN is verified on the news dataset and proves
that W-RNN is superior to other four baseline methods in Precision, Recall, F1
and loss values, which is suitable for text classification.


  Learning to communicate through interaction, rather than relying on explicit
supervision, is often considered a prerequisite for developing a general AI. We
study a setting where two agents engage in playing a referential game and, from
scratch, develop a communication protocol necessary to succeed in this game.
Unlike previous work, we require that messages they exchange, both at train and
test time, are in the form of a language (i.e. sequences of discrete symbols).
We compare a reinforcement learning approach and one using a differentiable
relaxation (straight-through Gumbel-softmax estimator) and observe that the
latter is much faster to converge and it results in more effective protocols.
Interestingly, we also observe that the protocol we induce by optimizing the
communication success exhibits a degree of compositionality and variability
(i.e. the same information can be phrased in different ways), both properties
characteristic of natural languages. As the ultimate goal is to ensure that
communication is accomplished in natural language, we also perform experiments
where we inject prior information about natural language into our model and
study properties of the resulting protocol.


  In this thesis we study the classical and quantum momentum maps and the
theory of reduction. We focus on the notion of momentum map in Poisson geometry
and we discuss the classification of the momentum map in this framework.
Furthermore, we describe the so-called Poisson Reduction, a technique that
allows us to reduce the dimension of a manifold in presence of symmetries
implemented by Poisson actions.


  In this thesis, we study asymptotic properties of the standard branching
Brownian motion, with a specific emphasis on the additive martingales at high
temperature. We start by presenting classic and fundamental tools for our
investigation. Subsequently, we establish various convergence results that
enhance our understanding of the model. In particular, these results include
the determination of particles contributing to the additive martingales, the
description of the fluctuations of these martingales around their limits, and
an approximation of the so-called overlap distribution. Regarding the latter,
we believe this is the first time that such an approximation is given.
Remarkably, we identify a specific regime in which stable distributions emerge.


  We describe the pi N -> omega N cross section from threshold to a center of
mass energy of 2 GeV in a unitary coupled-channel model and analyze it in terms
of rescattering and resonance excitations. The amplitude is mainly composed of
D13, P13, and P11 contributions, where the D13 dominates over the complete
considered energy range. We also outline the generalization of the standard
partial-wave formalism necessary for the decomposition of the omega N final
state.


  A classical result by Alexander Grigor'yan states that on a stochastically
complete manifold the non-negative superharmonic $L^1$-functions are
necessarily constant. In this paper we address the question of whether and to
what extent the reverse implication holds.


  Multiplier Hopf algebroids are algebraic versions of quantum groupoids that
generalize Hopf algebroids to the non-unital case and weak (multiplier) Hopf
algebras to non-separable base algebras. The main structure maps of a
multiplier Hopf algebroid are a left and a right comultiplication. We show that
bijectivity of two associated canonical maps is equivalent to the existence of
an antipode, discuss invertibility of the antipode, and present some examples
and special cases.


  In the manufacturing process of heavy industrial equipment, the specific unit
in the welding diagram is first manually redrawn and then the corresponding
sheet metal parts are cut, which is inefficient. To this end, this paper
proposes a U-net-based method for the segmentation and extraction of specific
units in welding engineering drawings. This method enables the cutting device
to automatically segment specific graphic units according to visual information
and automatically cut out sheet metal parts of corresponding shapes according
to the segmentation results. This process is more efficient than traditional
human-assisted cutting. Two weaknesses in the U-net network will lead to a
decrease in segmentation performance: first, the focus on global semantic
feature information is weak, and second, there is a large dimensional
difference between shallow encoder features and deep decoder features. Based on
the CBAM (Convolutional Block Attention Module) attention mechanism, this paper
proposes a U-net jump structure model with an attention mechanism to improve
the network's global semantic feature extraction ability. In addition, a U-net
attention mechanism model with dual pooling convolution fusion is designed, the
deep encoder's maximum pooling + convolution features and the shallow encoder's
average pooling + convolution features are fused vertically to reduce the
dimension difference between the shallow encoder and deep decoder. The
dual-pool convolutional attention jump structure replaces the traditional U-net
jump structure, which can effectively improve the specific unit segmentation
performance of the welding engineering drawing. Using vgg16 as the backbone
network, experiments have verified that the IoU, mAP, and Accu of our model in
the welding engineering drawing dataset segmentation task are 84.72%, 86.84%,
and 99.42%, respectively.


  This paper completes a classification of the types of orientable and
non-orientable cusps that can arise in the quotients of hyperbolic knot
complements. In particular, $S^2(2,4,4)$ cannot be the cusp cross-section of
any orbifold quotient of a hyperbolic knot complement. Furthermore, if a knot
complement covers an orbifold with a $S^2(2,3,6)$ cusp, it also covers an
orbifold with a $S^2(3,3,3)$ cusp. We end with a discussion that shows all cusp
types arise in the quotients of link complements.


  A search for Supersymmetry involving the pair production of gluinos decaying
via third-generation squarks to the lightest neutralino is reported. It uses an
LHC proton--proton dataset at a center-of-mass energy $\sqrt{s} = 13$ TeV with
an integrated luminosity of 3.2 fb$^{-1}$ collected with the ATLAS detector in
2015. The signal is searched for in events containing several energetic jets,
of which at least three must be identified as $b$-jets, large missing
transverse momentum and, potentially, isolated electrons or muons. Large-radius
jets with a high mass are also used to identify highly boosted top quarks. No
excess is found above the predicted background. For neutralino masses below
approximately 700 GeV, gluino masses of less than 1.78 TeV and 1.76 TeV are
excluded at the 95% CL in simplified models of the pair production of gluinos
decaying via sbottom and stop, respectively. These results significantly extend
the exclusion limits obtained with the $\sqrt{s} = 8$ TeV dataset.


  We construct a complete set of eigenfunctions of the q-deformed harmonic
oscillator on the quantum line. In particular the eigenfunctions corresponding
to the non-Fock part of the spectrum will be constructed.


  We apply a full-polaron master equation and a weak-coupling non-Markovian
master equation to describe the steady-state time-averaged properties of a
driven two-level system, an electron coherently tunneling between double
quantum dots (DQDs), interacting with a bosonic phonon bath. Comparing the
results obtained using these two master equations with those from a recent DQD
experiment and its corresponding weak-coupling theoretical method, we find that
the original parameter set used in the experiment and theoretical method is not
in the weak-coupling parameter regime. By using the full-polaron master
equation with a slight adjustment on only the value of the interdot separation
in the original experimental parameter set, we find that a reasonable fit to
the experimentally measured time-averaged steady-state population data can be
achieved. The adjusted interdot separation is within the possible values
allowed by the geometry of the surface gates that define the DQD in the
experiment. Our full-polaron equation approach does not require the special
renormalization scheme employed in their weak-coupling theoretical method, and
can still describe the experimental results of driving-induced phonon-enhanced
steplike shoulder behaviors in the experiment. This demonstrates that the
full-polaron master equation approach is a correct and efficient tool to
describe the steady-state properties of a driven spin-boson model in the case
of strong system-environment coupling.


  Two emerging architectural paradigms, i.e., Software Defined Networking (SDN)
and Network Function Virtualization (NFV), enable the deployment and management
of Service Function Chains (SFCs). A SFC is an ordered sequence of abstract
Service Functions (SFs), e.g., firewalls, VPN-gateways,traffic monitors, that
packets have to traverse in the route from source to destination. While this
appealing solution offers significant advantages in terms of flexibility, it
also introduces new challenges such as the correct configuration and ordering
of SFs in the chain to satisfy overall security requirements. This paper
presents a formal model conceived to enable the verification of correct policy
enforcements in SFCs. Software tools based on the model can then be designed to
cope with unwanted network behaviors (e.g., security flaws) deriving from
incorrect interactions of SFs in the same SFC.


