  Today's propositional satisfiability (SAT) solvers are extremely powerful and
can be used as an efficient back-end for solving NP-complete problems. However,
many fundamental problems in knowledge representation and reasoning are located
at the second level of the Polynomial Hierarchy or even higher, and hence
polynomial-time transformations to SAT are not possible, unless the hierarchy
collapses. Recent research shows that in certain cases one can break through
these complexity barriers by fixed-parameter tractable (fpt) reductions which
exploit structural aspects of problem instances in terms of problem parameters.
In this paper we develop a general theoretical framework that supports the
classification of parameterized problems on whether they admit such an
fpt-reduction to SAT or not. This framework is based on several new
parameterized complexity classes. As a running example, we use the framework to
classify the complexity of the consistency problem for disjunctive answer set
programming, with respect to various natural parameters. We underpin the
robustness of our theory by providing a characterization of the new complexity
classes in terms of weighted QBF satisfiability, alternating Turing machines,
and first-order model checking. In addition, we provide a compendium of
parameterized problems that are complete for the new complexity classes,
including problems related to Knowledge Representation and Reasoning, Logic,
and Combinatorics.


  We investigate the causality and stability of three different relativistic
dissipative fluid-dynamical formulations emerging from a system of classical,
ultra-relativistic scalar particles self-interacting via a quartic potential.
For this particular interaction, all transport coefficients of Navier-Stokes,
Bemfica-Disconzi-Noronha-Kovtun and second-order transient theories can be
computed in analytical form. We first show that Navier-Stokes theory is acausal
and unstable regardless of the matching conditions. On the other hand, BDNK
theory can be linearly causal and stable for a particular set of matching
choices that does not contain the so-called exotic Eckart prescription. In
particular, using the Li\'enard-Chipart criterion, we obtain a set of
sufficient conditions that guarantee the stability of the theory. Last,
second-order transient hydrodynamic theory in Landau matching is shown to be
linearly causal and stable.


  We consider Thue equations of the form $ax^k+by^k = 1$, and assuming the
truth of the $abc$-conjecture, we show that almost all locally soluble Thue
equations of degree at least three violate the Hasse principle. A similar
conclusion holds true for Fermat equations $ax^k+by^k+cz^k = 0$ of degree at
least six.


  Fast and accurate optimization and simulation is widely becoming a necessity
for large scale transmission resiliency and planning studies such as N-1 SCOPF,
batch contingency solvers, and stochastic power flow. Current commercial tools,
however, prioritize speed of convergence over accuracy by relying on initial
conditions that are taken from the steady state solution of similar network
configurations that are not guaranteed to lie within a convex region of a valid
solution. In this paper we introduce a globally convergent algorithm to
facilitate fast and accurate AC steady state simulation and optimization based
on prior knowledge from similar networks. The approach uses a homotopy method
that gradually and efficiently translates a previously known network
configuration to the current network configuration. The proposed formulation is
highly scalable, and its efficacy is demonstrated for resiliency study and
optimization of large networks up to 70k buses.


  We use the variational method for the Sturm-Liouville eigenvalue problem to
analytically calculate some properties of holographic superconductors with
Gauss-Bonnet gravity in probe limit. By studying the holographic p-wave and
s-wave superconductors in (3+1)-dimensional boundary field theories, it is
found that near the critical temperature, the critical exponent of the
condensation is 1/2 which is the universal value in mean-field theory. We also
find that when Gauss-Bonnet coefficients grow bigger the operators on the
boundary field theory will be harder to condense. These are in good agreement
with the numerical results.


  The past several years has witnessed a surge of interest in organometallic
trihalide perovskites, which are at the heart of the new generation of
solid-state solar cells. Here, we calculated the static conductivity of charged
domain walls in n- and p- doped organometallic uniaxial ferroelectric
semiconductor perovskite CH3NH3PbI3 using the Landau-Ginzburg-Devonshire (LGD)
theory. We find that due to the charge carrier accumulation, the static
conductivity may drastically increase at the domain wall by 3-4 orders of
magnitude in comparison with conductivity through the bulk of the material.
Also, a two-dimensional degenerated gas of highly mobile charge carriers could
be formed at the wall. The high values of conductivity at domain walls and
interfaces explain high efficiency in organometallic solution-processed
perovskite films which contains lots of different point and extended defects.
These results could suggest new routes to enhance the performance of this
promising class of novel photovoltaic materials.


  We introduce the notion of pseudohermitian k-curvature, which is a natural
extension of the Webster scalar curvature, on an orientable manifold endowed
with a strictly pseudoconvex pseudohermitian structure (referred here as a CR
manifold) and raise the k-Yamabe problem on a compact CR manifold. When k=1,
the problem was proposed and partially solved by Jerison and Lee for CR
manifolds non-locally CR-equivalent to the CR sphere. For k > 1, the problem
can be translated in terms of the study of a fully nonlinear equation of type
complex k-Hessian. We provide some partial answers related to the CR k-Yamabe
problem. We establish that its solutions with null Cotton tensor are critical
points of a suitable geometric functional constrained to pseudohermitian
structures of unit volume. Thanks to this variational property, we establish a
Obata type result for the problem and also compute the infimum of the
functional on the CR sphere. Furthermore, we show that this value is an upper
bound for the corresponding one on any compact CR manifolds and, assuming the
CR Yamabe invariant is positive, we prove that such an upper bound is only
attained for compact CR manifolds locally CR-equivalent to the CR sphere. In
the Riemannian field, recent advances have been produced in a series of
outstanding works.


  In the preceding paper, the structure and thermodynamics of a given quantum
system was represented by a corresponding classical system having an effective
temperature, local chemical potential, and pair potential. Here, that formal
correspondence is implemented approximately for applications to two quantum
systems. The first is the electron gas (jellium) over a range of temperatures
and densities. The second is an investigation of quantum effects on shell
structure for charges confined by a harmonic potential.


  We present an $rp$-adaptation strategy for high-fidelity simulation of
compressible inviscid flows with shocks. The mesh resolution in regions of flow
discontinuities is increased by using a variational optimiser to $r$-adapt the
mesh and cluster degrees of freedom there. In regions of smooth flow, we
locally increase or decrease the local resolution through increasing or
decreasing the polynomial order of the elements, respectively. This dual
approach allows us to take advantage of the strengths of both methods for best
computational performance, thereby reducing the overall cost of the simulation.
The adaptation workflow uses a sensor for both discontinuities and smooth
regions that is cheap to calculate, but the framework is general and could be
used in conjunction with other feature-based sensors or error estimators. We
demonstrate this proof-of-concept using two geometries at transonic and
supersonic flow regimes. The method has been implemented in the open-source
spectral/$hp$ element framework $Nektar++$, and its dedicated high-order mesh
generation tool $NekMesh$. The results show that the proposed $rp$-adaptation
methodology is a reasonably cost-effective way of improving accuracy.


  Starting from gauged N=8 supergravity in three dimensions we construct
actions for multiple membranes by taking the limit to global supersymmetry for
different choices of the embedding tensor. This provides a general framework
that reproduces many recent results on multiple membrane actions as well as
generalisations thereof. As examples we discuss conformal (non-conformal)
gaugings leading to multiple M2-branes (D2-branes) and massive deformations of
these systems.


  Non-cubic crystals exhibit anisotropic physical and functional properties.
Microscopic crystallites as constituents of polycrystalline materials are
randomly oriented, thus polycrystalline ceramics lack the anisotropic
properties of their monocrystalline counterparts. We propose a technology that
exploits the synergy between magnetic alignment and colloidal ceramics
processing, and enables to independently tune the orientation of grains in
different sample regions by infinitesimal magnetic fields (<10 millitesla). The
grain pivot mechanism enables the emulation of single crystals, as well as the
creation of large complex-shaped ceramic elements with designed
crystallographic landscapes and spatially and directionally tuned properties.
Ultra-high magnetic response arises from magnetic shape anisotropy of
platelet-shaped seed crystallites coated with small amounts of iron oxide
nanoparticles. To control crystallographic growth directions during subsequent
annealing procedures, the seeds are dispersed and aligned in a matrix of
chemically identical, but much finer spherical particles. The degree of
crystalline orientation in accordingly prepared aluminum oxide exceeds 99%.
This technology opens an avenue to remarkably improve structural and functional
properties of ceramic elements employed in numerous industrial applications.


  This paper discusses compelling science cases for a future long-baseline
interferometer operating at millimeter and centimeter wavelengths, like the
proposed Next Generation Vary Large Array (ngVLA). We report on the activities
of the Cradle of Life science working group, which focused on the formation of
low- and high-mass stars, the formation of planets and evolution of
protoplanetary disks, the physical and compositional study of Solar System
bodies, and the possible detection of radio signals from extraterrestrial
civilizations. We propose 19 scientific projects based on the current
specification of the ngVLA. Five of them are highlighted as possible Key
Science Projects: (1) Resolving the density structure and dynamics of the
youngest HII regions and high-mass protostellar jets, (2) Unveiling
binary/multiple protostars at higher resolution, (3) Mapping planet formation
regions in nearby disks on scales down to 1 AU, (4) Studying the formation of
complex molecules, and (5) Deep atmospheric mapping of giant planets in the
Solar System. For each of these projects, we discuss the scientific importance
and feasibility. The results presented here should be considered as the
beginning of a more in-depth analysis of the science enabled by such a
facility, and are by no means complete or exhaustive.


  We consider whether or not Hamiltonians which are sums of commuting
projectors have "trivial" ground states which can be constructed by a local
quantum circuit of bounded depth and range acting on a product state. While the
toric code only has nontrivial ground states, commuting projector Hamiltonians
which are sums of two-body interactions have trivial ground states.
  We define an "interaction complex" for a Hamiltonian, generalizing the
interaction graph, and we show that if this complex can be continuously mapped
to a 1-complex using a map with bounded diameter of pre-images then the
Hamiltonian has a trivial ground state assuming one technical condition on the
Hamiltonian (this condition holds for all stabilizer Hamiltonians, and we also
prove the result for all Hamiltonians under an assumption on the 1-complex).
While this includes cases considered by Ref., it also includes other
Hamiltonians whose interaction complexes cannot be coarse-grained into the case
of Ref.
  One motivation for this is the quantum PCP conjecture. Many commonly studied
interaction complexes can be mapped to a 1-complex after removing a small
fraction of sites. For commuting projector Hamiltonians on such complexes, a
trivial ground state for the Hamiltonian with those sites removed is a low
energy trivial state for the original Hamiltonian. Such states can act as a
classical witness to the existence of a low energy state. While this result
applies only to commuting Hamiltonians, it suggests that to prove a quantum PCP
conjecture one should consider interaction complexes which cannot be mapped to
1-complexes after removing a small fraction of cells. We define this more
precisely below; in a sense this generalizes the idea of an expander graph.
Surprisingly, such complexes do exist as will be shown elsewhere, and have
useful properties in quantum coding theory.


