  Monocular depth prediction is an important task in scene understanding. It
aims to predict the dense depth of a single RGB image. With the development of
deep learning, the performance of this task has made great improvements.
However, two issues remain unresolved: (1) The deep feature encodes the wrong
farthest region in a scene, which leads to a distorted 3D structure of the
predicted depth; (2) The low-level features are insufficient utilized, which
makes it even harder to estimate the depth near the edge with sudden depth
change. To tackle these two issues, we propose the Boundary-induced and
Scene-aggregated network (BS-Net). In this network, the Depth Correlation
Encoder (DCE) is first designed to obtain the contextual correlations between
the regions in an image, and perceive the farthest region by considering the
correlations. Meanwhile, the Bottom-Up Boundary Fusion (BUBF) module is
designed to extract accurate boundary that indicates depth change. Finally, the
Stripe Refinement module (SRM) is designed to refine the dense depth induced by
the boundary cue, which improves the boundary accuracy of the predicted depth.
Several experimental results on the NYUD v2 dataset and \xff{the iBims-1
dataset} illustrate the state-of-the-art performance of the proposed approach.
And the SUN-RGBD dataset is employed to evaluate the generalization of our
method. Code is available at https://github.com/XuefengBUPT/BS-Net.


  In this work we propose a chemically-informed data-driven approach to
benchmark the approximate density-functional tight-binding (DFTB) excited state
(ES) methods that are currently available within the DFTB+ suite. By taking
advantage of the large volume of low-detail ES-data in the machine learning
(ML) dataset, QM8, we were able to extract valuable insights regarding the
limitations of the benchmarked methods in terms of the approximations made to
the parent formalism, density-functional theory (DFT), while providing
recommendations on how to overcome them. For this benchmark, we compared the
first singlet-singlet vertical excitation energies ($E_1$) predicted by the
DFTB-approximate methods with predictions of less approximate methods from the
reference ML-dataset. For the nearly 21,800 organic molecules in the GDB-8
chemical space, we were able to identify clear trends in the $E_1$ prediction
error distributions, with respect to second-order approximate coupled cluster
(CC2), showing a strong dependence on chemical identity.


  The increasing frequency of attacks on Android applications coupled with the
recent popularity of large language models (LLMs) necessitates a comprehensive
understanding of the capabilities of the latter in identifying potential
vulnerabilities, which is key to mitigate the overall risk. To this end, the
work at hand compares the ability of nine state-of-the-art LLMs to detect
Android code vulnerabilities listed in the latest Open Worldwide Application
Security Project (OWASP) Mobile Top 10. Each LLM was evaluated against an open
dataset of over 100 vulnerable code samples, including obfuscated ones,
assessing each model's ability to identify key vulnerabilities. Our analysis
reveals the strengths and weaknesses of each LLM, identifying important factors
that contribute to their performance. Additionally, we offer insights into
context augmentation with retrieval-augmented generation (RAG) for detecting
Android code vulnerabilities, which in turn may propel secure application
development. Finally, while the reported findings regarding code vulnerability
analysis show promise, they also reveal significant discrepancies among the
different LLMs.


  Various physical properties (electronic, optical and thermoelectric) of cubic
perovskite oxides $SrXO_3\; (X=Sc,\; Ge,\; Si)$ are investigated by using the
density functional theory (DFT) within Wien2k code. This code is based on
different approximations such as generalized gradient approximation GGA,
PBEsol, LDA, WC and the modified Becke-Johnson exchange potentials (mBJ, nmBJ
and unmBJ). Structural properties and the optimization have been calculated
using PBEsol functional which showed a significant results that are in good
agreement with the experimental ones. The results for physical properties such
as electronic, thermoelectric and optical are analyzed in detail by using the
nmBJ approximation. The obtained results present an opening gap for $SrSiO_3$,
$SrGeO_3$ and a metallic behavior for $SrScO_3$. An average of transmittance
which is about $94\%$ to $97\%$ was observed in the range of visible light. The
increase of electrical conductivity with temperature confirms the effect of
thermal agitation on the concentration of charges carriers using BolzTrap
Package. Lastly a phonon dispersion was made and show that for $X=\; Ge$ and
$Si$, the structure is relatively stable while $SrScO_3$ is dynamically
unstable. These results prove the ability that these materials can be exploited
in many applications and manufacturing of optoelectronics for Sensors.


  In this work, we present preliminary work on a novel method for Human-Swarm
Interaction (HSI) that can be used to change the macroscopic behavior of a
swarm of robots with decentralized sensing and control. By integrating a small
yet capable hand gesture recognition convolutional neural network (CNN) with
the next-generation Robot Operating System \emph{ros2}, which enables
decentralized implementation of robot software for multi-robot applications, we
demonstrate the feasibility of programming a swarm of robots to recognize and
respond to a sequence of hand gestures that capable of correspond to different
types of swarm behaviors. We test our approach using a sequence of gestures
that modifies the target inter-robot distance in a group of three Turtlebot3
Burger robots in order to prevent robot collisions with obstacles. The approach
is validated in three different Gazebo simulation environments and in a
physical testbed that reproduces one of the simulated environments.


  We show that closed 3-manifolds with high Heegaard distance and bounded
subsurface Heegaard distance are primitive stable when they are regarded as
representations from the free group corresponding to the handlebody. This
implies that any point on the boundary of Schottky space can be approximated by
primitive stable representations corresponding to closed hyperbolic
3-manifolds.


  We investigate the sums $(1/\sqrt{H}) \sum_{X < n \leq X+H} \chi(n)$, where
$\chi$ is a fixed non-principal Dirichlet character modulo a prime $q$, and $0
\leq X \leq q-1$ is uniformly random. Davenport and Erd\H{o}s, and more
recently Lamzouri, proved central limit theorems for these sums provided $H
\rightarrow \infty$ and $(\log H)/\log q \rightarrow 0$ as $q \rightarrow
\infty$, and Lamzouri conjectured these should hold subject to the much weaker
upper bound $H=o(q/\log q)$. We prove this is false for some $\chi$, even when
$H = q/\log^{A}q$ for any fixed $A > 0$. On the other hand, we show it is true
for "almost all" characters on the range $q^{1-o(1)} \leq H = o(q)$.
  Using P\'{o}lya's Fourier expansion, these results may be reformulated as
statements about the distribution of certain Fourier series with number
theoretic coefficients. Tools used in the proofs include the existence of
characters with large partial sums on short initial segments, and moment
estimates for trigonometric polynomials with random multiplicative
coefficients.


  I report two general methods to construct quantum convolutional codes for
$N$-state quantum systems. Using these general methods, I construct a quantum
convolutional code of rate 1/4, which can correct one quantum error for every
eight consecutive quantum registers.


  The one dimensional S=1/2 Heisenberg model with dimerization and
quadrumerization is studied by means of the numerical exact diagonalization of
finite size systems. Using the phenomenological renormalization group and
finite size scaling law, the ground state phase diagram is obtained in the
isotropic case. It exhibits a variety of the ground states which contains the
S=1 Haldane state, S=1 dimer state and S=1/2 dimer state as limiting cases. The
gap exponent $\nu$ is also calculated which coincides with the value for the
dimerization transition of the isotropic Heisenberg chain. In the XY limit, the
phase diagram is obtained analytically and the comparison is made with the
isotropic case.


  Probabilistic models are proposed for bounding the forward error in the
numerically computed inner product (dot product, scalar product) between of two
real $n$-vectors. We derive probabilistic perturbation bounds, as well as
probabilistic roundoff error bounds for the sequential accumulation of the
inner product. These bounds are non-asymptotic, explicit, and make minimal
assumptions on perturbations and roundoffs.
  The perturbations are represented as independent, bounded, zero-mean random
variables, and the probabilistic perturbation bound is based on Azuma's
inequality. The roundoffs are also represented as bounded, zero-mean random
variables. The first probabilistic bound assumes that the roundoffs are
independent, while the second one does not. For the latter, we construct a
Martingale that mirrors the sequential order of computations.
  Numerical experiments confirm that our bounds are more informative, often by
several orders of magnitude, than traditional deterministic bounds -- even for
small vector dimensions~$n$ and very stringent success probabilities. In
particular the probabilistic roundoff error bounds are functions of $\sqrt{n}$
rather than~$n$, thus giving a quantitative confirmation of Wilkinson's
intuition. The paper concludes with a critical assessment of the probabilistic
approach.


  A new class of artificially structured materials called metamaterials makes
it possible to achieve electromagnetic properties that do not exist in nature.
In this paper we review the recent progress made in the area of optical
metamaterials. It was predicted that nanostructured metamaterials could provide
us with artificial magnetic response and negative refractive index at optical
frequencies. To date, optical metamagnetics have been already fabricated to
demonstrate artificial magnetic response in the infrared and across the entire
visible spectrum, while metamaterials showing negative refractive index, also
called negative index materials (NIM), have been demonstrated in the infrared
and at the border with the visible spectral range. Here we report the results
of a sample that displays NIM behavior for red light at a wavelength of 710 nm.
This is the shortest wavelength so far at which NIM behavior has been observed
for light (excluding a device built on surface plasmon polaritons). We also
discuss the fabrication challenges and the impact of fabrication limitations,
specifically surface roughness of the fabricated structures on the optical
properties of the metamaterials.


  We present near-infrared spectroscopy of the NGC 5128 supernova SN 2016adj in
the first 2 months following discovery. We report the detection of first
overtone carbon monoxide emission at $\sim58.2$ d after discovery, one of the
earliest detections of CO in an erupting supernova. We model the CO emission to
derive the CO mass, temperature and velocity, assuming both pure $^{12}$CO and
a composition that includes $^{13}$CO; the case for the latter is the isotopic
analyses of meteoritic grains, which suggest that core collapse supernovae can
synthesise significant amounts of $^{13}$C. Our models show that, while the CO
data are adequately explained by pure $^{12}$CO, they do not preclude the
presence of $^{13}$CO, to a limit of $^{12}$C/$^{13}$C $> 3$, the first
constraint on the $^{12}$C/$^{13}$C ratio determined from near-infrared
observations. We estimate the reddening to the object, and the effective
temperature from the energy distribution at outburst. We discuss whether the
ejecta of SN 2016adj may be carbon-rich, what the infrared data tell us about
the classification of this supernova, and what implications the early formation
of CO in supernovae may have for CO formation in supernovae in general.