  In the past years, EUV lithography scanner systems have entered High-Volume
Manufacturing for state-of-the-art Integrated Circuits (IC), with critical
dimensions down to 10 nm. This technology uses 13.5 nm EUV radiation, which is
transmitted through a near-vacuum H2 background gas, imaging the pattern of a
reticle onto a wafer. The energetic EUV photons excite the background gas into
a low-density H2 plasma. The resulting plasma will locally change the
near-vacuum into a conducting medium, and can charge floating surfaces and
particles, also away from the direct EUV beam. This paper will discuss the
interaction between EUV-induced plasma and electrostatics, by modeling and
experiments. We show that the EUV-induced plasma can trigger discharges well
below the classical Paschen limit. Furthermore, we demonstrate the charging
effect of the EUV plasma on both particles and surfaces. Uncontrolled, this can
lead to unacceptably high voltages on the reticle backside and the generation
and transport of particles. We demonstrate a special unloading sequence to use
the EUV-induced plasma to actively solve the charging and defectivity
challenges.


  We consider the minimum weight and smallest weight minimum-size dominating
set problems in vertex-weighted graphs and networks. The latter problem is a
two-objective optimization problem, which is different from the classic minimum
weight dominating set problem that requires finding a dominating set of the
smallest weight in a graph without trying to optimize its cardinality. In other
words, the objective of minimizing the size of the dominating set in the
two-objective problem can be considered as a constraint, i.e. a particular case
of finding Pareto-optimal solutions. First, we show how to reduce the
two-objective optimization problem to the minimum weight dominating set problem
by using Integer Linear Programming formulations. Then, under different
assumptions, the probabilistic method is applied to obtain upper bounds on the
minimum weight dominating sets in graphs. The corresponding randomized
algorithms for finding small-weight dominating sets in graphs are described as
well. Computational experiments are used to illustrate the results for two
different types of random graphs.


  We study issues of robustness in the context of Quantitative Risk Management
and Optimization. We develop a general methodology for determining whether a
given risk measurement related optimization problem is robust, which we call
"robustness against optimization". The new notion is studied for various
classes of risk measures and expected utility and loss functions. Motivated by
practical issues from financial regulation, special attention is given to the
two most widely used risk measures in the industry, Value-at-Risk (VaR) and
Expected Shortfall (ES). We establish that for a class of general optimization
problems, VaR leads to non-robust optimizers whereas convex risk measures
generally lead to robust ones. Our results offer extra insight on the ongoing
discussion about the comparative advantages of VaR and ES in banking and
insurance regulation. Our notion of robustness is conceptually different from
the field of robust optimization, to which some interesting links are derived.


  We construct a functional model for rank one perturbations of compact normal
operators acting in a certain Hilbert spaces of entire functions generalizing
de Branges spaces. Using this model we study completeness and spectral
synthesis problems for such perturbations. Previously, we developed the
spectral theory of rank one perturbations in the selfadjoint case. In the
present paper we extend and significantly simplify most of known results in the
area. We also prove an Ordering Theorem for invariant subspaces with common
spectral part. This result is essentially new even for rank one perturbations
of compact selfadjoint operators.


  We present a conceptual design for a space based Galactic Exoplanet Survey
Telescope (GEST) which will use the gravitational microlensing technique to
detect extra solar planets with masses as low as that of Mars at all
separations >~ 1 AU. The microlensing data would be collected by a diffraction
limited, wide field imaging telescope of ~ 1.5m aperture equipped with a large
array of red-optimized CCD detectors. Such a system would be able to monitor
$\sim 2\times 10^8$ stars in $\sim 6$ square degrees of the Galactic bulge at
intervals of 20-30 minutes, and it would observe $\sim 12000$ microlensing
events in three bulge seasons. If planetary systems like our own are common,
GEST should be able to detect $\sim 5000$ planets over a 2.5 year lifetime. If
gas giants like Jupiter and Saturn are rare, then GEST would detect $\sim 1300$
planets in a 2.5 year mission if we assume that most planetary systems are
dominated by planets of about Neptune's' mass. Such a mission would also
discover $\sim 100$ planets of an Earth mass or smaller if such planets are
common. This is a factor of $\sim 50$ better than the most ambitious ground
based programs that have been proposed. GEST will also be sensitive to planets
which have been separated from their parent stars.


  We consider computing the on-shell disk action of open-closed string field
theory as a gauge-invariant way of capturing the shift in D-brane tension that
is induced by a deformation of the bulk CFT. We study the effect of bulk matter
deformations (both marginal and relevant) on a wide range of boundary
conditions in a number of CFTs up to subleading (two-loop) order in
perturbation theory. In all analyzed examples, we find that the shift in the
$g$-function of the matter boundary state is always accompanied by a
boundary-independent shift in the string coupling constant, whose leading
behaviour is universally proportional to the sphere two-point function of the
deforming bulk operator.


  The results from the ALMA proposal peer review process in Cycles 0-6 are
analyzed to identify any systematics in the scientific rankings that may
signify bias. Proposal rankings are analyzed with respect to the experience
level of a Principal Investigator (PI) in submitting ALMA proposals, regional
affiliation (Chile, East Asia, Europe, North America, or Other), and gender.
The analysis was conducted for both the Stage 1 rankings, which are based on
the preliminary scores from the reviewers, and the Stage 2 rankings, which are
based on the final scores from the reviewers after participating in a
face-to-face panel discussion. Analysis of the Stage 1 results shows that PIs
who submit an ALMA proposal in multiple cycles have systematically better
proposal ranks than PIs who have submitted proposals for the first time. In
terms of regional affiliation, PIs from Europe and North America have better
Stage 1 rankings than PIs from Chile and East Asia. Consistent with Lonsdale et
al. (2016), proposals led by men have better Stage 1 rankings than women when
averaged over all cycles. This trend was most noticeably present in Cycle 3,
but no discernible differences in the Stage 1 rankings are present in recent
cycles. Nonetheless, in each cycle to date, women have had a lower proposal
acceptance rate than men even after differences in demographics are considered.
Comparison of the Stage 1 and Stage 2 rankings reveal no significant changes in
the distribution of proposal ranks by experience level, regional affiliation,
or gender as a result of the panel discussions, although the proposal ranks for
East Asian PIs show a marginally significant improvement from Stage 1 to Stage
2 when averaged over all cycles. Thus any systematics in the proposal rankings
are introduced primarily in the Stage 1 process and not from the face-to-face
discussions.


  Milky Way-like galaxies are predicted to host a very large number of dark
matter subhalos. Some massive and nearby subhalos could generate detectable
gamma-rays, appearing as unidentified, spatially-extended and stable gamma-ray
sources. We search for such sources in the third Fermi Large Area Telescope
source List (3FGL) and report the identification of a new candidate, 3FGL
J1924.8-1034. With the Fermi-LAT Pass 8 data, we find that 3FGL J1924.8-1034 is
spatially-extended at a high confidence level of $5.4\sigma$, with a best-fit
extension radius of $\sim0.15^{\circ}$. No significant variability has been
found and its gamma-ray spectrum is well fitted by the dark matter annihilation
into $b\bar{b}$ with a mass of $\sim 43$ GeV. All these facts make 3FGL
J1924.8-1034 a possible dark matter subhalo candidate. However, due to the
limited angular resolution, the possibility of that the spatial extension of
3FGL J1924.8-1034 is caused by the contamination from the other un-resolved
point source can not be ruled out.


  In the light of the proposal of hep-th/0207195, we discuss in detail the
issue of the cosmological constant, explaining how can string theory naturally
predict the value which is experimentally observed, without low-energy
supersymmetry.


  The evolution of the pion distribution amplitude in next-to-leading order is
studied for a fixed and a running coupling constant. In both cases, the
evolution provides a logarithmic modification in the endpoint region. Assuming
a simple parameterization of the distribution amplitude at a scale of $Q_0\sim
0.5\ \rm GeV$, it is shown numerically that these effects are large enough at
$Q\sim 2\ \rm GeV$ that they have to be taken into account in the
next-to-leading-order analysis for exclusive processes. Alternatively, by
introducing a new distribution amplitude that evolves more smoothly, this
logarithmic modification can be included in the hard-scattering part of the
considered process.


