  Due to their exceptional mechanical and chemical properties and their natural
abundance, cellulose nanocrystals (CNCs) are promising building blocks of
sustainable polymer composites. However, the rapid gelation of CNC dispersions
has generally limited CNC-based composites to low CNC fractions, in which
polymer remains the dominant phase. Here we report on the formulation and
processing of crosslinked CNC-epoxy composites with a CNC fraction exceeding 50
wt.%. The microstructure comprises sub-micrometer aggregates of CNCs
crosslinked to polymer, which are analogous to the lamellar structure of nacre
and promotes toughening mechanisms associated with bulk ductile behavior,
despite the brittle behavior of the aggregates at the nanoscale. At 63 wt.%
CNCs, the composites exhibit a hardness of 0.66 GPa and a fracture toughness of
5.2 MPa.m$^{1/2}$. The hardness of this all-organic material is comparable to
aluminum alloys, and the fracture toughness at the centimeter scale is
comparable to that of wood cell wall. We show that CNC-epoxy composite objects
can be shaped from the gel precursors by direct-write printing and by casting,
while the cured composites can be machined into complex 3D shapes. The
formulation, processing route, and the insights on toughening mechanisms gained
from our multiscale approach can be applied broadly to highly loaded
nanocomposites.


  The stability of social relationships is important to animals living in
groups, and social network analysis provides a powerful tool to help
characterize and understand their (in)stability and the consequences at the
group level. However, the use of dynamic social networks is still limited in
this context as it requires long-term social data and new analytical tools.
Here, we study the dynamic evolution of a group of 29 Guinea baboons using a
dataset of automatically collected cognitive tests comprising more than 16M
records collected over 3 years. We first built a monthly aggregated temporal
network describing the baboon's co-presence in the cognitive testing booths. We
then used a null model, considering the heterogeneity in the baboons' activity,
to define both positive (association) and negative (avoidance) monthly
networks. We tested social balance theory by combining these positive and
negative social networks. The results showed that the networks were
structurally balanced and that newly created edges also tended to preserve
social balance. We investigated several network metrics to gain insights into
the individual level and group level social networks long-term temporal
evolution. A measure of similarity between successive monthly networks was able
to pinpoint periods of stability and instability and to show how some baboons'
ego-networks remained stable while others changed radically. Our study confirms
the prediction of social balance theory but also shows that large fluctuations
in the numbers of triads may limit its applicability to study the dynamic
evolution of animal social networks. In contrast, the use of the similarity
measure proved to be very versatile and sensitive in detecting relationships'
(in)stabilities at different levels. The changes we identified can be linked,
at least in some cases, to females changing primary male, as observed in the
wild.


  Logic programs are now used as a representation of object-oriented source
code in academic prototypes for about a decade. This representation allows a
clear and concise implementation of analyses of the object-oriented source
code. The full potential of this approach is far from being explored. In this
paper, we report about an application of the well-established theory of update
propagation within logic programs. Given the representation of the
object-oriented code as facts in a logic program, a change to the code
corresponds to an update of these facts. We demonstrate how update propagation
provides a generic way to generate incremental versions of such analyses.


  At present, there are many methods of quantum entanglement of particles with
an electromagnetic field. Most methods have a low probability of quantum
entanglement and not an exact theoretical apparatus based on an approximate
solution of the Schrodinger equation. There is a need for new methods for
obtaining quantum-entangled particles and mathematically accurate studies of
such methods. In this paper, a quantum harmonic oscillator (for example, an
electron in a magnetic field) interacting with a quantized electromagnetic
field is considered. Based on the exact solution of the Schrodinger equation
for this system, it is shown that for certain parameters there can be a large
quantum entanglement between the electron and the electromagnetic field.
Quantum entanglement is analyzed on the basis of a mathematically exact
expression for the Schmidt modes and the Von Neumann entropy.