  In analog to counterparts widely used in electronic circuits, all optical
non-reciprocal devices are basic building blocks for both classical and quantum
optical information processing. Approaching the fundamental limit of such
devices, where the propagation of a single photon exhibits a good
non-reciprocal characteristic, requires an asymmetric strong coupling between a
single photon and a matter. Unfortunately it has been not realized yet. Here,
we propose and experimentally realize a quantum non-reciprocity device with low
optical losses and a high isolation of larger than 14 dB based on the cold
atoms. Besides, the non-reciprocal transmission of a quantum qubit and
non-reciprocal quantum storage of a true single photon are also realized. All
results achieved would be very promising in building up quantum non-reciprocal
devices for quantum networks.


  Under structural conditions which are almost optimal, we derive a
quantitative version of boundary estimate then prove existence of solutions to
Dirichlet problem for a class of fully nonlinear elliptic equations on
Hermitian manifolds.


  We consider the mean field Fokker-Planck equation subject to nonlinear
no-flux boundary conditions, which necessarily arise when subjecting a system
of Brownian particles interacting via a pair potential in a bounded domain.
With the additional presence of an external potential $V_1$, we show, by
analysing the linearised Fokker-Planck operator, that the spectral properties
of the equilibrium densities can differ considerably when compared with
previous studies, e.g., with periodic boundary conditions. Amongst other mean
field models of complex many-body particle systems, we present numerical
experiments encompassing in a wide range of physical applications, including:
generalised exponential models (Gaussian, Morse); a Kuramoto model, for noisy
coupled oscillators; and an Onsager model for liquid crystals. We showcase our
results by using the numerical methods developed in the pseudospectral
collocation scheme 2DChebClass.


  We revisit the polaron-molecule transition in three-dimensional(3D) fermion
systems using the well-established variational approach. The molecule is found
to be intrinsically unstable against lowest-order particle-hole excitations,
and it can only approximate the ground state of impurity system with finite
total momentum in the strong coupling regime. The polaron-molecule transition
can therefore be reinterpreted as a first-order transition between single
impurity systems with different total momenta. Within certain interaction
window near their transition, both states appear as local minima in the
dispersion curve, indicating they can coexist in a realistic system. We have
further confirmed the polaron-molecule coexistence in the presence of a finite
impurity concentration and at low temperature, which directly leads to a smooth
polaron-molecule transition as observed in recent experiments of 3D ultracold
Fermi gases. Our results have provided an unambiguous physical picture for the
competition and conversion between polaron and molecule, and also shed light on
Fermi polaron properties in low dimensions.


  This paper examines the scientific performance of South Africa since 1994
(post-apartheid) until 2014 in comparisons with the rest of the world,
utilizing relative indicator. It provides a view over current standing of South
Africa in the scientific world as well as its temporal evolution after the
apartheid. This study focuses on four major aspects of scientific performance,
namely quantity, productivity, impact and quality, as the main attributes of
scientific perfomance on national level. These are measured by re-based
(relative) publication, publication per population or GDP, citations and
citations per publication respectively. The study focuses on scientific outputs
(in the form of papers published in peer-reviewed journals) and their impact
(measured by the citations they have received) to bring into a light a
homogeneous comprehension of South Africa's scientific performance in all these
four aspects. Indicators are adopted cautiously by considering the measures put
forward recently for scientometrics indicators and their usage in the long-term
comparisons studies. The temporal evolution of these indicators for South
Africa are discussed in the context of three major groups of countries, namely
African countries, developing countries, and developed (including BRICS)
countries. It aims to examine the process of transition of South Africa from a
developing world economy system into a knowledge-based and innovation-driven
one of the developed world. The study reveals that South Africa has shown
steady increase in its scientific performance during the studied period when
compared to the rest of the world. However, due to the increasing competition
from the other developing countries, South Africa's position stands the same
during this period, while countries such as China, Iran, Turkey and Malaysia
have shown great jump at least in the quantity of their scientific performance.


  SCYNet (SUSY Calculating Yield Net) is a tool for testing supersymmetric
models against LHC data. It uses neural network regression for a fast
evaluation of the profile likelihood ratio. Two neural network approaches have
been developed: one network has been trained using the parameters of the
11-dimensional phenomenological Minimal Supersymmetric Standard Model
(pMSSM-11) as an input and evaluates the corresponding profile likelihood ratio
within milliseconds. It can thus be used in global pMSSM-11 fits without time
penalty. In the second approach, the neural network has been trained using
model-independent signature-related objects, such as energies and particle
multiplicities, which were estimated from the parameters of a given new physics
model. While the calculation of the energies and particle multiplicities takes
up computation time, the corresponding neural network is more general and can
be used to predict the LHC profile likelihood ratio for a wider class of new
physics models.


  This article is intended as a kind of precursor to the document Geometry for
Post-primary School Mathematics, part of the Mathematics Syllabus for Junior
Certicate issued by the Irish National Council for Curriculum and Assessment in
the context of Project Maths.
  Our purpose is to place that document in the context of an overview of plane
geometry, touching on several important pedagogical and historical aspects, in
the hope that this will prove useful for teachers.


  We develop a theory to derive effective Floquet Hamiltonians in the weak
drive and low-frequency regime. We construct the theory in analogy with band
theory for electrons in a spatially-periodic and weak potential, such as occurs
in some crystalline materials. As a prototypical example, we apply this theory
to graphene driven by circularly polarized light of low intensity. We find an
analytic expression for the effective Floquet Hamiltonian in the low-frequency
regime which accurately predicts the quasienergy spectrum and the Floquet
states. Furthermore, we identify self-consistency as the crucial feature
effective Hamiltonians in this regime need to satisfy to achieve a high
accuracy. The method is useful in providing a realistic description of
off-resonant drives for multi-band solid state systems where light-induced
topological band structure changes are sought.


  This paper refines previous work by the first author. We study the question
of which links in the 3-sphere can be obtained as closures of a given
1-manifold in an unknotted solid torus in the 3-sphere (or genus-1 tangle) by
adjoining another 1-manifold in the complementary solid torus. We distinguish
between even and odd closures, and define even and odd versions of the Kauffman
bracket ideal. These even and odd Kauffman bracket ideals are used to obstruct
even and odd tangle closures. Using a basis of Habiro's for the even Kauffman
bracket skein module of the solid torus, we define bases for the even and odd
skein module of the solid torus relative to two points. These even and odd
bases allow us to compute a finite list of generators for the even and odd
Kauffman bracket ideals of a genus-1 tangle. We do this explicitly for three
examples. Furthermore, we use the even and odd Kauffman bracket ideals to
conclude in some cases that the determinants of all even/odd closures of a
genus-1 tangle possess a certain divisibility.


  The ability of robots to navigate through doors is crucial for their
effective operation in indoor environments. Consequently, extensive research
has been conducted to develop robots capable of opening specific doors.
However, the diverse combinations of door handles and opening directions
necessitate a more versatile door opening system for robots to successfully
operate in real-world environments. In this paper, we propose a mobile
manipulator system that can autonomously open various doors without prior
knowledge. By using convolutional neural networks, point cloud extraction
techniques, and external force measurements during exploratory motion, we
obtained information regarding handle types, poses, and door characteristics.
Through two different approaches, adaptive position-force control and deep
reinforcement learning, we successfully opened doors without precise trajectory
or excessive external force. The adaptive position-force control method
involves moving the end-effector in the direction of the door opening while
responding compliantly to external forces, ensuring safety and manipulator
workspace. Meanwhile, the deep reinforcement learning policy minimizes applied
forces and eliminates unnecessary movements, enabling stable operation across
doors with different poses and widths. The RL-based approach outperforms the
adaptive position-force control method in terms of compensating for external
forces, ensuring smooth motion, and achieving efficient speed. It reduces the
maximum force required by 3.27 times and improves motion smoothness by 1.82
times. However, the non-learning-based adaptive position-force control method
demonstrates more versatility in opening a wider range of doors, encompassing
revolute doors with four distinct opening directions and varying widths.


  We study mean convergence of multiple ergodic averages, where the iterates
arise from smooth functions of polynomial growth that belong to a Hardy field.
Our results include all logarithmico-exponential functions of polynomial
growth, such as the functions $t^{3/2}, t\log t$ and $e^{\sqrt{\log t}}$. We
show that if all non-trivial linear combinations of the functions $a_1,...,a_k$
stay logarithmically away from rational polynomials, then the $L^2$-limit of
the ergodic averages $\frac{1}{N}
\sum_{n=1}^{N}f_1(T^{\lfloor{a_1(n)}\rfloor}x)\cdots
f_k(T^{\lfloor{a_k(n)}\rfloor}x)$ exists and is equal to the product of the
integrals of the functions $f_1,...,f_k$ in ergodic systems, which establishes
a conjecture of Frantzikinakis. Under some more general conditions on the
functions $a_1,...,a_k$, we also find characteristic factors for convergence of
the above averages and deduce a convergence result for weak-mixing systems.


  In this paper, we consider nine OEIS sequences, the analysis of which allows
us to find a connection between Motzkin numbers and Fibonacci numbers. In each
Motzkin number, we distinguish an even component and an odd component, the
difference of these two components is called the shadow of the Motzkin number.
Reverse of the Motzkin shadows give us a sequence from the family of Fibonacci
numbers.