  Harmonization improves data consistency and is central to effective
integration of diverse imaging data acquired across multiple sites. Recent deep
learning techniques for harmonization are predominantly supervised in nature
and hence require imaging data of the same human subjects to be acquired at
multiple sites. Data collection as such requires the human subjects to travel
across sites and is hence challenging, costly, and impractical, more so when
sufficient sample size is needed for reliable network training. Here we show
how harmonization can be achieved with a deep neural network that does not rely
on traveling human phantom data. Our method disentangles site-specific
appearance information and site-invariant anatomical information from images
acquired at multiple sites and then employs the disentangled information to
generate the image of each subject for any target site. We demonstrate with
more than 6,000 multi-site T1- and T2-weighted images that our method is
remarkably effective in generating images with realistic site-specific
appearances without altering anatomical details. Our method allows
retrospective harmonization of data in a wide range of existing modern
large-scale imaging studies, conducted via different scanners and protocols,
without additional data collection.


  In this work, we present a methodology and a corresponding code-base for
constructing mock integral field spectrograph (IFS) observations of simulated
galaxies in a consistent and reproducible way. Such methods are necessary to
improve the collaboration and comparison of observation and theory results, and
accelerate our understanding of how the kinematics of galaxies evolve over
time. This code, SimSpin, is an open-source package written in R, but also with
an API interface such that the code can be interacted with in any coding
language. Documentation and individual examples can be found at the open-source
website connected to the online repository. SimSpin is already being utilised
by international IFS collaborations, including SAMI and MAGPI, for generating
comparable data sets from a diverse suite of cosmological hydrodynamical
simulations.


  In this article, we establish several almost critical regularity conditions
such that the weak solutions of the 3D Navier-Stokes equations become regular,
based on one component of the solutions, say $u_3$ and $\partial_3u_3$.


  Out of the handful of asteroids that have been imaged, some have
distributions of blocks that are not easily explained. In this paper, we
investigate the possibility that seismic shaking leads to the size sorting of
particles in asteroids. In particular, we focus on the so-called Brazil Nut
Effect (BNE) that separates large particles from small ones under vibrations.
We study the BNE over a wide range of parameters by using the N-body code
PKDGRAV, and find that the effect is largely insensitive to the coefficients of
restitution, but sensitive to friction constants and oscillation speeds.
Agreeing with the previous results, we find that convection drives the BNE,
where the intruder rises to the top of the particle bed. For the wide-cylinder
case, we also observe a "whale" effect, where the intruder follows the
convective current and does not stay at the surface. We show that the
non-dimensional critical conditions for the BNE agree well with previous
studies. We also show that the BNE is scalable for low-gravity environments and
that the rise speed of an intruder is proportional to the square root of the
gravitational acceleration. Finally, we apply the critical conditions to
observed asteroids, and find that the critical oscillation speeds are
comparable to the seismic oscillation speeds that are expected from
non-destructive impacts.


  In this paper, we generalize the finite generation result of Sormani to
non-branching $RCD(0,N)$ geodesic spaces (and in particular, Alexandrov spaces)
with full support measures. This is a special case of the Milnor's Conjecture
for complete non-compact $RCD(0,N)$ spaces. One of the key tools we use is the
Abresch-Gromoll type excess estimates for non-smooth spaces obtained by
Gigli-Mosconii.


  Knowledge Graphs have become a ubiquitous technology powering search engines,
recommender systems, connected objects, corporate knowledge management and Open
Data. They rely on small units of information named triples that can be
combined to form higher level statements across datasets following information
needs. But data producers face a problem: reconstituting chains of triples has
a high cognitive cost, which hinders them from gaining meaningful overviews of
their own datasets. We introduce path outlines: conceptual objects
characterizing sequences of triples with descriptive statistics. We interview
11 data producers to evaluate their interest. We present Path Outlines, a tool
to browse path-based summaries, based on coordinated views with 2 novel
visualisations. We compare Path Outlines with the current baseline technique in
an experiment with 36 participants. We show that it is 3 times faster, leads to
better task completion, less errors, that participants prefer it, and find
tasks easier with it.


  A skew polynomial ring $R=K[x;\sigma,\delta]$ is a ring of polynomials with
non-commutative multiplication. This creates a difference between left and
right divisibility, and thus a concept of left and right evaluations and roots.
A polynomial in such a ring may have more roots than its degree, which leads to
the concepts of closures and independent sets of roots. There is also a
structure of conjugacy classes on the roots. In $R=F_{q^m}[x,\sigma]$, this
leads to matroids of right independent and left independent sets. These
matroids are isomorphic via the extension of the map $\phi:[1]\to[1]$ defined
by $\phi(a)=a^{\frac{q^{i-1}-1}{q-1}}$. Additionally, extending the field of
coefficients of $R$ results in a new skew polynomial ring $S$ of which $R$ is a
subring, and if the extension is taken to include roots of an evaluation
polynomial of $f(x)$ (which does not depend on which side roots are being
considered on), then all roots of $f(x)$ in $S$ are in the same conjugacy
class.


  A theory of Clebsch-Gordan coefficients for $SL(2, C)$ is given using only
rational numbers. Features include orthogonality relations, recurrence
relations, and Regge's symmetry group. Results follow from elementary
representation theory and properties of binomial coefficients. A computational
algorithm is given based on Pascal's recurrence.


  The recent application of deep learning in various areas of medical image
analysis has brought excellent performance gains. In particular, technologies
based on deep learning in medical image registration can outperform traditional
optimisation-based registration algorithms both in registration time and
accuracy. However, the U-net based architectures used in most of the image
registration frameworks downscale the data, which removes global information
and affects the deformation. In this paper, we present a densely connected
convolutional architecture for deformable image registration. Our proposed
dense network downsizes data only in one stage and have dense connections
instead of the skip connections in U-net architecture. The training of the
network is unsupervised and does not require ground-truth deformation or any
synthetic deformation as a label. The proposed architecture is trained and
tested on two different versions of tissue-cleared data, at 10\% and 25\%
resolution of the original single-cell-resolution dataset. We demonstrate
comparable registration performance to state-of-the-art registration methods
and superior performance to the deep-learning based VoxelMorph method in terms
of accuracy and increased resolution handling ability. In both resolutions, the
proposed DenseDeformation network outperforms VoxelMorph in registration
accuracy. Importantly, it can register brains in one minute where conventional
methods can take hours at 25\% resolution.


  Simulations of neutrino flavor evolution in compact merger environments have
shown that neutrino flavor, and hence nucleosynthesis, can be strongly affected
by the presence of matter-neutrino resonances (MNRs), where there is a
cancelation between the matter and the neutrino potential. Simulations
performed thus far follow flavor evolution along a single neutrino trajectory,
but self-consistency requires all trajectories to be treated simultaneously,
and it has not been known whether MNR phenomena would still occur in
multi-angle models. In this paper, we present the first fully multi-angle
calculations of MNR. We find that familiar MNR phenomena, where neutrinos
transform to a greater extent than anti-neutrinos and a feedback mechanism
maintains the cancellation between the matter and neutrino potential, still
occurs for a subset of angular bins, although the flavor transformation is not
as efficient as in the single-angle case. In addition, we find other types of
flavor transformation that are not seen in single-angle simulations. These
flavor transformation phenomena appear to be robust and are present for a wide
range of model parameters, as long as an MNR is present. Although computational
constraints currently limit us to models with spherical symmetry, our results
suggest that the presence of an MNR generally leads to large-scale neutrino
flavor evolution in multi-angle systems.


  We calculate the number density and luminosity of the sources of ultra high
energy cosmic rays (UHECRs), using the information about the small scale
anisotropies and the observed spectra. We find that the number of doublets and
triplets observed by AGASA can be best reproduced for a source density of $\sim
10^{-5} Mpc^{-3}$, with large uncertainties. The spectrum of UHECRs implies an
energy input of $\sim 6\times 10^{44} erg yr^{-1} Mpc^{-3}$ above $10^{19}$ eV
and an injection spectrum $\propto E^{-2.6}$. A flatter injection spectrum,
$E^{-2.4}$, can be adopted if the sources have luminosity evolution $\propto
(1+z)^4$. The combination of these two pieces of information suggests that the
single sources should on average have a cosmic ray luminosity above $10^{19}$
eV of $L_{source}\approx 2\times 10^{42} erg s^{-1}$, weakly dependent upon the
injection spectrum. Unfortunately, with the limited statistics of events
available at present, there are approximately one-two orders of magnitude
uncertainty in the source density provided above. We make predictions on the
expected performances of the Auger and EUSO experiments, with particular
attention for the expected improvements in our understanding of the nature of
the sources of UHECRs. We find that a critical experimental exposure $\Sigma_c$
exists, such that experiments with exposure larger than $\Sigma_c$ can detect
at least one event from each source at energies above $10^{20}$ eV. This
represents a unique opportunity to directly count and identify the sources of
UHECRs.