  Modern recommender systems aim to improve user experience. As reinforcement
learning (RL) naturally fits this objective -- maximizing an user's reward per
session -- it has become an emerging topic in recommender systems. Developing
RL-based recommendation methods, however, is not trivial due to the
\emph{offline training challenge}. Specifically, the keystone of traditional RL
is to train an agent with large amounts of online exploration making lots of
`errors' in the process. In the recommendation setting, though, we cannot
afford the price of making `errors' online. As a result, the agent needs to be
trained through offline historical implicit feedback, collected under different
recommendation policies; traditional RL algorithms may lead to sub-optimal
policies under these offline training settings.
  Here we propose a new learning paradigm -- namely Prompt-Based Reinforcement
Learning (PRL) -- for the offline training of RL-based recommendation agents.
While traditional RL algorithms attempt to map state-action input pairs to
their expected rewards (e.g., Q-values), PRL directly infers actions (i.e.,
recommended items) from state-reward inputs. In short, the agents are trained
to predict a recommended item given the prior interactions and an observed
reward value -- with simple supervised learning. At deployment time, this
historical (training) data acts as a knowledge base, while the state-reward
pairs are used as a prompt. The agents are thus used to answer the question:
\emph{ Which item should be recommended given the prior interactions \& the
prompted reward value}? We implement PRL with four notable recommendation
models and conduct experiments on two real-world e-commerce datasets.
Experimental results demonstrate the superior performance of our proposed
methods.


  In this paper we give a survey of what is currently known about Diophantine
exponents of lattices and propose several problems.


  In this Paper, we present the first results from the Flux Angle operation
mode of the Faraday Cup instrument onboard Parker Solar Probe. The Flux Angle
mode allows rapid measurements of phase space density fluctuations close to the
peak of the proton velocity distribution function with a cadence of 293 Hz.
This approach provides an invaluable tool for understanding kinetic scale
turbulence in the solar wind and solar corona. We describe a technique to
convert the phase space density fluctuations into vector velocity components
and compute several turbulence parameters such as spectral index, residual
energy and cross helicity during two intervals the Flux Angle mode was used in
Parker Solar Probe's first encounter at 0.174 AU distance from the Sun.


  In nanoscale metrology applications, measurements are commonly limited by the
performance of the sensor. Here we show that in nuclear magnetic resonance
(NMR) spectroscopy measurements using single nitrogen-vacancy (NV) centers in
diamond, the NV sensor electron spin limits spectral resolution down to a few
hundred Hz, which constraints the characterization and coherent control of
finite spin systems, and furthermore, is insufficient for high resolution NMR
spectroscopy aiming at single molecule recognition and structure analysis of
the latter. To overcome the limitation, we support an NV electron spin sensor
with a nuclear spin qubit acting as quantum and classical memory allowing for
intermediate nonvolatile storage of metrology information, while suppressing
the deleterious back-action of the sensor onto the system under investigation.
We demonstrate quantum and classical memory lifetimes of 8 ms and 4 minutes
respectively under ambient conditions. Furthermore, we design and test
measurement and decoupling protocols, which exploit such memory qubits
efficiently. Using our hybrid quantum-classical sensor device, we achieve high
resolution NMR spectra with linewidths of single spins down to 13 Hz. Our work
is therefore a prerequisite for high resolution NMR spectroscopy on nanoscopic
quantum systems down to the single level.


  Minimizing the Gaussian curvature of meshes can play a fundamental role in 3D
mesh processing. However, there is a lack of computationally efficient and
robust Gaussian curvature optimization method. In this paper, we present a
simple yet effective method that can efficiently reduce Gaussian curvature for
3D meshes. We first present the mathematical foundation of our method. Then, we
introduce a simple and robust implicit Gaussian curvature optimization method
named Gaussian Curvature Filter (GCF). GCF implicitly minimizes Gaussian
curvature without the need to explicitly calculate the Gaussian curvature
itself. GCF is highly efficient and this method can be used in a large range of
applications that involve Gaussian curvature. We conduct extensive experiments
to demonstrate that GCF significantly outperforms state-of-the-art methods in
minimizing Gaussian curvature, and geometric feature preserving soothing on 3D
meshes. GCF program is available at https://github.com/tangwenming/GCF-filter.


  Probabilistic Logic Programs (PLPs) generalize traditional logic programs and
allow the encoding of models combining logical structure and uncertainty. In
PLP, inference is performed by summarizing the possible worlds which entail the
query in a suitable data structure, and using it to compute the answer
probability. Systems such as ProbLog, PITA, etc., use propositional data
structures like explanation graphs, BDDs, SDDs, etc., to represent the possible
worlds. While this approach saves inference time due to substructure sharing,
there are a number of problems where a more compact data structure is possible.
We propose a data structure called Ordered Symbolic Derivation Diagram (OSDD)
which captures the possible worlds by means of constraint formulas. We describe
a program transformation technique to construct OSDDs via query evaluation, and
give procedures to perform exact and approximate inference over OSDDs. Our
approach has two key properties. Firstly, the exact inference procedure is a
generalization of traditional inference, and results in speedup over the latter
in certain settings. Secondly, the approximate technique is a generalization of
likelihood weighting in Bayesian Networks, and allows us to perform
sampling-based inference with lower rejection rate and variance. We evaluate
the effectiveness of the proposed techniques through experiments on several
problems. This paper is under consideration for acceptance in TPLP.


  In this paper, we compute the integral cohomology groups for all examples of
Calabi-Yau 3-folds obtained from hypersurfaces in 4-dimensional Gorenstein
toric Fano varieties. Among 473 800 776 families of Calabi-Yau 3-folds $X$
corresponding to 4-dimensional reflexive polytopes there exist exactly 32
families having non-trivial torsion in $H^*(X, \Z)$. We came to an interesting
observation that the torsion subgroups in $H^2$ and $H^3$ are exchanged by the
mirror symmetry involution, i.e. the torsion subgroup in the Picard group of
$X$ is isomorphic to the Brauer group of the mirror $X^*$


  Toll optimization in a large-scale dynamic traffic network is typically
characterized by an expensive-to-evaluate objective function. In this paper, we
propose two toll level problems (TLPs) integrated with a large-scale
simulation-based dynamic traffic assignment (DTA) model of Melbourne,
Australia. The first TLP aims to control the pricing zone (PZ) through a
time-varying joint distance and delay toll (JDDT) such that the network
fundamental diagram (NFD) of the PZ does not enter the congested regime. The
second TLP is built upon the first TLP by further considering the minimization
of the heterogeneity of congestion distribution in the PZ. To solve the two
TLPs, a computationally efficient surrogate-based optimization method, i.e.,
regressing kriging (RK) with expected improvement (EI) sampling, is applied to
approximate the simulation input-output mapping, which can balance well between
local exploitation and global exploration. Results show that the two optimal
TLP solutions reduce the average travel time in the PZ (entire network) by
29.5% (1.4%) and 21.6% (2.5%), respectively. Reducing the heterogeneity of
congestion distribution achieves higher network flows in the PZ and a lower
average travel time or a larger total travel time saving in the entire network.


  Making changes to a program to optimize its performance is an unscalable task
that relies entirely upon human intuition and experience. In addition,
companies operating at large scale are at a stage where no single individual
understands the code controlling its systems, and for this reason, making
changes to improve performance can become intractably difficult. In this paper,
a learning system is introduced that provides AI assistance for finding
recommended changes to a program. Specifically, it is shown how the evaluative
feedback, delayed-reward performance programming domain can be effectively
formulated via the Monte Carlo tree search (MCTS) framework. It is then shown
that established methods from computational games for using learning to
expedite tree-search computation can be adapted to speed up computing
recommended program alterations. Estimates of expected utility from MCTS trees
built for previous problems are used to learn a sampling policy that remains
effective across new problems, thus demonstrating transferability of
optimization knowledge. This formulation is applied to the Apache Spark
distributed computing environment, and a preliminary result is observed that
the time required to build a search tree for finding recommendations is reduced
by up to a factor of 10x.


  General hyperplane sections of a Fano threefold $Y$ of index 2 and Picard
rank 1 are del Pezzo surfaces, and their Picard group is related to a root
system. To the corresponding roots, we associate objects in the Kuznetsov
component of $Y$ and investigate their moduli spaces, using the stability
condition constructed by Bayer, Lahoz, Macr\`i, and Stellari, and the
Abel--Jacobi map. We identify a subvariety of the moduli space isomorphic to
$Y$ itself, and as an application we prove a (refined) categorical Torelli
theorem for general quartic double solids.


  It is shown that the solution for the electrostatic potential used in [Phys.
Rev. Lett. 96 (2006) 030402, arXiv:math-ph/0506069] is not correct and
therefore cannot provide a more accurate spectrum of the hydrogen atom in the
Maxwell-Born-Infeld theory than those obtained previously.


  Hard constraints imposed in statistical mechanics models can lead to
interesting thermodynamical behaviors, but may at the same time raise
obstructions in the thoroughfare to thermal equilibration. Here we study a
variant of Baxter's 3-color model in which local interactions and defects are
included, and discuss its connection to triangular arrays of Josephson
junctions of superconductors and \textit{kagom\'e} networks of superconducting
wires. The model is equivalent to an Ising model in a hexagonal lattice with
the constraint that the magnetization of each hexagon is $\pm 6$ or 0. For
ferromagnetic interactions, we find that the system is critical for a range of
temperatures (critical line) that terminates when it undergoes an exotic first
order phase transition with a jump from a zero magnetization state into the
fully magnetized state at finite temperature. Dynamically, however, we find
that the system becomes frozen into domains. The domain walls are made of
perfectly straight segments, and domain growth appears frozen within the time
scales studied with Monte Carlo simulations. This dynamical obstruction has its
origin in the topology of the allowed reconfigurations in phase space, which
consist of updates of closed loops of spins. As a consequence of the dynamical
obstruction, there exists a dynamical temperature, lower than the (avoided)
static critical temperature, at which the system is seen to jump from a
``supercooled liquid'' to a ``polycrystalline'' phase. In contrast, for
antiferromagnetic interactions, we argue that the system orders for
infinitesimal coupling because of the constraint, and we observe no interesting
dynamical effects.