  We study the (M,sigma) and (M,Re) projections of the thin Mass Plane (MP)
(M,sigma,Re) which describes the distribution of the galaxy population. The
distribution of galaxy properties on the MP is characterized by: (i) a zone of
exclusion described by two power-laws joined by a break at M 3e10 Msun. This
results in a break in the mean M-sigma relation with Msigma^2.3 and M sigma^4.7
at small and large sigma respectively; (ii) a mass M 2e11 Msun which separates
a population dominated by flat fast rotator with disks and spiral galaxies at
lower masses, from one dominated by quite round slow rotators at larger masses;
(iii) below that mass the distribution of ETGs properties tends to be constant
along lines of constant sigma; (iv) it forms a parallel sequence with the
distribution of spiral galaxies; (v) at even lower masses, the distribution of
fast rotator ETGs and late spirals naturally extends to that of dwarf ETGs
(Sph) and dwarf irregulars (Im) respectively. We show via dynamical models that
sigma traces the bulge fraction, which drives the observed trends in M/L,
Hbeta, colour, IMF and molecular gas fraction. We interpret this as due to a
combination of two main effects: (i) an increase of the bulge fraction which
increases sigma and greatly enhances the likelihood for a galaxy to have its
star formation quenched, and (ii) dry merging, increasing galaxy mass along
lines of nearly constant sigma, while leaving the population unchanged.
[Abriged]


  In this note, starting with any group homomorphism $f\colon\Gamma\to G$,
which is surjective upon abelianization, we construct a universal central
extension $u\colon U\twoheadrightarrow G,$ UNDER $\Gamma$ with the same
surjective property, such that for any central extension $m\colon
M\twoheadrightarrow G,$ under $f,$ there is a unique homomorphism $U\to M$ with
the obvious commutation condition. The kernel of $u$ is the relative Schur
multiplier group $H_2(G,\Gamma;\mathbb{Z})$ as defined in the paper. The case
where $G$ is perfect corresponds to $\Gamma=1$. This yields homological
obstructions to lifting solution of equations in $G.$ Upon repetition, for
finite groups, this gives a universal hypercentral factorization of the map
$f\colon\Gamma\to G$.


  Work extraction from the Gibbs ensemble by a cyclic operation is impossible,
as represented by the second law of thermodynamics. On the other hand, the
eigenstate thermalization hypothesis (ETH) states that just a single energy
eigenstate can describe a thermal equilibrium state. Here we attempt to unify
these two perspectives and investigate the second law at the level of
individual energy eigenstates, by examining the possibility of extracting work
from a single energy eigenstate. Specifically, we performed numerical exact
diagonalization of a quench protocol of local Hamiltonians and evaluated the
number of work-extractable energy eigenstates. We found that it becomes exactly
zero in a finite system size, implying that a positive amount of work cannot be
extracted from any energy eigenstate, if one or both of the pre- and the
post-quench Hamiltonians are non-integrable. We argue that the mechanism behind
this numerical observation is based on the ETH for a non-local observable. Our
result implies that quantum chaos, characterized by non-integrability, leads to
a stronger version of the second law than the conventional formulation based on
the statistical ensembles.


  We study the combinatorial function $L(k,q),$ the maximum number of nonzero
weights a linear code of dimension $k$ over $\F_q$ can have. We determine it
completely for $q=2,$ and for $k=2,$ and provide upper and lower bounds in the
general case when both $k$ and $q$ are $\ge 3.$ A refinement $L(n,k,q),$ as
well as nonlinear analogues $N(M,q)$ and $N(n,M,q),$ are also introduced and
studied.


  A new method is developed for estimating photometric redshifts to galaxies,
using realistic template SEDs, extending over four decades in wavelength (i.e.
from 0.05 micron to 1 mm). The template SEDs are constructed for four different
spectral types of galaxies (elliptical, spiral, irregular and starburst),
satisfying the following characteristics: a). they are normalised to produce
the observed colours of galaxies at z ~ 0; b). incorporate the
chemo-photometric spectral evolution of galaxies of different types, in
agreement with the observations; c). allow treatment of dust contribution and
its evolution with redshift, consistent with the spectral evolution model; d).
include absorption and re-emission of radiation by dust and hence, realistic
estimates of the far-infrared radiation; e). include correction for
inter-galactic absorption by Lyman continuum and Lyman forest. Using these
template SEDs, the photometric redshifts are estimated to an accuracy of ~
0.11. The effect on the estimated photometric redshifts, due to assumptions in
the evolutionary population synthesis models, are investigated and discussed.
  The simultaneous and self-consistent modelling of both the photometric and
chemical evolution of galaxies and the effect of dust, makes this technique
particularly useful for high redshift galaxies. Moreover, since the template
SEDs (at different redshifts) cover the range from UV to far-infrared and
sub-mm wavelengths, one could consistently use the optimised SEDs to estimate
the contribution from individual galaxies to these wavelengths, where no
observational data are available.


  We prove that if a non-selfadjoint dual operator algebra admitting a normal
virtual diagonal and an injective von Neumann algebra are close enough for the
Kadison-Kastler's metric, then they are similar. The bound explicitly depends
on the norm of the normal virtual diagonal. This is inspired from E.
Christensen's work on perturbation of operator algebras.


  Description logic programs (dl-programs) under the answer set semantics
formulated by Eiter {\em et al.} have been considered as a prominent formalism
for integrating rules and ontology knowledge bases. A question of interest has
been whether dl-programs can be captured in a general formalism of nonmonotonic
logic. In this paper, we study the possibility of embedding dl-programs into
default logic. We show that dl-programs under the strong and weak answer set
semantics can be embedded in default logic by combining two translations, one
of which eliminates the constraint operator from nonmonotonic dl-atoms and the
other translates a dl-program into a default theory. For dl-programs without
nonmonotonic dl-atoms but with the negation-as-failure operator, our embedding
is polynomial, faithful, and modular. In addition, our default logic encoding
can be extended in a simple way to capture recently proposed weakly
well-supported answer set semantics, for arbitrary dl-programs. These results
reinforce the argument that default logic can serve as a fruitful foundation
for query-based approaches to integrating ontology and rules. With its simple
syntax and intuitive semantics, plus available computational results, default
logic can be considered an attractive approach to integration of ontology and
rules.


  Non-negative matrix factorization (NMF) is one of the most popular
decomposition techniques for multivariate data. NMF is a core method for many
machine-learning related computational problems, such as data compression,
feature extraction, word embedding, recommender systems etc. In practice,
however, its application is challenging for large datasets. The efficiency of
NMF is constrained by long data loading times, by large memory requirements and
by limited parallelization capabilities. Here we present a novel and efficient
compressed NMF algorithm. Our algorithm applies a random compression scheme to
drastically reduce the dimensionality of the problem, preserving well the
pairwise distances between data points and inherently limiting the memory and
communication load. Our algorithm supersedes existing methods in speed.
Nonetheless, it matches the best non-compressed algorithms in reconstruction
precision.


  Single particle tracking is essential in many branches of science and
technology, from the measurement of biomolecular forces to the study of
colloidal crystals. Standard current methods rely on algorithmic approaches: by
fine-tuning several user-defined parameters, these methods can be highly
successful at tracking a well-defined kind of particle under low-noise
conditions with constant and homogenous illumination. Here, we introduce an
alternative data-driven approach based on a convolutional neural network, which
we name DeepTrack. We show that DeepTrack outperforms algorithmic approaches,
especially in the presence of noise and under poor illumination conditions. We
use DeepTrack to track an optically trapped particle under very noisy and
unsteady illumination conditions, where standard algorithmic approaches fail.
We then demonstrate how DeepTrack can also be used to track multiple particles
and non-spherical objects such as bacteria, also at very low signal-to-noise
ratios. In order to make DeepTrack readily available for other users, we
provide a Python software package, which can be easily personalized and
optimized for specific applications.


  The article presents four identities containing the spatio-temporal
differential operator also known as four-divergence. These equations are used
to prove the invariance of wave equation under orthogonal paravector
transformations. Moreover, the transformation of equations containing
spatio-temporal differential operators under the rotation of reference frame
has been presented.


  GN-z11 is an unusually luminous high redshift galaxy which was recently
observed to have strong nitrogen lines while at the same time lacking
traditional signatures of AGN activity. These observations have been
interpreted as a super-solar nitrogen abundance which is challenging to explain
with standard stellar evolution and supernovae enrichment. We present
simulations of four models of metal enriched supermassive stars after the zero
age main sequence which produce super-solar nitrogen consistent with the
observations of GN-z11. We then show that the most massive model ends its life
in a violent explosion which results in even greater nitrogen pollution.


  The X-ray data of A2029 obtained with XMM-Newton show no evidence of an
embedded AGN in the central region of this cluster, which was suggested from
the analysis of restored ASCA image data, although some hot spots are seen
within or around the central cD galaxy. The absence of AGN at the cluster
center is consistentent with the result of Chandra observations. Radial
profiles of the iron abundance and the 2D (surface) temperature obtained from
the XMM-Newton data are in good agreement with the Chandra data as a whole.


  Following an idea of Hopkins, we construct a model of the determinant sphere
$S\langle det \rangle$ in the category of $K(n)$-local spectra. To do this, we
build a spectrum which we call the Tate sphere $S(1)$. This is a $p$-complete
sphere with a natural continuous action of $\mathbb{Z}_p^\times$. The Tate
sphere inherits an action of $\mathbb{G}_n$ via the determinant and smashing
Morava $E$-theory with $S(1)$ has the effect of twisting the action of
$\mathbb{G}_n$. A large part of this paper consists of analyzing continuous
$\mathbb{G}_n$-actions and their homotopy fixed points in the setup of Devinatz
and Hopkins.


  We explore the electromagnetic field coupled to a mechanical resonator via
quadratic optomechanical interaction in the reversed dissipation regime where
the mechanical damping rate is much larger than the cavity field dissipation
rate. It is shown that in this regime, the cavity field effectively acquires an
additional reservoir which is conditioned by the temperature of the mechanical
bath as well as the mechanical damping rate. We analytically find the
steady-state mean photon number and the critical temperature of the mechanical
oscillator to cool or heat the coupled electromagnetic field. We also show that
in the case of quadratic coupling, the temperature of the mechanical oscillator
can be estimated in the quantum regime by observing the noise spectrum of the
cavity field.


  Resource allocation and task prioritisation are key problem domains in the
fields of autonomous vehicles, networking, and cloud computing. The challenge
in developing efficient and robust algorithms comes from the dynamic nature of
these systems, with many components communicating and interacting in complex
ways. The multi-group resource allocation optimisation (MG-RAO) algorithm we
present uses multiple function approximations of resource demand over time,
alongside reinforcement learning techniques, to develop a novel method of
optimising resource allocation in these multi-agent systems. This method is
applicable where there are competing demands for shared resources, or in task
prioritisation problems. Evaluation is carried out in a simulated environment
containing multiple competing agents. We compare the new algorithm to an
approach where child agents distribute their resources uniformly across all the
tasks they can be allocated. We also contrast the performance of the algorithm
where resource allocation is modelled separately for groups of agents, as to
being modelled jointly over all agents. The MG-RAO algorithm shows a 23 - 28%
improvement over fixed resource allocation in the simulated environments.
Results also show that, in a volatile system, using the MG-RAO algorithm
configured so that child agents model resource allocation for all agents as a
whole has 46.5% of the performance of when it is set to model multiple groups
of agents. These results demonstrate the ability of the algorithm to solve
resource allocation problems in multi-agent systems and to perform well in
dynamic environments.