  The study of ancient writings has great value for archaeology and philology.
Essential forms of material are photographic characters, but manual
photographic character recognition is extremely time-consuming and
expertise-dependent. Automatic classification is therefore greatly desired.
However, the current performance is limited due to the lack of annotated data.
Data generation is an inexpensive but useful solution for data scarcity.
Nevertheless, the diverse glyph shapes and complex background textures of
photographic ancient characters make the generation task difficult, leading to
the unsatisfactory results of existing methods. In this paper, we propose an
unsupervised generative adversarial network called AGTGAN. By the explicit
global and local glyph shape style modeling followed by the stroke-aware
texture transfer, as well as an associate adversarial learning mechanism, our
method can generate characters with diverse glyphs and realistic textures. We
evaluate our approach on the photographic ancient character datasets, e.g.,
OBC306 and CSDD. Our method outperforms the state-of-the-art approaches in
various metrics and performs much better in terms of the diversity and
authenticity of generated samples. With our generated images, experiments on
the largest photographic oracle bone character dataset show that our method can
achieve a significant increase in classification accuracy, up to 16.34%.


  We prove that the existence of a complete metric space of cardinality at most
$2^{\kappa}$ admitting Kuratowski partition is a consequence of $\kappa$ being
the smallest real-valued measurable cardinal not greater than $ 2^{\aleph_0}$.


  The shell model embedded in the continuum is applied to calculate the
astrophysical S-factor and the reaction rate for the radiative proton capture
reaction 17F(p,gamma)18Ne. The dominant contribution to the cross-section at
very low energies is due to M1 transitions J_i^pi = 2^+ --> J_f^pi = 2_1^+
whose magnitude is controlled by a weakly bound 2_2^+ state at the excitation
energy E_x = 3.62 MeV.


  Numerous exact solutions to the nonlinear mean-field equations of motion are
constructed for multicomponent Bose-Einstein condensates on one, two, and three
dimensional optical lattices. We find both stationary and nonstationary
solutions, which are given in closed form. Among these solutions are a
vortex-anti-vortex array on the square optical lattice and modes in which two
or more components slosh back and forth between neighboring potential wells. We
obtain a variety of solutions for multicomponent condensates on the simple
cubic lattice, including a solution in which one condensate is at rest and the
other flows in a complex three-dimensional array of intersecting vortex lines.
A number of physically important solutions are stable for a range of parameter
values, as we show by direct numerical integration of the equations of motion.


  Beam structure is one of the most widely used structures in mechanical
engineering and civil engineering. Ultrasonic guided wave based crack
identification is one of the most important and accepted approaches applied to
detect unseen small flaws in structures. Numerical simulations of ultrasonic
guided wave propagation have caught more and more attention due to the fast
development of hardware and software in the last few years. From all the
numerical simulation methods, wavelet based finite element method has been
proved to be one of the most efficient methods due to its better spatial
resolution, which means it needs fewer elements to get the same accuracy and it
can improve the calculation cost significantly. However, it needs a very small
time interval. Laplace transform can easily convert the time domain into a
frequency domain and then revert it back to a time domain. Laplace transform
has thus the advantage of finding better results with a very large time
interval. which can save a lot of time cost. This paper will present an
innovative method combining Laplace transform and the B-spline wavelet on
interval (BSWI) finite element method. This novel method allows to get results
with the same accuracy and with a significantly lower time cost, which would
not only decrease the total number of elements in the structure but also
increase the time integration interval. The numerical Laplace transform and
BSWI finite element will be introduced. Moreover, this innovative method is
applied to simulate the ultrasonic wave propagation in a beam structure in
different materials. Numerical examples for crack identification in beam
structures have been studied for verification.


  We present ultrahigh-resolution measurements of state-to-state inelastic
differential cross sections for NO-Ne and NO-Ar collisions, obtained by
combining the Stark deceleration and velocity map imaging techniques. We show
that for counterpropagating crossed beam geometries, the effect of the velocity
spreads of the reagent beams on the angular resolution of the images is
minimized. Futhermore, the counterpropagating geometry results in images that
are symmetric with respect to the relative velocity vector. This allows for the
use of inverse Abel transformation methods that enhance the resolution further.
State-resolved diffraction oscillations in the differential cross sections are
measured with an angular resolution approaching 0.3$^\circ$. Distinct
structures observed in the cross sections gauge the quality of recent \emph{ab
initio} potential energy surfaces for NO-rare gas atom collisions with
unprecedented precision.


