  This work is concerned with the proof-complexity of certifying that
optimization problems do \emph{not} have good solutions. Specifically we
consider bounded-degree "Sum of Squares" (SOS) proofs, a powerful algebraic
proof system introduced in 1999 by Grigoriev and Vorobjov. Work of Shor,
Lasserre, and Parrilo shows that this proof system is automatizable using
semidefinite programming (SDP), meaning that any $n$-variable degree-$d$ proof
can be found in time $n^{O(d)}$. Furthermore, the SDP is dual to the well-known
Lasserre SDP hierarchy, meaning that the "$d/2$-round Lasserre value" of an
optimization problem is equal to the best bound provable using a degree-$d$ SOS
proof. These ideas were exploited in a recent paper by Barak et al.\ (STOC
2012) which shows that the known "hard instances" for the Unique-Games problem
are in fact solved close to optimally by a constant level of the Lasserre SDP
hierarchy.
  We continue the study of the power of SOS proofs in the context of difficult
optimization problems. In particular, we show that the Balanced-Separator
integrality gap instances proposed by Devanur et al.\ can have their optimal
value certified by a degree-4 SOS proof. The key ingredient is an SOS proof of
the KKL Theorem. We also investigate the extent to which the Khot--Vishnoi
Max-Cut integrality gap instances can have their optimum value certified by an
SOS proof. We show they can be certified to within a factor .952 ($> .878$)
using a constant-degree proof. These investigations also raise an interesting
mathematical question: is there a constant-degree SOS proof of the Central
Limit Theorem?


  The task of controlling a quantum system under time and bandwidth limitations
is made difficult by unwanted excitations of spectrally neighboring energy
levels. In this article we review the Derivative Removal by Adiabatic Gate
(DRAG) framework. DRAG is a multi-transition variant of counterdiabatic
driving, where multiple low-lying gapped states in an adiabatic evolution can
be avoided simultaneously, greatly reducing operation times compared to the
adiabatic limit. In its essence, the method corresponds to a convergent version
of the superadiabatic expansion where multiple counterdiabaticity conditions
can be met simultaneously. When transitions are strongly crowded, the system of
equations can instead be favorably solved by an average Hamiltonian (Magnus)
expansion, suggesting the use of additional sideband control. We give some
examples of common systems where DRAG and variants thereof can be applied to
improve performance.


  Symmetric edge polytopes $\mathcal{A}_G$ of type A are lattice polytopes
arising from the root system $A_n$ and finite simple graphs $G$. There is a
connection between $\mathcal{A}_G$ and the Kuramoto synchronization model in
physics. In particular, the normalized volume of $\mathcal {A}_G$ plays a
central role. In the present paper, we focus on a particular class of graphs.
In fact, for any cactus graph $G$, we give a formula for the $h^*$-polynomial
of $\mathcal{A}_{\widehat{G}}$ by using matching generating polynomials, where
$\widehat{G}$ is the suspension of $G$. This gives also a formula for the
normalized volume of $\mathcal{A}_{\widehat{G}}$. Moreover, via the chemical
graph theory, we show that for any cactus graph $G$, the $h^*$-polynomial of
$\mathcal{A}_{\widehat{G}}$ is real-rooted. Finally, we extend the discussion
to symmetric edge polytopes of type $B$, which are lattice polytopes arising
from the root system $B_n$ and finite simple graphs.


  The effect of discrete breathers (DBs) on macroscopic properties of the
Fermi-Pasta-Ulam chain with symmetric and asymmetric potentials is
investigated. The total to kinetic energy ratio (related to specific heat),
stress (related to thermal expansion), and Young's modulus are monitored during
the development of modulational instability of the zone boundary mode. The
instability results in the formation of chaotic DBs followed by the transition
to thermal equilibrium when DBs disappear due to energy radiation in the form
of small-amplitude phonons. It is found that DBs reduce the specific heat for
all the considered chain parameters. They increase the thermal expansion when
the potential is asymmetric and, as expected, thermal expansion is not observed
in the case of symmetric potential. The Young's modulus in the presence of DBs
is smaller than in thermal equilibrium for the symmetric potential and for the
potential with a small asymmetry, but it is larger than in thermal equilibrium
for the potential with greater asymmetry. Our results can be useful for setting
experiments on the identification of DBs in crystals by measuring their
macroscopic properties.


  In the Minimal Supersymmetric Standard Model heavy superparticles introduce
large logarithms in the calculation of the lightest $\mathcal{CP}$-even Higgs
boson mass. These logarithmic contributions can be resummed using effective
field theory techniques. For light superparticles, however, fixed-order
calculations are expected to be more accurate. To gain a precise prediction
also for intermediate mass scales, both approaches have to be combined. Here,
we report on an improvement of this method in various steps: the inclusion of
electroweak contributions, of separate electroweakino and gluino thresholds, as
well as resummation at the NNLL level. These improvements can lead to
significant numerical effects. In most cases, the lightest $\mathcal{CP}$-even
Higgs boson mass is shifted downwards by about 1 GeV. This is mainly caused by
higher order corrections to the $\bar{\text{MS}}$ top-quark mass. We also
describe the implementation of the new contributions in the code {\tt
FeynHiggs}.


  We focus in this paper on dataset reduction techniques for use in k-nearest
neighbor classification. In such a context, feature and prototype selections
have always been independently treated by the standard storage reduction
algorithms. While this certifying is theoretically justified by the fact that
each subproblem is NP-hard, we assume in this paper that a joint storage
reduction is in fact more intuitive and can in practice provide better results
than two independent processes. Moreover, it avoids a lot of distance
calculations by progressively removing useless instances during the feature
pruning. While standard selection algorithms often optimize the accuracy to
discriminate the set of solutions, we use in this paper a criterion based on an
uncertainty measure within a nearest-neighbor graph. This choice comes from
recent results that have proven that accuracy is not always the suitable
criterion to optimize. In our approach, a feature or an instance is removed if
its deletion improves information of the graph. Numerous experiments are
presented in this paper and a statistical analysis shows the relevance of our
approach, and its tolerance in the presence of noise.


  During its 2005 outburst, GRO J1655-40 was observed at high spectral
resolution with the Chandra HETGS, revealing a spectrum rich with blueshifted
absorption lines indicative of an accretion disk wind -- apparently too hot,
too dense, and too close to the black hole to be driven by radiation pressure
or thermal pressure (Miller et al.). But this exotic wind represents just one
piece of the puzzle in this outburst, as its presence coincides with an
extremely soft and curved X-ray continuum spectrum, remarkable X-ray
variability (Uttley & Klein-Wolt), and a bright, unexpected optical/infrared
blackbody component that varies on the orbital period. Focusing on the X-ray
continuum and the optical/infrared/UV spectral energy distribution, we argue
that the unusual features of this "hypersoft state" are natural consequences of
a super-Eddington Compton-thick wind from the disk: the optical/infrared
blackbody represents the cool photosphere of a dense, extended outflow, while
the X-ray emission is explained as Compton scattering by the relatively cool,
optically thick wind. This wind obscures the intrinsic luminosity of the inner
disk, which we suggest may have been at or above the Eddington limit.


  We report the first variational Monte Carlo (VMC) study of the iron-based
superconductors. We use realistic band structures, and the ordering
instabilities/variational ansatzs are suggested by previous functional
renormalization group calculations. We examine antiferromagnetism,
superconducting pairing, normal state fermi surface distortion, and orbital
order in the antiferromagnetic state.


  Recently, pedestrian behavior research has shifted towards machine learning
based methods and converged on the topic of modeling pedestrian interactions.
For this, a large-scale dataset that contains rich information is needed. We
propose a data collection system that is portable, which facilitates accessible
large-scale data collection in diverse environments. We also couple the system
with a semi-autonomous labeling pipeline for fast trajectory label production.
We further introduce the first batch of dataset from the ongoing data
collection effort -- the TBD pedestrian dataset. Compared with existing
pedestrian datasets, our dataset contains three components: human verified
labels grounded in the metric space, a combination of top-down and perspective
views, and naturalistic human behavior in the presence of a socially
appropriate "robot".


  Recent experiments on bismuth have uncovered remarkably rich magnetization
structure at fields well beyond the regime in which all carriers are expected
to reside in the lowest Landau level. Motivated by these findings, we start
from a microscopic tight-binding model and derive a low-energy Hamiltonian for
the holes and three Dirac electrons pockets in bismuth. We find that an
unconventional electron Zeeman effect, overlooked previously, suppresses the
quantum limit for the electrons dramatically, giving rise to the observed
anomalous magnetization structure. We further study interaction effects near
fields at which the 2nd Landau level for one electron pocket empties, where
magnetization hysteresis was observed. Here we find instabilities towards both
charge density wave and Wigner crystal phases, and propose that hysteresis
arises from a first-order transition out of the latter.


  Baseball is one of the few sports in which each team plays a game nearly
everyday. For instance, in the baseball league in South Korea, namely the KBO
(Korea Baseball Organization) league, every team has a game everyday except for
Mondays. This consecutiveness of the KBO league schedule could make a team's
match outcome be associated to the results of recent games. This paper deals
with modeling the match outcomes of each of the ten teams in the KBO league as
a higher-order Markov chain, where the possible states are win ($"W"$), draw
($"D"$), and loss ($"L"$). For each team, the value of $k$ in which the
$k^{\text{th}}$ order Markov chain model best describes the match outcome
sequence is computed. Further, whether there are any patterns between such a
value of k and the team's overall performance in the league is examined. We
find that for the top three teams in the league, lower values of $k$ tend to
have the $k^{th}$ order Markov chain to better model their outcome, but the
other teams don't reveal such patterns.


  Building on a recent paper by Georgiou and Lindquist [1] on the problem of
rank deficiency of spectral densities and hidden dynamical relations after
sampling of continuous-time stochastic processes, this paper is devoted to
understanding related questions of feedback and Granger causality that affect
stability properties. This then naturally connects to CARMA identification,
where we remark on certain oversights in the literature.


  We study a model in which a Hubbard Hamiltonian is coupled to the dispersive
phonons in a classical nonlinear lattice. Our calculations are restricted to
the case where we have only two quasi-particles of opposite spins, and we
investigate the dynamics when the second quasi-particle is added to a state
corresponding to a minimal energy single quasi-particle state. Depending on the
parameter values, we find a number of interesting regimes. In many of these,
discrete breathers (DBs) play a prominent role with a localized lattice mode
coupled to the quasiparticles. Simulations with a purely harmonic lattice show
much weaker localization effects. Our results support the possibility that DBs
are important in HTSC.