  Decoherence of the 795 nm $^3$H$_6$ to $^3$H$_4$ transition in
1%Tm$^{3+}$:Y$_3$Ga$_5$O$_{12}$ (Tm:YGG) is studied at temperatures as low as
1.2 K. The temperature, magnetic field, frequency, and time-scale (spectral
diffusion) dependence of the optical coherence lifetime is measured. Our
results show that the coherence lifetime is impacted less by spectral diffusion
than other known thulium-doped materials. Photon echo excitation and spectral
hole burning methods reveal uniform decoherence properties and the possibility
to produce full transparency for persistent spectral holes across the entire 56
GHz inhomogeneous bandwidth of the optical transition. Temperature-dependent
decoherence is well described by elastic Raman scattering of phonons with an
additional weaker component that may arise from a low density of glass-like
dynamic disorder modes (two-level systems). Analysis of the observed behavior
suggests that an optical coherence lifetime approaching one millisecond may be
possible in this system at temperatures below 1 K for crystals grown with
optimized properties. Overall, we find that Tm:YGG has superior decoherence
properties compared to other Tm-doped crystals and is a promising candidate for
applications that rely on long coherence lifetimes, such as optical quantum
memories and photonic signal processing.


  We consider a circular string in $\hat{\gamma}$ deformed $AdS_5 \times
T^{1,1}$ which is localized in the center of $AdS_5$ and winds around the two
circles of deformed $T^{1,1}$. We observe chaos in the phase space of the
circular string implying non-integrability of string dynamics. The chaotic
behaviour in phase space is controlled by energy as well as the deforming
parameter $\hat{\gamma}$. We further show that the point like object exhibits
non-chaotic behaviour. Finally we calculate the Lyapunov exponent for both
extended and point like object in support of our first result.


  Computing a shortest path between two nodes in an undirected unweighted graph
is among the most basic algorithmic tasks. Breadth first search solves this
problem in linear time, which is clearly also a lower bound in the worst case.
However, several works have shown how to solve this problem in sublinear time
in expectation when the input graph is drawn from one of several classes of
random graphs. In this work, we extend these results by giving sublinear time
shortest path (and short path) algorithms for expander graphs. We thus identify
a natural deterministic property of a graph (that is satisfied by typical
random regular graphs) which suffices for sublinear time shortest paths. The
algorithms are very simple, involving only bidirectional breadth first search
and short random walks. We also complement our new algorithms by near-matching
lower bounds.


  Stochastic features of decay of a metastable phase have been investigated
with the help of a new monodisperse approximation. This approximation is more
precise than the already used one and namely it allows to give a very simple
but rather precise way to calculate dispersion of the total droplets number
initiated by stochastic appearance of supercritical embryos. The derivation is
done for a free molecular regime of droplets growth but the diffusion regime is
also discussed.


  Entanglement entropy is a statistical entropy measuring information loss due
to coarse-graining corresponding to a spatial division of a system. In this
paper we construct a thermodynamics (entanglement thermodynamics) which
includes the entanglement entropy as the entropy variable, for a massless
scalar field in Minkowski, Schwarzschild and Reissner-Nordstr{\"o}m spacetimes
to understand the statistical origin of black-hole thermodynamics. It is shown
that the entanglement thermodynamics in Minkowski spacetime differs
significantly from black-hole thermodynamics. On the contrary, the entanglement
thermodynamics in Schwarzschild and Reissner-Nordstr{\"o}m spacetimes has close
relevance to black-hole thermodynamics.


  By developing the method of multipliers, we establish sufficient conditions
on the magnetic field and the complex, matrix-valued electric potential, which
guarantee that the corresponding system of Schr\"odinger operators has no point
spectrum. In particular, this allows us to prove analogous results for Pauli
operators under the same electromagnetic conditions and, in turn, as a
consequence of the supersymmetric structure, also for magnetic Dirac operators.


  This paper deals with the two-species chemotaxis-competition models
\begin{align*}
  \begin{cases}
  u_t = d_1 \Delta u
  - \chi_1 \nabla \cdot (u \nabla w)
  + \mu_1 u (1- u^{\kappa_1-1} - a_1 v^{\lambda_1-1}),
  &\quad x \in \Omega,\ t>0,\\ %
  v_t = d_2 \Delta v
  - \chi_2 \nabla \cdot (v \nabla w)
  + \mu_2 v (1- a_2 u^{\lambda_2-1} - v^{\kappa_2-1}),
  &\quad x \in \Omega,\ t>0,\\ %
  0 = d_3 \Delta w + \alpha u + \beta v - h(u,v,w),
  &\quad x \in \Omega,\ t>0,
  \end{cases}
  \end{align*} where $\Omega \subset \mathbb{R}^n$ $(n\ge2)$ is a bounded
domain with smooth boundary, and $h=\gamma w$ or
$h=\frac{1}{|\Omega|}\int_\Omega(\alpha u+ \beta v)\,dx$. In the case that
$\kappa_1=\lambda_1=\kappa_2=\lambda_2=2$ and $h=\gamma w$, it is known that
smallness conditions for the chemotacic effects lead to boundedness of
solutions (Math.\ Methods Appl.\ Sci.; 2018; 41; 234--249). However, the case
that the chemotactic effects are large seems not to have been studied yet;
therefore it remains to consider the question whether the solution is bounded
also in the case that the chemotactic effects are large. The purpose of this
paper is to give a negative answer to this question.


  Color Transparency refers to the vanishing of the hadron-nucleon interaction
for hadrons produced inside a nucleus in high momentum exclusive processes. We
briefly review the concept behind this unique Quantum Chromo Dynamics'
phenomenon, the experimental search for its onset and the recent progress made
at intermediate energies.


  High degree of preservation of spin states during energy relaxation processes
mediated by optical phonons is demonstrated in a single quantum dot.
Optical-phonon resonance and relevant suppression of spin relaxation are
clearly identified as dip structures in photoluminescence excitation spectra
probed by the positive trion emission. The absence of continuum states makes
this observation possible under the cross-circularly polarized detection with
respect to a circularly polarized pumping. Consequently, distinguishably high
degree of circular polarization up to ~0.85 is achieved without applying
external magnetic field at the optical-phonon resonance. Rate equation analysis
reveals that the spin-flip probability during energy relaxation is restricted
to less than 7.5%. It is also indicated that the spin flip time of the positive
trion ground state is extended by more than 3 times compared with that of
neutral exciton ground state. This corresponds to the spin flip time longer
than 11 ns for the positive trion ground state. The influence of nuclear
polarization to the present measurements is also discussed.


  Phosphorus-bearing compounds have only been studied in the circumstellar
environments (CSEs) of the asymptotic giant branch (AGB) star IRC +10216 and
the protoplanetary nebula CRL 2688, both C-rich objects, and the O-rich red
supergiant VY CMa. The current chemical models cannot reproduce the high
abundances of PO and PN derived from observations of VY CMa. No observations
have been reported of phosphorus in the CSEs of O-rich AGB stars. We aim to set
observational constraints on the phosphorous chemistry in the CSEs of O-rich
AGB stars, by focussing on the Mira-type variable star IK Tau. Using the IRAM
30m telescope and the Submillimeter Array (SMA), we observed four rotational
transitions of PN (J=2-1,3-2,6-5,7-6) and four of PO
(J=5/2-3/2,7/2-5/2,13/2-11/2,15/2-13/2). The IRAM 30m observations were
dedicated line observations, while the SMA data come from an unbiased spectral
survey in the frequency range 279-355 GHz.
  We present the first detections of PN and PO in an O-rich AGB star and
estimate abundances X(PN/H2) of about 3x10^-7 and X(PO/H2) in the range
0.5-6.0x10^-7. This is several orders of magnitude higher than what is found
for the C-rich AGB star IRC +10216. The diameter (<=0.7") of the PN and PO
emission distributions measured in the interferometric data corresponds to a
maximum radial extent of about 40 stellar radii. The abundances and the spatial
occurrence of the molecules are in very good agreement with the results
reported for VY CMa. We did not detect PS or PH3 in the survey. We suggest that
PN and PO are the main carriers of phosphorus in the gas phase, with abundances
possibly up to several 10^-7. The current chemical models cannot account for
this, underlining the strong need for updated chemical models that include
phosphorous compounds.


  E865 at the Brookhaven National Laboratory AGS collected about 70,000 K+(e3)
events with the purpose of measuring the relative K+(e3) branching ratio. The
pi0 in all the decays was detected using the e+e- pair from pi0 -> e+e-gamma
decay and no photons were required. Using the Particle Data Group branching
ratios for the normalization decays we obtain
BR(K+(e3(gamma))=(5.13+/-0.02(stat)+/-0.09(sys)+/-0.04(norm))%, where
$K+(e3(gamma)) includes the effect of virtual and real photons. This result is
2.3 sigma higher than the current Particle Data Group value. The implications
of this result for the $V_{us}$ element of the CKM matrix, and the matrix's
unitarity are discussed.


  We investigate statistical properties of Cluster-Weighted Modeling, which is
a framework for supervised learning originally developed in order to recreate a
digital violin with traditional inputs and realistic sound. The analysis is
carried out in comparison with Finite Mixtures of Regression models. Based on
some geometrical arguments, we highlight that Cluster-WeightedModeling provides
a quite general framework for local statistical modeling. Theoretical results
are illustrated on the ground of some numerical simulations.


  We study by simulation and theory how the addition of insulating spherical
particles affects the conductivity of fluids of conducting rods, modeled by
spherocylinders. The electrical connections are implemented as tunneling
processes, leading to a more detailed and realistic description than a
discontinuous percolation approach. We find that the spheres enhance the
tunneling conductivity for a given concentration of rods and that the
enhancement increases with rod concentration into the regime where the
conducting network is well established. By reformulating the network of rods
using a critical path analysis, we quantify the effect of depletion-induced
attraction between the rods due to the spheres. Furthermore, we show that our
conductivity data are quantitatively reproduced by an effective medium
approximation, which explicitly relates the system tunneling conductance to the
structure of the rod-sphere fluid.