  In a recent paper -- F. Ciccarello \emph{et al.}, New J. Phys. \textbf{8},
214 (2006) -- we have demonstrated that the electron transmission properties of
a one-dimensional (1D) wire with two identical embedded spin-1/2 impurities can
be significantly affected by entanglement between the spins of the scattering
centers. Such effect is of particular interest in the control of transmission
of quantum information in nanostructures and can be used as a detection scheme
of maximally entangled states of two localized spins. In this letter, we relax
the constraint that the two magnetic impurities are equal and investigate how
the main results presented in the above paper are affected by a static disorder
in the exchange coupling constants of the impurities. Good robustness against
deviation from impurity symmetry is found for both the entanglement dependent
transmission and the maximally entangled states generation scheme.


  We provide evidence that UGC1382, long believed to be a passive elliptical
galaxy, is actually a giant low surface brightness (GLSB) galaxy which rivals
the archetypical GLSB Malin 1 in size. Like other GLSB galaxies, it has two
components: a high surface brightness disk galaxy surrounded by an extended low
surface brightness (LSB) disk. For UGC1382, the central component is a
lenticular system with an effective radius of 6 kpc. Beyond this, the LSB disk
has an effective radius of ~38 kpc and an extrapolated central surface
brightness of ~26 mag/arcsec^2. Both components have a combined stellar mass of
~8x10^10 M_sun, and are embedded in a massive (10^10 M_sun) low-density (<3
M_sun/pc^2) HI disk with a radius of 110 kpc, making this one of the largest
isolated disk galaxies known. The system resides in a massive dark matter halo
of at least 2x10^12 M_sun. Although possibly part of a small group, its low
density environment likely plays a role in the formation and retention of the
giant LSB and HI disks. We model the spectral energy distributions and find
that the LSB disk is likely older than the lenticular component. UGC1382 has
UV-optical colors typical of galaxies transitioning through the green valley.
Within the LSB disk are spiral arms forming stars at extremely low
efficiencies. The gas depletion time scale of ~10^11 yr suggests that UGC1382
may be a very long term resident of the green valley. We find that the
formation and evolution of the LSB disk is best explained by the accretion of
gas-rich LSB dwarf galaxies.


  Control systems can show robustness to many events, like disturbances and
model inaccuracies. It is natural to speculate that they are also robust to
sporadic deadline misses when implemented as digital tasks on an embedded
platform. This paper proposes a comprehensive stability analysis for control
systems subject to deadline misses, leveraging a new formulation to describe
the patterns experienced by the control task under different handling
strategies. Such analysis brings the assessment of control systems robustness
to computational problems one step closer to the controller implementation.


  In this paper, we discuss the crossing change operation along exchangeable
double curves of a surface-knot diagram. We show that under certain condition,
a finite sequence of Roseman moves preserves the property of those exchangeable
double curves. As an application for this result, we also define a numerical
invariant for a set of surface-knots called $du$-exchangeable set.


  It is shown that the linear correlation relates the S-wave phase shifts from
the threshold up to dipion mass 900 MeV. By using this correlation at the
solution of the Roy equations, the accuracy of determination of S-wave lengths
is considerably improved. The obtained result unambiguously witnesses in favor
of the standard ChPT version with large quark condensate.


  This paper presents a novel approach, called AirScript, for creating,
recognizing and visualizing documents in air. We present a novel algorithm,
called 2-DifViz, that converts the hand movements in air (captured by a
Myo-armband worn by a user) into a sequence of x, y coordinates on a 2D
Cartesian plane, and visualizes them on a canvas. Existing sensor-based
approaches either do not provide visual feedback or represent the recognized
characters using prefixed templates. In contrast, AirScript stands out by
giving freedom of movement to the user, as well as by providing a real-time
visual feedback of the written characters, making the interaction natural.
AirScript provides a recognition module to predict the content of the document
created in air. To do so, we present a novel approach based on deep learning,
which uses the sensor data and the visualizations created by 2-DifViz. The
recognition module consists of a Convolutional Neural Network (CNN) and two
Gated Recurrent Unit (GRU) Networks. The output from these three networks is
fused to get the final prediction about the characters written in air.
AirScript can be used in highly sophisticated environments like a smart
classroom, a smart factory or a smart laboratory, where it would enable people
to annotate pieces of texts wherever they want without any reference surface.
We have evaluated AirScript against various well-known learning models (HMM,
KNN, SVM, etc.) on the data of 12 participants. Evaluation results show that
the recognition module of AirScript largely outperforms all of these models by
achieving an accuracy of 91.7% in a person independent evaluation and a 96.7%
accuracy in a person dependent evaluation.


  The large $N_c$ nuclear potential puzzle arose because three- and
higher-meson exchange contributions to the nucleon-nucleon potential did not
automatically yield cancellations that make these contributions consistent with
the general large $N_c$ scaling rules for the potential. Here it is proposed
that the resolution to this puzzle is that the scaling rules only apply for
energy-independent potentials while all of the cases with apparent
inconsistencies were for energy-dependent potentials. It is shown explicitly
how energy-dependent potentials can have radically different large N behavior
than an equivalent energy-independent one. One class of three-meson graphs is
computed in which the contribution to the energy-independent potential is
consistent with the general large N rules even though the energy-dependent
potential is not.


  Particular boundary correlation functions of conformal field theory are
needed to answer some questions related to random conformally invariant curves
known as Schramm-Loewner evolutions (SLE). In this article, we introduce a
correspondence and establish its fundamental properties, which are used in the
companion articles [JJK16, KP16] for explicitly solving two such problems. The
correspondence associates Coulomb gas type integrals to vectors in a tensor
product representation of a quantum group, a q-deformation of the Lie algebra
sl2. We show that desired properties of the functions are guaranteed by natural
representation theoretical properties of the vectors.


  We construct projectors in the ring of correspondences of a complex uniruled
3-fold $X$ which lift the Kuenneth components of the diagonal in singular
cohomology and have other properties which were conjectured by J. Murre. Such
Murre decompositions have been already obtained for curves, surfaces, abelian
varieties and varieties with cell decompositions by the work of Manin,
Shermenev, Beauville, Murre et.al.. In particular they define a natural
filtration on the Chow groups of $X$ which was conjectured by Bloch and
Beilinson. To do this we use Mori theory and construct projectors in the
situation of a fiber space over a surface. These projectors may also be used in
more general situations.


  The geometry of various plasmonic nanoantennae was numerically optimized to
maximize their sensitivity to the carrier envelope phase (CEP) of the exciting
ultra-short laser pulses. To verify the CEP sensitivity, the near-field
response of the investigated nanoantennae was analyzed by combining frequency
and time-domain numerical computations. The simulation methodology, capable of
accurately calculating the time-dependent photocurrent stem from optical field
emission, enabled the determination and optimization of all key parameters
characterizing and governing the CEP dependence of the near-field responses.
Three-types of structures were inspected, including individual triangular and
teardrop-shaped nanoantennae and plasmonic lenses consisting of three
hemispheres with gradually decreasing diameters. All structure types were
optimized in solid and hollow compositions of gold nanoresonators as well. It
was shown that hollow /solid singlets produce the largest /intermediate CEP
dependent - to - CEP independent integrated current components' ratio, while
their absolute CEP dependent integrated currents were the smallest
/intermediate among the optimized structures. The highest /intermediate CEP
sensitivity was achieved via solid plasmonic lenses due to their very large
absolute CEP dependent integrated photocurrent originating from huge near-field
enhancement in the nanogaps, while the integrated current components' ratio was
smaller than for counterpart singlets.


  Information is the key asset of all organizations and can exist in many
forms. It can be printed or written on paper, stored electronically,
transmitted by mail or by electronic means, shown in films, or spoken in
conversation. In today's competitive business environment, such information is
constantly under threat from many sources, which can be internal, external,
accidental, or malicious. Joomla is a very popular Content Management System
(CMS) used for web page maintenance. This highly versatile software has found
itself in both large corporate web portals, and simple web pages such as blogs.
Such popularity increases its vulnerability to potential attacks and therefore
needs an appropriate security management. ISO (the International Organization
for Standardization) and IEC (the International Electrotechnical Commission)
created the series of standards aimed at providing a model for establishing,
implementing, operating, monitoring, reviewing, maintaining and improving an
Information Security Management System (ISMS). This paper shows how principles
set in ISO/IEC 27000 series of standards can be used to improve security of
Joomla based web portals.


  An orientation of a graph $G$ is proper if any two adjacent vertices have
different indegrees. The proper orientation number $\overrightarrow{\chi}(G)$
of a graph $G$ is the minimum of the maximum indegree, taken over all proper
orientations of $G$. In this paper, we show that a connected bipartite graph
may be properly oriented even if we are only allowed to control the orientation
of a specific set of edges, namely, the edges of a spanning tree and all the
edges incident to one of its leaves. As a consequence of this result, we prove
that 3-connected planar bipartite graphs have proper orientation number at most
6. Additionally, we give a short proof that $\overrightarrow{\chi}(G) \leq 4$,
when $G$ is a tree and this proof leads to a polynomial-time algorithm to
proper orient trees within this bound.


  Fine-tuning large pre-trained language models on various downstream tasks
with whole parameters is prohibitively expensive. Hence, Parameter-efficient
fine-tuning has attracted attention that only optimizes a few task-specific
parameters with the frozen pre-trained model. In this work, we focus on prefix
tuning, which only optimizes continuous prefix vectors (i.e. pseudo tokens)
inserted into Transformer layers. Based on the observation that the learned
syntax and semantics representation varies a lot at different layers, we argue
that the adaptive prefix will be further tailored to each layer than the fixed
one, enabling the fine-tuning more effective and efficient. Thus, we propose
Adaptive Prefix Tuning (APT) to adjust the prefix in terms of both fine-grained
token level and coarse-grained layer level with a gate mechanism. Experiments
on the SuperGLUE and NER datasets show the effectiveness of APT. In addition,
taking the gate as a probing, we validate the efficiency and effectiveness of
the variable prefix.