  The formation of bound states of holes in an antiferromagnetic spin-1/2
background is studied using numerical techniques applied to the ${\rm t-J}$
Hamiltonian on clusters with up to 26 sites. An analysis of the binding energy
as a function of cluster size suggests that a two hole bound state is formed
for couplings larger than a ``critical'' value ${\rm J/t]_c}$. The symmetry of
the bound state is $\dx2y2$. We also observed that its ``quasiparticle'' weight
${\rm Z_{2h}}$ (defined in the text), is finite for all values of the coupling
${\rm J/t}$. Thus, in the region ${\rm J/t \geq J/t]_c}$ the bound state of two
holes behaves like a quasiparticle with charge $Q=2e$, spin $S=0$, and $\dx2y2$
internal symmetry. The relation with recent ideas that have suggested the
possibility of d-wave pairing in the high temperature cuprate superconductors
is briefly discussed.


  Magnetic-field-induced ordering of electrons around vortices is a striking
phenomenon recently found in high-$T_c$ cuprates. To identify its consequence
in the quasiparticle dynamics, the magnetic-field ($H$) dependence of the
low-temperature thermal conductivity $\kappa$ of La$_{2-x}$Sr$_x$CuO$_4$
crystals is studied for a wide doping range. It is found that the behavior of
$\kappa(H)$ in the sub-Kelvin region changes drastically across optimum doping,
and the data for underdoped samples are indicative of unusual
magnetic-field-induced localization of quasiparticles; this localization
phenomenon is probably responsible for the unusual "insulating normal state"
under high magnetic fields.


  Recent experiments on atom loss in ultra-cold Fermi gases all show a maximum
at a magnetic field below Feshbach resonance, where the s-wave scattering
length is large (close to inter-particle distance) and positive. These
experiments have been performed over a wide range of conditions, with
temperatures and trap depths spanning over three decades. Different groups have
come up with different explanations, among them the emergence of Stoner
ferromagnetism. Here, we show that this maximum is a consequence of two major
steps. The first is the establishment of a population of shallow dimers, which
is the combined effect of dimer formation through three-body recombination, and
the dissociation of shallow dimers back to atoms through collisions. The
dissociation process will be temperature dependent, and is affected by Pauli
blocking at low temperatures. The second is the relaxation of shallow dimers
into tightly bound dimers through atom-dimer and dimer-dimer collisions.
  We have constructed a simple set of rate equations describing these
processes. Remarkably, even with only a few parameters, these equations
reproduce the loss rate observed in all recent experiments, despite their
widely different experimental conditions. Our studies show that the location of
the maximum loss rate depends crucially on experimental parameters such as trap
depth and temperature. These extrinsic characters show that this maximum is not
a reliable probe of the nature of the underlying quantum states. The physics of
our equations also explains some general trends found in current experiments.


  We consider a Persistent Intelligence, Surveillance and Reconnaissance (PISR)
routing problem, which includes collecting data from a set of specified task
locations and delivering that data to a control station. Each task is assigned
a refresh rate based on its priority, where higher priority tasks require
higher refresh rates. The UAV team's objective is to minimize the maximum of
the delivery times of all the tasks' data to the control station, while
simultaneously, satisfying each task's revisit period constraint. The
centralized path planning problem for this PISR routing problem is formulated
using mixed integer linear programming and solved using a branch-and-cut
algorithm. Heuristics are presented to find sub-optimal feasible solutions that
require much less computation time. The algorithms are tested on several
instances and their performance is compared with respect to the optimal cost
and computation time.


  In this paper, we investigate the existence and uniqueness of convex, entire,
spacelike hypersurfaces of constant $\sigma_k$ curvature with prescribed set of
lightlike directions $\mathcal{F}\subset\mathbb{S}^{n-1}$ and perturbation $q$
on $\mathcal{F}$. We prove that given a closed set $\mathcal{F}$ in the ideal
boundary at infinity of hyperbolic space and a perturbation $q$ that satisfies
some mild conditions, there exists a complete entire spacelike constant
$\sigma_k$ curvature hypersurface $\mathcal{M}_u$ with prescribed set of
lightlike directions $\mathcal{F}$ satisfying when
$\frac{x}{|x|}\in\mathcal{F},$ as $|x|\rightarrow\infty,$ $u(x)-|x|\rightarrow
q\left(\frac{x}{|x|}\right).$ This result is new even for the case of constant
Gauss curvature. We also prove that when the Gauss map image is a half disc
$\bar{B}_1^+$ and the perturbation $q\equiv 0,$ if a CMC hypersurface
$\mathcal{M}_u$ satisfies $|u(x)-V_{\bar{\mathcal{B}}_+}(x)|$ is bounded, then
$u(x)$ is unique.


  This is an elementary introduction to infinite-dimensional probability. In
the lectures, we compute the exact mean values of some functionals on C[0,1]
and L[0,1] by considering these functionals as infinite-dimensional random
variables. The results show that there exist the complete concentration of
measure phenomenon for these mean values since the variances are all zeroes.


  Inflationary models driven by a large number of axion fields are discussed in
the context of type IIB compactifications with N=1 supersymmetry. The inflatons
arise as the scalar modes of the R-R two-forms evaluated on vanishing
two-cycles in the compact geometry. The vanishing cycles are resolved by small
two-volumes or NS-NS B-fields which sit together with the inflatons in the same
supermultiplets. String world-sheets wrapping the vanishing cycles correct the
metric of the R-R inflatons. They can help to generate kinetic terms close to
the Planck scale and a mass hierarchy between the axions and their non-axionic
partners during inflation. At small string coupling, D-brane corrections are
subleading in the metric of the R-R inflatons. However, an axion potential can
be generated by D1 instantons or gaugino condensates on D5 branes. Models with
sufficiently large number of axions admit regions of chaotic inflation which
can stretch over the whole axion field range for potentials from gaugino
condensates. These models could allow for a possibly detectable amount of
gravitational waves with tensor to scalar ratio as high as r<0.14.


  The search for suitable materials for solid-state stationary storage of green
hydrogen is pushing the implementation of efficient renewable energy systems.
This involves rational design and modification of cheap alloys for effective
storage in mild conditions of temperature and pressure. Among many
intermetallic compounds described in the literature, TiFe-based systems have
recently regained vivid interest as materials for practical applications since
they are low-cost and they can be tuned to match required pressure and
operation conditions. This work aims to provide a comprehensive review of
publications involving chemical substitution in TiFe-based compounds for
guiding compound design and materials selection in current and future hydrogen
storage applications. Mono- and multi-substituted compounds modify TiFe
thermodynamics and are beneficial for many hydrogenation properties. They will
be reviewed and deeply discussed, with a focus on manganese substitution.


  The volume phase transition of microgels is one of the most paradigmatic
examples of stimuli-responsiveness, enabling a collapse from a highly swollen
microgel state into a densely coiled state by an external stimulus. Although
well characterized in bulk, it remains unclear how the phase transition is
affected by the presence of a confining interface. Here, we demonstrate that
the temperature-induced volume phase transition of poly(N-isopropylacrylamide)
microgels, conventionally considered an intrinsic molecular property of the
polymer, is in fact largely suppressed when the microgel is adsorbed to an
air/liquid interface. We further observe a hysteresis in core morphology and
interfacial pressure between heating and cooling cycles. Our results, supported
by molecular dynamics simulations, reveal that the dangling polymer chains of
microgel particles, spread at the interface under the influence of surface
tension, do not undergo any volume phase transition, demonstrating that the
balance in free energy responsible for the volume phase transition is
fundamentally altered by interfacial confinement. These results imply that
important technological properties of such systems, including the
temperature-induced destabilization of emulsions does not occur via a decrease
in interfacial coverage of the microgels.


  When structured light is propagated through the atmosphere, turbulence
results in modal scattering and distortions. An extensively studied example is
that of light carrying orbital angular momentum (OAM), where the atmosphere is
treated as a phase distortion and numerical tools extract the resulting modal
cross-talk. This approach focuses on the light itself, perturbed by the
atmosphere, yet does not easily lend itself to physical insights, and fails to
ask a pertinent question: where did the OAM that the beam gained or lost come
from? Here, we address this by forgoing the beam and instead calculating the
OAM of the atmosphere itself. With this intuitive model we are able to draw
general conclusions on the impact of atmospheric turbulence on OAM beams, which
we confirm experimentally. Our work alters the perspective on this problem,
opening new insights into the physics of OAM in turbulence, and is easily
extended to other structured light fields through arbitrary aberrations.


  With every locally compact group $G$, one can associate several interesting
bi-invariant subspaces $X(G)$ of the weakly almost periodic functions
$\mathrm{WAP}(G)$ on $G$, each of which captures parts of the representation
theory of $G$. Under certain natural assumptions, such a space $X(G)$ carries a
unique invariant mean and has a natural predual, and we view the
weak$^*$-continuity of this mean as a rigidity property of $G$. Important
examples of such spaces $X(G)$, which we study explicitly, are the algebra
$M_{\mathrm{cb}}A_p(G)$ of $p$-completely bounded multipliers of the
Fig\`a-Talamanca-Herz algebra $A_p(G)$ and the $p$-Fourier-Stieltjes algebra
$B_p(G)$. In the setting of connected Lie groups $G$, we relate the
weak$^*$-continuity of the mean on these spaces to structural properties of
$G$. Our results generalise results of Bekka, Kaniuth, Lau and Schlichting.


  We discuss the prediction accuracy of assumed statistical models in terms of
prediction errors for the generalized linear model and penalized maximum
likelihood methods. We derive the forms of estimators for the prediction
errors, such as $C_p$ criterion, information criteria, and leave-one-out cross
validation (LOOCV) error, using the generalized approximate message passing
(GAMP) algorithm and replica method. These estimators coincide with each other
when the number of model parameters is sufficiently small; however, there is a
discrepancy between them in particular in the parameter region where the number
of model parameters is larger than the data dimension. In this paper, we review
the prediction errors and corresponding estimators, and discuss their
differences. In the framework of GAMP, we show that the information criteria
can be expressed by using the variance of the estimates. Further, we
demonstrate how to approach LOOCV error from the information criteria by
utilizing the expression provided by GAMP.