  We argue that the vacuum polarization by the virtual electron-positron pairs
can be measured by studying a Josephson junction in a strong magnetic field.
The vacuum polarization results in a weak dependence of the Josephson constant
on the magnetic field strength which is within the reach of the existing
experimental techniques.


  Variational data assimilation optimizes for an initial state of a dynamical
system such that its evolution fits observational data. The physical model can
subsequently be evolved into the future to make predictions. This principle is
a cornerstone of large scale forecasting applications such as numerical weather
prediction. As such, it is implemented in current operational systems of
weather forecasting agencies across the globe. However, finding a good initial
state poses a difficult optimization problem in part due to the non-invertible
relationship between physical states and their corresponding observations. We
learn a mapping from observational data to physical states and show how it can
be used to improve optimizability. We employ this mapping in two ways: to
better initialize the non-convex optimization problem, and to reformulate the
objective function in better behaved physics space instead of observation
space. Our experimental results for the Lorenz96 model and a two-dimensional
turbulent fluid flow demonstrate that this procedure significantly improves
forecast quality for chaotic systems.


  Extracting cultivated land accurately from high-resolution remote images is a
basic task for precision agriculture. This report introduces our solution to
the iFLYTEK challenge 2021 cultivated land extraction from high-resolution
remote sensing image. The challenge requires segmenting cultivated land objects
in very high-resolution multispectral remote sensing images. We established a
highly effective and efficient pipeline to solve this problem. We first divided
the original images into small tiles and separately performed instance
segmentation on each tile. We explored several instance segmentation algorithms
that work well on natural images and developed a set of effective methods that
are applicable to remote sensing images. Then we merged the prediction results
of all small tiles into seamless, continuous segmentation results through our
proposed overlap-tile fusion strategy. We achieved the first place among 486
teams in the challenge.


  A vortex-lattice method for wing aerodynamics that uses nonlinear airfoil
data is presented. Two applications of this procedure are presented: Direct
Design of a Flying Wing and Inverse Identification from wind tunnel
measurements with low-aspect ratio wings. A Newton method is employed, which
not only allows very fast solutions to the nonlinear equations but enables the
calculation of static and dynamic stability and control derivatives without
further cost.


  In this paper we deal with aspects of transverse polarization for the purpose
of energy calibration of proposed circular colliders like the FCC-ee and the
CEPC. The main issues of such a measurement will be discussed. The possibility
of using this method to accurately determine the energy at the WW threshold as
well as the Z peak will be addressed. The use of wigglers for reducing long
polarization times will be discussed and a possible strategy will be presented
for minimising the energy uncertainty error in these large machines.


  In this work, we investigate the quantum phase transition in a non-Hermitian
XY spin chain. The phase diagram shows that the critical points of Ising phase
transition expand into a critical transition zone after introducing a
non-Hermitian effect. By analyzing the non-Hermitian gap and long-range
correlation function, one can distinguish different phases by means of
different gap features and decay properties of correlation function, a tricky
problem in traditional XY model. Furthermore, the results reveal the
relationship among different regions of the phase diagram, non-Hermitian energy
gap and long-range correlation function.


  A general method is presented for determining the maximum electric energy in
a bounded region of optical fields with given time-averaged flux of
electromagnetic energy. Time-harmonic fields are considered whose plane wave
expansion consists of propagating plane waves only, i.e., evanescent waves are
excluded. The bounded region can be quite general: it can consist of finitely
many points, or be a curve, a curved surface or a bounded volume. The optimum
optical field is eigenfield corresponding to the maximum eigenvalue of a
compact linear integral operator which depends on the bounded region. It is
explained how these optimum fields can be realized by focusing appropriate
pupil fields. The special case that the region is a circular disc perpendicular
to the direction of optical axis is investigated by numerical simulations.


  In recent years, deep learning has surpassed traditional approaches to the
problem of singing voice separation. The Wave-U-Net is a recent deep network
architecture that operates directly on the time domain. The standard Wave-U-Net
is trained with data augmentation and early stopping to prevent overfitting.
Minimum hyperspherical energy (MHE) regularization has recently proven to
increase generalization in image classification problems by encouraging a
diversified filter configuration. In this work, we apply MHE regularization to
the 1D filters of the Wave-U-Net. We evaluated this approach for separating the
vocal part from mixed music audio recordings on the MUSDB18 dataset. We found
that adding MHE regularization to the loss function consistently improves
singing voice separation, as measured in the Signal to Distortion Ratio on test
recordings, leading to the current best time-domain system for singing voice
extraction.


  A new functional model for pairs of commuting isometries is described.
Intertwining operators between such models are then studied in order to
approach the classification of invariant subspaces of such pairs.


  We treat two different topics on the log minimal model program, especially
for four-dimensional log canonical pairs. (a) Finite generation of the log
canonical ring in dimension four. (b) Abundance theorem for irregular
fourfolds. We obtain (a) as a direct consequence of the existence of
four-dimensional log minimal models by using Fukuda's theorem on the
four-dimensional log abundance conjecture. We can prove (b) only by using
traditional arguments. More precisely, we prove the abundance conjecture for
irregular $(n+1)$-folds on the assumption that the minimal model conjecture and
the abundance conjecture hold in dimension $\leq n$.


  Micro unmanned aerial vehicles (mUAV) became very common in recent years. As
a result of their widespread usage, when they are flown by hobbyists illegally,
crucial risks are imposed and such mUAVs need to be sensed by security systems.
Furthermore, the sensing of mUAVs are essential for also swarm robotics
research where the individuals in a flock of robots require systems to sense
and localize each other for coordinated operation. In order to obtain such
systems, there are studies to detect mUAVs utilizing different sensing mediums,
such as vision, infrared and sound signals, and small-scale radars. However,
there are still challenges that awaits to be handled in this field such as
integrating tracking approaches to the vision-based detection systems to
enhance accuracy and computational complexity. For this reason, in this study,
we combine various tracking approaches to a vision-based mUAV detection system
available in the literature, in order to evaluate different tracking approaches
in terms of accuracy and as well as investigate the effect of such integration
to the computational cost.


  Analytical and numerical results, for the orbital and spin content carried by
different quark flavors in the baryons, are given in the chiral quark model
with symmetry breaking. The reduction of the quark spin, due to the spin
dilution in the chiral splitting processes, is transferred into the orbital
motion of quarks and antiquarks. The orbital angular momentum for each quark
flavor in the proton as a function of the partition factor $\kappa$ and the
chiral splitting probability $a$ is shown. The cancellation between the spin
and orbital contributions in the spin sum rule and in the baryon magnetic
moments is discussed.


  Model substructure learning aims to find an invariant network substructure
that can have better out-of-distribution (OOD) generalization than the original
full structure. Existing works usually search the invariant substructure using
modular risk minimization (MRM) with fully exposed out-domain data, which may
bring about two drawbacks: 1) Unfairness, due to the dependence of the full
exposure of out-domain data; and 2) Sub-optimal OOD generalization, due to the
equally feature-untargeted pruning on the whole data distribution. Based on the
idea that in-distribution (ID) data with spurious features may have a lower
experience risk, in this paper, we propose a novel Spurious Feature-targeted
model Pruning framework, dubbed SFP, to automatically explore invariant
substructures without referring to the above drawbacks. Specifically, SFP
identifies spurious features within ID instances during training using our
theoretically verified task loss, upon which, SFP attenuates the corresponding
feature projections in model space to achieve the so-called spurious
feature-targeted pruning. This is typically done by removing network branches
with strong dependencies on identified spurious features, thus SFP can push the
model learning toward invariant features and pull that out of spurious features
and devise optimal OOD generalization. Moreover, we also conduct detailed
theoretical analysis to provide the rationality guarantee and a proof framework
for OOD structures via model sparsity, and for the first time, reveal how a
highly biased data distribution affects the model's OOD generalization.
Experiments on various OOD datasets show that SFP can significantly outperform
both structure-based and non-structure-based OOD generalization SOTAs, with
accuracy improvement up to 4.72% and 23.35%, respectively


  Magnetic particle imaging (MPI) is a promising new in-vivo medical imaging
modality in which distributions of super-paramagnetic nanoparticles are tracked
based on their response in an applied magnetic field. In this paper we provide
a mathematical analysis of the modeled MPI operator in the univariate
situation. We provide a Hilbert space setup, in which the MPI operator is
decomposed into simple building blocks and in which these building blocks are
analyzed with respect to their mathematical properties. In turn, we obtain an
analysis of the MPI forward operator and, in particular, of its ill-posedness
properties. We further get that the singular values of the MPI core operator
decrease exponentially. We complement our analytic results by some numerical
studies which, in particular, suggest a rapid decay of the singular values of
the MPI operator.


  Quantum coherent transport of Dirac fermions in a mesoscopic nanowire of the
3D topological insulator Bi2Se3 is studied in the weak-disorder limit. At very
low temperatures, many harmonics are evidenced in the Fourier transform of
Aharonov-Bohm oscillations, revealing the long phase-coherence length of
surface states. Remarkably, from their exponential temperature dependence, we
infer an unusual 1/T power law for the phase coherence length. This decoherence
is typical for quasi-ballistic fermions weakly coupled to the dynamics of their
environment.


  Capturing smooth motions from videos using markerless techniques typically
involves complex processes such as temporal constraints, multiple stages with
data-driven regression and optimization, and bundle solving over temporal
windows. These processes can be inefficient and require tuning multiple
objectives across stages. In contrast, BundleMoCap introduces a novel and
efficient approach to this problem. It solves the motion capture task in a
single stage, eliminating the need for temporal smoothness objectives while
still delivering smooth motions. BundleMoCap outperforms the state-of-the-art
without increasing complexity. The key concept behind BundleMoCap is manifold
interpolation between latent keyframes. By relying on a local manifold
smoothness assumption, we can efficiently solve a bundle of frames using a
single code. Additionally, the method can be implemented as a sliding window
optimization and requires only the first frame to be properly initialized,
reducing the overall computational burden. BundleMoCap's strength lies in its
ability to achieve high-quality motion capture results with simplicity and
efficiency. More details can be found at https://moverseai.github.io/bundle/.