  We propose a scheme to create a metastable state of paired bosonic atoms in
an optical lattice. The most salient features of this state are that the
wavefunction of each pair is a Bell state and that the pair size spans half the
lattice, similar to fermionic Cooper pairs. This mesoscopic state can be
created with a dynamical process that involves crossing a quantum phase
transition and which is supported by the symmetries of the physical system. We
characterize the final state by means of a measurable two-particle correlator
that detects both the presence of the pairs and their size.


  The Internet of Things is arriving to our homes or cities through fields
already known like Smart Homes, Smart Cities, or Smart Towns. The monitoring of
environmental conditions of cities can help to adapt the indoor locations of
the cities in order to be more comfortable for people who stay there. A way to
improve the indoor conditions is an efficient temperature control, however, it
depends on many factors like the different combinations of outdoor temperature
and humidity. Therefore, adjusting the indoor temperature is not setting a
value according to other value. There are many more factors to take into
consideration, hence the traditional logic based in binary states cannot be
used. Many problems cannot be solved with a set of binary solutions and we need
a new way of development. Fuzzy logic is able to interpret many states, more
than two states, giving to computers the capacity to react in a similar way to
people. In this paper we will propose a new approach to control the temperature
using the Internet of Things together its platforms and fuzzy logic regarding
not only the indoor temperature but also the outdoor temperature and humidity
in order to save energy and to set a more comfortable environment for their
users. Finally, we will conclude that the fuzzy approach allows us to achieve
an energy saving around 40% and thus, save money.


  According to classical nucleation theory, a crystal grows from a small
nucleus that already bears the symmetry of its end phase - but experiments with
colloids now reveal that, from an amorphous precursor, crystallites with
different structures can develop.


  Accurate object tracking in low-light environments is crucial, particularly
in surveillance and ethology applications. However, achieving this is
significantly challenging due to the poor quality of captured sequences.
Factors such as noise, color imbalance, and low contrast contribute to these
challenges. This paper presents a comprehensive study examining the impact of
these distortions on automatic object trackers. Additionally, we propose a
solution to enhance tracking performance by integrating denoising and low-light
enhancement methods into the transformer-based object tracking system.
Experimental results show that the proposed tracker, trained with low-light
synthetic datasets, outperforms both the vanilla MixFormer and Siam R-CNN.


  Research concerning organization and coordination within multi-agent systems
continues to draw from a variety of architectures and methodologies. The work
presented in this paper combines techniques from game theory and multi-agent
systems to produce self-organizing, polymorphic, lightweight, embedded agents
for systems scheduling within a large-scale real-time systems environment.
Results show how this approach is used to experimentally produce optimum
real-time scheduling through the emergent behavior of thousands of agents.
These results are obtained using a SWARM simulation of systems scheduling
within a High Energy Physics experiment consisting of 2500 digital signal
processors.


  The so-called 2d/4d correspondences connect two-dimensional conformal field
theory (2d CFT), N=2 supersymmetric gauge theories and quantum integrable
systems. The latter in the simplest case of the SU(2) gauge group are nothing
but the quantum-mechanical systems. In the present article we summarize our
recent results and list open problems concerning an application of the
aforementioned dualities in the studies of spectral problems for some
Schrodinger operators with Mathieu-type periodic, periodic PT-symmetric and
(Heun's) elliptic potentials.


  Quantum computers are a leading platform for the simulation of many-body
physics. This task has been recently facilitated by the possibility to program
directly the time-dependent pulses sent to the computer. Here, we use this
feature to simulate quantum lattice models with long-range hopping. Our
approach is based on an exact mapping between periodically driven quantum
systems and one-dimensional lattices in the synthetic Floquet direction. By
engineering a periodic drive with a power-law spectrum, we simulate a lattice
with long-range hopping, whose decay exponent is freely tunable. We propose and
realize experimentally two protocols to probe the long tails of the Floquet
eigenfunctions and to identify a scaling transition between weak and strong
long-range couplings. Our work offers a useful benchmark of pulse engineering
and opens the route towards quantum simulations of rich nonequilibrium effects.


  Specialized applications of nanoparticles often call for particular,
well-characterized particle size distributions in solution. But, this property
can prove difficult to measure. High-throughput methods, such as dynamic light
scattering, detect nanoparticles in solution with an efficiency that scales
with diameter to the sixth power. This diminishes the accuracy of any
determination that must span a range of particle sizes. The accurate
classification of broadly distributed systems thus requires very large numbers
of measurements. Mass-filtered particle-sensing techniques offer a better
dynamic range, but are labor-intensive and so have low throughput. Progress in
many areas of nanotechnology requires a faster, lower-cost, and more accurate
measure of particle size distributions, particularly for diameters smaller than
20 nm. Here, we present a tailored interferometric microscope system, combined
with a high-speed image-processing strategy, optimized for real-time particle
tracking that determines accurate size distributions in nominal 5, 10, and 15
nm colloidal gold nanoparticle systems by automatically sensing and classifying
thousands of single particles sampled from solution at rates as high as 4,000
particles per minute. We demonstrate this method by sensing the irreversible
binding of gold nanoparticles to poly-D-lysine functionalized coverslips.
Variations in the single-particle signal as a function of time and mass,
calibrated by TEM, show clear evidence for the presence of diffusion-limited
transport that most affects larger particles in solution.


  We investigate the balance of power between stars and AGN across cosmic
history, based on the comparison between the infrared (IR) galaxy luminosity
function (LF) and the IR AGN LF. The former corresponds to emission from dust
heated by stars and AGN, whereas the latter includes emission from AGN-heated
dust only. We find that at all redshifts (at least up to z~2.5), the high
luminosity tails of the two LFs converge, indicating that the most
infrared-luminous galaxies are AGN-powered. Our results shed light to the
decades-old conundrum regarding the flatter high-luminosity slope seen in the
IR galaxy LF compared to that in the UV and optical. We attribute this
difference to the increasing fraction of AGN-dominated galaxies with increasing
total infrared luminosity (L_IR). We partition the L_IR-z parameter space into
a star-formation and an AGN-dominated region, finding that the most luminous
galaxies at all epochs lie in the AGN-dominated region. This sets a potential
`limit' to attainable star formation rates, casting doubt on the abundance of
`extreme starbursts': if AGN did not exist, L_IR>10^13 Lsun galaxies would be
significantly rarer than they currently are in our observable Universe. We also
find that AGN affect the average dust temperatures (T_dust) of galaxies and
hence the shape of the well-known L_IR-T_dust relation. We propose that the
reason why local ULIRGs are hotter than their high redshift counterparts is
because of a higher fraction of AGN-dominated galaxies amongst the former
group.


  We consider the coherent control of a quantum bit by the use of short pulses
with finite duration \tau_p. By shaping the pulse, we perturbatively decouple
the dynamics of the bath from the dynamics of the quantum bit during the pulse.
Such shaped pulses provide single quantum bit gates robust against decoherence
which are useful for quantum information processing. We extend previous results
in two ways: (i) we treat frequency modulated pulses and (ii) we pass from
time-independent baths to analytically time-dependent baths. First and second
order solutions for \pi- and \pi/2-pulses are presented. They are useful in
experiments where amplitude modulation is difficult to realize.


  In this paper we will show that two surfaces of the same genus and homology
class in a simply connected 4-manifold are concordant. We will show they are
often topologically isotopic when their complements have cyclic fundamental
group. Finally, we will show that if they are 0-concordant, then surgery on one
is equivalent to surgery on the other.