  The stability of hybrid stars with first-order phase transitions as
determined by calculating fundamental radial oscillation modes is known to
differ from the predictions of the widely-used Bardeen--Thorne--Meltzer
criterion. We consider the effects of out-of-chemical-equilibrium physics on
the radial modes and hence stability of these objects. For a barotropic
equation of state, this is done by allowing the adiabatic sound speed to differ
from the equilibrium sound speed. We show that doing so extends the stable
branches of stellar models, allowing stars with rapid phase transitions to
support stable higher-order stellar multiplets similarly to stars with multiple
slow phase transitions. We also derive a new junction condition to impose on
the oscillation modes at the phase transition. Termed the reactive condition,
it is physically motivated, consistent with the generalized junction conditions
between two phases, and has the common rapid and slow conditions as limiting
cases. Unlike the two common cases, it can only be applied to nonbarotropic
stars. We apply this junction condition to hybrid stellar models generated
using a two-phase equation of state consisting of nuclear matter with unpaired
quark matter at high densities joined by a first-order phase transition and
show that like in the slow limiting case, stars that are classically unstable
are stabilized by a finite chemical reaction speed.


  In the absence of Gaussianity assumptions without disturbing spatial
continuity interpolating along the whole spatial surface for different time
lags is challenging. The past researchers pay enough attention to
Spatio-temporal interpolation ignoring the dynamic behavior of a spatial mean
function, threshold distance, and direction of maintaining spatial continuity.
Therefore, we employ hierarchical spatial clustering (HSC) to preserve local
spatial stationarity. This research work introduces a hybrid extreme valued
copula-based Spatio-temporal interpolation algorithm. Spatial dependence is
captured by a blended extreme valued probability distribution (BEVD). Temporal
dependency is modeled by the Bi-directional long short-time memory (BLSTM) at
different temporal granularities, 1 month, 2 months, and 3 months.
Spatio-temporal dependence is modeled by the Gumbel-Hougaard copula (GH). We
apply the proposed Spatio-temporal interpolation approach to the air pollution
data (Outdoor Particulate Matter (PM) concentration) of Delhi, collected from
the website of the Central Pollution Control Board, India as a crucial
circumstantial study. This article describes a probabilistic-recurrent neural
networking algorithm for Spatio-temporal interpolation. This Spatio-temporal
hybrid copula interpolation algorithm outperforms and is efficient enough to
detect spatial trends and temporal influence. From the entire research, we
notice that PM concentration in a year reaches a maximum, generally in November
and December. The northern and central part of Del-hi is the most sensitive
regarding air pollution.


  We give some applications of closure operators in category of groups and link
them with the join problem of subnormal subgroups.


  The advent of all-sky facilities, such as the Neil Gehrels Swift observatory,
the All Sky Automated Search for Supernovae (ASASSN), eROSITA and Gaia has led
to a new appreciation of the importance of transient sources in solving
outstanding astrophysical questions. Identification and catalogue
cross-matching of transients has been eased over the last two decades by the
Virtual Observatory but we still lack a client capable of providing a seamless,
self-consistent, analysis of all observations made of a particular object by
current and historical facilities. HILIGT is a web-based interface which polls
individual servers written for XMM-Newton, INTEGRAL and other missions, to find
the fluxes, or upper limits, from all observations made of a given target.
These measurements are displayed as a table or a time series plot, which may be
downloaded in a variety of formats. HILIGT currently works with data from X-ray
and Gamma-ray observatories.


  In 2004, Das, Saxena and Gulati proposed a dynamic ID-based remote user
authentication scheme which has many advantage such as no verifier table, user
freedom to choose and change password and so on. However the subsequent papers
have shown that this scheme is completely insecure and vulnerable to many
attacks. Since then many schemes with improvements to Das et al's scheme has
been proposed but each has its pros and cons. Recently Yan-yan Wang et al. have
proposed a scheme to overcome security weaknesses of Das et al.'s scheme.
However this scheme too is vulnerable to various security attacks such as
password guessing attack, masquerading attack, denial of service attack.