  Plasmonic nanojunctions, consisting of adjacent metal structures with
nanometre gaps, can support localised plasmon resonances that boost light
matter interactions and concentrate electromagnetic fields at the nanoscale. In
this regime, the optical response of the system is governed by poorly
understood dynamical phenomena at the frontier between the bulk, molecular and
atomic scales. Here, we report ubiquitous spectral fluctuations in the
intrinsic light emission from photo-excited gold nanojunctions, which we
attribute to the light-induced formation of domain boundaries and
quantum-confined emitters inside the noble metal. Our data suggest that
photoexcited carriers and gold adatom - molecule interactions play key roles in
triggering luminescence blinking. Surprisingly, this internal restructuring of
the metal has no measurable impact on the Raman signal and scattering spectrum
of the plasmonic cavity. Our findings demonstrate that metal luminescence
offers a valuable proxy to investigate atomic fluctuations in plasmonic
cavities, complementary to other optical and electrical techniques.


  We study --both in theory and practice-- the use of momentum motions in
classic iterative hard thresholding (IHT) methods. By simply modifying plain
IHT, we investigate its convergence behavior on convex optimization criteria
with non-convex constraints, under standard assumptions. In diverse scenaria,
we observe that acceleration in IHT leads to significant improvements, compared
to state of the art projected gradient descent and Frank-Wolfe variants. As a
byproduct of our inspection, we study the impact of selecting the momentum
parameter: similar to convex settings, two modes of behavior are observed
--"rippling" and linear-- depending on the level of momentum.


  This work introduces a time-adaptive strategy that uses a refinement
estimator based on the first Frenet curvature. In dynamics, a time-adaptive
strategy is a mechanism that interactively proposes changes to the time step
used in iterative methods of solution. These changes aim to improve the
relation between quality of response and computational cost. The method here
proposed is suitable for a variety of numerical time integration problems,
e.g., in the study of bodies subjected to dynamical loads. The motion equation
in its space-discrete form is used as reference to derive the formulation
presented in this paper. Our method is contrasted with other ones based on
local error estimator and apparent frequencies. We check the performance of our
proposal when employed with the central difference, the explicit
generalized-alpha and the Chung-Lee integration methods. The proposed
refinement estimator demands low computational resources, being easily applied
to several direct integration methods.


  We show that particle detectors coupled to a massless quantum field through
its derivative can genuinely harvest entanglement form the field even when they
are in causal contact in flat spacetime. This is particularly relevant since
the derivative coupling model captures some interesting experimentally
realizable systems and since the harvested entanglement peaks at full light
contact.


  We show that an infinite dimensional Lie group in Milnor's sense has the
strong Trotter property if it is locally $\mu$-convex. This is a continuity
condition imposed on the Lie group multiplication that generalizes the triangle
inequality for locally convex vector spaces, and is equivalent to
$C^0$-continuity of the evolution map on its domain. In particular, the result
proven in this paper significantly extends the respective result obtained by
Gl\"ockner in the context of measurable regularity.


  Sen's action for a $p$-form gauge field with self-dual field strength coupled
to a spacetime metric $g$ involves an explicit Minkowski metric and the
presence of this raises questions as to whether the action is coordinate
independent and whether it can be used on a general spacetime manifold. A
natural generalisation of Sen's action is presented in which the Minkowski
metric is replaced by a second metric $\bar g$ on spacetime. The theory is
covariant and can be formulated on any spacetime. The theory describes a
physical sector, consisting of the chiral $p$-form gauge field coupled to the
dynamical metric $g$, plus a shadow sector consisting of a second chiral
$p$-form and the second metric $\bar g$. The fields in this shadow sector only
couple to each other and have no interactions with the physical sector, so that
they decouple from the physical sector. The resulting theory is covariant and
can be formulated on any spacetime. Explicit expressions are found for the
interactions and extensions to include interactions with other physical fields
or higher-derivative field equations are given. A spacetime with two metrics
has some interesting geometry and some of this is explored here and used in the
construction of the interactions.The action has two diffeomorphism-like
symmetries, one acting only on the physical sector and one acting only on the
shadow sector, with the spacetime diffeomorphism symmetry arising as the
diagonal subgroup. This allows a further generalisation in which $\bar g$ is
not a tensor field but is instead a gauge field whose transition functions
involve the usual coordinate transformation together with a shadow sector gauge
transformation.


  The notion of descent set, for permutations as well as for standard Young
tableaux (SYT), is classical. Cellini introduced a natural notion of {\em
cyclic descent set} for permutations, and Rhoades introduced such a notion for
SYT --- but only for rectangular shapes. In this work we define {\em cyclic
extensions} of descent sets in a general context, and prove existence and
essential uniqueness for SYT of almost all shapes. The proof applies
nonnegativity properties of Postnikov's toric Schur polynomials, providing a
new interpretation of certain Gromov-Witten invariants.


  Context: The Wilson depression is the difference in geometric height of unit
continuum optical depth between the sunspot umbra and the quiet Sun. Measuring
the Wilson depression is important for understanding the geometry of sunspots.
Current methods suffer from systematic effects or need to make assumptions on
the geometry of the magnetic field. This leads to large systematic
uncertainties of the derived Wilson depressions.
  Aims: We aim at developing a robust method for deriving the Wilson depression
that only requires the information about the magnetic field that is accessible
from spectropolarimetry, and that does not rely on assumptions on the geometry
of sunspots or on their magnetic field.
  Methods: Our method is based on minimizing the divergence of the magnetic
field vector derived from spectropolarimetric observations. We focus on large
spatial scales only in order to reduce the number of free parameters.
  Results: We test the performance of our method using synthetic Hinode data
derived from two sunspot simulations. We find that the maximum and the umbral
averaged Wilson depression for both spots determined with our method typically
lies within 100 km of the true value obtained from the simulations. In
addition, we apply the method to Hinode observations of a sunspot. The derived
Wilson depression (about 600 km) is consistent with results typically obtained
from the Wilson effect. We also find that the Wilson depression obtained from
using horizontal force balance gives 110 - 180 km smaller Wilson depressions
than both, what we find and what we deduce directly from the simulations. This
suggests that the magnetic pressure and the magnetic curvature force contribute
to the Wilson depression by a similar amount.


  We investigate the evolution of the star formation rate-stellar mass relation
(SFR-M*) and Galaxy Stellar Mass Function (GSMF) of z ~ 4-7 galaxies, using
cosmological simulations run with the smoothed particle hydrodynamics code
P-GADGET3(XXL). We explore the effects of different feedback prescriptions
(supernova driven galactic winds and AGN feedback), initial stellar mass
functions and metal cooling. We show that our fiducial model, with strong
energy-driven winds and early AGN feedback, is able to reproduce the observed
stellar mass function obtained from Lyman-break selected samples of star
forming galaxies at redshift 6 < z < 7. At z ~ 4, observed estimates of the
GSMF vary according to how the sample was selected. Our simulations are more
consistent with recent results from K-selected samples, which provide a better
proxy of stellar masses and are more complete at the high mass end of the
distribution. We find that in some cases simulated and observed SFR-M*
relations are in tension, and this can lead to numerical predictions for the
GSMF in excess of the GSMF observed. By combining the simulated SFR(M*)
relationship with the observed star formation rate function at a given
redshift, we argue that this disagreement may be the result of the uncertainty
in the SFR-M* (Luv-M*) conversion. Our simulations predict a population of
faint galaxies not seen by current observations.


  Yang-Mills instantons in a pure Yang-Mills theory in four Euclidean space can
be promoted to particle-like topological solitons in d=4+1 dimensional
space-time. When coupled to Higgs fields, they transform themselves in the
Higgs phase into Skyrmions, lumps and sine-Gordon kinks, with trapped inside a
non-Abelian domain wall, non-Abelian vortex and monopole string, respectively.
Here, we point out that a closed monopole string, non-Abelian vortex sheet and
non-Abelian domain wall in $S^1$, $S^2$ and $S^3$ shapes, respectively, are all
Yang-Mills instantons if their $S^1$, $S^2$ and $S^3$ moduli, respectively, are
twisted along their world-volumes.


  This paper investigates the problem of minimizing the age-of-information
(AoI) and transmit power consumption in a vehicular network, where a roadside
unit (RSU) provides timely updates about a set of physical processes to
vehicles. Each vehicle is interested in maintaining the freshness of its
information status about one or more physical processes. A framework is
proposed to optimize the decisions to unicast, multicast, broadcast, or not
transmit updates to vehicles as well as power allocations to minimize the AoI
and the RSU's power consumption over a time horizon. The formulated problem is
a mixed-integer nonlinear programming problem (MINLP), thus a global optimal
solution is difficult to achieve. In this context, we first develop an ant
colony optimization (ACO) solution which provides near-optimal performance and
thus serves as an efficient benchmark. Then, for real-time implementation, we
develop a deep reinforcement learning (DRL) framework that captures the
vehicles' demands and channel conditions in the state space and assigns
processes to vehicles through dynamic unicast-multicast scheduling actions.
Complexity analysis of the proposed algorithms is presented. Simulation results
depict interesting trade-offs between AoI and power consumption as a function
of the network parameters.


  We study the dynamics of two-component vector solitons, namely, bright-bright
(BB) solitons interacting with parity-time-($\mathcal{PT}$) symmetric
potentials. We employ direct numerical simulations to demonstrate the
unidirectional segregation of the BB soliton. Using a modified perturbed
dynamical variational Lagrangian approximation, we develop an analytical model
to verify the results obtained from the numerical calculations. Simplified
variational equations of motion suggest that the splitting of BB solitons can
be explained by considering the effective force between the two components.


  We comment on the recent manuscript by Raines et al. [arXiv:0905.0269v2] (now
published in Nature, vol. 463, p. 214-217, 2010), which suggests that in
certain conditions a single diffraction measurement may be sufficient to
reconstruct the full three-dimensional density of a scatterer. We show that
past literature contains the tools to assess rigorously the feasibility of this
approach. We question the formulation of the reconstruction algorithm used by
the authors and we argue that the experimental data used as a demonstration is
not suitable for this method, and thus that the reconstruction is not valid.
  This second version was produced for documentation purposes. In addition to
the minimally modified original comment, it includes in appendix a subsequent
reply to one of the authors (J. Miao).