  We consider the standard site percolation model on the $d$-dimensional
lattice. A direct consequence of the proof of the uniqueness of the infinite
cluster of Aizenman, Kesten and Newman [Comm. Math. Phys. 111 (1987) 505-531]
is that the two-arms exponent is larger than or equal to $1/2$. We improve
slightly this lower bound in any dimension $d\geq2$. Next, starting only with
the hypothesis that $\theta(p)>0$, without using the slab technology, we derive
a quantitative estimate establishing long-range order in a finite box.


  Time series research has gathered lots of interests in the last decade,
especially for Time Series Classification (TSC) and Time Series Forecasting
(TSF). Research in TSC has greatly benefited from the University of California
Riverside and University of East Anglia (UCR/UEA) Time Series Archives. On the
other hand, the advancement in Time Series Forecasting relies on time series
forecasting competitions such as the Makridakis competitions, NN3 and NN5
Neural Network competitions, and a few Kaggle competitions. Each year,
thousands of papers proposing new algorithms for TSC and TSF have utilized
these benchmarking archives. These algorithms are designed for these specific
problems, but may not be useful for tasks such as predicting the heart rate of
a person using photoplethysmogram (PPG) and accelerometer data. We refer to
this problem as Time Series Extrinsic Regression (TSER), where we are
interested in a more general methodology of predicting a single continuous
value, from univariate or multivariate time series. This prediction can be from
the same time series or not directly related to the predictor time series and
does not necessarily need to be a future value or depend heavily on recent
values. To the best of our knowledge, research into TSER has received much less
attention in the time series research community and there are no models
developed for general time series extrinsic regression problems. Most models
are developed for a specific problem. Therefore, we aim to motivate and support
the research into TSER by introducing the first TSER benchmarking archive. This
archive contains 19 datasets from different domains, with varying number of
dimensions, unequal length dimensions, and missing values. In this paper, we
introduce the datasets in this archive and did an initial benchmark on existing
models.


  We define the notion of a parahoric group scheme $\mathcal G$ over a smooth
projective curve, and formulate four conjectures on the structure of the stack
of $\mathcal G$-bundles, which generalize to this case well-known results on
$G$-bundles with $G$ a constant reductive group. The conjectures concern the
set of connected components, the uniformization by affine flag varieties of
twisted loop groups, the Picard groups, and the space of global sections of a
dominant line bundle. Since a first version of this paper was circulated,
Heinloth [arXiv:0711.4450] has proved a good part of these conjectures.


  Solitons are peculiar excitations that appear in a wide range of nonlinear
systems such as in fluids or optics. We show here that the collective transport
of charges observed in charge density wave (CDW) systems can be explained by
using a similar theory based on a traveling soliton lattice. Coherent x-ray
diffraction experiment performed in the sliding state of a CDW material reveals
peculiar diffraction patterns in good agreement with this assumption.
Therefore, the collective transport of charges in CDW systems may be due to a
nonlinear interaction leading to a self-localized excitation, carrying charges
without deformation through the sample, on top of the CDW ground state. This
single theory explains why charges remain spatially correlated over very long
distances and reconciles the main features of sliding CDW systems, either
observed by transport measurements or diffraction.


  We study the anisotropy in the arrival directions of PAO UHECRs, using the
point source correlational angular distance distribution. The result shows that
the anisotropy is characterized by one prominent excess region and one void
region. The excess region is located near the Centaurus A direction, supporting
that the Centaurus A is a promising UHECR source. The void region near the
south pole direction may be used to limit the diffuse isotropic background
contribution.


  The fragmentation of high-energy gluons at small opening angles is largely
unconstrained by present measurements. Gluon splitting to $b$-quark pairs is a
unique probe into the properties of gluon fragmentation because identified
$b$-tagged jets provide a proxy for the quark daughters of the initial gluon.
In this study, key differential distributions related to the $g\rightarrow
b\bar{b}$ process are measured using 33 fb$^{-1}$ of $\sqrt{s}=13$ TeV $pp$
collision data recorded by the ATLAS experiment at the LHC in 2016. Jets
constructed from charged-particle tracks, clustered with the anti-$k_t$ jet
algorithm with radius parameter $R = 0.2$, are used to probe angular scales
below the $R=0.4$ jet radius. The observables are unfolded to particle level in
order to facilitate direct comparisons with predictions from present and future
simulations. Multiple significant differences are observed between the data and
parton shower Monte Carlo predictions, providing input to improve these
predictions of the main source of background events in analyses involving
boosted Higgs bosons decaying into $b$-quarks.


  We show that the non-linear autonomus Wei-Norman equations, expressing the
solution of a linear system of non-autonomous equations on a Lie algebra, can
be reduced to the hierarchy of matrix Riccati equations in the case of all
classical simple Lie algebras. The result generalizes our previous one
concerning the complex Lie algebra of the special linear group. We show that it
cannot be extended to all simple Lie algebras, in particular to the exceptional
$G_2$ algebra.


  A generalized Courant algebroid structure is defined on the direct sum bundle
D(E) +J(E), where D(E) and J(E) are the gauge Lie algebroid and the jet bundle
of a vector bundle E respectively. Such a structure is called an omni-Lie
algebroid since it is reduced to the omni-Lie algebra introduced by A.Weinstein
if the base manifold is a point. We prove that any Lie algebroid structure on E
is characterized by a Dirac structure as the graph of a bundle map from J(E) to
D(E).


  We study two-band one-dimensional superconducting chains of spinless fermions
with inter and intra-band pairing. These bands hybridize and depending on the
relative angular momentum of their orbitals this can be symmetric or
anti-symmetric. The competition between intra and inter-band superconductivity
and how it is affected by the symmetry of the hybridization is investigated.
The interband pairing is shown to be dominant on a large region of parameter
space. A rich phase diagram is found in the presence of anti-symmetric
hybridization. The topological properties of the model are obtained through the
topological invariant winding number. We find the existence of a topological
phase due to the inter-band superconductivity and induced by symmetric
hybridization. Robustness of zero-energy edge states are discussed and are
shown to be present in the topological phase.


  The phase structure of $d=3$ Nambu-Jona-Lasinio model in curved spacetime
with magnetic field is investigated in the leading order of the $1/N$-expansion
and in linear curvature approximation (an external magnetic field is treated
exactly). The possibility of the chiral symmetry breaking under the combined
action of the external gravitational and magnetic fields is shown explicitly.
At some circumstances the chiral symmetry may be restored due to the
compensation of the magnetic field by the gravitational field.


  Rapid analysis of DNA sequences is important in preventing the evolution of
different viruses and bacteria during an early phase, early diagnosis of
genetic predispositions to certain diseases (cancer, cardiovascular diseases),
and in DNA forensics. However, real-world DNA sequences may comprise several
Gigabytes and the process of DNA analysis demands adequate computational
resources to be completed within a reasonable time. In this paper we present a
scalable approach for parallel DNA analysis that is based on Finite Automata,
and which is suitable for analyzing very large DNA segments. We evaluate our
approach for real-world DNA segments of mouse (2.7GB), cat (2.4GB), dog
(2.4GB), chicken (1GB), human (3.2GB) and turkey (0.2GB). Experimental results
on a dual-socket shared-memory system with 24 physical cores show speed-ups of
up to 17.6x. Our approach is up to 3x faster than a pattern-based parallel
approach that uses the RE2 library.


  We study equivariant coarse homology theories through an axiomatic framework.
To this end we introduce the category of equivariant bornological coarse spaces
and construct the universal equivariant coarse homology theory with values in
the category of equivariant coarse motivic spectra. As examples of equivariant
coarse homology theories we discuss equivariant coarse ordinary homology and
equivariant coarse algebraic $K$-homology. Moreover, we discuss the cone
functor, its relation with equivariant homology theories in equivariant
topology, and assembly and forget-control maps. This is a preparation for
applications in subsequent papers aiming at split-injectivity results for the
Farrell-Jones assembly map.


  In this paper, a mathematical framework for the coupling of gas networks to
electric grids is presented to describe in particular the transition from gas
to power. The dynamics of the gas flow are given by the isentropic Euler
equations, while the power flow equations are used to model the power grid. We
derive pressure laws for the gas flow that allow for the well-posedness of the
coupling and a rigorous treatment of solutions. For simulation purposes, we
apply appropriate numerical methods and show in a experimental study how
gas-to-power might influence the dynamics of the gas and power network,
respectively.


  The physiological tradition of biological research analyzes biological
systems using reduced descriptions much as an engineer uses a 'black box'
description of an amplifier. Simple models have been used by physiologists for
a very long time. Physiologists have successfully analyzed a broad range of
biological systems using a 'device-oriented' approach similar to the approach
an engineer would use to investigate her devices. The present generation views
biology through the powerful lenses of structural and (molecular) dynamic
analysis, understandably enough because of the beauty and power of the
analysis, and the ease of using these structures with present freely available
software. The problem is that these powerful lenses offer such magnification
that the engineering approach cannot be seen. High magnification means limited
field of view, because the (spatial) dynamic range cannot cover everything. The
function of the structures and molecular dynamics cannot be seen in the work of
many biologists, probably because function cannot be immediately seen in the
structures and molecular dynamics they compute. It is just as important for
biologists to measure the inputs and outputs of their systems as it is to
measure their structures. It seems clear, at least to one physiologist, that
this research will be catalyzed by assuming that most biological systems are
devices that can be analyzed with the same strategies one would use to analyze
engineering devices. Thinking today about your biological preparation as a
device tells you what experiments to do tomorrow. An important task for many of
us is to transmit the physiological tradition to the next generation of
biophysicists to help them adapt traditional questions to the new length scales
and techniques of molecular and atomic biology.


  We present a novel approach for improving particle filters for multi-target
tracking. The suggested approach is based on drift homotopy for stochastic
differential equations. Drift homotopy is used to design a Markov Chain Monte
Carlo step which is appended to the particle filter and aims to bring the
particle filter samples closer to the observations. Also, we present a simple
Metropolis Monte Carlo algorithm for tackling the target-observation
association problem. We have used the proposed approach on the problem of
multi-target tracking for both linear and nonlinear observation models. The
numerical results show that the suggested approach can improve significantly
the performance of a particle filter.