  This is an introductory review of the main features of leptogenesis, one of
the most attractive models of baryogenesis for the explanation of the
matter-antimatter asymmetry of the Universe. The calculation of the asymmetry
in leptogenesis is intimately related to neutrino properties so that
leptogenesis is also an important phenomenological tool to test the see-saw
mechanism for the generation of neutrino masses and mixing and the underlying
theory beyond the Standard Model.


  The potential discovery of unparticles could have far-reaching implications
for particle physics and cosmology. For over a decade, high-energy physicists
have extensively studied the effects of unparticles. In this study, we derive
six types of nonrelativistic potentials between fermions induced by unparticle
exchange in coordinate space. We consider all possible combinations of scalar,
pseudo-scalar, vector, and axial-vector couplings to explore the full range of
possibilities. Previous studies have only examined scalar-scalar (SS),
pseudoscalar-pseudoscalar (PP), vector-vector (VV), and axial-axial-vector (AA)
type interactions, which are all parity even. We propose SP and VA interactions
to extend our understanding of unparticle physics, noting that parity
conservation is not always guaranteed in modern physics. We explore the
possibilities of detecting unparticles through the long-range interactions they
may mediate with ordinary matter. Dedicated experiments using precision
measurement methods can be employed to search for such interactions. We discuss
the properties of these potentials and estimate constraints on several coupling
constants based on existing experimental data. Our findings indicate that the
coupling between vector unparticles and fermions is constrained by up to 9
orders of magnitude more tightly than the previous limits.


  We investigate linearized gauge theories on globally hyperbolic spacetimes in
the BRST formalism. A consistent definition of the classical phase space and of
its Cauchy surface analogue is proposed. We prove that it is isomorphic to the
phase space in the subsidiary condition approach of Hack and Schenkel in the
case of Maxwell, Yang-Mills, and Rarita-Schwinger fields. Defining Hadamard
states in the BRST formalism in a standard way, their existence in the Maxwell
and Yang-Mills case is concluded from known results in the subsidiary condition
(or Gupta-Bleuler) formalism. Within our framework, we also formulate criteria
for non-degeneracy of the phase space in terms of BRST cohomology and discuss
special cases. These include an example in the Yang-Mills case, where
degeneracy is not related to a non-trivial topology of the Cauchy surface.


  We construct a kappa symmetric WZNW model for the OSp(2|2) supergroup, whose
bosonic part is AdS3xS1 space. The field equation gives the chiral current
conservation and the right/left factorization is shown after the kappa symmetry
is fixed. The right-moving modes contain both bosons and fermions while the
left-moving modes contain only bosons.


  We consider parameter estimation for the spread of the Neolithic incipient
farming across Europe using radiocarbon dates. We model the arrival time of
farming at radiocarbon-dated, early Neolithic sites by a numerical solution to
an advancing wavefront. We allow for (technical) uncertainty in the radiocarbon
data, lack-of-fit of the deterministic model and use a Gaussian process to
smooth spatial deviations from the model. Inference for the parameters in the
wavefront model is complicated by the computational cost required to produce a
single numerical solution. We therefore employ Gaussian process emulators for
the arrival time of the advancing wavefront at each radiocarbon-dated site. We
validate our model using predictive simulations.