  Modern spoken language understanding (SLU) systems rely on sophisticated
semantic notions revealed in single utterances to detect intents and slots.
However, they lack the capability of modeling multi-turn dynamics within a
dialogue particularly in long-term slot contexts. Without external knowledge,
depending on limited linguistic legitimacy within a word sequence may overlook
deep semantic information across dialogue turns. In this paper, we propose to
equip a BERT-based joint model with a knowledge attention module to mutually
leverage dialogue contexts between two SLU tasks. A gating mechanism is further
utilized to filter out irrelevant knowledge triples and to circumvent
distracting comprehension. Experimental results in two complicated multi-turn
dialogue datasets have demonstrate by mutually modeling two SLU tasks with
filtered knowledge and dialogue contexts, our approach has considerable
improvements compared with several competitive baselines.


  The velocity dispersion of 7 Seyfert 1 galaxies at z~0.37 is measured using
high signal-to-noise Keck spectra. Black hole (BH) mass estimates are obtained
via an empirically calibrated photoionization method. We derive the BH mass
velocity dispersion relationship at z~0.37. We find an offset with respect to
the local relationship, in the sense of somewhat lower velocity dispersion at a
fixed BH mass at z~0.37 than today, significant at the 97% level. The offset
corresponds to Delta log sigma = -0.16 with rms scatter of 0.13 dex. If
confirmed by larger samples and independent checks on systematic uncertainties
and selection effects, this result would be consistent with spheroids evolving
faster than BHs in the past 4 Gyrs and inconsistent with pure luminosity
evolution.


  In this paper, we study the persistence of invariant tori of integrable
Hamiltonian systems satisfying R\"{u}ssmann's non-degeneracy condition when
symplectic integrators are applied to them. Meanwhile, we give an estimate of
the measure of the set occupied by the invariant tori in the phase space. On an
invariant torus, the one-step map of the scheme is conjugate to a one parameter
family of linear rotations with a step size dependent frequency vector in terms
of iteration. These results are a generalization of Shang's theorems (1999,
2000), where the non-degeneracy condition is assumed in the sense of
Kolmogorov. In comparison, R\"{u}ssmann's condition is the weakest
non-degeneracy condition for the persistence of invariant tori in Hamiltonian
systems. These results provide new insight into the nonlinear stability of
symplectic integrators.


  Mark-and-Recapture is a methodology from Population Biology to estimate the
number of a species without counting every individual. This is done by multiple
samplings of the species using traps and discounting the instances that were
caught repeated. In this paper we show that this methodology is applicable for
citation analysis as it is also not feasible to count all the relevant
publications of a research topic. In addition this estimation also allows us to
propose a stopping rule for researchers to decide how far one should extend
their search for relevant literature.


  We consider the feasibility problem of integer linear programming (ILP). We
show that solutions of any ILP instance can be naturally represented by an
FO-definable class of graphs. For each solution there may be many graphs
representing it. However, one of these graphs is of path-width at most 2n,
where n is the number of variables in the instance. Since FO is decidable on
graphs of bounded path- width, we obtain an alternative decidability result for
ILP. The technique we use underlines a common principle to prove decidability
which has previously been employed for automata with auxiliary storage. We also
show how this new result links to automata theory and program verification.


  In this article, we introduce and study the notion of a complete special
holonomy manifold $(X,\omega)$ which is given by a global perturbation
potential function, i.e., there is a function $f$ on $X$ such that
$\omega'=\omega-\mathcal{L}_{\nabla f}\omega$ is sufficiently small in
$L^{\infty}$-norm. We establish some vanishing theorems on the $L^{2}$ harmonic
forms under some conditions on the global perturbation potential function.


  The classical trajectories of the family of complex PT-symmetric Hamiltonians
$H=p^2+x^2(ix)^\epsilon$ ($\epsilon\geq0$) form closed orbits. All such complex
orbits that have been studied in the past are PT symmetric (left-right
symmetric). The periods of these orbits exhibit an unusual dependence on the
parameter $\epsilon$. There are regions in $\epsilon$ of smooth behavior
interspersed with regions of rapid variation. It is demonstrated that the onset
of rapid variation is associated with strange new kinds of classical
trajectories that have never been seen previously. These rare kinds of
trajectories are not PT symmetric and occur only for special rational values of
$\epsilon$.


  We present an approximate, analytical formulae for the computation of
hadronically-produced gamma-ray luminosity in the innermost regions of stellar
winds. We put this into the context of other recent research on regions of star
formation as gamma-ray sources.


  Recommendation systems play a crucial role in various domains, suggesting
items based on user behavior.However, the lack of transparency in presenting
recommendations can lead to user confusion. In this paper, we introduce
Data-level Recommendation Explanation (DRE), a non-intrusive explanation
framework for black-box recommendation models.Different from existing methods,
DRE does not require any intermediary representations of the recommendation
model or latent alignment training, mitigating potential performance issues.We
propose a data-level alignment method, leveraging large language models to
reason relationships between user data and recommended items.Additionally, we
address the challenge of enriching the details of the explanation by
introducing target-aware user preference distillation, utilizing item reviews.
Experimental results on benchmark datasets demonstrate the effectiveness of the
DRE in providing accurate and user-centric explanations, enhancing user
engagement with recommended item.


  A new algorithm is proposed to impose a macroscopic stress or mixed
stress/deformation gradient history in the context of non-linear Galerkin based
FFT homogenization. The method proposed is based in the definition of a
modified projection operator in which the null frequencies enforce the type of
control (stress or strain) for each component of either the macroscopic first
Piola stress or the deformation gradient. The resulting problem is solved
exactly as the original variational method and it does not require additional
iterations compared to the strain control version, neither in the linear
iterative solver, nor in the Newton scheme. The efficiency of the method
proposed is demonstrated with a series of numerical examples, including a
polycrystal and a particle reinforced hyperelastic material.


  We propose a variational calculation scheme utilizing the superposition of
the angular-momentum, parity, number projected quasiparticle vacua, that is
especially suitable for applying to medium-heavy nuclei in shell-model
calculations. We derive a formula for the energy variance with quasi-particle
vacua and apply the energy-variance extrapolation to the present scheme for
further precise estimation of the exact shell-model energy. The validity of the
method is presented for the shell-model calculation of $^{132}$Ba in the $50
\leq Z,N \leq 82$ model space. We also discuss the feasibility of this scheme
in the case of the $^{150}$Nd in the $50 \leq Z \leq 82$ and $82 \leq Z \leq
126$ model space and demonstrate that its neutrinoless-double-beta-decay matrix
element is obtained showing good convergence.


  We study photoproduction reactions in a polarized ep collider mode of HERA at
sqrt(s)=298 GeV. We examine the sensitivity of the cross sections and their
asymmetries to the proton's polarized gluon distribution and to the completely
unknown parton distributions of longitudinally polarized photons.


  This paper presents a BeppoSAX observation of NGC 7582 made during 1998
November and an optical spectrum taken in 1998 October. The new X-ray data
reveal a previously unknown hard X-ray component in NGC 7582, peaking close to
20 keV. Rapid variability is observed with correlated changes in the 5-10 and
13-60 keV bands indicating that a single continuum component, produced by the
active nucleus, provides the dominant flux across both bands. Changes in the
nuclear X-ray flux appear unrelated to the gradual decline in optical flux
noted since the high-state in 1998 July. The X-ray continuum is attenuated by a
thick absorber of N_H ~ 1.6 x 10E24 cm^-2 covering ~60% of the nucleus, plus a
screen with N_H ~ 1.4 x 10E23 cm^-2 covering the entire nucleus. Comparison of
the BeppoSAX and ASCA spectra shows an increase in the full screen by N_H ~7 x
10E22 cm^-2 since 1994, confirming the absorption variability found by Xue et
al. The increase in soft X-ray flux between 1994 and 1998 is consistent with
the appearance of holes in the full screen producing some clear lines-of-sight
to the broad-line-region.


  Value decomposition is widely used in cooperative multi-agent reinforcement
learning, however, its implicit credit assignment mechanism is not yet fully
understood due to black-box networks. In this work, we study an interpretable
value decomposition framework via the family of generalized additive models. We
present a novel method, named Neural Attention Additive Q-learning
(N$\text{A}^\text{2}$Q), providing inherent intelligibility of collaboration
behavior. N$\text{A}^\text{2}$Q can explicitly factorize the optimal joint
policy induced by enriching shape functions to model all possible coalitions of
agents into individual policies. Moreover, we construct identity semantics to
promote estimating credits together with the global state and individual value
functions, where local semantic masks help us diagnose whether each agent
captures relevant-task information. Extensive experiments show that
N$\text{A}^\text{2}$Q consistently achieves superior performance compared to
different state-of-the-art methods on all challenging tasks, while yielding
human-like interpretability.


  Several topologies can be defined on the prime, the maximal and the minimal
prime spectra of a commutative ring; among them, we mention the Zariski
topology, the patch topology and the flat topology. By using these topologies,
Tarizadeh and Aghajani obtained recently new characterizations of various
classes of rings: Gelfand rings, clean rings, absolutely flat rings, $mp$ -
rings,etc. The aim of this paper is to generalize some of their results to
quantales, structures that constitute a good abstractization for lattices of
ideals, filters and congruences. We shall study the flat and the patch
topologies on the prime, the maximal and the minimal prime spectra of a
coherent quantale. By using these two topologies one obtains new
characterization theorems for hyperarchimedean quantales, normal quantales,
B-normal quantales, $mp$ - quantales and $PF$ - quantales. The general results
can be applied to several concrete algebras: commutative rings, bounded
distributive lattices, MV-algebras, BL-algebras, residuated lattices,
commutative unital $l$ - groups, etc.


  The gauge theory on a set of D3-branes at a toric Calabi-Yau singularity can
be encoded in a tiling of the 2-torus denoted dimer diagram (or brane tiling).
We use these techniques to describe the effect on the gauge theory of geometric
operations partially smoothing the singularity at which D3-branes sit, namely
partial resolutions and complex deformations. More specifically, we describe
the effect of arbitrary partial resolutions, including those which split the
original singularity into two separated. The gauge theory correspondingly
splits into two sectors (associated to branes in either singularity) decoupled
at the level of massless states. We also describe the effect of complex
deformations, associated to geometric transitions triggered by the presence of
fractional branes with confinement in their infrared. We provide tools to
easily obtain the remaining gauge theory after such partial confinement.