  This paper presents the arrangement of an in-pipe climbing robot that works
using a clever differential part to explore complex associations of lines.
Standard wheeled/continued in-pipe climbing robots are leaned to slip and take
while exploring in pipe turns. The mechanism helps in achieving the first
eventual outcome of clearing out slip and drag in the robot tracks during
development. The proposed differential comprehends the down to earth limits of
the standard two-yield differential, which is cultivated the underlying time
for a differential with three outcomes. The mechanism definitively changes the
track paces of the robot considering the powers applied on each track inside
the line association, by clearing out the prerequisite for any unique control.
The entertainment of the robot crossing in the line network in different
bearings and in pipe-turns without slip shows the proposed arrangement's
ampleness.


  We find that the fermion determinant is not generally positive in a class of
lattice actions recently constructed by Cohen et al. [hep-lat/0307012]; these
are actions that contain an exact lattice supersymmetry and have as their
target (continuum) theory (4,4) 2-dimensional super-Yang-Mills. We discuss the
implications of this finding for lattice simulations and give some preliminary
results for the phase of the determinant in the phase-quenched ensemble.


  We review a variety of theoretical and experimental results concerning
electronic band structure of superconducting materials based on FeSe
monolayers. Three type of systems are analyzed: intercalated FeSe systems
A_xFe_2Se_{2-x}S_x and [Li_{1-x}Fe_xOH]FeSe as well as the single FeSe layer
films on SrTiO_3 substrate. We present the results of detailed first principle
electronic band structure calculations for these systems together with
comparison with some experimental ARPES data. The electronic structure of these
systems is rather different from that of typical FeAs superconductors, which is
quite significant for possible microscopic mechanism of superconductivity. This
is reflected in the absence of hole pockets of the Fermi surface at
\Gamma-point in Brillouin zone, so that there are no "nesting" properties of
different Fermi surface pockets. LDA+DMFT calculations show that correlation
effects on Fe-3d states in the single FeSe layer are not that strong as in most
of FeAs systems. As a result, at present there is no theoretical understanding
of the formation of rather "shallow" electronic bands at M points. LDA
calculations show that the main difference in electronic structure of FeSe
monolayer on SrTiO_3 substrate from isolated FeSe layer is the presence of the
band of O-2p surface states of TiO_2 layer on the Fermi level together with
Fe-3d states, which may be important for understanding the enhanced T_c values
in this system. We briefly discuss the implications of our results for
microscopic models of superconductivity.


  Despite growing interest in applications based on natural customer support
conversations, there exist remarkably few publicly available datasets that
reflect the expected characteristics of conversations in these settings.
Existing task-oriented dialogue datasets, which were collected to benchmark
dialogue systems mainly in written human-to-bot settings, are not
representative of real customer support conversations and do not provide
realistic benchmarks for systems that are applied to natural data. To address
this gap, we introduce NatCS, a multi-domain collection of spoken customer
service conversations. We describe our process for collecting synthetic
conversations between customers and agents based on natural language phenomena
observed in real conversations. Compared to previous dialogue datasets, the
conversations collected with our approach are more representative of real
human-to-human conversations along multiple metrics. Finally, we demonstrate
potential uses of NatCS, including dialogue act classification and intent
induction from conversations as potential applications, showing that dialogue
act annotations in NatCS provide more effective training data for modeling real
conversations compared to existing synthetic written datasets. We publicly
release NatCS to facilitate research in natural dialog systems


  Feature-based format is the main data representation format used by machine
learning algorithms. When the features do not properly describe the initial
data, performance starts to degrade. Some algorithms address this problem by
internally changing the representation space, but the newly-constructed
features are rarely comprehensible. We seek to construct, in an unsupervised
way, new features that are more appropriate for describing a given dataset and,
at the same time, comprehensible for a human user. We propose two algorithms
that construct the new features as conjunctions of the initial primitive
features or their negations. The generated feature sets have reduced
correlations between features and succeed in catching some of the hidden
relations between individuals in a dataset. For example, a feature like $sky
\wedge \neg building \wedge panorama$ would be true for non-urban images and is
more informative than simple features expressing the presence or the absence of
an object. The notion of Pareto optimality is used to evaluate feature sets and
to obtain a balance between total correlation and the complexity of the
resulted feature set. Statistical hypothesis testing is used in order to
automatically determine the values of the parameters used for constructing a
data-dependent feature set. We experimentally show that our approaches achieve
the construction of informative feature sets for multiple datasets.


  Non-convex optimization problems have multiple local optimal solutions.
Non-convex optimization problems are commonly found in numerous applications.
One of the methods recently proposed to efficiently explore multiple local
optimal solutions without random re-initialization relies on the concept of
deflation. In this paper, different ways to use deflation in non-convex
optimization and nonlinear system solving are discussed. A simple, general and
novel deflation constraint is proposed to enable the use of deflation together
with existing nonlinear programming solvers or nonlinear system solvers. The
connection between the proposed deflation constraint and a minimum distance
constraint is presented. Additionally, a number of variations of deflation
constraints and their limitations are discussed. Finally, a number of
applications of the proposed methodology in the fields of approximate Bayesian
inference and topology optimization are presented.


  Previous analysis of AstroSat observations of the black hole system MAXI
J1535-571, have revealed the presence of a strong Quasi-Periodic Oscillation
(QPO) whose frequency is correlated with the high energy spectral index. Here,
we fit the spectra as emitted from a truncated disc with an inner hot corona,
study the QPO frequency dependence on other spectral parameters and model the
energy dependent r.m.s and time-lag of the QPO to identify the physical
spectral parameters whose variation are responsible for the QPO. The QPO
frequency is found to also correlate with the scattering fraction (i.e. the
fraction of the soft photons Comptonized) and its dependence on the accretion
rate and inner disc radii is consistent with it being the dynamical frequency.
The time-lag between the hard and soft photons is negative for QPO frequency >
2.2 Hz and is positive for lesser values, making this the second black hole
system to show this behaviour after GRS 1915+105. Modelling the energy
dependent time-lag and r.m.s requires correlated variation of the accretion
rate, inner disc radii and the coronal heating rate, with the latter having a
time-lag compared to the other two for QPO frequencies less than < 2.2 Hz and
which changes sign (i.e. the coronal heating variation precedes the accretion
rate one) for higher values. The implications of the results are discussed.


  Metaphor is a prominent linguistic device in human language and literature,
as they add color, imagery, and emphasis to enhance effective communication.
This paper introduces a large-scale high quality annotated Chinese Metaphor
Corpus, which comprises around 28K sentences drawn from a diverse range of
Chinese literary sources, such as poems, prose, song lyrics, etc. To ensure the
accuracy and consistency of our annotations, we introduce a comprehensive set
of guidelines. These guidelines address the facets of metaphor annotation,
including identifying tenors, vehicles, and grounds to handling the
complexities of similes, personifications, juxtapositions, and hyperboles.
Breaking tradition, our approach to metaphor generation emphasizes grounds and
their distinct features rather than the conventional combination of tenors and
vehicles. By integrating "ground" as a CoT (Chain of Thoughts) input, we are
able to generate metaphors that resonate more with real-world intuition. We
test generative models such as Belle, Baichuan, and Chinese-alpaca-33B using
our annotated corpus. These models are able to generate creative and fluent
metaphor sentences more frequently induced by selected samples from our
dataset, demonstrating the value of our corpus for Chinese metaphor research.
The code is available in
https://github.com/JasonShao55/Chinese_Metaphor_Explanation.


  Manipulating cables is challenging for robots because of the infinite degrees
of freedom of the cables and frequent occlusion by the gripper and the
environment. These challenges are further complicated by the dexterous nature
of the operations required for cable routing and assembly, such as weaving and
inserting, hampering common solutions with vision-only sensing. In this paper,
we propose to integrate tactile-guided low-level motion control with high-level
vision-based task parsing for a challenging task: cable routing and assembly on
a reconfigurable task board. Specifically, we build a library of tactile-guided
motion primitives using a fingertip GelSight sensor, where each primitive
reliably accomplishes an operation such as cable following and weaving. The
overall task is inferred via visual perception given a goal configuration
image, and then used to generate the primitive sequence. Experiments
demonstrate the effectiveness of individual tactile-guided primitives and the
integrated end-to-end solution, significantly outperforming the method without
tactile sensing. Our reconfigurable task setup and proposed baselines provide a
benchmark for future research in cable manipulation. More details and video are
presented in \url{https://helennn.github.io/cable-manip/}


  Dynamo action in planetary cores has been extensively studied in the context
of convectively-driven flows. We show in this letter that mechanical forcings,
namely tides, libration and precession, are also able to kinematically sustain
a magnetic field against ohmic diffusion. Previous attempts published in the
literature focused on the laminar response or considered idealized spherical
configurations. In contrast, we focus here on the developed turbulent regime
and we self-consistently solve the magnetohydrodynamic (MHD) equations in an
ellipsoidal container. Our results open new avenues of research in dynamo
theory where both convection and mechanical forcing can play a role,
independently or simultaneously.


  Omnidirectional and 360{\deg} images are becoming widespread in industry and
in consumer society, causing omnidirectional computer vision to gain attention.
Their wide field of view allows the gathering of a great amount of information
about the environment from only an image. However, the distortion of these
images requires the development of specific algorithms for their treatment and
interpretation. Moreover, a high number of images is essential for the correct
training of computer vision algorithms based on learning. In this paper, we
present a tool for generating datasets of omnidirectional images with semantic
and depth information. These images are synthesized from a set of captures that
are acquired in a realistic virtual environment for Unreal Engine 4 through an
interface plugin. We gather a variety of well-known projection models such as
equirectangular and cylindrical panoramas, different fish-eye lenses,
catadioptric systems, and empiric models. Furthermore, we include in our tool
photorealistic non-central-projection systems as non-central panoramas and
non-central catadioptric systems. As far as we know, this is the first reported
tool for generating photorealistic non-central images in the literature.
Moreover, since the omnidirectional images are made virtually, we provide
pixel-wise information about semantics and depth as well as perfect knowledge
of the calibration parameters of the cameras. This allows the creation of
ground-truth information with pixel precision for training learning algorithms
and testing 3D vision approaches. To validate the proposed tool, different
computer vision algorithms are tested as line extractions from dioptric and
catadioptric central images, 3D Layout recovery and SLAM using equirectangular
panoramas, and 3D reconstruction from non-central panoramas.