  Here in this work we propose a modified gravity with the action of $f(R) =
\sqrt{R^2 - R_0^2}$ instead of Einstein-Hilbert action to describe the late
time acceleration of the universe. We obtain the equation of the modified
gravity both in the metric and Palatini formalisms. An asymptotic solution of
gravity equations corresponding to a constant Ricci scalar causes a late time
acceleration of the universe. We do a conformal transformation in the action of
the modified gravity and obtain the equivalent minimally coupled scalar-tensor
gravity. The equivalent Brans-Dicke gravity of this model is also studied. To
examine this model with the observation, the perihelion Precession of the
Mercury is compared with our prediction and we put an upper constraint of
$R_0<H_0^2$. This range for $R_0$ is also in agreement with the cosmological
acceleration at the present time. Finally we show that this action has
instability for the small perturbations of the metric in vacuum solution in
which adding a quadratic term of Ricci scalar can stabilize it.


  We have studied the X-ray emission from four historical Type-II supernovae
(the newly-discovered 1941C in NGC 4631 and 1959D in NGC 7331; and 1968D, 1980K
in NGC 6946), using Chandra ACIS-S imaging. In particular, the first three are
the oldest ever found in the X-ray band, and provide constraints on the
properties of the stellar wind and circumstellar matter encountered by the
expanding shock at more advanced stages in the transition towards the remnant
phase. We estimate emitted luminosities ~ 5 x 10^{37} erg/s for SN 1941C, ~ a
few x 10^{37} erg/s for SN 1959D, ~ 2 x 10^{38} erg/s for SN 1968D, and ~ 4 x
10^{37} erg/s for SN 1980K, in the 0.3-8 keV band. X-ray spectral fits to SN
1968D suggest the presence of a harder component, possibly a power law with
photon index ~ 2, contributing ~ 10^{37} erg/s in the 2-10 keV band. We
speculate that it may be evidence of non-thermal emission from a Crab-like
young pulsar.


  A new analogy between superfluid systems and cosmology is here presented,
which relies strongly on the following ingredient: the back-reaction of the
vacuum to the quanta of sound waves. We show how the presence of thermal
phonons, the excitations above the quantum vacuum for $T> 0$, enable us to
deduce an hydrodynamical equation formally similar to the one obtained for a
perfect fluid in a Universe obeying the Friedmann-Robertson-Walker metric.


  We introduce transformation matrix connecting sets of the displaced states
with different displacement amplitudes. Arbitrary pure one-mode state can be
represented in new basis of the displaced number (Fock) states (
representation) by multiplying the transposed transformation matrix on a column
vector of initial state. Analytical expressions of the representation of
superposition of vacuum and single photon and two-mode squeezed vacuum (TMSV)
are obtained. On the basis of the developed mathematical formalism, we consider
the mechanism of interaction between qubits which is based on their displaced
properties. Superposed coherent states deterministically displace target state
on equal modulo but opposite on sign values. Registration of the single photon
in auxiliary mode (probabilistic operation) results in constructive
interference and gives birth to entangled hybrid state corresponding to outcome
of elementary quantum gates. The method requires minimal number of resource and
works in realistic scenario


  The deep inferior epigastric artery perforator (DIEAP) flap is the most
common free flap used for breast reconstruction after a mastectomy. It makes
use of the skin and fat of the lower abdomen to build a new breast mound either
at the same time of the mastectomy or in a second surgery. This operation
requires preoperative imaging studies to evaluate the branches - the
perforators - that irrigate the tissue that will be used to reconstruct the
breast mound. These branches will support tissue viability after the
microsurgical ligation of the inferior epigastric vessels to the receptor
vessels in the thorax. Usually through a Computed Tomography Angiography (CTA),
each perforator, diameter and direction is manually identified by the imaging
team, who will subsequently draw a map for the identification of the best
vascular support for the reconstruction. In the current work we propose a
semi-automatic methodology that aims at reducing the time and subjectivity
inherent to the manual annotation. In 21 CTAs from patients proposed for breast
reconstruction with DIEAP flaps, the subcutaneous region of each perforator was
extracted, by means of a tracking procedure, whereas the intramuscular portion
was detected through a minimum cost approach. Both were subsequently compared
with the radiologist manual annotation. Results showed that the semi-automatic
procedure was able to correctly detect the course of the DIEAPs with a minimum
error (average error of 0.64 mm and 0.50 mm regarding the extraction of
subcutaneous and intramuscular paths, respectively). The objective methodology
is a promising tool in the automatic detection of perforators in CTA and can
contribute to spare human resources and reduce subjectivity in the
aforementioned task.


  Recent study suggests that the streaming instability, one of the leading
mechanisms for driving the formation of planetesimals, may not be as efficient
as previously thought. Under some disc conditions, the growth timescale of the
instability can be longer than the disc lifetime when multiple dust species are
considered. To further explore this finding, we use both linear analysis and
direct numerical simulations with gas fluid and dust particles to mutually
validate and study the unstable modes of the instability in more detail. We
extend the previously studied parameter space by one order of magnitude in both
the range of the dust-size distribution $[T_{s,min}, T_{s,max}]$ and the total
solid-to-gas mass ratio $\varepsilon$ and introduce a third dimension with the
slope $q$ of the size distribution. We find that the fast-growth regime and the
slow-growth regime are distinctly separated in the $\varepsilon$-$T_{s,max}$
space, while this boundary is not appreciably sensitive to $q$ or $T_{s,min}$.
With a wide range of dust sizes present in the disc (e.g.
$T_{s,min}\lesssim10^{-3}$), the growth rate in the slow-growth regime
decreases as more dust species are considered. With a narrow range of dust
sizes (e.g. $T_{s,max}/T_{s,min}=5$), on the other hand, the growth rate in
most of the $\varepsilon$-$T_{s,max}$ space is converged with increasing dust
species, but the fast and the slow growth regimes remain clearly separated.
Moreover, it is not necessary that the largest dust species dominate the growth
of the unstable modes, and the smaller dust species can affect the growth rate
in a complicated way. In any case, we find that the fast-growth regime is
bounded by $\varepsilon\gtrsim 1$ or $T_{s,max}\gtrsim 1$, which may represent
the favourable conditions for planetesimal formation.


  In order to investigate the Galactic-scale environmental effects on the
evolution of protoplanetary disks, we explored the near-infrared (NIR) disk
fraction of the Quartet cluster, which is a young cluster in the innermost
Galactic disk at the Galactocentric radius Rg ~ 4 kpc. Because this cluster has
a typical cluster mass of ~10^3 M_sun as opposed to very massive clusters,
which have been observed in previous studies (>10^4 M_sun), we can avoid
intra-cluster effects such as strong UV field from OB stars. Although the age
of the Quartet is previously estimated to be 3-8 Myr old, we find that it is
most likely ~3-4.5 Myr old. In moderately deep JHK images from the UKIDSS
survey, we found eight HAeBe candidates in the cluster, and performed K-band
medium-resolution ($R \equiv \Delta \lambda / \lambda ~ 800$) spectroscopy for
three of them with the Subaru 8.2 m telescope. These are found to have both
Br\gamma absorption lines as well as CO bandhead emission, suggesting that they
are HAeBe stars with protoplanetary disks. We estimated the intermediate-mass
disk fraction (IMDF) to be ~25 % for the cluster, suggesting slightly higher
IMDF compared to those for young clusters in the solar neighborhood with
similar cluster age, although such conclusion should await future spectroscopic
study of all candidates of cluster members.


  We introduce new invariants in equivariant birational geometry and study
their relation to modular symbols and cohomology of arithmetic groups.


  In this work, we focus on connections between $K$-means clustering approaches
and Orthogonal Nonnegative Matrix Factorization (ONMF) methods. We present a
novel framework to extract the distance measure and the centroids of the
$K$-means method based on first order conditions of the considered ONMF
objective function, which exploits the classical alternating minimization
schemes of Nonnegative Matrix Factorization (NMF) algorithms. While this
technique is characterized by a simple derivation procedure, it can also be
applied to non-standard regularized ONMF models. Using this framework, we
consider in this work ONMF models with $\ell_1$ and standard $\ell_2$
discrepancy terms with an additional elastic net regularization on both
factorization matrices and derive the corresponding distance measures and
centroids of the generalized $K$-means clustering model. Furthermore, we give
an intuitive view of the obtained results, examine special cases and compare
them to the findings described in the literature.