  We propose a projection pursuit (PP) algorithm based on Gaussian mixture
models (GMMs). The negentropy obtained from a multivariate density estimated by
GMMs is adopted as the PP index to be maximised. For a fixed dimension of the
projection subspace, the GMM-based density estimation is projected onto that
subspace, where an approximation of the negentropy for Gaussian mixtures is
computed. Then, Genetic Algorithms (GAs) are used to find the optimal,
orthogonal projection basis by maximising the former approximation. We show
that this semi-parametric approach to PP is flexible and allows highly
informative structures to be detected, by projecting multivariate datasets onto
a subspace, where the data can be feasibly visualised. The performance of the
proposed approach is shown on both artificial and real datasets.


  We investigate Bell inequalities for neutral kaon systems from Phi resonance
decay to test local realism versus quantum mechanics. We emphasize the unitary
time evolution of the states, that means we also include all decay product
states, in contrast to other authors. Only this guarantees the use of the
complete Hilbert space. We develop a general formalism for Bell inequalities
including both arbitrary "quasi spin" states and different times; finally we
analyze Wigner-type inequalities. They contain an additional term, a correction
function h, as compared to the spin 1/2 or photon case, which changes
considerably the possibility of quantum mechanics to violate the Bell
inequality. Examples for special "quasi spin" states are given, especially
those which are sensitive to the CP parameters epsilon and epsilon'.


  In this paper we consider a post-quantum digital signature scheme based on
low-density generator matrix codes and propose efficient algorithmic solutions
for its implementation. We also review all known attacks against this scheme
and derive closed-form estimates of their complexity when running over both
classical and quantum computers. Based on these estimates, we propose new
parametrization for the considered system to achieve given pre-quantum and
post-quantum security levels. Finally, we provide and discuss performance
benchmarks obtained through a suitably developed and publicly available
reference implementation of the considered system.


  The lattice Ginzburg-Landau model in d=3 and d=2 is simulated, for different
values of the coherence length $\xi$ in units of the lattice spacing $a$, using
a Monte Carlo method. The energy, specific heat, vortex density $v$, helicity
modulus $\Gamma_\mu$ and mean square amplitude are measured to map the phase
diagram on the plane $T-\xi$. When amplitude fluctuations, controlled by the
parameter $\xi$, become large ($\xi \sim 1$) a proliferation of vortex
excitations occurs changing the phase transition from continuous to first
order.


  The purpose of this paper is to derive volume and other geometric information
for three-dimensional complete manifolds with positive scalar curvature. In the
case that the Ricci curvature is nonnegative, it is shown that the volume of
the manifold must be of linear growth when the scalar curvature is bounded from
below by a positive constant. This answers a question of Gromov in the
affirmative for dimension three. Volume growth estimates are also obtained for
the case when scalar curvature decays to zero. In fact, results of similar
nature are established for the more general case that the Ricci curvature is
asymptotically nonnegative.


  We present near-infrared spectroscopy and imaging of the compact steep-
spectrum radio source 3C 318 which shows it to be a quasar at redshift z=1.574
(the z=0.752 value previously reported is incorrect). 3C 318 is an IRAS, ISO
and SCUBA source so its new redshift makes it the most intrinsically luminous
far-infrared (FIR) source in the 3C catalogue (there is no evidence of strong
gravitational lensing effects). Its bolometric luminosity greatly exceeds the
10^13 solar luminosity level above which an object is said to be hyperluminous.
Its spectral energy distribution (SED) requires that the quasar heats the dust
responsible for the FIR flux, as is believed to be the case in other
hyperluminous galaxies, and contributes (at the >10% level) to the heating of
the dust responsible for the sub-mm emission. We cannot determine whether a
starburst makes an important contribution to the heating of the coolest dust,
so evidence for a high star-formation rate (SFR) is circumstantial being based
on the high dust mass required by its sub-mm detection. We show that the
current sub-mm and FIR data available for high-z radio galaxies are consistent
with SEDs similar to that of 3C 318. This indicates that at least some of this
population may be detected in the sub-mm because of dust heated by the quasar
nucleus, and that interpreting sub-mm detection as evidence for very high SFRs
may not always be valid. We show that the 3C318 quasar is slightly reddened
(A(V) ~ 0.5), the most likely cause of which is SMC-type dust in the host
galaxy. If very distant radio galaxies are reddened in a similar way then we
show that only slightly greater amounts of dust could obscure the quasars in
these sources, thus explaining the low fraction of quasars amongst the very
high redshift (z > 3) objects in low-frequency radio-selected samples.


  We consider in this paper a networked system of opinion dynamics in
continuous time, where the agents are able to evaluate their self-appraisals in
a distributed way. In the model we formulate, the underlying network topology
is described by a rooted digraph. For each ordered pair of agents $(i,j)$, we
assign a function of self-appraisal to agent $i$, which measures the level of
importance of agent $i$ to agent $j$. Thus, by communicating only with her
neighbors, each agent is able to calculate the difference between her level of
importance to others and others' level of importance to her. The dynamical
system of self-appraisals is then designed to drive these differences to zero.
We show that for almost all initial conditions, the trajectory generated by
this dynamical system asymptotically converges to an equilibrium point which is
exponentially stable.


  In the pursuit of real-time motion planning, a commonly adopted practice is
to compute a trajectory by running a planning algorithm on a simplified,
low-dimensional dynamical model, and then employ a feedback tracking controller
that tracks such a trajectory by accounting for the full, high-dimensional
system dynamics. While this strategy of planning with model mismatch generally
yields fast computation times, there are no guarantees of dynamic feasibility,
which hampers application to safety-critical systems. Building upon recent work
that addressed this problem through the lens of Hamilton-Jacobi (HJ)
reachability, we devise an algorithmic framework whereby one computes, offline,
for a pair of "planner" (i.e., low-dimensional) and "tracking" (i.e.,
high-dimensional) models, a feedback tracking controller and associated
tracking bound. This bound is then used as a safety margin when generating
motion plans via the low-dimensional model. Specifically, we harness the
computational tool of sum-of-squares (SOS) programming to design a bilinear
optimization algorithm for the computation of the feedback tracking controller
and associated tracking bound. The algorithm is demonstrated via numerical
experiments, with an emphasis on investigating the trade-off between the
increased computational scalability afforded by SOS and its intrinsic
conservativeness. Collectively, our results enable scaling the appealing
strategy of planning with model mismatch to systems that are beyond the reach
of HJ analysis, while maintaining safety guarantees.


  Noise is ubiquitous and unwanted in detecting weak signals, which would give
rise to incorrect filtering frequency-band selection in signal filtering-based
methods including fast kurtogram, teager energy operators and wavelet packet
transform filters and meanwhile would result in incorrect selection of useful
components and even mode mixing, end effects and etc. in signal
decomposition-based methods including empirical mode decomposition, singular
value decomposition and local mean decomposition. On the contrary, noise in
stochastic resonance (SR) is beneficial to enhance weak signals of interest
embedded in signals with strong background noise. Taking into account that
nonlinear systems are crucial ingredients to activate the SR, here we
investigate the SR in the cases of overdamped and underdamped harmonic-Gaussian
double-well potential systems subjected to noise and a periodic signal. We
derive and measure the analytic expression of the output signal-to-noise ratio
(SNR) and the steady-state probability density (SPD) function under approximate
adiabatic conditions. When the harmonic-Gaussian double-well potential loses
its stability, we can observe the antiresonance phenomenon, whereas adding the
damped factor into the overdamped system can change the stability of the
harmonic-Gaussian double-well potential, resulting that the antiresonance
behavior disappears in the underdamped system. Then, we use the overdamped and
underdamped harmonic-Gaussian double-well potential SR to enhance weak useful
characteristics for diagnosing incipient rotating machinery failures.


  The 0.5(BiGdxFe1-xO3)-0.5(PbZrO3) composite was synthesized using a high
temperature solid-state reaction technique. Preliminary X-ray structural
analysis confirms the formation of the composite. The dielectric constant and
loss tangent have been studied. The hysteresis loop suggest that the material
is lossy. The impedance parameters were studied using an impedance analyzer in
a wide range of frequency (102-106 Hz) at different temperatures for all
samples. The Nyquist plot suggests the contribution of bulk effect as well as
grain boundary effect and the bulk resistance deceases with rise in temperature
for all samples. The electrical transport confirms the presence of hopping
mechanism in the material. The dc conductivity increases with rise in
temperature. The frequency variation of ac conductivity shows that the compound
obeys Jonschers universal power law and confirms the Small Polaron (SP)
tunneling effect due to low activation energy for all samples. Temperature
dependence of dc and ac conductivity indicates that electrical conduction in
the materials are thermally activated process.


  The integer hull of a polyhedron is the convex hull of the integer points
contained in it. We show that the vertices of the integer hulls of a rational
family of polyhedra of size O(n) have quasipolynomial coordinates. As a
corollary, we show that the stable commutator length of elements in a surgery
family is a ratio of quasipolynomials, and that unit balls in the scl norm
quasi-converge in finite dimensional surgery families.


  Creating stable superposed states of matter is one of the most intriguing
aspects of quantum physics, leading to a variety of counter-intuitive scenarios
along with a possibility of restructuring the way we understand, process and
communicate information. Accordingly, there has been a major research thrust in
understanding and quantifying such coherent superposed states. Here we propose
and experimentally explore a quantifier that captures effective coherent
superposition of states in an atomic ensemble at room-temperature. The
quantifier provides a direct measure of ground state coherence for
electromagnetically induced transparency (EIT) along with distinct signature of
transition from EIT to Autler-Townes splitting (ATS) regime in the ensemble.
Using the quantifier as an indicator, we further demonstrate a mechanism to
coherently control and freeze coherence by introducing an active decay
compensation channel. In the growing pursuit of quantum systems at
room-temperature, our results provide a unique way to phenomenologically
quantify and coherently control coherence in atom-like systems.