  In this work, we introduce a numerical method for approximating arbitrary
differential operators on vector fields in the weak form given point cloud data
sampled randomly from a $d$ dimensional manifold embedded in $\mathbb{R}^n$.
This method generalizes the local linear mesh method to the local curved mesh
method, thus, allowing for the estimation of differential operators with
nontrivial Christoffer symbols, such as the Bochner or Hodge Laplacians. In
particular, we leverage the potentially small intrinsic dimension of the
manifold $(d \ll n)$ to construct local parameterizations that incorporate both
local meshes and higher-order curvature information. The former is constructed
using low dimensional meshes obtained from local data projected to the tangent
spaces, while the latter is obtained by fitting local polynomials with the
generalized moving least squares. Theoretically, we prove the weak and spectral
convergence rates for the proposed method for the estimation of the Bochner
Laplacian. We provide numerical results supporting the theoretical convergence
rates for the Bochner and Hodge Laplacians on simple manifolds.


  Unitarity is the fundamental property of the S-matrix while its usage for a
scattering of unstable particles has been subtle as unstable particles do not
appear in the asymptotic states. Defining unstable-particle amplitudes as
residues of a higher-point amplitude at an appropriate complex pole, we find
unitarity equations for the 2-to-2 unstable-particle amplitudes from unitarity
and analyticity of stable-particle scattering amplitudes. The unstable-particle
unitarity equations take a form analogous to those of the stable-particle
amplitudes when the in and out states are chosen to be complex-conjugate
positions. In particular, as in the optical theorem, we find a positivity
constraint on a discontinuity of the amplitudes in a positive region of the
momentum transfer variable.


  Research investigating the origins of life usually focuses on exploring
possible life-bearing chemistries in the pre-biotic Earth, or else on synthetic
approaches. Little work has been done exploring fundamental issues concerning
the spontaneous emergence of life using only concepts (such as information and
evolution) that are divorced from any particular chemistry. Here, I advocate
studying the probability of spontaneous molecular self-replication as a
function of the information contained in the replicator, and the environmental
conditions that might enable this emergence. I show that (under certain
simplifying assumptions) the probability to discover a self-replicator by
chance depends exponentially on the rate of formation of the monomers. If the
rate at which monomers are formed is somewhat similar to the rate at which they
would occur in a self-replicating polymer, the likelihood to discover such a
replicator by chance is increased by many orders of magnitude. I document such
an increase in searches for a self-replicator within the digital life system
avida


  We present the results of electrical resistivity, ac specific heat, magnetic
susceptibility, X-ray absorption spectroscopy (XAS) and X-ray magnetic circular
dichroism (XMCD) of the ternary iron arsenide EuFe2As2 single crystal under
pressure. Applying pressure leads to a continuous suppression of the
antiferromagnetism associated with Fe moments and the antiferromagnetic
transition temperature becomes zero in the vicinity of a critical pressure Pc
~2.5-2.7 GPa. Pressure-induced re-entrant superconductivity, which is highly
sensitive to the homogeneity of the pressure, only appears in the narrow
pressure region in the vicinity of Pc due to the competition between
superconductivity and the antiferromagnetic ordering of Eu2+ moments. The
antiferromagnetic state of Eu2+ moments changes to the ferromagnetic state
above 6 GPa. We also found that the ferromagnetic order is suppressed with
further increasing pressure, which is connected with a valence change of Eu
ions.


  A weakly interacting dark matter candidate is difficult to detect at
high-energy colliders like the LHC, if its mass is close to, or higher than a
TeV. On the other hand, pair-annihilation of such particles may give rise to
$e^+ e^-$ pairs in dwarf spheroidal galaxies (dSph), which in turn can lead to
radio synchrotron signals that are detectable at the upcoming Square Kilometre
Array (SKA) telescope within a moderate observation time. We investigate the
circumstances under which this complementarity between collider and radio
signals of dark matter can be useful in probing physics beyond the standard
model of elementary particles. Both particle physics issues and the roles of
diffusion and electromagnetic energy loss of the $e^\pm$ are taken into
account. First, the criteria for detectability of trans-TeV dark matter are
analysed independently of the particle physics model(s) involved. We thereafter
use some benchmarks based on a popular scenario, namely, the minimal
supersymmetric standard model. It is thus shown that the radio flux from a dSph
like Draco should be observable in about 100 hours at the SKA, for dark matter
masses upto 4-8 TeV. In addition, the regions in the space spanned by
astrophysical parameters, for which such signals should be detectable at the
SKA, are marked out.


  We present a proof that all straight domains are locally
divided$\unicode{x2014}$thereby answering two open problems posed by Dobbs and
Picavet, which appeared in the survey "Open Problems in Commutative Ring
Theory" written by Cahen, Fontana, Frisch, and Glaz. In fact, we are able to
prove a stronger result: a prime ideal of a domain is straight if and only if
it is locally divided.


  This thesis summarises four years of research aiming at revealing the
prospects for detection of long-lived particles at the LHC. It contains results
of four projects, which have been published as independent articles. Each of
the projects investigated prospects for the detection of long-lived particles
predicted by one of the many BSM models, e.g. supersymmetry, seesaw, radiative
neutrino mass generation models, and simplified models. The sensitivity to New
Physics of ATLAS, CMS and (for the first time) MoEDAL experiments was
estimated.


  The artistic style of a painting is a subtle aesthetic judgment used by art
historians for grouping and classifying artwork. The recently introduced
`neural-style' algorithm substantially succeeds in merging the perceived
artistic style of one image or set of images with the perceived content of
another. In light of this and other recent developments in image analysis via
convolutional neural networks, we investigate the effectiveness of a
`neural-style' representation for classifying the artistic style of paintings.


  Recent years witnessed a growing interest in non-standard epistemic logics of
knowing whether, knowing how, knowing what, knowing why and so on. The new
epistemic modalities introduced in those logics all share, in their semantics,
the general schema of $\exists x \Box \phi$, e.g., knowing how to achieve
$\phi$ roughly means that there exists a way such that you know that it is a
way to ensure that $\phi$. Moreover, the resulting logics are decidable.
Inspired by those particular logics, in this work, we propose a very general
and powerful framework based on quantifier-free predicate language extended by
a new modality $\Box^x$, which packs exactly $\exists x \Box$ together. We show
that the resulting language, though much more expressive, shares many good
properties of the basic propositional modal logic over arbitrary models, such
as finite-tree-model property and van Benthem-like characterization w.r.t.\
first-order modal logic. We axiomatize the logic over S5 frames with intuitive
axioms to capture the interaction between $\Box^x$ and know-that operator in an
epistemic setting.


  This work proposes a clusterization algorithm called k-Morphological Sets
(k-MS), based on morphological reconstruction and heuristics. k-MS is faster
than the CPU-parallel k-Means in worst case scenarios and produces enhanced
visualizations of the dataset as well as very distinct clusterizations. It is
also faster than similar clusterization methods that are sensitive to density
and shapes such as Mitosis and TRICLUST. In addition, k-MS is deterministic and
has an intrinsic sense of maximal clusters that can be created for a given
input sample and input parameters, differing from k-Means and other
clusterization algorithms. In other words, given a constant k, a structuring
element and a dataset, k-MS produces k or less clusters without using random/
pseudo-random functions. Finally, the proposed algorithm also provides a
straightforward means for removing noise from images or datasets in general.


  Studies indicate that much of the software created today is not accessible to
all users, indicating that developers don't see the need to devote sufficient
resources to creating accessible software. Compounding this problem, there is a
lack of robust, easily adoptable educational accessibility material available
to instructors for inclusion in their curricula. To address these issues, we
have created five Accessibility Learning Labs (ALL) using an experiential
learning structure. The labs are designed to educate and create awareness of
accessibility needs in computing. The labs enable easy classroom integration by
providing instructors with complete educational materials including lecture
slides, activities, and quizzes. The labs are hosted on our servers and require
only a browser to be utilized.
  To demonstrate the benefit of our material and the potential benefits of our
experiential lab format with empathy-creating material, we conducted a study
involving 276 students in ten sections of an introductory computing course. Our
findings include: (I) The demonstrated potential of the proposed experiential
learning format and labs are effective in motivating and educating students
about the importance of accessibility (II) The labs are effective in informing
students about foundational accessibility topics (III) Empathy-creating
material is demonstrated to be a beneficial component in computing
accessibility education, supporting students in placing a higher value on the
importance of creating accessible software. Created labs and project materials
are publicly available on the project website: http://all.rit.edu


  We examine the experimental signature of a UV complete Supersymmetry (SUSY)
theory, the $G_2$-MSSM. This model predicts that only some superpartners will
be produced in possibly detectable amounts at LHC: $p p \rightarrow
\tilde{g}\tilde{g}$, $p p \rightarrow \tilde{\chi}^{\pm}_1
\tilde{\chi}^{\mp}_1$, and $p p \rightarrow \tilde{\chi}^{0}_2
\tilde{\chi}^{\pm}_1$. We exclude spectra with $m_{\tilde{g}} \approx1.5$ TeV.
While spectra with $m_{\tilde{g}} \approx1.7$ TeV and $m_{\tilde{g}}
\approx1.9$ TeV are currently allowed (contrary to what is often claimed), data
in hand could exclude these spectra. This is not in tension with reported
exclusion limits due to the difference in decay topologies between simplified
models and a UV motivated ($G_2$-MSSM) model.


  Giant low surface brightness galaxies (GLSBs) have flat discs extending up to
~100 kpc. Their formation is a puzzle for cosmological simulations in the cold
dark matter scenario. We suggest that GLSBs might be the final product of the
evolution of collisional ring galaxies. In fact, our simulations show that,
approximately 0.5-1.5 Gyr after the collision which led to the formation of the
ring galaxy, the ring keeps expanding and fades, while the disc becomes very
large (~100 kpc) and flat. At this stage, our simulated galaxies match many
properties of GLSBs (surface brightness profile, morphology, HI spectrum and
rotation curve).