  The goal of this paper is to combine ideas from the theory of mixed spectral
problems for differential operators with new results in the area of the
Uncertainty Principle in Harmonic Analysis (UP). Using recent solutions of Gap
and Type Problems of UP we prove a version of Borg's two-spectra theorem for
Schr\"odinger operators, allowing uncertainty in the placement of the
eigenvalues. We give a formula for the exact 'size of uncertainty', calculated
from the lengths of the intervals where the eigenvalues may occur. Among other
applications, we describe pairs of indeterminate operators in the
three-interval case of the mixed spectral problem. At the end of the paper we
discuss further questions and open problems.


  We propose a novel M-estimate conjugate gradient (CG) algorithm, termed
Tukey's biweight M-estimate CG (TbMCG), for system identification in impulsive
noise environments. In particular, the TbMCG algorithm can achieve a faster
convergence while retaining a reduced computational complexity as compared to
the recursive least-squares (RLS) algorithm. Specifically, the Tukey's biweight
M-estimate incorporates a constraint into the CG filter to tackle impulsive
noise environments. Moreover, the convergence behavior of the TbMCG algorithm
is analyzed. Simulation results confirm the excellent performance of the
proposed TbMCG algorithm for system identification and active noise control
applications.


  By completing the old discussion of K.~Wilson, we express the chiral anomaly
in terms of a double integral of a three-point function of chiral currents over
an arbitrarily small region in the coordinate space. An integrability condition
provides an important finite local counterterm to the integral.


  Oxygen vacancies are ubiquitous in TiO$_2$ and play key roles in catalysis
and magnetism applications.Despite being extensively investigated, the
electronic structure of oxygen vacancies in TiO$_2$ remains controversial both
experimentally and theoretically.Here we report a study of a neutral oxygen
vacancy in TiO$_2$ using state-of-the-art quantum chemical electronic structure
methods.We find that the ground state is a color center singlet state in both
the rutile and the anatase phase of TiO$_2$. Specifically, embedded CCSD(T)
calculations find, for an oxygen vacancy in rutile, that the lowest triplet
state energy is 0.6 eV above the singlet state, and in anatase the triplet
state energy is higher by 1.4 eV. Our study provides fresh insights on the
electronic structure of the oxygen vacancy in TiO$_2$, clarifying earlier
controversies and potentially inspiring future studies of defects with
correlated wave function theories.


  Nitrogen-vacancy (NV) spin ensembles in diamond provide an advanced magnetic
sensing platform, with applications in both the physical and life sciences. The
development of isotopically engineered $^{15}$NV diamond offers advantages over
naturally occurring $^{14}$NV for magnetometry, due to its simpler hyperfine
structure. However, for sensing modalities requiring a bias magnetic field not
aligned with the sensing NV axis, the absence of a quadrupole moment in the
$^{15}$N nuclear spin leads to pronounced envelope modulation effects in
time-dependent measurements of $^{15}$NV spin evolution. While such behavior in
spin echo experiments are well studied, analogous effects in Ramsey
measurements and the implications for magnetometry remain under-explored. Here,
we derive the modulated $^{15}$NV Ramsey response to a misaligned bias field,
using a simple vector description of the effective magnetic field on the
nuclear spin. The predicted modulation properties are then compared to
experimental results, revealing significant magnetic sensitivity loss if
unaddressed. We demonstrate that double-quantum coherences of the NV $S=1$
electronic spin states dramatically suppress these envelope modulations, while
additionally proving resilient to other parasitic effects such as strain
heterogeneity and temperature shifts.


  The Brent-McMillan algorithm B3 (1980), when implemented with binary
splitting, is the fastest known algorithm for high-precision computation of
Euler's constant. However, no rigorous error bound for the algorithm has ever
been published. We provide such a bound and justify the empirical observations
of Brent and McMillan. We also give bounds on the error in the asymptotic
expansions of functions related to modified Bessel functions.


  In this paper, we consider some frustrated spin models for which the ground
states are known exactly. The concurrence, a measure of the amount of
entanglement can be calculated exactly for entangled spin pairs. Quantum phase
transitions involving macroscopic magnetization changes at critical values of
the magnetic field are accompanied by macroscopic jumps in the (T=0)
entanglement. A specific example is given in which magnetization plateaus give
rise to a plateau structure in the amount of entanglement associated with
nearest-neighbour bonds. We further show that macroscopic entanglement changes
can occur in quantum phase transitions brought about by the tuning of exchange
interaction strengths.


  The latest cosmological N-body simulations find two intriguing properties for
dark matter haloes: (1) their radial density profile, rho, is better fit by a
form that flattens to a constant at the halo center (the Einasto profile) than
the widely-used NFW form; (2) the radial profile of the pseudo-phase-space
density, rho/sigma3, on the other hand, continues to be well fit by a power
law, as seen in earlier lower-resolution simulations. In this paper we use the
Jeans equation to argue that (1) and (2) cannot both be true at all radii. We
examine the implied radial dependence of rho/sigma3 over 12 orders of magnitude
in radius by solving the Jeans equation for a broad range of input rho and
velocity anisotropy beta. Independent of beta, we find that rho/sigma3 is
approximately a power law only over the limited range of halo radius resolvable
by current simulations (down to ~0.1% of the virial radius), and rho/sigma3
deviates significantly from a power-law below this scale for both the Einasto
and NFW rho. The same conclusion also applies to a more general
density-velocity relation rho/sigma_D^epsilon. Conversely, when we enforce
rho/sigma^3 r^{-eta} as an input, none of the physically allowed rho (occurring
for the narrow range 1.8<eta<1.9444) follows the Einasto form. We expect the
next generation simulations with better spatial resolution to settle the
debate: either the Einasto profile will continue to hold and rho/sigma3 will
deviate from a power law, or rho/sigma3 will continue as a power law and rho
will deviate from its current parameterizations.


  The equations of state of spin-polarized nuclear matter and pure neutron
matter are studied in the framework of the Brueckner-Hartree-Fock theory
including a three-body force. The energy per nucleon $E_A(\delta)$ calculated
in the full range of spin polarization ${\delta} =
\frac{\rho_{\uparrow}-\rho_{\downarrow}}{\rho}$ for symmetric nuclear matter
and pure neutron matter fulfills a parabolic law. In both cases the
spin-symmetry energy is calculated as a function of the baryonic density along
with the related quantities such as the magnetic susceptibility and the Landau
parameter $G_0$. The main effect of the three-body force is to strongly reduce
the degenerate Fermi gas magnetic susceptibility even more than the value with
only two body force. The EOS is monotonically increasing with the density for
all spin-aligned configurations studied here so that no any signature is found
for a spontaneous transition to a ferromagnetic state.


  We observed the pre-stellar core L1521F in dust emission at 1.2mm and in two
transitions each of N2H+, N2D+, C18O, and C17O in order to increase the sample
of well studied centrally concentrated and chemically evolved starless cores,
likely on the verge of star formation, and to determine the initial conditions
for low--mass star formation in the Taurus Molecular Cloud. We derived in this
object a molecular hydrogen number density n(H2) ~ 10^6 cm-3 and a CO depletion
factor, integrated along the line of sight, fD ~ 15 in the central 20'',
similar to the pre-stellar core L1544. However, the N(N2D+)/N(N2H+) column
density ratio is ~0.1, a factor of about 2 lower than that found in L1544. The
observed relation between the deuterium fractionation and the integrated CO
depletion factor across the core can be reproduced by chemical models if N2H+
is slightly (factor of ~2 in fractional abundance) depleted in the central 3000
AU. The N2H+ and N2D+ linewidths in the core center are ~0.3 km/s,
significantly larger than in other more quiescent Taurus starless cores but
similar to those observed in the center of L1544. The kinematical behaviour of
L1521F is more complex than seen in L1544, and a model of contraction due to
ambipolar diffusion is only marginally consistent with the present data. Other
velocity fields, perhaps produced by unresolved substructure, are present. Both
chemical and kinematical analyses suggest that L1521F is less evolved than
L1544, but, in analogy with L1544, it is approaching the ``critical'' state.