  Let $(T,d)$ be a metric space and $\phi:\mathbb{R}_+\to \mathbb{R}$ an
increasing, convex function with $\phi(0)=0$. We prove that if $m$ is a
probability measure $m$ on $T$ which is majorizing with respect to $d,\phi$,
that is, $\mathcal{S}:=\sup_{x\in
T}\int^{D(T)}_0\phi^{-1}(\frac{1}{m(B(x,\epsilon))}) d\epsilon <\infty$, then
\[\mathbf{E}\sup_{s,t\in T}|X(s)-X(t)|\leq 32\mathcal{S}\] for each separable
stochastic process $X(t)$, $t\in T$, which satisfies
$\mathbf{E}\phi(\frac{|X(s)-X(t)|}{d(s,t)})\leq 1$ for all $s,t\in T$, $s\neq
t$. This is a strengthening of one of the main results from Talagrand [Ann.
Probab. 18 (1990) 1--49], and its proof is significantly simpler.


  Addressing the communication bottleneck inherent in federated learning (FL),
over-the-air FL (AirFL) has emerged as a promising solution, which is, however,
hampered by deep fading conditions. In this paper, we propose AirFL-Mem, a
novel scheme designed to mitigate the impact of deep fading by implementing a
\emph{long-term} memory mechanism. Convergence bounds are provided that account
for long-term memory, as well as for existing AirFL variants with short-term
memory, for general non-convex objectives. The theory demonstrates that
AirFL-Mem exhibits the same convergence rate of federated averaging (FedAvg)
with ideal communication, while the performance of existing schemes is
generally limited by error floors. The theoretical results are also leveraged
to propose a novel convex optimization strategy for the truncation threshold
used for power control in the presence of Rayleigh fading channels.
Experimental results validate the analysis, confirming the advantages of a
long-term memory mechanism for the mitigation of deep fading.


  Gabrielov numbers describe certain Coxeter-Dynkin diagrams of the 14
exceptional unimodal singularities and play a role in Arnold's strange duality.
In a previous paper, the authors defined Gabrielov numbers of a cusp
singularity with an action of a finite abelian subgroup $G$ of ${\rm
SL}(3,\CC)$ using the Gabrielov numbers of the cusp singularity and data of the
group $G$. Here we consider a crepant resolution $Y \to \CC^3/G$ and the
preimage $Z$ of the image of the Milnor fibre of the cusp singularity under the
natural projection $\CC^3 \to \CC^3/G$. Using the McKay correspondence, we
compute the homology of the pair $(Y,Z)$. We construct a basis of the relative
homology group $H_3(Y,Z;\QQ)$ with a Coxeter-Dynkin diagram where one can read
off the Gabrielov numbers.


  We address the question of how the time-resolved bulk Hall response of a two
dimensional honeycomb lattice develops when driving the system with a pulsed
perturbation. A simple toy model that switches a valley Hall signal by breaking
inversion symmetry is studied in detail for slow quasi-adiabatic ramps and
sudden quenches, obtaining an oscillating dynamical response that depends
strongly on doping and time-averaged values that are determined both by the out
of equilibrium occupations and the Berry curvature of the final states. On the
other hand, the effect of irradiating the sample with a circularly-polarized
infrared pump pulse that breaks time reversal symmetry and thus ramps the
system into a non-trivial topological regime is probed. Even though there is a
non quantized average signal due to the break down of the Floquet adiabatical
picture, some features of the photon-dressed topological bands are revealed to
be present even in a few femtosecond timescale. Small frequency oscillations
during the transient response evidence the emergence of dynamical Floquet gaps
which are consistent with the instantaneous amplitude of the pump envelope. On
the other hand, a characteristic heterodyining effect is manifested in the
model. The presence of a remnant Hall response for ultra-short pulses that
contain only a few cycles of the radiation field is briefly discussed.


  Portfolio diversification and active risk management are essential parts of
financial analysis which became even more crucial (and questioned) during and
after the years of the Global Financial Crisis. We propose a novel approach to
portfolio diversification using the information of searched items on Google
Trends. The diversification is based on an idea that popularity of a stock
measured by search queries is correlated with the stock riskiness. We penalize
the popular stocks by assigning them lower portfolio weights and we bring
forward the less popular, or peripheral, stocks to decrease the total riskiness
of the portfolio. Our results indicate that such strategy dominates both the
benchmark index and the uniformly weighted portfolio both in-sample and
out-of-sample.


  We deal with dynamics of the~$\beta$-Fermi-Pasta-Ulam-Tsingou chain with one
free end, subjected to the sinusoidal periodic force. We examine evolution of
the total energy, supplied at large times. In the harmonic case~($\beta=0$),
the energy grows in time linearly at non-zero group velocities, corresponding
to the excitation frequency and grows in time as~$\sqrt{t}$ at zero group
velocity. Explanation of behavior in time of the energy is proposed by analysis
of obtained approximate closed-form expression for the field of particle
velocities.
  In the weak anharmonic case, large-time asymptotic approximation for the
total energy is obtained by using the renormalized dispersion relation.
Operating of the approximation, we analyze energy transfer at the driving
frequencies, lying both in the pass-band and in the stop-band of the harmonic
chain. Consistency of the asymptotic assesses with the results of numerical
simulations is discussed.


  We construct a gauge-invariant action for covariant type II string field
theory in the NS-NS sector. Our construction is based on the large Hilbert
space description and Zwiebach's string products are used. First, we rewrite
the action for bosonic string field theory into a new form where a state in the
kernel of the generator of the gauge transformation appears explicitly. Then we
use the same strategy and write down our type II action, where a projector onto
the small Hilbert space plays an important role. We present lower-order terms
up to quartic order and show that three-point amplitudes are reproduced
correctly.


  For the interactions between a He($2 ^3S$) atom and a He($2 ^3P$) atom for
like isotopes, we report perturbation theoretic calculations using accurate
variational wave functions in Hylleraas coordinates of the coefficients
determining the potential energies at large internuclear separations. We
evaluate the coefficient $C_{3}$ of the first order resonant dipole-dipole
energy and the van der Waals coefficients $C_{6}$, $C_{8}$, and $C_{10}$ for
the second order energies arising from the mutual perturbations of
instantaneous electric dipole, quadrupole, and octupole interactions. We also
evaluate the coefficient $C_{9}$ of the leading contribution to the third order
energy. We establish definitive values including treatment of the finite
nuclear mass for the ${}^3$He($2 ^3S$)--${}^3$He($2 ^3P$) and ${}^4$He($2
^3S$)--${}^4$He($2 ^3P$) interactions.


  The effective representation, precessing, analysis, and visualization of
large-scale structured data over graphs are gaining a lot of attention. So far
most of the literature has focused on real-valued signals. However, signals are
often sparse in the Fourier domain, and more informative and compact
representations for them can be obtained using the complex envelope of their
spectral components, as opposed to the original real-valued signals. Motivated
by this fact, in this work we generalize graph convolutional neural networks
(GCN) to the complex domain, deriving the theory that allows to incorporate a
complex-valued graph shift operators (GSO) in the definition of graph filters
(GF) and process complex-valued graph signals (GS). The theory developed can
handle spatio-temporal complex network processes. We prove that complex-valued
GCNs are stable with respect to perturbations of the underlying graph support,
the bound of the transfer error and the bound of error propagation through
multiply layers. Then we apply complex GCN to power grid state forecasting,
power grid cyber-attack detection and localization.


  We investigate exciton spin memory in individual InAs/GaAs self-assembled
quantum dots via optical alignment and conversion of exciton polarization in a
magnetic field. Quasiresonant phonon-assisted excitation is successfully
employed to define the initial spin polarization of neutral excitons. The
conservation of the linear polarization generated along the bright exciton
eigenaxes of up to 90% and the conversion from circular- to linear polarization
of up to 47% both demonstrate a very long spin relaxation time with respect to
the radiative lifetime. Results are quantitatively compared with a model of
pseudo-spin 1/2 including heavy-to-light hole mixing.


  The Bluetooth Special Interest Group (Bluetooth SIG) introduced a new feature
for highly accurate localization called the Direction Finding in the Bluetooth
Core Specification 5.1. Since this new localization feature is relatively new,
despite the significant interest of industry and academia in the accurate
positioning of Bluetooth devices/tags, there are only a handful of experimental
studies conducted to evaluate the performance of the new technology.
Furthermore, these experimental works are constrained to only indoor
environments or performed with hardware emulation of Bluetooth 5.1 via
Universal Software Radio Peripherals (USRPs). In this paper, we perform an
experimental study on the positioning accuracy of the direction finding using
COTS Bluetooth 5.1 devices in booth indoor and outdoor environments to provide
insights on the performance gap under these different experimental settings.
Our results demonstrate that the average angular error in an outdoor
environment is 0.28 degrees, significantly improving the angular error measured
in an indoor environment by 73%. It is also demonstrated that the average
positioning accuracy measured in an outdoor environment is 22cm which is 39.7%
smaller than that measured in an indoor environment.


  Using confocal-microscopy we investigate the structure of binary mixtures of
colloidal hard spheres with size ratio q=0.61. As a function of the packing
fraction of the two particle species, we observe a marked change of the
dominant wavelength in the pair correlation function. This behavior is in
excellent agreement with a recently predicted structural crossover in such
mixtures. In addition, the repercussions of structural crossover on the
real-space structure of a binary fluid are analyzed. We suggest a relation
between crossover and the lateral extension of networks containing only equally
sized particles that are connected by nearest neighbor bonds. This is supported
by Monte-Carlo simulations which are performed at different packing fractions
and size ratios.


  Aims. We aim to infer the sub-surface distribution of the Sun's
non-axisymmetric azimuthal magnetic flux from observable quantities, such as
the surface magnetic field and the large scale plasma flows.
  Methods. We have built a kinematic flux transport model of the solar dynamo
based on the Babcock-Leighton framework. We constructed the source term for the
poloidal field using SOLIS magnetograms spanning three solar cycles. Based on
this source we calculated the azimuthal flux below the surface. The flux
transport model has two free parameters which we constrain using sunspot
observations from cycle 22. We compared the model results with observations
from cycle 23.
  Results. The structure of the azimuthal field is mainly axisymmetric. The
departures from axisymmetry represent, on average, ~3% of the total azimuthal
flux. Owing to its relative weakness, the non-axisymmetric structure of the
azimuthal field does not have a significant impact on the location in which the
emergences appear or on the amount of flux contained in them. We find that the
probability of emergence is a function of the ratio between the flux content of
an active region and the underlying azimuthal flux.