  We present a study of the critical phenomena around the quantum critical
point in heavy-fermion systems. In the framework of the S=1/2 Kondo lattice
model, we introduce an extended decoupling scheme of the Kondo interaction
which allows one to treat the spin fluctuations and the Kondo effect on an
equal footing. The calculations, developed in a self-consistent one-loop
approximation, lead to the formation of a damped collective mode with a dynamic
exponent z=2 in the case of an antiferromagnetic instability. The system
displays a quantum-classical crossover at finite temperature depending how the
energy of the mode, on the scale of the magnetic correlation length, compares
to k_B T. The low temperature behavior, in the different regimes separated by
the crossover temperatures, is then discussed for both 2- and 3-dimensional
systems.


  Using fully kinetic simulations, we demonstrate that magnetic reconnection in
relativistic plasmas is highly efficient at accelerating particles through a
first-order Fermi process resulting from the curvature drift of particles in
the direction of the electric field induced by the relativistic flows. This
mechanism gives rise to the formation of hard power-law spectra in parameter
regimes where the energy density in the reconnecting field exceeds the rest
mass energy density $\sigma \equiv B^2/(4 \pi n m_ec^2) > 1$ and when the
system size is sufficiently large. In the limit $\sigma \gg 1$, the spectral
index approaches $p=1$ and most of the available energy is converted into
non-thermal particles. A simple analytic model is proposed which explains these
key features and predicts a general condition under which hard power-law
spectra will be generated from magnetic reconnection.


  The notion of non-classical correlations is a powerful contrivance for
explaining phenomena exhibited in quantum systems. It is well known, however,
that quantum systems are not free to explore arbitrary correlations---the
church of the smaller Hilbert space only accepts monogamous congregants. We
demonstrate how to characterize the limits of what is quantum mechanically
possible with a computable measure, entanglement negativity. We show that
negativity only saturates the standard linear monogamy inequality in trivial
cases implied by its monotonicity under LOCC, and derive a necessary and
sufficient inequality which, for the first time, is a non-linear higher degree
polynomial. For very large quantum systems, we prove that the negativity can be
distributed at least linearly for the tightest constraint and conjecture that
it is at most linear.


  We investigate ground-state and finite temperature properties of the
mixed-spin $(s, S)$ Kitaev model. When one of spins is half-integer and the
other is integer, we introduce two kinds of local symmetries, which results in
a macroscopic degeneracy in each energy level. Applying the exact
diagonalization to several clusters with $(s, S)=(1/2, 1)$, we confirm the
presence of this large degeneracy in the ground states, in contrast to the
conventional Kitaev models. By means of the thermal pure quantum state
technique, we calculate the specific heat, entropy, and spin-spin correlations
in the system. We find that in the mixed-spin Kitaev model with $(s, S)=(1/2,
1)$, at least, the double peak structure appears in the specific heat and the
plateau in the entropy at intermediate temperatures, indicating the existence
of the spin fractionalization. Deducing the entropy in the mixed-spin system
with $s, S\le 2$ systematically, we clarify that the smaller spin-$s$ is
responsible for the thermodynamic properties at higher temperatures.


  To detect plagiarism of any form, it is essential to have broad knowledge of
its possible forms and classes, and existence of various tools and systems for
its detection. Based on impact or severity of damages, plagiarism may occur in
an article or in any production in a number of ways. This survey presents a
taxonomy of various plagiarism forms and include discussion on each of these
forms. Over the years, a good number tools and techniques have been introduced
to detect plagiarism. This paper highlights few promising methods for
plagiarism detection based on machine learning techniques. We analyse the pros
and cons of these methods and finally we highlight a list of issues and
research challenges related to this evolving research problem.


  The gas dynamics in the Galactic disc is modeled by releasing an initially
axisymmetric SPH component in a completely self-consistent and symmetry-free 3D
N-body simulation of the Milky Way in which the stellar components display a
COBE-like bar. The density centre of the stellar bar wanders around the centre
of mass and the resulting gas flow is asymmetric and non-stationary,
reproducing the HI and CO l-V diagrams only at specific times and thus
suggesting a transient nature of the observed inner gas kinematics.
  The best matching models allow a new and coherent interpretation of the main
features standing out of the l-V data within the bar region. In particular, the
l-V traces of the prominent offset dustlanes leading the bar major axis in
early-type barred spirals can be unambiguously identified, and the 3-kpc arm
and its non-symmetric galactocentric opposite counterarm are the inner
prolongations of disc spiral arms passing round the bar and joining the
dustlanes at very different galactocentric distances. Bania's clump 1 and 2,
and another velocity-elongated feature near l= 5.5 deg, are interpreted as gas
lumps crossing the dustlane shocks. The terminal velocity peaks near l=+/- 2.5
deg are produced by gas along the dustlanes and not by the trace of the cusped
x1 orbit, which passes farther away from the Galactic centre. According to
these models and to related geometrical constraints, the Galactic bar must have
an inclination angle of 25+/-4 deg, a corotation radius of 4.0-4.5 kpc and a
face-on axis ratio b/a=0.6.


  In this work, we study open quantum random walks, as described by S. Attal et
al. These objects are given in terms of completely positive maps acting on
trace-class operators, leading to one of the simplest open quantum versions of
the recurrence problem for classical, discrete-time random walks. This work
focuses on obtaining criteria for site recurrence of nearest-neighbor,
homogeneous walks on the integer line, with the description presented here
making use of recent results of the theory of open walks, most particularly
regarding reducibility properties of the operators involved. This allows us to
obtain a complete criterion for site recurrence in the case for which the
internal degree of freedom of each site (coin space) is of dimension 2. We also
present the analogous result for irreducible walks with an internal degree of
arbitrary finite dimension and the absorption problem for walks on the
semi-infinite line.


  Federated learning uses a set of techniques to efficiently distribute the
training of a machine learning algorithm across several devices, who own the
training data. These techniques critically rely on reducing the communication
cost -- the main bottleneck -- between the devices and a central server.
Federated learning algorithms usually take an optimization approach: they are
algorithms for minimizing the training loss subject to communication (and
other) constraints. In this work, we instead take a Bayesian approach for the
training task, and propose a communication-efficient variant of the Langevin
algorithm to sample a posteriori. The latter approach is more robust and
provides more knowledge of the \textit{a posteriori} distribution than its
optimization counterpart. We analyze our algorithm without assuming that the
target distribution is strongly log-concave. Instead, we assume the weaker log
Sobolev inequality, which allows for nonconvexity.


  We obtain predictions for the neutrino masses, the effective Majorana mass in
neutrinoless double beta decay and for the rates of the lepton flavor violating
processes $\mu\rightarrow e + \gamma$, $\tau \rightarrow e + \gamma$ and $ \tau
\rightarrow \mu + \gamma$ in a SUSY $SU(5) \times T^{\prime}$ Model of flavour,
which gives rise to realistic masses and mixing patterns for quarks and
leptons.


  This work studies the design of safe control policies for large-scale
non-linear systems operating in uncertain environments. In such a case, the
robust control framework is a principled approach to safety that aims to
maximize the worst-case performance of a system. However, the resulting
optimization problem is generally intractable for non-linear systems with
continuous states. To overcome this issue, we introduce two tractable methods
that are based either on sampling or on a conservative approximation of the
robust objective. The proposed approaches are applied to the problem of
autonomous driving.


  We study quantum spin-1/2 Heisenberg ferromagnetic chains with dilute, random
antiferromagnetic impurity bonds with modified spin-wave theory. By describing
thermal excitations in the language of spin waves, we successfully observe a
low-temperature Curie susceptibility due to formation of large spin clusters
first predicted by the real-space renormalization-group approach, as well as a
crossover to a pure ferromagnetic spin chain behavior at intermediate and high
temperatures. We compare our results of the modified spin-wave theory to
quantum Monte Carlo simulations.


  The correlations involving the long-GRB prompt emission energy represent a
new key to understand the GRB physics. These correlations have been proved to
be the tool which makes long-GRBs a new class of standard candles. Gamma Ray
Bursts, being very powerful cosmological sources detected in the hard X-ray
band, represent a new tool to investigate the Universe in a redshift range
which is complementary to that covered by other cosmological probes (SNIa and
CMB). A review of the Ep-Eiso, Ep-Egamma, Ep-Eiso-tjet, Ep-Liso-T0.45
correlations is presented. Open issues related to these correlations (e.g.
presence of outliers and selection effects) and to their use for cosmographic
purposes (e.g. dependence on model assumptions) are discussed. Finally, the
relevance of thermal components in GRB spectra is discussed in the light of
some of the models recently proposed for the interpretation of the
spectral-energy correlations.


  We report an experiment to check the identification of a set of words in
popular written Portuguese with two versions of a computational dictionary of
Brazilian Portuguese, DELAF PB 2004 and DELAF PB 2015. This dictionary is
freely available for use in linguistic analyses of Brazilian Portuguese and
other researches, which justifies critical study. The vocabulary comes from the
PorPopular corpus, made of popular newspapers Di{\'a}rio Ga{\'u}cho (DG) and
Massa! (MA). From DG, we retained a set of texts with 984.465 words (tokens),
published in 2008, with the spelling used before the Portuguese Language
Orthographic Agreement adopted in 2009. From MA, we examined papers of 2012,
2014 e 2015, with 215.776 words (tokens), all with the new spelling. The
checking involved: a) generating lists of words (types) occurring in DG and MA;
b) comparing them with the entry lists of both versions of DELAF PB; c)
assessing the coverage of this vocabulary; d) proposing ways of incorporating
the items not covered. The results of the work show that an average of 19% of
the types in DG were not found in DELAF PB 2004 or 2015. In MA, this average is
13%. Switching versions of the dictionary affected slightly the performance in
recognizing the words.


  In this article we study the action of the non-planar two-loop dilatation
operator in an SU(2)*SU(2) sub-sector of the ABJ Chern-Simons-matter theory.
The gauge invariant operators we consider are the restricted Schur polynomials.
As in ABJM theory, there is a limit in which the spectrum reduces to a set of
decoupled harmonic oscillators, indicating integrability in the large M and N
double limit of the theory. We then consider parity transformations on the
gauge invariant operators. In this case the non-planar anomalous dimensions
break parity invariance. Our analysis shows that (M-N) is related to the
holonomy in the string theory, confirming one of the main features of the
theory and its string dual. Furthermore, in the limit where ABJ theory reduces
to ABJM theory, parity invariance is restored.