  Axial flux permanent magnet designs are compact and becoming an attractive
design for electric vehicles as an auxiliary braking system. This work develops
the design of an Axial Flux Permanent Magnet Eddy current brake for application
on Light Weight Motor Vehicles as guided by industry regulations. The work
makes a link between the common Finite Element Method approach used in the
literature and the Analytical approach previously done. The design is conducted
to meet the torque requirements per wheel. The average torque over the
operating range closest to the design requirement was used as the solution.


  The novel application of a piezoelectric quartz resonator for the detection
of trapped ions has developed in the observation of the quartz-ions interaction
under non-equilibrium conditions, opening new perspectives for high-sensitive
motional frequency measurements of radioactive particles. Energized quartz
crystals have (long) constant-decay times in the order of milliseconds,
permitting the coherent detection of charged particles within short times. In
this publication we develop in detail a model governing the interaction between
trapped $^{40}$Ca$^+$ ions and a quartz resonator connected to a low-noise
amplifier. We apply this model to experimental data and extract relevant
information like the coupling constant $g=2\pi \times 1.449(2)$~Hz and the
ions' modified-cyclotron frequency in our 7-tesla Penning trap. The study on
the latter is specially important for the use of this resonator in precision
Penning-trap mass spectrometry. The improvement in sensitivity can be
accomplished by increasing the coupling constant through the quality factor of
the resonator. This can develop in the use of the hybrid quartz-ion system for
other applications.


  The authors give a complete classification of projective threefolds admitting
a holomorphic normal projective connection. Moreover, they prove a general
structure theorem on complex projective manifolds admitting a holomorphic
normal projective connection, saying in particular, that any such manifold is
either the projective space or minimal in the sense of Mori.


  The world's largest sample of $J/\psi$ events accumulated at the BESIII
dector offers a unique opportunity to investigate $\eta$ and $\eta^\prime$
physics via two body $J/\psi$ radiative or hadronic decays. In recent years the
BESIII experiment has made significant progresses in $\eta/\eta^\prime$ decays.
A selection of recent highlights in light meson spectroscopy at BESIII are
reviewed in this report, including the observation of
$\eta^\prime\rightarrow\pi^+\pi^-\mu^+\mu^-$, the study of
$\eta^\prime\rightarrow\pi^+\pi^-e^+e^-$, and search for $CP$-violation in this
decay, search for the rare decays of $\eta^\prime\rightarrow4\pi^0$ and
$\eta^\prime\rightarrow\gamma\gamma\eta$, as well as the precision measurement
of the branching fraction of $\eta^\prime$ decays.


  Biological neural networks operate in the presence of task disruptions as
they guide organisms toward goals. A familiar stream of stimulus-response
causations can be disrupted by subtask streams imposed by the environment. For
example, taking a familiar path to a foraging area might be disrupted by the
presence of a predator, necessitating a "detour" to the area. The detour can be
a known alternative path that must be dynamically composed with the original
path to accomplish the overall task. In this project, overarching base paths
are disrupted by independently learned path modules in the form of insertion,
substitution, and deletion modifications to the base paths such that the
resulting modified paths are novel to the network. The network's performance is
then tested on these paths that have been learned in piecemeal fashion. In sum,
the network must compose a new task on the fly. Several network architectures
are tested: Time delay neural network (TDNN), Long short-term memory (LSTM),
Temporal convolutional network (TCN), and Morphognosis, a hierarchical neural
network. LSTM and Morphognosis perform significantly better for this task.


  A monitoring programme of CSS 121005:212625+201948 covering nearly two
observing seasons has shown that it is a typical SU UMa dwarf nova, but it has
one of the shortest supercycles of its class, at 66.9(6) d. The superoutbursts
are interspersed with 3 to 7 short duration (~2 days) normal outbursts each of
which are separated by a mean interval of 11 days, but can be as short as 2
days. The most intensively studied superoutburst was that of 2014 November,
which lasted 14 days and had an outburst amplitude of >4.8 magnitudes, reaching
magnitude 15.7 at its brightest. Time resolved photometry revealed superhumps
with a peak-to-peak amplitude of 0.2 magnitudes, later declining to 0.1
magnitude. The superhump period was Psh = 0.08838(18) d. Time resolved
photometry was conducted during several other superoutbursts, which gave
broadly similar results.


  Index coding is often studied with the assumption that a single source has
all the messages requested by the receivers. We refer to this as
\emph{centralized} index coding. In contrast, this paper focuses on
\emph{distributed} index coding and addresses the following question: How does
the availability of messages at distributed sources (storage nodes) affect the
solutions and achievable rates of index coding? An extension to the work of
Arbabjolfaei et al. in ISIT 2013 is presented when distributed sources
communicate via a semi-deterministic multiple access channel (MAC) to
simultaneous receivers. A numbers of examples are discussed that show the
effect of message distribution and redundancy across the network on achievable
rates of index coding and motivate future research on designing practical
network storage codes that offer high index coding rates.


  In a recent publication a procedure was developed which can be used to derive
completely gauge invariant models from general Lagrangian densities with $N$
order of derivatives and $M$ rank of tensor potential. This procedure was then
used to show that unique models follow for each order, namely classical
electrodynamics for $N = M = 1$ and linearized Gauss-Bonnet gravity for $N = M
= 2$. In this article, the nature of the connection between these two well
explored physical models is further investigated by means of an additional
common property; a complete dual formulation. First we give a review of
Gauss-Bonnet gravity and the dual formulation of classical electrodynamics. The
dual formulation of linearized Gauss-Bonnet gravity is then developed. It is
shown that the dual formulation of linearized Gauss-Bonnet gravity is analogous
to the homogenous half of Maxwell's theory; both have equations of motion
corresponding to the (second) Bianchi identity, built from the dual form of
their respective field strength tensors. In order to have a dually symmetric
counterpart analogous to the non-homogenous half of Maxwell's theory, the first
invariant derived from the procedure in $N = M = 2$ can be introduced. The
complete gauge invariance of a model with respect to Noether's first theorem,
and not just the equation of motion, is a necessary condition for this dual
formulation. We show that this result can be generalized to the higher spin
gauge theories, where the spin-$n$ curvature tensors for all $N = M = n$ are
the field strength tensors for each $n$. These completely gauge invariant
models correspond to the Maxwell-like higher spin gauge theories whose
equations of motion have been well explored in the literature.


  Continual learning (CL) in deep neural networks (DNNs) involves incrementally
accumulating knowledge in a DNN from a growing data stream. A major challenge
in CL is that non-stationary data streams cause catastrophic forgetting of
previously learned abilities. A popular solution is rehearsal: storing past
observations in a buffer and then sampling the buffer to update the DNN.
Uniform sampling in a class-balanced manner is highly effective, and better
sample selection policies have been elusive. Here, we propose a new sample
selection policy called GRASP that selects the most prototypical (easy) samples
first and then gradually selects less prototypical (harder) examples. GRASP has
little additional compute or memory overhead compared to uniform selection,
enabling it to scale to large datasets. Compared to 17 other rehearsal
policies, GRASP achieves higher accuracy in CL experiments on ImageNet.
Compared to uniform balanced sampling, GRASP achieves the same performance with
40% fewer updates. We also show that GRASP is effective for CL on five text
classification datasets.


  We consider GLq(N)-covariant quantum algebras with generators satisfying
quadratic polynomial relations. We show that, up to some inessential
arbitrariness, there are only two kinds of such quantum algebras, namely, the
algebras with q-deformed commutation and q-deformed anticommutation relations.
The connection with the bicovariant differential calculus on the linear quantum
groups is disscussed.