  Our series of recent work on the transmission coefficient of open quantum
systems in one dimension will be reviewed. The transmission coefficient is
equivalent to the conductance of a quantum dot connected to leads of quantum
wires. We will show that the transmission coefficient is given by a sum over
all discrete eigenstates without a background integral. An apparent
"background" is in fact not a background but generated by tails of various
resonance peaks. By using the expression, we will show that the Fano asymmetry
of a resonance peak is caused by the interference between various discrete
eigenstates. In particular, an unstable resonance can strongly skew the peak of
a nearby resonance.


  We construct self-adjoint operators in the direct sum of a complex Hilbert
space $H$ and a finite dimensional complex inner product space $W$. The
operator theory developed in this paper for the Hilbert space $H\oplus W$ is
originally motivated by some fourth-order differential operators, studied by
Everitt and others, having orthogonal polynomial eigenfunctions. Generated by a
closed symmetric operator $T_{0}$ in $H$ with equal and finite deficiency
indices and its adjoint $T_{1}$, we define \textit{families} of minimal
operators $\{\widehat{T}_{0}\}$ and maximal operators $\{\widehat{T}_{1}\}$ in
the extended space $H\oplus W$ and establish, using a recent theory of complex
symplectic geometry, developed by Everitt and Markus, a characterization of
self-adjoint extensions of $\{\widehat{T}_{0}\}$ when the dimension of the
extension space $W$ is not greater than the deficiency index of $T_{0}$. A
generalization of the classical Glazman-Krein-Naimark (GKN) Theorem - called
the GKN-EM Theorem to acknowledge the work of Everitt and Markus - is key to
finding these self-adjoint extensions in $H\oplus W.$ We consider several
examples to illustrate our results.


  If supernova remnants (SNRs) are the sites of cosmic-ray acceleration, the
associated nuclear interactions should result in observable fluxes of TeV
gamma-rays from the nearest SNRs. Measurements of the gamma-ray flux from six
nearby, radio-bright, SNRs have been made with the Whipple Observatory
gamma-ray telescope. No significant emission has been detected and upper limits
on the $>$300 GeV flux are reported. Three of these SNRs (IC443, gamma-Cygni
and W44) are spatially coincident with low latitude unidentified sources
detected with EGRET. These upper limits weaken the case for the simplest models
of shock acceleration and energy dependent propagation.


  We present the first symmetry inheritance analysis of fields nonminimally
coupled to gravity. In this work we are focused on the real scalar field $\phi$
with nonminimal coupling of the form $\xi\phi^2 R$. Possible cases of the
symmetry noninheriting fields are constrained by the properties of the Ricci
tensor and the scalar potential. Examples of such spacetimes can be found among
those which are "dressed" with the stealth scalar field, a nontrivial scalar
field configuration with the vanishing energy-momentum tensor. We classify the
scalar field potentials which allow the symmetry noninheriting stealth field
configurations on top of the exact solutions of the Einstein's gravitational
field equation with the cosmological constant.


  In this paper we present a method for single-channel wind noise reduction
using our previously proposed diffusion-based stochastic regeneration model
combining predictive and generative modelling. We introduce a non-additive
speech in noise model to account for the non-linear deformation of the membrane
caused by the wind flow and possible clipping. We show that our stochastic
regeneration model outperforms other neural-network-based wind noise reduction
methods as well as purely predictive and generative models, on a dataset using
simulated and real-recorded wind noise. We further show that the proposed
method generalizes well by testing on an unseen dataset with real-recorded wind
noise. Audio samples, data generation scripts and code for the proposed methods
can be found online (https://uhh.de/inf-sp-storm-wind).


  We investigate the quality of associations of astronomical sources from
multi-wavelength observations using simulated detections that are realistic in
terms of their astrometric accuracy, small-scale clustering properties and
selection functions. We present a general method to build such mock catalogs
for studying associations, and compare the statistics of cross-identifications
based on angular separation and Bayesian probability criteria. In particular,
we focus on the highly relevant problem of cross-correlating the ultraviolet
Galaxy Evolution Explorer (GALEX) and optical Sloan Digital Sky Survey (SDSS)
surveys. Using refined simulations of the relevant catalogs, we find that the
probability thresholds yield lower contamination of false associations, and are
more efficient than angular separation. Our study presents a set of recommended
criteria to construct reliable cross-match catalogs between SDSS and GALEX with
minimal artifacts.


  Electron acceleration to non-thermal, ultra-relativistic energies (~ 10-100
TeV) is revealed by radio and X-ray observations of shocks in young supernova
remnants (SNRs). The diffusive shock acceleration (DSA) mechanism is usually
invoked to explain this acceleration, but the way in which electrons are
initially energized or 'injected' into this acceleration process starting from
thermal energies is an unresolved problem. In this paper we study the initial
acceleration of electrons in non-relativistic shocks from first principles,
using two- and three-dimensional particle-in-cell (PIC) plasma simulations. We
systematically explore the space of shock parameters (the Alfv\'enic Mach
number, M_A, the shock velocity, v_{sh}, the angle between the upstream
magnetic field and the shock normal, theta_{Bn}, and the ion to electron mass
ratio, m_i/m_e). We find that significant non-thermal acceleration occurs due
to the growth of oblique whistler waves in the foot of quasi-perpendicular
shocks. The obtained electron energy distributions show power law tails with
spectral indices up to alpha ~ 3-4. The maximum energies of the accelerated
particles are consistent with the electron Larmor radii being comparable to
that of the ions, indicating potential injection into the subsequent DSA
process. This injection mechanism, however, requires the shock waves to have
fairly low Alf\'enic Mach numbers, M_A <~ 20, which is consistent with the
theoretical conditions for the growth of whistler waves in the shock foot (M_A
<~ (m_i/m_e)^{1/2}). Thus, if the whistler mechanism is the only robust
electron injection process at work in SNR shocks, then SNRs that display
non-thermal emission must have significantly amplified upstream magnetic
fields. Such field amplification is likely achieved by the escaping cosmic
rays, so electron and proton acceleration in SNR shocks must be interconnected.


  Aim: The late stages of stellar evolution are mainly governed by the mass of
the stars. Low- and intermediate-mass stars lose copious amounts of mass during
the asymptotic giant branch (AGB) which obscure the central star making it
difficult to study the stellar spectra and determine the stellar mass. In this
study, we present observational data that can be used to determine lower limits
to the stellar mass. Method: Spectra of nine heavily reddened AGB stars taken
by the Herschel Space Observatory display numerous molecular emission lines.
The strongest emission lines are due to H2O. We search for the presence of
isotopologues of H2O in these objects. Result: We detected the 16O and 17O
isotopologues of water in these stars, but lines due to H2^{18}O are absent.
The lack of 18O is predicted by a scenario where the star has undergone
hot-bottom burning which preferentially destroys 18O relative to 16O and 17O.
From stellar evolution calculations, this process is thought to occur when the
stellar mass is above 5 Msun for solar metallicity. Hence, observations of
different isotopologues of H2O can be used to help determine the lower limit to
the initial stellar mass. Conclusion: From our observations, we deduce that
these extreme OH/IR stars are intermediate-mass stars with masses of >= 5 Msun.
Their high mass-loss rates of ~ 1.0e-4 Msun/yr may affect the enrichment of the
interstellar medium and the overall chemical evolution of our Galaxy.


  Unmanned aerial vehicles (UAVs), also known as drones, have emerged as a
promising mode of fast, energy-efficient, and cost-effective package delivery.
A considerable number of works have studied different aspects of drone package
delivery service by a supplier, one of which is delivery planning. However,
existing works addressing the planning issues consider a simple case of perfect
delivery without service interruption, e.g., due to accident which is common
and realistic. Therefore, this paper introduces the joint ground and aerial
delivery service optimization and planning (GADOP) framework. The framework
explicitly incorporates uncertainty of drone package delivery, i.e., takeoff
and breakdown conditions. The GADOP framework aims to minimize the total
delivery cost given practical constraints, e.g., traveling distance limit.
Specifically, we formulate the GADOP framework as a three-stage stochastic
integer programming model. To deal with the high complexity issue of the
problem, a decomposition method is adopted. Then, the performance of the GADOP
framework is evaluated by using two data sets including Solomon benchmark suite
and the real data from one of the Singapore logistics companies. The
performance evaluation clearly shows that the GADOP framework can achieve
significantly lower total payment than that of the baseline methods which do
not take uncertainty into account.


  We investigate the issue of regularization/renormalization in the presence of
a nontrivial background in the case of 1+1-(supersymmetric) solitons. In
particular we study and compare the commonly employed regularization methods
(mode- energy/momentum- cutoff and derivative regularization). We show that the
main point for a consistent regularization/renormalization is to find a
relation between the ``cutoffs'' in the vacuum and the nontrivial sector so
that they can be related in a consistent manner. For each scheme we give a
principle to derive this relation and to perform calculations in a consistent
way. These principles are simple and not restricted to two dimensions or
supersymmetric theories.


  This paper introduces a novel idea for representation of individuals using
quaternions in swarm intelligence and evolutionary algorithms. Quaternions are
a number system, which extends complex numbers. They are successfully applied
to problems of theoretical physics and to those areas needing fast rotation
calculations. We propose the application of quaternions in optimization, more
precisely, we have been using quaternions for representation of individuals in
Bat algorithm. The preliminary results of our experiments when optimizing a
test-suite consisting of ten standard functions showed that this new algorithm
significantly improved the results of the original Bat algorithm. Moreover, the
obtained results are comparable with other swarm intelligence and evolutionary
algorithms, like the artificial bees colony, and differential evolution. We
believe that this representation could also be successfully applied to other
swarm intelligence and evolutionary algorithms.