  In this paper, we develop efficient decoders for non-binary low-density
parity-check (LDPC) codes using the alternating direction method of multipliers
(ADMM). We apply ADMM to two decoding problems. The first problem is linear
programming (LP) decoding. In order to develop an efficient algorithm, we focus
on non-binary codes in fields of characteristic two. This allows us to
transform each constraint in $\mathbb{F}_{2^m}$ to a set of constraints in
$\mathbb{F}_{2}$ that has a factor graph representation. Applying ADMM to the
LP decoding problem results in two types of non-trivial sub-routines. The first
type requires us to solve an unconstrained quadratic program. We solve this
problem efficiently by leveraging new results obtained from studying the above
factor graphs. The second type requires Euclidean projection onto polytopes
that are studied in the literature, a projection that can be solved efficiently
using off-the-shelf techniques, which scale linearly in the dimension of the
vector to project. ADMM LP decoding scales linearly with block length, linearly
with check degree, and quadratically with field size. The second problem we
consider is a penalized LP decoding problem. This problem is obtained by
incorporating a penalty term into the LP decoding objective. The purpose of the
penalty term is to make non-integer solutions (pseudocodewords) more expensive
and hence to improve decoding performance. The ADMM algorithm for the penalized
LP problem requires Euclidean projection onto a polytope formed by embedding
the constraints specified by the non-binary single parity-check code, which can
be solved by applying the ADMM technique to the resulting quadratic program.
Empirically, this decoder achieves a much reduced error rate than LP decoding
at low signal-to-noise ratios.


  In this work we present a number of generalizations of Wick's theorems on
integrals with Gaussian weight to a larger class of weights which we call
subgaussian. Examples of subgaussian contractions are that of Kac-Moody or
Virasoro type, although the concept of a subgaussian weight does not refer a
priori to two-dimensional field theory. The generalization was chosen in such a
way that the contraction rules become a combinatorical way of solving the
Schwinger-Dyson equation. In a still more general setting we prove a relation
between solutions of the Schwinger-Dyson equation and a map $N$, which in the
Gaussian case reduces to normal ordering. Furthermore, we give a number of
results concerning contractions of composite insertions, which do not suffer
from the Johnson-Low problem of ``commutation'' relations that do not satisfy
the Jacobi identity.


  A wide class of Hamiltonian systems with N degrees of freedom and endowed
with, at least, (N-2) functionally independent integrals of motion in
involution is constructed by making use of the two-photon Lie-Poisson
coalgebra. The set of (N-2) constants of the motion is shown to be a universal
one for all these Hamiltonians, irrespectively of the dependence of the latter
on several arbitrary functions and N free parameters. Within this large class
of quasi-integrable N-dimensional Hamiltonians, new families of completely
integrable systems are identified by finding explicitly a new independent
integral through the analysis of the sub-coalgebra structure of the two-photon
algebra. In particular, new completely integrable N-dimensional Hamiltonians
describing natural systems, geodesic flows and static electromagnetic
Hamiltonians are presented.


  We define, for an arbitrary partially ordered set, a multi-variable
polynomial generalizing the hook polynomial.


  The security of two-state quantum key distribution against individual attack
is estimated when the channel has losses and noises. We assume that Alice and
Bob use two nonorthogonal single-photon polarization states. To make our
analysis simple, we propose a modified B92 protocol in which Alice and Bob make
use of inconclusive results and Bob performs a kind of symmetrization of
received states. Using this protocol, Alice and Bob can estimate Eve's
information gain as a function of a few parameters which reflect the
imperfections of devices or Eve's disturbance. In some parameter regions, Eve's
maximum information gain shows counter-intuitive behavior, namely, it decreases
as the amount of disturbances increases. For a small noise rate Eve can extract
perfect information in the case where the angle between Alice's two states is
small or large, while she cannot extract perfect information for intermediate
angles. We also estimate the secret key gain which is the net growth of the
secret key per one pulse. We show the region where the modified B92 protocol
over a realistic channel is secure against individual attack.


  M. E. Rudin in "Partial orders on the types of $\beta {N}$", (Trans. Amer.
Math. Soc., 155, 1971, 353-362) proved (under CH) that for each P-point $u$
there is a P-point $v$ such that $v>_{RK}u$. A. Blass in "Rudin - Kisler
ordering on P-points" (Trans. Amer. Math. Soc. 179, 1973, 145-166) improved
that theorem assuming MA in the place of CH, in that paper he also proved that
under MA each RK-increasing sequence of P-points is upper bounded by a P-point.
We improve Blass results simultaneously in 3 directions - we prove it for each
class of index $\geq 2$ of P-hierarchy (P-points coincidence with a class $P_2$
of P-hierarchy), assuming $\mathfrak{b}=\mathfrak{c}$ in the place of MA and we
show that there are at least $\mathfrak{b}$ many Rudin-Kisler incomparable such
upper bounds.