  We present a comprehensive framework for the study of the size and large
intersection properties of sets of limsup type that arise naturally in
Diophantine approximation and multifractal analysis. This setting encompasses
the classical ubiquity techniques, as well as the mass and the large
intersection transference principles, thereby leading to a thorough description
of the properties in terms of Hausdorff measures and large intersection classes
associated with general gauge functions. The sets issued from eutaxic sequences
of points and optimal regular systems may naturally be described within this
framework. The discussed applications include the classical homogeneous and
inhomogeneous approximation, the approximation by algebraic numbers, the
approximation by fractional parts, the study of uniform and Poisson random
coverings, and the multifractal analysis of L{\'e}vy processes.


  We present two explicit combinatorial constructions of finitely summable
reduced "Gamma"-elements $\gamma_r\,\in\,KK(C^*_r(\Gamma),{\mathbb C})$ for any
word-hyperbolic group $(\Gamma,S)$ and obtain summability bounds for them in
terms of the cardinality of the generating set $S\subset\Gamma$ and the
hyperbolicity constant of the associated Cayley graph.


  Suppose $E$ is an elliptic curve over $\mathbb{Q}$ and $\chi$ is a Dirichlet
character. We use statistical properties of modular symbols to estimate
heuristically the probability that $L(E,\chi,1) = 0$. Via the Birch and
Swinnerton-Dyer conjecture, this gives a heuristic estimate of the probability
that the Mordell-Weil rank grows in abelian extensions of $\mathbb{Q}$. Using
this heuristic we find a large class of infinite abelian extensions $F$ where
we expect $E(F)$ to be finitely generated.
  Our work was inspired by earlier conjectures (based on random matrix
heuristics) due to David, Fearnley, and Kisilevsky. Where our predictions and
theirs overlap, the predictions are consistent.


  We present a simple method for narrowing the intrinsic Lorentzian linewidth
of a commercial ultraviolet grating extended-cavity diode laser (TOPTICA DL
Pro) using weak optical feedback from a long external cavity. We achieve a
suppression in frequency noise spectral density of 20 dB measured at
frequencies around 1 MHz, corresponding to the narrowing of the intrinsic
Lorentzian linewidth from 200 kHz to 2 kHz. The system is suitable for
experiments requiring a tunable ultraviolet laser with narrow linewidth and low
high-frequency noise, such as precision spectroscopy, optical clocks, and
quantum information science experiments.


  This paper introduces the Consumer Feedback Insight & Prediction Platform, a
system leveraging machine learning to analyze the extensive Consumer Financial
Protection Bureau (CFPB) Complaint Database, a publicly available resource
exceeding 4.9 GB in size. This rich dataset offers valuable insights into
consumer experiences with financial products and services. The platform itself
utilizes machine learning models to predict two key aspects of complaint
resolution: the timeliness of company responses and the nature of those
responses (e.g., closed, closed with relief etc.). Furthermore, the platform
employs Latent Dirichlet Allocation (LDA) to delve deeper, uncovering common
themes within complaints and revealing underlying trends and consumer issues.
This comprehensive approach empowers both consumers and regulators. Consumers
gain valuable insights into potential response wait times, while regulators can
utilize the platform's findings to identify areas where companies may require
further scrutiny regarding their complaint resolution practices.


  We propose a new type of hybrid systems formed by conventional semiconductor
nanostructures with the addition of remote insulating layers, where the
electron-hole interaction is enhanced by combining quantum and dielectric
confinement over different length scales. Due to the polarization charges
induced by the dielectric mismatch at the semiconductor/insulator interfaces,
we show that the exciton binding energy can be more than doubled. For
conventional III-V quantum wires such remote dielectric confinement allows
exciton binding at room temperature.


  Motivated by the recent experiments that reported the discovery of vortex
Majorana bound states (vMBSs) in iron-based superconductors, we establish a
portable scheme to unveil the non-Abelian statistics of vMBSs using normal
fermionic modes. The unique non-Abelian statistics of vMBSs is characterized by
the charge flip signal of the fermions that can be easily read out through the
charge sensing measurement. In particular, the charge flip signal will be
significantly suppressed for strong hybridized vMBSs or trivial vortex modes,
which efficiently identifies genuine vMBSs. To eliminate the error induced by
the unnecessary dynamical evolution of the fermionic modes, we further propose
a correction strategy by continually reversing the energy of the fermions,
reminiscent of the quantum Zeno effect. Finally, we establish a feasible
protocol to perform non-Abelian braiding operations on vMBSs.


  The observation of a superconducting phase, an intertwined insulating phase,
and a continuous transition between the two at a commensurate filling of
$\nu=1$ in bilayers of twisted WSe$_2$ (tWSe$_2$) at $\theta=3.65^0$ raises a
number of intriguing questions about the origin of this phenomenology. Starting
with a simplified three-orbital model of tWSe$_2$, including an on-site and
nearest-neighbor density-density interactions, as well as a chiral-exchange
interaction, we discuss the possibility of a displacement-field induced direct
superconductor to quantum spin-liquid Mott insulator transition at $\nu=1$
using parton mean-field theory. We discuss the nature of these correlated
insulators, their expected evolution with the displacement-field, and their
phenomenological properties. Further experiments will likely help unravel the
mysteries tied to this fascinating experimental platform.


  The concepts of machine homomorphism and machine products developed in the
automata theory literature in the 1960s are more relevant to concurrent systems
than is acknowledged in the process algebra literature and offer a
sophisticated mathematical basis for understanding concurrent systems.


  We propose a censored quantile regression estimator motivated by unbiased
estimating equations. Under the usual conditional independence assumption of
the survival time and the censoring time given the covariates, we show that the
proposed estimator is consistent and asymptotically normal. We develop an
efficient computational algorithm which uses existing quantile regression code.
As a result, bootstrap-type inference can be efficiently implemented. We
illustrate the finite-sample performance of the proposed method by simulation
studies and analysis of a survival data set.


  The results of the FORS and ISAAC Science Verification of the FORS and ISAAC
instruments at the VLT ANTU/UT1 are described. The following observations have
been carried out: 1) the Cluster Deep Field MS1008.1-1224 2) the Antlia dwarf
spheroidal Galaxy 3) multiple Object Spectroscopy of Lyman break galaxies in
the AXAF and Hubble Deep Field South 4) ISAAC IR Spectroscopy of a
gravitationally magnified galaxy at z=2.72. The data have been made public for
the ESO community and, in the case of HDF-S, worldwide.


  We generalize the recently developed inchworm quantum Monte Carlo method to
the full Keldysh contour with forward, backward, and equilibrium branches to
describe the dynamics of strongly correlated impurity problems with time
dependent parameters. We introduce a method to compute Green's functions,
spectral functions, and currents for inchworm Monte Carlo and show how
systematic error assessments in real time can be obtained. We then illustrate
the capabilities of the algorithm with a study of the behavior of quantum
impurities after an instantaneous voltage quench from a thermal equilibrium
state.


  As a result of the interaction of rapid development and competition in
information technologies, the reliability of a network and how solid it remains
is important. It is called the hat vulnerability of the network to measure the
endurance of the network until communication is interrupted by the
deterioration of the connection lines between some centers or centers in a
network. The centers of the network can be modeled such that the vertex of the
network and the connecting lines are the distances of the graph, while
investigating the strength of a communication network against disturbances that
may occur in the centers or connecting lines. Networks can be modeled with
graphs and there are several parameters to measure the vulnerability of these
graphs. In this study, the average binding number was studied. In this paper,
some bounds of the average binding number of some special graphs are obtained.
Finally, the algorithm for calculation of average binding numbers of graphs is
given. The algorithms of these parameters are developed that calculates for any
graph and the algorithms are explained. The algorithms are analyzed by code
metrics and their usefulness is shown.


  We show that the Cauchy--Born model of a single-species 2-lattice is second
order if the atomistic and continuum kinematics are connected in a novel way.
Our proof uses a generalization to 2-lattices of the point symmetry of Bravais
lattices. Moreover, by identifying similar symmetries in multi-species pair
interaction models, we construct a new stored energy density, using
shift-gradients but not strain gradients, that is also second order accurate.
These results can be used to develop highly accurate continuum models and
atomistic/continuum coupling methods for materials such as graphene, hcp
metals, and shape memory alloys.


  Recent results than an assembly of Fermions below the Fermi temperature would
exhibit anamolous semionic behaviour are examined in the context of assoociated
magnetic fields.


  The Dine-Seiberg-Thomas model (DSTM) is the simplest version of the new
physics beyond the minimal supersymmetric standard model (MSSM), in the sense
that its Higgs sector has just two dimension-five operators, which are obtained
from the power series of the energy scale for the new physics in the effective
action analysis. We study the possibility of spontaneous CP violation in the
Higgs sector of the DSTM, which consists of two Higgs doublets. We find that
the CP violation may be triggered spontaneously by a complex phase, obtained as
the relative phase between the vacuum expectation values of the two Higgs
doublets. At the tree level, for a reasonably established parameter region, the
masses of the three neutral Higgs bosons and their corresponding coupling
coefficients to a pair of $Z$ bosons in the DSTM are calculated such that the
results are inconsistent with the experimental constraint by the LEP data.
Thus, the LEP2 data exclude the possibility of spontaneous CP violation in the
DSTM at the tree level. On the other hand, we find that, for a wide area in the
parameter region, the CP symmetry may be broken spontaneously in the Higgs
sector of the DSTM at the one-loop level, where top quark and scalar top quark
loops are taken into account. The upper bound on the radiatively corrected mass
of the lightest neutral Higgs boson of the DSTM is about 87 GeV, in the
spontaneous CP violation scenario. We confirm that the LEP data does not
exclude this numerical result.


  Electronic Health Record (EHR) coding involves automatically classifying EHRs
into diagnostic codes. While most previous research treats this as a
multi-label classification task, generating probabilities for each code and
selecting those above a certain threshold as labels, these approaches often
overlook the challenge of identifying complex diseases. In this study, our
focus is on detecting complication diseases within EHRs.
  We propose a novel coarse-to-fine ICD path generation framework called the
Copy Recurrent Neural Network Structure Network (CRNNet), which employs a Path
Generator (PG) and a Path Discriminator (PD) for EHR coding. By using RNNs to
generate sequential outputs and incorporating a copy module, we efficiently
identify complication diseases. Our method achieves a 57.30\% ratio of complex
diseases in predictions, outperforming state-of-the-art and previous
approaches.
  Additionally, through an ablation study, we demonstrate that the copy
mechanism plays a crucial role in detecting complex diseases.