  The Juno mission is delivering spectacular data of Jupiter's magnetic field,
while the gravity measurements finally allow constraining the depth of the
winds observed at cloud level. However, to which degree the zonal winds
contribute to the planet's dynamo action remains an open question. Here we
explore numerical dynamo simulations that include an Jupiter-like electrical
conductivity profile and successfully model the planet's large scale field. We
concentrate on analyzing the dynamo action in the Steeply Decaying Conductivity
Region (SDCR) where the high conductivity in the metallic Hydrogen region drops
to the much lower values caused by ionization effects in the very outer
envelope of the planet. Our simulations show that the dynamo action in the SDCR
is strongly ruled by diffusive effects and therefore quasi stationary. The
locally induced magnetic field is dominated by the horizontal toroidal field,
while the locally induced currents flow mainly in the latitudinal direction.
The simple dynamics can be exploited to yield estimates of surprisingly high
quality for both the induced field and the electric currents in the SDCR. These
could be potentially be exploited to predict the dynamo action of the zonal
winds in Jupiter's SDCR but also in other planets.


  Objective: To combine medical knowledge and medical data to interpretably
predict the risk of disease. Methods: We formulated the disease prediction task
as a random walk along a knowledge graph (KG). Specifically, we build a KG to
record relationships between diseases and risk factors according to validated
medical knowledge. Then, a mathematical object walks along the KG. It starts
walking at a patient entity, which connects the KG based on the patient current
diseases or risk factors and stops at a disease entity, which represents the
predicted disease. The trajectory generated by the object represents an
interpretable disease progression path of the given patient. The dynamics of
the object are controlled by a policy-based reinforcement learning (RL) module,
which is trained by electronic health records (EHRs). Experiments: We utilized
two real-world EHR datasets to evaluate the performance of our model. In the
disease prediction task, our model achieves 0.743 and 0.639 in terms of macro
area under the curve (AUC) in predicting 53 circulation system diseases in the
two datasets, respectively. This performance is comparable to the commonly used
machine learning (ML) models in medical research. In qualitative analysis, our
clinical collaborator reviewed the disease progression paths generated by our
model and advocated their interpretability and reliability. Conclusion:
Experimental results validate the proposed model in interpretably evaluating
and optimizing disease prediction. Significance: Our work contributes to
leveraging the potential of medical knowledge and medical data jointly for
interpretable prediction tasks.


  We look to gradations of Kac-Moody Lie algebras by Kac-Moody root systems
with finite dimensional weight spaces. We extend, to general Kac-Moody Lie
algebras, the notion of C-admissible pair as introduced by H. Rubenthaler and
J. Nervi for semi-simple and affine Lie algebras. If g is a Kac-Moody Lie
algebra (with Dynkin diagram indexed by I) and (I,J) is such a C-admissible
pair, we construct a C-admissible subalgebra g^J, which is a Kac-Moody Lie
algebra of the same type as g, and whose root system \Sigma grades finitely the
Lie algebra g. For an admissible quotient \rho : I \rightarrow I we build also
a Kac-Moody subalgebra g^\rho which grades finitely the Lie algebra g. If g is
affine or hyperbolic, we prove that the classification of the gradations of g
is equivalent to those of the C-admissible pairs and of the admissible
quotients. For general Kac-Moody Lie algebras of indefinite type, the situation
may be more complicated; it is (less precisely) described by the concept of
generalized C-admissible pairs.


  Motivated by the engineering applications of uncertainty quantification, in
this work we draw connections between the notions of random quantum states and
operations in quantum information with probability distributions commonly
encountered in the field of orientation statistics. This approach identifies
natural probability distributions that can be used in the analysis, simulation,
and inference of quantum information systems. The theory of exponential
families on Stiefel manifolds provides the appropriate generalization to the
classical case, and fortunately there are many existing techniques for
inference and sampling that exist for these distributions. Furthermore, this
viewpoint motivates a number of additional questions into the convex geometry
of quantum operations relative to both the differential geometry of Stiefel
manifolds as well as the information geometry of exponential families defined
upon them. In particular, we draw on results from convex geometry to
characterize which quantum operations can be represented as the average of a
random quantum operation.


  We present a method for discovering never-seen-before objects in 3D point
clouds obtained from sensors like Microsoft Kinect. We generate supervoxels
directly from the point cloud data and use them with a Siamese network, built
on a recently proposed 3D convolutional neural network architecture. We use
known objects to train a non-linear embedding of supervoxels, by optimizing the
criteria that supervoxels which fall on the same object should be closer than
those which fall on different objects, in the embedding space. We test on
unknown objects, which were not seen during training, and perform clustering in
the learned embedding space of supervoxels to effectively perform novel object
discovery. We validate the method with extensive experiments, quantitatively
showing that it can discover numerous unseen objects while being trained on
only a few dense 3D models. We also show very good qualitative results of
object discovery in point cloud data when the test objects, either specific
instances or even categories, were never seen during training.


  Using the effective potential method, we computed one-loop corrections to the
mass matrix of neutral Higgs bosons of the Non-Holomorphic Supersymmetric
Standard Model (NHSSM) with explicit CP violation, where the radiative
corrections due to the quarks and squarks of the third generation were taken
into account. We observed that the non-holomorphic trilinear couplings can
compete with the holomorphic ones in CP violating issues for the mass and
mixing of the neutral Higgs bosons.


  Networks are paradigms for describing complex biological, social and
technological systems. Here I argue that networks provide a coherent framework
to construct coarse-grained models for many different physical systems. To
elucidate these ideas, I discuss two long-standing problems. The first concerns
the structure and dynamics of magnetic fields in the solar corona, as
exemplified by sunspots that startled Galileo almost 400 years ago. We
discovered that the magnetic structure of the corona embodies a scale free
network, with spots at all scales. A network model representing the
three-dimensional geometry of magnetic fields, where links rewire and nodes
merge when they collide in space, gives quantitative agreement with available
data, and suggests new measurements. Seismicity is addressed in terms of
relations between events without imposing space-time windows. A metric
estimates the correlation between any two earthquakes. Linking strongly
correlated pairs, and ignoring pairs with weak correlation organizes the
spatio-temporal process into a sparse, directed, weighted network. New scaling
laws for seismicity are found. For instance, the aftershock decay rate
decreases as 1/t in time up to a correlation time, t[omori]. An estimate from
the data gives t[omori] to be about one year for small magnitude 3 earthquakes,
about 1400 years for the Landers event, and roughly 26,000 years for the
earthquake causing the 2004 Asian tsunami. Our results confirm Kagan's
conjecture that aftershocks can rumble on for centuries.


  The Lambda polarization in muon neutrino charged current interactions has
been measured in the NOMAD experiment. We observe negative polarization along
the W - boson direction which is enhanced in the target fragmentation region:
  Px (xF < 0) = -0.21 +/- 0.04(stat) +/- 0.02(sys). In the current
fragmentation region we find: Px (xF > 0) = -0.09 +/- 0.06(stat) +/- 0.03(sys).
These results provide a test of different models describing the nucleon spin
composition and the spin transfer mechanisms. A significant transverse
polarization (in the direction orthogonal to the Lambda production plane) has
been observed for the first time in a neutrino experiment: Py = -0.22 +/-
0.03(stat) +/- 0.01(sys). The dependence of the absolute value of Py on the
Lambda transverse momentum with respect to the hadronic jet direction is in
qualitative agreement with the results from unpolarized hadron-hadron
experiments.


  We give an overview of the recursive characterisations of random matrix
ensembles that are currently at the forefront of random matrix theory by way of
studying two classes of ensembles using two different types of recursive
schemes: Established theory on Selberg correlation integrals is used to derive
linear differential equations on the eigenvalue densities and resolvents of the
classical matrix ensembles, which lead to $1$-point recursions, understood to
be analogues of the Harer-Zagier recursion, for the expansion coefficients of
the associated $1$-point cumulants, while loop equation analysis is used to
recursively compute some leading order correlator expansion coefficients
pertaining to certain products of random matrices that have recently come into
interest due to their connections to Muttalib-Borodin ensembles and integrals
of Harish-Chandra-Itzykson-Zuber type. We also show how the aforementioned
differential equations can be used to characterise the large $N$ limiting
statistics of the classical matrix ensembles' eigenvalue densities in the
global and edge scaling regimes and moreover give a comprehensive review of how
the Isserlis-Wick theorem implies ribbon graph interpretations for mixed
moments and cumulants of some of the ensembles at hand. It is expected that
this thesis will serve as a valuable resource for readers wanting a
well-rounded introduction to classical matrix ensembles, matrix product
ensembles, $1$-point recursions, loop equations, Selberg correlation integrals,
and ribbon graphs.


  In the event of a black hole (BH) forming stellar collapse, the neutrino
signal should terminate abruptly at the moment of BH formation, after a phase
of steady accretion. Since neutrinos are expected to reach Earth hours before
the electromagnetic signal, the combined detection of the neutrino burst
through multiple neutrino telescopes could allow to promptly determine the
angular location of a nearby stellar collapse in the sky with high precision.
In this paper, we contrast the triangulation pointing procedure that relies on
the rise time of the neutrino curve, often considered in the literature, to the
one that takes advantage of the cutoff of the neutrino curve at the moment of
BH formation. By forecasting the neutrino signal expected in the IceCube
Neutrino Observatory, Hyper-Kamiokande and DUNE, we devise a strategy to
optimize the identification of the rise and cutoff time of the neutrino curve.
We show that the triangulation method developed by employing the end tail of
the neutrino curve allows to achieve at least one order of magnitude
improvement in the pointing precision for a galactic burst, while being
insensitive to the neutrino mixing scenario. The triangulation pointing method
based on the cutoff of the neutrino curve will also guarantee a better
performance for BH forming collapses occurring beyond our own Galaxy.


  We provide new results showing identification of a large class of fixed-T
panel models, where the response variable is an unknown, weakly monotone,
time-varying transformation of a latent linear index of fixed effects,
regressors, and an error term drawn from an unknown stationary distribution.
Our results identify the transformation, the coefficient on regressors, and
features of the distribution of the fixed effects. We then develop a
full-commitment intertemporal collective household model, where the implied
quantity demand equations are time-varying functions of a linear index. The
fixed effects in this index equal logged resource shares, defined as the
fractions of household expenditure enjoyed by each household member. Using
Bangladeshi data, we show that women's resource shares decline with household
budgets and that half of the variation in women's resource shares is due to
unobserved household-level heterogeneity.


  This paper studies a non-stochastic version of Fernholz's stochastic
portfolio theory for a simple model of stock markets with continuous price
paths. It establishes non-stochastic versions of the most basic results of
stochastic portfolio theory and discusses connections with Stroock-Varadhan
martingales.