  We generalise Merzlyakov's theorem about the first-order theory of
non-abelian free groups to all acylindrically hyperbolic groups. As a
corollary, we deduce that if $G$ is an acylindrically hyperbolic group and
$E(G)$ denotes the unique maximal finite normal subgroup of $G$, then $G$ and
the HNN extension $G\dot{\ast}_{E(G)}$, which is simply the free product
$G\ast\mathbb{Z}$ when $E(G)$ is trivial, have the same
$\forall\exists$-theory. As a consequence, we prove the following conjecture,
formulated by Casals-Ruiz, Garreta and de la Nuez Gonz\'alez: acylindrically
hyperbolic groups have trivial positive theory. In particular, one recovers a
result proved by Bestvina, Bromberg and Fujiwara, stating that, with only the
obvious exceptions, verbal subgroups of acylindrically hyperbolic groups have
infinite width.


  We report the first measurements of inclusive W and Z cross sections times
leptonic branching ratios for p-pbar collisions at $\sqrt{s} = 1.96$ TeV, based
on their decays to electrons and muons. The data correspond to an integrated
luminosity of 72 pb-1 recorded with the CDF detector at the Fermilab Tevatron.
We test e-mu universality in W decays, and we measure the ratio of leptonic W
and Z rates from which the leptonic branching fraction $B(W\goto\ell\nu)$ can
be extracted as well as an indirect value for the total width of the W and the
CKM matrix element, Vcs.


  The last decade has witnessed a surge in the interaction of people through
social networking platforms. While there are several positive aspects of these
social platforms, the proliferation has led them to become the breeding ground
for cyber-bullying and hate speech. Recent advances in NLP have often been used
to mitigate the spread of such hateful content. Since the task of hate speech
detection is usually applicable in the context of social networks, we introduce
CRUSH, a framework for hate speech detection using user-anchored
self-supervision and contextual regularization. Our proposed approach secures ~
1-12% improvement in test set metrics over best performing previous approaches
on two types of tasks and multiple popular english social media datasets.


  We describe two algebraic solutions of the sixth Painlev\'e equation which
are related to (isomonodromic) deformations of Picard-Fuchs equations of order
two.


  Ensuring the ultra-low end-to-end latency and ultrahigh reliability required
by tactile internet is challenging. This is especially true when the stringent
Quality-of-Service (QoS) requirement is expected to be satisfied not at the
cost of significantly reducing spectral efficiency and energy efficiency (EE).
In this paper, we study how to maximize the EE for tactile internet under the
stringent QoS constraint, where both queueing delay and transmission delay are
taken into account. We first validate that the upper bound of queueing delay
violation probability derived from the effective bandwidth can be used to
characterize the queueing delay violation probability in the short delay regime
for Poisson arrival process. However, the upper bound is not tight for short
delay, which leads to conservative designs and hence leads to wasting energy.
To avoid this, we optimize resource allocation that depends on the queue state
information and channel state information. Analytical results show that with a
large number of transmit antennas the EE achieved by the proposed policy
approaches to the EE limit achieved for infinite delay bound, which implies
that the policy does not lead to any EE loss. Simulation and numerical results
show that even for not-so-large number of antennas, the EE achieved by the
proposed policy is still close to the EE limit.


  The Lowest Landau Level on a torus is studied. The dimension of the many-body
Hilbert space is obtained and is found to be different from the formula given
by Haldane. Our result can be tested in numerical investigations of the
low-energy spectrum of fractional quantum Hall states on a torus.


  Conflict-free Replicated Data Types (CRDTs) allow collaborative access to an
app's data. We describe a novel CRDT operation, for-each on the list of CRDTs,
and demonstrate its use in collaborative apps. Our for-each operation applies a
given mutation to each element of a list, including elements inserted
concurrently. This often preserves user intention in a way that would otherwise
require custom CRDT algorithms. We give example applications of our for-each
operation to collaborative rich-text, recipe, and slideshow editors.


  We consider the 2D Navier-Stokes equation on $\mathbb T \times \mathbb R$,
with initial datum that is $\varepsilon$-close in $H^N$ to a shear flow
$(U(y),0)$, where $\| U(y) - y\|_{H^{N+4}} \ll 1$ and $N>1$. We prove that if
$\varepsilon \ll \nu^{1/2}$, where $\nu$ denotes the inverse Reynolds number,
then the solution of the Navier-Stokes equation remains $\varepsilon$-close in
$H^1$ to $(e^{t \nu \partial_{yy}}U(y),0)$ for all $t>0$. Moreover, the
solution converges to a decaying shear flow for times $t \gg \nu^{-1/3}$ by a
mixing-enhanced dissipation effect, and experiences a transient growth of
gradients. In particular, this shows that the stability threshold in finite
regularity scales no worse than $\nu^{1/2}$ for 2D shear flows close to the
Couette flow.


  The spin-vector Monte Carlo model is widely used as a benchmark for the
classicality of quantum annealers but severely restricts the time evolution.
The spin-vector Langevin (SVL) model has been proposed and tested as an
alternative, closely reproducing the real-time dynamics of physical quantum
annealers such as D-Wave machines in the dissipative regime. We investigate the
SVL annealing dynamics of classical O(2) rotors on regular graphs, identifying
universal features in the nonequilibrium dynamics when changing the range of
interactions and the topology of the graph. Regular graphs with low connectance
or edge density exhibit universal scaling dynamics consistent with the
Kibble-Zurek mechanism, which leads to a power-law dependence of the density of
defects and the residual energy as a function of the annealing time. As the
interaction range is increased, the power-law scaling is suppressed, and an
exponential scaling with the annealing time sets in. Our results establish a
universal breakdown of the Kibble-Zurek mechanism in classical systems
characterized by long-range interactions, in sharp contrast with previous
findings in the quantum domain.


  We propose an effective method which can simplify the optimization of the
increase of the trace distance over all pairs of initial states in calculating
the non-Markovianity $\mathcal{N}$ for single channel open systems. For the
amplitude damping channel, we can unify the results of Breuer $et$ $al$. [Phys.
Rev. Lett. \bf 103\rm, 210401 (2009)] in the large-detuning case and the
results of Xu $et$ $al$. [Phys. Rev. A \bf 81\rm, 044105 (2010)] in the
resonant case; furthermore, for the general off-resonant cases we can obtain a
very tight lower bound of $\mathcal{N}$.
  As another application of our method, we also discuss $\mathcal{N}$ for the
non-Markovian depolarizing channel.


  We perform one of the first studies into the nonlinear evolution of tidally
excited inertial waves in a uniformly rotating fluid body, exploring a
simplified model of the fluid envelope of a planet (or the convective envelope
of a solar-type star) subject to the gravitational tidal perturbations of an
orbiting companion. Our model contains a perfectly rigid spherical core, which
is surrounded by an envelope of incompressible uniform density fluid. The
corresponding linear problem was studied in previous papers which this work
extends into the nonlinear regime, at moderate Ekman numbers (the ratio of
viscous to Coriolis accelerations). By performing high-resolution numerical
simulations, using a combination of pseudo-spectral and spectral element
methods, we investigate the effects of nonlinearities, which lead to
time-dependence of the flow and the corresponding dissipation rate. Angular
momentum is deposited non-uniformly, leading to the generation of significant
differential rotation in the initially uniformly rotating fluid, i.e. the body
does not evolve towards synchronism as a simple solid body rotator. This
differential rotation modifies the properties of tidally excited inertial
waves, changes the dissipative properties of the flow, and eventually becomes
unstable to a secondary shear instability provided that the Ekman number is
sufficiently small. Our main result is that the inclusion of nonlinearities
eventually modifies the flow and the resulting dissipation from what linear
calculations would predict, which has important implications for tidal
dissipation in fluid bodies. We finally discuss some limitations of our
simplified model, and propose avenues for future research to better understand
the tidal evolution of rotating planets and stars.


  Grover search is one of the most important quantum algorithms. In this paper,
we consider a kind of search that the conditions of satisfaction $T$ can be
rewritten as $T=T_1\bigcap T_2$. Then we present a new Grover search with
smaller oracles. The time complexity of this algorithm
$O(\frac{\pi}{4}\sqrt{\frac{N}{b\lambda}}+\frac{\pi}{4}\sqrt{\frac{b}{\tau}})$,
which is smaller than the time complexity of original Grover search, i.e.
$O(\frac{\pi}{4}\sqrt{\frac{N}{M}})$.