  The optimal use of quantum and classical computational techniques together is
important to address problems that cannot be easily solved by quantum
computations alone. This is the case of the ground state problem for quantum
many-body systems. We show here that probabilistic generative models can work
in conjunction with quantum algorithms to design hybrid quantum-classical
variational ans\"atze that forge entanglement to lower quantum resource
overhead. The variational ans\"atze comprise parametrized quantum circuits on
two separate quantum registers, and a classical generative neural network that
can entangle them by learning a Schmidt decomposition of the whole system. The
method presented is efficient in terms of the number of measurements required
to achieve fixed precision on expected values of observables. To demonstrate
its effectiveness, we perform numerical experiments on the transverse field
Ising model in one and two dimensions, and fermionic systems such as the t-V
Hamiltonian of spinless fermions on a lattice.


  Attention-based learning for fine-grained image recognition remains a
challenging task, where most of the existing methods treat each object part in
isolation, while neglecting the correlations among them. In addition, the
multi-stage or multi-scale mechanisms involved make the existing methods less
efficient and hard to be trained end-to-end. In this paper, we propose a novel
attention-based convolutional neural network (CNN) which regulates multiple
object parts among different input images. Our method first learns multiple
attention region features of each input image through the one-squeeze
multi-excitation (OSME) module, and then apply the multi-attention multi-class
constraint (MAMC) in a metric learning framework. For each anchor feature, the
MAMC functions by pulling same-attention same-class features closer, while
pushing different-attention or different-class features away. Our method can be
easily trained end-to-end, and is highly efficient which requires only one
training stage. Moreover, we introduce Dogs-in-the-Wild, a comprehensive dog
species dataset that surpasses similar existing datasets by category coverage,
data volume and annotation quality. This dataset will be released upon
acceptance to facilitate the research of fine-grained image recognition.
Extensive experiments are conducted to show the substantial improvements of our
method on four benchmark datasets.


  In practical work with American put options, it is important to be able to
know when to exercise the option, and when not to do so. In computer simulation
based on the standard theory of geometric Brownian motion for simulating stock
price movements, this problem is fairly easy to handle for options with a short
lifespan, by analyzing binomial trees. It is considerably more challenging to
make the decision for American put options with long lifespan. In order to
provide a satisfactory analysis, we look at the corresponding free boundary
problem, and show that the free boundary -- which is the curve that separates
the two decisions, to exercise or not to -- has an asymptotic expansion, where
the coefficient of the main term is expressed as an integral in terms of the
free boundary. This raises the perspective that one could use numerical
simulation to approximate the integral and thus get an effective way to make
correct decisions for long life options.


  We study opportunistic scheduling and the sum capacity of cellular networks
with a full-duplex multi-antenna base station and a large number of
single-antenna half-duplex users. Simultaneous uplink and downlink over the
same band results in uplink-to-downlink interference, degrading performance. We
present a simple opportunistic joint uplink-downlink scheduling algorithm that
exploits multiuser diversity and treats interference as noise. We show that in
homogeneous networks, our algorithm achieves the same sum capacity as what
would have been achieved if there was no uplink-to-downlink interference,
asymptotically in the number of users. The algorithm does not require
interference CSI at the base station or uplink users. It is also shown that for
a simple class of heterogeneous networks without sufficient channel diversity,
it is not possible to achieve the corresponding interference-free system
capacity. We discuss the potential for using device-to-device side-channels to
overcome this limitation in heterogeneous networks.


  For a finite field $\mathbb{F}$, it is a basic result of Galois theory that
the fixed field $E$ of $\text{Aut}(\mathbb{F}(x)/\mathbb{F})$ is a proper
extension of $\mathbb{F}$. In this expository paper we construct, for all
finite fields, an element $f\in \mathbb{F}(x)$ such that $E = \mathbb{F}(f)$.
This element is shown to be easily computable in all cases using a simple
formula. The approach is entirely elementary, and aimed at the student level;
only a basic familiarity with Galois theory and field extensions is assumed.