  We present deep radio observations of the most distant complete quasar sample
drawn from the Sloan Digital Sky Survey. Combining our new data with those from
literature we obtain a sample which is ~100 per cent complete down to S_1.4GHz
= 60 \mu Jy over the redshift range 3.8 < z < 5. The fraction of radio
detections is relatively high (~43 per cent), similar to what observed locally
in bright optical surveys. Even though the combined radio and optical
properties of quasars remain overall unchanged from z ~ 5 to the local
Universe, there is some evidence for a slight over-abundance of radio-loud
sources at the highest redshifts when compared with the lower-z regime.
  Exploiting the deep radio VLA observations we present the first attempt to
directly derive the radio luminosity function of bright quasars at z ~ 4. The
unique depth -- both in radio and optical -- allows us to thoroughly explore
the population of optically bright FR~II quasars up to z ~ 5 and opens a window
on the behaviour of the brightest FR~I sources. A close investigation of the
space density of radio loud quasars also suggests a differential evolution,
with the more luminous sources showing a less pronounced cut-off at high z when
compared with the less luminous ones.


  Ontologies can be a powerful tool for structuring knowledge, and they are
currently the subject of extensive research. Updating the contents of an
ontology or improving its interoperability with other ontologies is an
important but difficult process. In this paper, we focus on the presence of
vague concepts, which are pervasive in natural language, within the framework
of formal ontologies. We will adopt a framework in which vagueness is captured
via numerical restrictions that can be automatically adjusted. Since updating
vague concepts, either through ontology alignment or ontology evolution, can
lead to inconsistent sets of axioms, we define and implement a method to
detecting and repairing such inconsistencies in a local fashion.


  A conjecture for higher order separation on generic rational surfaces with
some new results about standard divisors.


  Let $G$ be a simply-connected, simple compact Lie group of type
$\{n_{1},\ldots,n_{\ell}\}$, where $n_{1}\le\cdots \le n_{\ell}$. Let
$\mathcal{G}_k$ be the gauge group of the principal $G$-bundle
(namedright{P}{}{S^{4}}) whose isomorphism class is determined by the the
second Chern class having value $k\in\mathbb{Z}$. We calculate the mod-$p$
homology of the classifying space $B\mathcal{G}_k$ provided that $n_{\ell}<p-1$
and $p$ does not divide $k$.


  We present a systematic procedure to renormalize the symplectic potential of
the electromagnetic field at null infinity in Minkowski space. We work in
$D\geq6$ spacetime dimensions as a toy model of General Relativity in $D\geq4$
dimensions. Total variation counterterms as well as corner counterterms are
both subtracted from the symplectic potential to make it finite. These
counterterms affect respectively the action functional and the Hamiltonian
symmetry generators. The counterterms are local and universal. We analyze the
asymptotic equations of motion and identify the free data associated with the
renormalized canonical structure along a null characteristic. This allows the
construction of the asymptotic renormalized charges whose Ward identity gives
the QED soft theorem, supporting the physical viability of the renormalization
procedure. We touch upon how to extend our analysis to the presence of
logarithmic anomalies and upon how our procedure compares to holographic
renormalization.


  Spontaneous strain and spontaneous folding of thin nanoplatelets are known
phenomena whose microscopic mechanisms are still debating. In this work,
first-principles calculations are used to study the mechanical stresses that
arise in Janus CdSe nanoplatelets and result in their spontaneous strain.
Calculations reveal the existence of three microscopic mechanisms of this
phenomenon. Two bulk mechanisms are associated with the inverse piezoelectric
effect in an electric field created by the difference in electronegativities of
ligands and by the depolarizing field resulting from the difference in the
potential jumps in electrical double layers on the surfaces of nanoplatelets.
These mechanisms account for 5-25% of the observed effect. The third mechanism
is associated with the surface strain of nanoplatelets by bridging bonds, and
its influence is predominant. It is shown that the latter mechanism cause
spontaneous folding of thin CdSe nanoplatelets and, depending on the values of
surface stresses and lateral orientation of nanoplatelets, can result in
formation of their experimentally observed structures such as scrolls, spirals,
and twisted ribbons.


  We introduce Situation Monitor, a novel zero-shot Out-of-Distribution (OOD)
detection approach for transformer-based object detection models to enhance
reliability in safety-critical machine learning applications such as autonomous
driving. The Situation Monitor utilizes the Diversity-based Budding Ensemble
Architecture (DBEA) and increases the OOD performance by integrating a
diversity loss into the training process on top of the budding ensemble
architecture, detecting Far-OOD samples and minimizing false positives on
Near-OOD samples. Moreover, utilizing the resulting DBEA increases the model's
OOD performance and improves the calibration of confidence scores, particularly
concerning the intersection over union of the detected objects. The DBEA model
achieves these advancements with a 14% reduction in trainable parameters
compared to the vanilla model. This signifies a substantial improvement in
efficiency without compromising the model's ability to detect OOD instances and
calibrate the confidence scores accurately.


  In this paper, we introduce the MIDI Degradation Toolkit (MDTK), containing
functions which take as input a musical excerpt (a set of notes with pitch,
onset time, and duration), and return a "degraded" version of that excerpt with
some error (or errors) introduced. Using the toolkit, we create the Altered and
Corrupted MIDI Excerpts dataset version 1.0 (ACME v1.0), and propose four tasks
of increasing difficulty to detect, classify, locate, and correct the
degradations. We hypothesize that models trained for these tasks can be useful
in (for example) improving automatic music transcription performance if applied
as a post-processing step. To that end, MDTK includes a script that measures
the distribution of different types of errors in a transcription, and creates a
degraded dataset with similar properties. MDTK's degradations can also be
applied dynamically to a dataset during training (with or without the above
script), generating novel degraded excerpts each epoch. MDTK could also be used
to test the robustness of any system designed to take MIDI (or similar) data as
input (e.g. systems designed for voice separation, metrical alignment, or chord
detection) to such transcription errors or otherwise noisy data. The toolkit
and dataset are both publicly available online, and we encourage contribution
and feedback from the community.


  We present a novel preconditioning technique for proximal optimization
methods that relies on graph algorithms to construct effective preconditioners.
Such combinatorial preconditioners arise from partitioning the graph into
forests. We prove that certain decompositions lead to a theoretically optimal
condition number. We also show how ideal decompositions can be realized using
matroid partitioning and propose efficient greedy variants thereof for
large-scale problems. Coupled with specialized solvers for the resulting scaled
proximal subproblems, the preconditioned algorithm achieves competitive
performance in machine learning and vision applications.


  The aurorae of Uranus were recently detected in the far ultraviolet with the
Hubble Space Telescope (HST) providing a new, so far unique, means to remotely
study the asymmetric Uranian magnetosphere from Earth. We analyze here two new
HST Uranus campaigns executed in Sept. 2012 and Nov. 2014 with different
temporal coverage and under variable solar wind conditions numerically
predicted by three different MHD codes. Overall, HST images taken with the
Space Telescope Imaging Spectrograph reveal auroral emissions in three pairs of
successive images (one pair acquired in 2012 and two in 2014), hence six
additional auroral detections in total, including the most intense Uranian
aurorae ever seen with HST. The detected emissions occur close the expected
arrival of interplanetary shocks. They appear as extended spots at southern
latitudes, rotating with the planet. They radiate 5-24 kR and 1.3-8.8 GW of
ultraviolet emission from H$_2$, last for tens of minutes and vary on
timescales down to a few seconds. Fitting the 2014 observations with model
auroral ovals constrains the longitude of the southern (northern) magnetic pole
to 104+\-26{\deg} (284-\-26{\deg}) in the Uranian Longitude System. We suggest
that the Uranian near-equinoctial aurorae are pulsed cusp emissions possibly
triggered by large-scale magnetospheric compressions.


  Hyperbolicity plays an important role in the study of dynamical systems, and
is a key concept in the iteration of rational functions of one complex
variable. Hyperbolic systems have also been considered in the study of
transcendental entire functions. There does not appear to be an agreed
definition of the concept in this context, due to complications arising from
the non-compactness of the phase space.
  In this article, we consider a natural definition of hyperbolicity that
requires expanding properties on the preimage of a punctured neighbourhood of
the isolated singularity. We show that this definition is equivalent to another
commonly used one: a {\tef} is hyperbolic if and only if its postsingular set
is a compact subset of the Fatou set. This leads us to propose that this notion
should be used as the general definition of hyperbolicity in the context of
entire functions, and, in particular, that speaking about hyperbolicity makes
sense only within the \emph{Eremenko-Lyubich class} $\mathcal{B}$ of
transcendental entire functions with a bounded set of singular values.
  We also considerably strengthen a recent characterisation of the class
$\mathcal{B}$, by showing that functions outside of this class cannot be
expanding with respect to a metric whose density decays at most polynomially.
In particular, this implies that no transcendental entire function can be
expanding with respect to the spherical metric. Finally we give a
characterisation of an analogous class of functions analytic in a hyperbolic
domain.


  Computer systems such as storage systems normally require transparent
white-box algorithms that are interpretable for human experts. In this work, we
propose a learning-aided heuristic design method, which automatically generates
human-readable strategies from Deep Reinforcement Learning (DRL) agents. This
method benefits from the power of deep learning but avoids the shortcoming of
its black-box property. Besides the white-box advantage, experiments in our
storage productions resource allocation scenario also show that this solution
outperforms the systems default settings and the elaborately handcrafted
strategy by human experts.


  We present theoretical predictions concerning horizontal branch stars in
globular clusters, including RR Lyrae variables, as derived from synthetic
procedures collating evolutionary and pulsational constraints. On this basis,
we explore the predicted behavior of the pulsators as a function of the
horizontal branch morphology and over the metallicity range Z=0.0001 to 0.006,
revealing an encouraging concordance with the observed distribution of
fundamentalised periods with metallicity. Theoretical relations connecting
periods to K magnitudes and BV or VI Wesenheit functions are presented, both
appearing quite independent of the horizontal branch morphology only with Z
greater or equal than 0.001. Predictions concerning the parameter R are also
discussed and compared under various assumptions about the horizontal branch
reference luminosity level.