  Long term observations and space missions have generated a wealth of data on
the magnetic fields of the Earth and other solar system planets.
planetMagfields is a Python package designed to have all the planetary magnetic
field data currently available in one place and to provide an easy interface to
access the data. planetMagfields focuses on planetary bodies that generate
their own magnetic field, namely Mercury, Earth, Jupiter, Saturn, Uranus,
Neptune and Ganymede. planetMagfields provides functions to compute as well as
plot the magnetic field on the planetary surface or at a distance above or
under the surface. It also provides functions to filter out the field to large
or small scales as well as to produce .vts files to visualize the field in 3D
using Paraview, VisIt or similar rendering software. Lastly, the
planetMagfields repository also provides a Jupyter notebook for easy
interactive visualizations.


  A simple flashing ratchet model in two dimensions is proposed to simulate the
hand-over-hand motion of two head molecular motors like kinesin. Extensive
Langevin simulations of the model are performed. Good qualitative agreement
with the expected behavior is observed. We discuss different regimes of motion
and efficiency depending of model parameters.


  $^{57}$Fe M\"ossbauer spectroscopy can probe several \emph{local} structural,
electronic and magnetic properties of Fe-containing systems. However, to
establish a direct relationship between these properties and a system's
geometric structure, the experimental M\"ossbauer parameters need to be
analyzed \emph{via} electronic structure calculations. Herein, structural,
electronic and magnetic effects of iron substituents in the topological
insulator $Bi_2Se_3$, as uniquely probed by $^{57}$Fe M\"ossbauer spectroscopy,
have been determined \emph{via} spin-polarized electronic structure
calculations. The iron ion substituents, of \emph{nominal} Fe$^{3+}(S = 5/2)$
oxidation and spin state, are unequivocally shown to substitute Bi$^{3+}$ sites
in epitaxial $Bi_2Se_3$ thin-films used for M\"ossbauer measurements.
Concomitant with iron substitution, \emph{localized} structural rearrangements
take place whereby the longer Bi-Se bonds of the native system are replaced by
significantly shorter Fe-Se counterparts in the Fe-containing system. The
resulting distorted-octahedral environment about substituent iron ions gives
rise to characteristic M\"ossbauer parameters ($\delta_{Fe} \approx$ 0.51 mm/s,
$\Delta E_{Q} \approx$ 0.20 mm/s) which have been calculated in excellent
agreement with measured values for Fe-doped $Bi_2Se_3$ thin films. Consistent
with a substituent Fe$^{3+}$ ion's \emph{nominal} high-spin electronic
configuration ($t_{2g}^{\uparrow \uparrow \uparrow} e_g^{\uparrow \uparrow}$),
an Fe-centered spin density has been established which, nevertheless, extends
towards neighboring Se atoms \emph{via} direct Fe-Se bonding and concomitant
Fe(d)-Se(p) hybridization.


  The purpose of this research were: to survey the needs of using the
information system for educational quality administration; to develop
Information System for Educational quality Administration (ISEs) in accordance
with quality assessment standard; to study the qualification of ISEs; and to
study satisfaction level of ISEs user. Subsequently, the tools of study have
been employed that there were the collection of 47 questionnaires and 5
interviews to specialist by responsible officers for Information center of
Technical colleges in Southern Thailand. The analysis of quantitative data has
employed descriptive statistics using mean and standard deviation as the tool
of measurement.


  We investigate the interplay of crystal bases and completions in the sense of
Enright on certain nonintegrable representations of quantum groups. We define
completions of crystal bases, show that this notion of completion is compatible
with Enright's completion of modules, prove that every module in our category
has a crystal basis which can be completed and that a completion of the crystal
lattice is unique. Furthermore, we give two constructions of the completion of
a crystal lattice.


  A study is made of frequency comb generation described by the driven and
damped nonlinear Schr\"odinger equation on a finite interval. It is shown that
frequency comb generation can be interpreted as a modulational instability of
the continuous wave pump mode, and a linear stability analysis, taking into
account the cavity boundary conditions, is performed. Further, a truncated
three-wave model is derived, which allows one to gain additional insight into
the dynamical behaviour of the comb generation. This formalism describes the
pump mode and the most unstable sideband and is found to connect the coupled
mode theory with the conventional theory of modulational instability. An
in-depth analysis is done of the nonlinear three-wave model. It is demonstrated
that stable frequency comb states can be interpreted as attractive fixed points
of a dynamical system. The possibility of soft and hard excitation states in
both the normal and the anomalous dispersion regime is discussed.
Investigations are made of bistable comb states, and the dependence of the
final state on the way the comb has been generated. The analytical predictions
are verified by means of direct comparison with numerical simulations of the
full equation and the agreement is discussed.


  I review possible resolution of the $J/\psi (\psi^{\prime}) \to \rho-\pi$
puzzle based on two inputs: the relative phase between the one- photon and the
gluonic decay amplitudes, and a possible hadronic excess in the inclusive
nonelectromagnetic decay rate of $\psi^{\prime}$. The status of a universal
large phase here is examined for its meaning and implications (including those
for B-physics). Since the future of tau/charm facility(s) are again under
consideration together with a future anti-proton facility at GSI, I propose to
extend my review to include a broader discussion of charmonium physics.
Outstanding questions like the status of the $^{1}P_{1}$ state of charmonium,
measuring $D^{0}-\bar D^{0}$ mixing and relative strong phases, status of
molecular P(S) - wave charmonia will also be discussed amongst others.


  We present a novel end-to-end memory network for stance detection, which
jointly (i) predicts whether a document agrees, disagrees, discusses or is
unrelated with respect to a given target claim, and also (ii) extracts snippets
of evidence for that prediction. The network operates at the paragraph level
and integrates convolutional and recurrent neural networks, as well as a
similarity matrix as part of the overall architecture. The experimental
evaluation on the Fake News Challenge dataset shows state-of-the-art
performance.


  We believe that the best chance to observe macroscopic quantum coherence
(MQC) in a rf-SQUID qubit is to use on-chip RSFQ digital circuits for
preparing, evolving and reading out the qubit's quantum state. This approach
allows experiments to be conducted on a very short time scale (sub-nanosecond)
without the use of large bandwidth control lines that would couple
environmental degrees of freedom to the qubit thus contributing to its
decoherence. In this paper we present our design of a RSFQ digital control
circuit for demonstrating MQC in a rf-SQUID. We assess some of the key
practical issues in the circuit design including the achievement of the
necessary flux bias stability. We present an "active" isolation structure to be
used to increase coherence times. The structure decouples the SQUID from
external degrees of freedom, and then couples it to the output measurement
circuitry when required, all under the active control of RSFQ circuits.
Research supported in part by ARO grant # DAAG55-98-1-0367.


  Obtaining first-order regret bounds -- regret bounds scaling not as the
worst-case but with some measure of the performance of the optimal policy on a
given instance -- is a core question in sequential decision-making. While such
bounds exist in many settings, they have proven elusive in reinforcement
learning with large state spaces. In this work we address this gap, and show
that it is possible to obtain regret scaling as
$\widetilde{\mathcal{O}}(\sqrt{d^3 H^3 \cdot V_1^\star \cdot K} +
d^{3.5}H^3\log K )$ in reinforcement learning with large state spaces, namely
the linear MDP setting. Here $V_1^\star$ is the value of the optimal policy and
$K$ is the number of episodes. We demonstrate that existing techniques based on
least squares estimation are insufficient to obtain this result, and instead
develop a novel robust self-normalized concentration bound based on the robust
Catoni mean estimator, which may be of independent interest.


  Measuring an annual modulation in a direct Dark Matter detection experiment
is not only a proof of the existence of WIMPs but can also tell us more about
their interaction with standard matter and maybe even their density and
velocity in the halo. Such a modulation has been measured by the DAMA/LIBRA
experiment in NaI(Tl) crystals. However, the interpretation as WIMP signal is
controversial due to contradicting results by other experiments. The SABRE
experiment aims to shed light on this controversy by detecting the annual
modulation in the same target material as DAMA with twin detectors at LNGS in
Italy and at SUPL in Australia. The two locations in the northern and southern
hemisphere allow to verify if other seasonal effects or the site have an
influence on the measurement, thus reducing systematic effects. This paper will
give an overview on the experimental design, the current status of the proof of
principle phase mainly devoted to high-purity crystal growing, and an outlook
on future plans.


  We consider 3D stochastic Landau-Lifshitz-Gilbert equations coupled with the
Maxwell equations with the full energy. We have proved the existence and some
further regularities of the weak solution.


  We consider the general nonvanishing, divergence-free vector fields defined
on a domain in three space and tangent to its boundary. Based on the theory of
finite type invariants, we define a family of invariants for such fields, in
the style of Arnold's asymptotic linking number. Our approach is based on the
configuration space integrals due to Bott and Taubes.


  A linear inference is a valid inequality of Boolean algebra in which each
variable occurs at most once on each side.
  In this work we leverage recently developed graphical representations of
linear formulae to build an implementation that is capable of more efficiently
searching for switch-medial-independent inferences. We use it to find four
`minimal' 8-variable independent inferences and also prove that no smaller ones
exist; in contrast, a previous approach based directly on formulae reached
computational limits already at 7 variables. Two of these new inferences derive
some previously found independent linear inferences. The other two (which are
dual) exhibit structure seemingly beyond the scope of previous approaches we
are aware of; in particular, their existence contradicts a conjecture of Das
and Strassburger.
  We were also able to identify 10 minimal 9-variable linear inferences
independent of all the aforementioned inferences, comprising 5 dual pairs, and
present applications of our implementation to recent `graph logics'.


  The research is devoted to a numerical solution of the Volterra equations of
the first kind that were obtained using the Laplace integral transforms for
solving the equation of heat conduction. The paper consists of an introduction
and two sections. The first section deals with the calculation of kernels from
the respective integral equations at a fixed length of the significand in the
floating point representation of a real number. The PASCAL language was used to
develop the software for the calculation of kernels, which implements the
function of tracking the valid digits of the significand. The test examples
illustrate the typical cases of systematic error accumulation. The second
section presents the results obtained from the computational algorithms which
are based on the product integration method and the midpoint rule. The results
of test calculations are presented to demonstrate the performance of the
difference methods.


  A central feature in the Copenhagen interpretation is the use of classical
concepts from the outset. Modern developments show, however, that the emergence
of classical properties can be understood within the framework of quantum
theory itself, through the process of decoherence. This fact becomes most
crucial for the interpretability of quantum cosmology - the application of
quantum theory to the Universe as a whole. I briefly review these developments
and emphasize the importance of an unbiased attitude on the interpretational
side for future progress in physics.