  We describe the expected scientific capabilities of CHARIS, a high-contrast
integral-field spectrograph (IFS) currently under construction for the Subaru
telescope. CHARIS is part of a new generation of instruments, enabled by
extreme adaptive optics (AO) systems (including SCExAO at Subaru), that promise
greatly improved contrasts at small angular separation thanks to their ability
to use spectral information to distinguish planets from quasistatic speckles in
the stellar point-spread function (PSF). CHARIS is similar in concept to GPI
and SPHERE, on Gemini South and the Very Large Telescope, respectively, but
will be unique in its ability to simultaneously cover the entire near-infrared
$J$, $H$, and $K$ bands with a low-resolution mode. This extraordinarily broad
wavelength coverage will enable spectral differential imaging down to angular
separations of a few $\lambda/D$, corresponding to $\sim$$0.\!\!''1$. SCExAO
will also offer contrast approaching $10^{-5}$ at similar separations,
$\sim$$0.\!\!''1$--$0.\!\!''2$. The discovery yield of a CHARIS survey will
depend on the exoplanet distribution function at around 10 AU. If the
distribution of planets discovered by radial velocity surveys extends unchanged
to $\sim$20 AU, observations of $\sim$200 mostly young, nearby stars targeted
by existing high-contrast instruments might find $\sim$1--3 planets. Carefully
optimizing the target sample could improve this yield by a factor of a few,
while an upturn in frequency at a few AU could also increase the number of
detections. CHARIS, with a higher spectral resolution mode of $R \sim 75$, will
also be among the best instruments to characterize planets and brown dwarfs
like HR 8799 cde and $\kappa$ And b.


  We prove that cohomological descent holds for finitely presented crystals on
the overconvergent site with respect to proper or fppf hypercovers.


  Due to weak spin-orbit coupling, the magnetic excitations of an itinerant
ferromagnet become magnetic rotons, excitations with degenerate minima on a
hypersphere at finite wavevector. Using self-consistent Hartree and
renormalization group calculations, we study weak fluctuation-driven
first-order quantum phase transitions, a quantum tricritical point controlled
by anisotropy and the non-Fermi liquid behavior associated with the large phase
volume of magnetic rotons. We propose that magnetic rotons are essential for
the description of the anomalous high-pressure behavior of the itinerant
helical ferromagnet MnSi.


  This research report introduces the generation of textual entailment within
the project CSIEC (Computer Simulation in Educational Communication), an
interactive web-based human-computer dialogue system with natural language for
English instruction. The generation of textual entailment (GTE) is critical to
the further improvement of CSIEC project. Up to now we have found few
literatures related with GTE. Simulating the process that a human being learns
English as a foreign language we explore our naive approach to tackle the GTE
problem and its algorithm within the framework of CSIEC, i.e. rule annotation
in NLML, pattern recognition (matching), and entailment transformation. The
time and space complexity of our algorithm is tested with some entailment
examples. Further works include the rules annotation based on the English
textbooks and a GUI interface for normal users to edit the entailment rules.


  The aviation industry aims to reduce CO2 emission by reducing energy
consumption and benefitting from more electrical systems than those based on
fossil fuels. The more electric aircraft (MEA) can take advantage of the drives
based on wide bandgap (WBG) based power modules that are lighter and can bear
higher voltages and currents. However, the fast-rise and repetitive voltage
pulses generated by WBG-based systems can endanger the insulating property of
dielectric materials due to the partial discharges. PDs cause the local
breakdown of insulation materials in regions with high electric field
magnitude. In the case of power electronic modules, silicone gel, which is a
predominant type of encapsulation material, is susceptible to these PDs. In
this study, it is aimed to investigate the impact of rise time on various PD
characteristics including PD true charge magnitude, inception and extinction
fields, duration, and so forth. Besides, those systems that are anticipated to
operate under harsh environmental conditions such as naval or aviation
industries, may expect additional threat. Therefore, this paper puts forth the
combination of low pressure conditions and fast rise, high frequency square
wave pulses. The results demonstrate that more intense and more intense ones
are going to be imposed at lower pressures. COMSOL Multiphysics interfaced with
MATLAB is used to simulate the PD detection process based on the experimental
data found in the literature.