  We propose Seiberg-Witten geometry for N=2 gauge theory with gauge group
$E_6$ with massive $N_f$ fundamental hypermultiplets. The relevant manifold is
described as a fibration of the ALE space of $E_6$ type. It is observed that
the fibering data over the base ${\bf CP}^1$ has an intricate dependence on
hypermultiplet bare masses.


  In the minimal Left-Right model the choice of left-right symmetry is twofold:
either generalized parity $\mathcal P$ or charge conjugation $\mathcal C$. In
the minimal model with spontaneously broken strict $\mathcal P$, a large
tree-level contribution to strong CP violation can be computed in terms of the
spontaneous phase $\alpha$. Searches for the neutron electric dipole moments
then constrain the size of $\alpha$. Following the latest update on indirect CP
violation in the kaon sector, a bound on $W_R$ mass at $20 \text{TeV}$ is set.
Possible ways out of this bound, either by an additional relaxation mechanism
or explicit breaking of $\mathcal P$ are considered. To this end, the chiral
loop of the neutron electric dipole moment at next-to-leading order is
re-computed and provides an estimate of the weak contribution. Combining this
constraint with other CP violating observables in the kaon sector allows for
$M_{W_R} \gtrsim 3 \text{TeV}$. On the other hand, $\mathcal C$-symmetry is
free from such constraints, leaving the right-handed scale within the
experimental reach.


  The Australian bushfires around the turn of the year 2020 generated an
unprecedented perturbation of stratospheric composition, dynamical circulation
and radiative balance. Here we show from satellite observations that the
resulting planetary-scale blocking of solar radiation by the smoke is larger
than any previously documented wildfires and of the same order as the radiative
forcing produced by moderate volcanic eruptions. A striking effect of the solar
heating of an intense smoke patch was the generation of a self-maintained
anticyclonic vortex measuring 1000 km in diameter and featuring its own ozone
hole. The highly stable vortex persisted in the stratosphere for over 13 weeks,
travelled 66,000 km and lifted a confined bubble of smoke and moisture to 35 km
altitude. Its evolution was tracked by several satellite-based sensors and was
successfully resolved by the European Centre for Medium-Range Weather Forecasts
operational system, primarily based on satellite data. Because wildfires are
expected to increase in frequency and strength in a changing climate, we
suggest that extraordinary events of this type may contribute significantly to
the global stratospheric composition in the coming decades.


  We extend the standard Kerr-Schild solution generating method to higher order
scalar tensor theories that are shift-invariant for the scalar field. Certain
degeneracy conditions, crucial for the absence of Ostrogradski ghosts, are
found to be required for the validity of the Kerr-Schild ansatz while on the
other hand, theories with no parity symmetry are excluded from the solution
generating method. The extended Kerr-Schild symmetry turns out to be a very
useful tool to easily construct black hole solutions from simple seed
configurations. In particular, the generating method developed is adapted to
construct generic black holes but also regular black hole solutions within
Degenerate Higher Order Scalar Tensor (DHOST) theories. As a particular example
we show how to construct explicitly the Hayward metric as a solution to a
specific DHOST theory.


  Renewable energy sources (RES) are getting closer to grid parity within
interconnected systems while their use in isolated and remote areas is already
cost competitive with conventional generation. In mini-grids, isolated and far
from the grid, the economics of different technology options (e.g. pure solar
photovoltaic (PV), wind, concentrated solar power (CSP), and open cycle gas
turbine (OCGT)) with different amounts of added capacity is assessed to allow
the peak demand to increase by 5 MW (or 5%) and 10 MW (or 10%). This assessment
is based on keeping the system reliability (measured in loss of load
expectation, LOLE) at the same level as it was before the addition of
conventional and renewable generators. An effective load carrying capability
(ELCC) increase by 5 MW (or 5%) can be realized by adding a 5 MW OCGT or 10 MW
PV and 10 MW wind. An ELCC increase of 10 MW (or 10%) requires either 11 MW
OCGT or 7.2 MW OCGT, 2.7 MW PV, and 8.1 MW wind. In both cases, the solution
with RES has 8% and 4% lower annual costs than the OCGT only solution (assuming
crude costs of $40/barrel). From an economic and system reliability
perspective, systems with low growth rates (<5%) in peak and energy demand
could focus on adding RES capacity while systems with higher growth rates (>5%)
still need to incorporate conventional generation.


  The local behavior of the lowest order boundary element method on
quasi-uniform meshes for Symm's integral equation and the stabilized
hyper-singular integral equation on polygonal/polyhedral Lipschitz domains is
analyzed. We prove local a priori estimates in $L^2$ for Symm's integral
equation and in $H^1$ for the hypersingular equation. The local rate of
convergence is limited by the local regularity of the sought solution and the
sum of the global regularity and additional regularity provided by the shift
theorem for a dual problem.


  Despite the acclaimed success of the magnetic field (H) formulation for
modeling the electromagnetic behavior of superconductors with the finite
element method, the use of vector-dependent variables in non-conducting domains
leads to unnecessarily long computation times. In order to solve this issue, we
have recently shown how to use a magnetic scalar potential together with the
H-formulation in the COMSOL Multiphysics environment to efficiently and
accurately solve for the magnetic field surrounding superconducting domains.
However, from the definition of the magnetic scalar potential, the
non-conducting domains must be made simply connected in order to obey Ampere's
law. In this work, we use thin cuts to apply a discontinuity in $\phi$ and make
the non-conducting domains simply connected. This approach is shown to be
easily implementable in the COMSOL Multiphysics finite element program, already
widely used by the applied superconductivity community. We simulate three
different models in 2-D and 3-D using superconducting filaments and tapes, and
show that the results are in very good agreement with the H-A and
H-formulations. Finally, we compare the computation times between the
formulations, showing that the H-$\phi$-formulation can be up to seven times
faster than the standard H-formulation in certain applications of interest.


  Data Poisoning attacks modify training data to maliciously control a model
trained on such data. In this work, we focus on targeted poisoning attacks
which cause a reclassification of an unmodified test image and as such breach
model integrity. We consider a particularly malicious poisoning attack that is
both "from scratch" and "clean label", meaning we analyze an attack that
successfully works against new, randomly initialized models, and is nearly
imperceptible to humans, all while perturbing only a small fraction of the
training data. Previous poisoning attacks against deep neural networks in this
setting have been limited in scope and success, working only in simplified
settings or being prohibitively expensive for large datasets. The central
mechanism of the new attack is matching the gradient direction of malicious
examples. We analyze why this works, supplement with practical considerations.
and show its threat to real-world practitioners, finding that it is the first
poisoning method to cause targeted misclassification in modern deep networks
trained from scratch on a full-sized, poisoned ImageNet dataset. Finally we
demonstrate the limitations of existing defensive strategies against such an
attack, concluding that data poisoning is a credible threat, even for
large-scale deep learning systems.


  This thesis consists of two independent parts: random matrices, which form
the first one-third of this thesis, and machine learning, which constitutes the
remaining part. The main results of this thesis are as follows: a necessary and
sufficient condition for the inverse moments of $(m,n,\beta)$-Laguerre matrices
and compound Wishart matrices to be finite; the universal weak consistency and
the strong consistency of the $k$-nearest neighbor rule in metrically
sigma-finite dimensional spaces and metrically finite dimensional spaces
respectively. In Part I, the Chapter 1 introduces the $(m,n,\beta)$-Laguerre
matrix, Wishart and compound Wishart matrix and their joint eigenvalue
distribution. While in Chapter 2, a necessary and sufficient condition to have
finite inverse moments has been derived. In Part II, the Chapter 1 introduces
the various notions of metric dimension and differentiation property followed
by our proof for the necessary part of Preiss' result. Further, Chapter 2 gives
an introduction to the mathematical concepts in statistical machine learning
and then the $k$-nearest neighbor rule is presented in Chapter 3 with a proof
of Stone's theorem. In chapters 4 and 5, we present our main results and some
possible future directions based on it.


  We show that analog gravity systems exist for charged, planar black holes in
asymptotic Anti-de Sitter space. These black holes have been employed to
describe, via the gauge-gravity duality, strongly coupled condensed matter
systems on the boundary of AdS-space. The analog gravity system is a different
condensed matter system that, in a suitable limit, describes the same bulk
physics as the theory on the AdS boundary. This combination of the
gauge-gravity duality and analog gravity therefore suggests a duality between
different condensed matter systems.


  This paper extends recent results on aging in mean field spin glasses on
short time scales, obtained by Ben Arous and Gun [2] in law with respect to the
environment, to results that hold almost surely, respectively in probability,
with respect to the environment. It is based on the methods put forward in
Gayrard [8,9] and naturally complements Bovier and Gayrard [6].


  The Stellar Imager (SI) is a UV-Optical, Space-Based Interferometer designed
to enable 0.1 milli-arcsecond (mas) spectral imaging of stellar surfaces and of
the Universe in general and asteroseismic imaging of stellar interiors. SI is
identified as a "Flagship and Landmark Discovery Mission" in the 2005 Sun Solar
System Connection (SSSC) Roadmap and as a candidate for a "Pathways to Life
Observatory" in the Exploration of the Universe Division (EUD) Roadmap (May,
2005). SI will revolutionize our view of many dynamic astrophysical processes:
its resolution will transform point sources into extended sources, and
snapshots into evolving views. SI's science focuses on the role of magnetism in
the Universe, particularly on magnetic activity on the surfaces of stars like
the Sun. SI's prime goal is to enable long-term forecasting of solar activity
and the space weather that it drives. SI will also revolutionize our
understanding of the formation of planetary systems, of the habitability and
climatology of distant planets, and of many magneto-hydrodynamically controlled
processes in the Universe. The results of the SI "Vision Mission" Study are
presented in this paper. Additional information on the SI mission concept and
related technology development can be found at URL:
http://hires.gsfc.nasa.gov/si/.


  The direct radiative capture process is well described by the spherical
potential model. In order for the model to explain direct captures more
accurately, the effect of the nuclear deformation has been added and analyzed
in this work, since most nucleuses are not spherical. The results imply that
the nuclear deformation largely affects the direct capture and should be taken
into account during discussing direct capture reactions.