  Exceptional points, where eigenvalues and eigenvectors coalesce, impact the
behavior of different photonics components that show, e.g., enhanced sensing,
coherent perfect absorption, unidirectional lasing, and chirality. However,
only a few passive geometries have been developed that work on these points.
Here, we introduce a novel non-Hermitian structure based on a microresonator
shaped as the infinity symbol twice coupled to a bus waveguide: the
infinity-loop microresonator. Unlike other structures working on an exceptional
surface, the infinity-loop microresonator can achieve either high- or
low-contrast unidirectional reflection with a negligible or identical
reflection for counterpropagating light. It allows an easy walking through the
Riemann sheet by simply controlling the phase of the light propagating in the
bus waveguide, which makes it a tunable component to build more complex
topological structures. Furthermore, the infinity-loop microresonator allows
sensors that show the features of both an exceptional point device and a
diabolic point device simultaneously.


  It has been shown for English that discrete and soft prompting perform
strongly in few-shot learning with pretrained language models (PLMs). In this
paper, we show that discrete and soft prompting perform better than finetuning
in multilingual cases: Crosslingual transfer and in-language training of
multilingual natural language inference. For example, with 48 English training
examples, finetuning obtains 33.74% accuracy in crosslingual transfer, barely
surpassing the majority baseline (33.33%). In contrast, discrete and soft
prompting outperform finetuning, achieving 36.43% and 38.79%. We also
demonstrate good performance of prompting with training data in multiple
languages other than English.


  With the increasing importance of the Mittag-Leffler function in the physical
applications, these days many researchers are studying various generalizations
and extensions of the Mittag-Leffler function. In this paper efforts are made
to define bicomplex extension of the Mittag-Leffler function and also its
analyticity and region of convergence are discussed. Various properties of the
bicomplex Mittag-Leffler function including integral representation, recurrence
relations, duplication formula and differential relations are established.


  We consider the problem of estimating the direction of arrival of desired
acoustic sources in the presence of multiple acoustic interference sources. All
the sources are located in noisy and reverberant environments and are received
by a microphone array. We propose a new approach for designing beamformers and
DoA estimation methods based on the Riemannian geometry of the manifold of
Hermitian positive definite matrices. Specifically, we show theoretically that
incorporating the Riemannian mean of the spatial correlation matrices into
frequently-used beamformers gives rise to spatial spectra that reject the
directions of interference sources and result in a higher
signal-to-interference ratio. We experimentally demonstrate the advantages of
our approach in designing several beamformers and a recent DoA estimation
method in the presence of simultaneously active multiple interference sources.


  Isaac Newton, in popular imagination the Ur-scientist, was an outstanding
humanist scholar. His researches on, among others, ancient philosophy, are
thorough and appear to be connected to and fit within his larger philosophical
and theological agenda. It is therefore relevant to take a closer look at
Newton's intellectual choices, at how and why precisely he would occupy himself
with specific text-sources, and how this interest fits into the larger picture
of his scientific and intellectual endeavours. In what follows, we shall follow
Newton into his study and look over his shoulder while reading compendia and
original source-texts in his personal library at Cambridge, meticulously
investigating and comparing fragments and commentaries, and carefully keeping
track in private notes of how they support his own developing ideas. Indeed,
Newton was convinced that precursors to his own insights and discoveries were
present already in Antiquity, even before the Greeks, in ancient Egypt, and he
puts a lot of time and effort into making the point, especially, and not
incidentially, in the period between the first and the second edition of the
Principia. A clear understanding of his reading of the classic sources
therefore matters to our understanding of its content and gestation process. In
what follows we will confine ourselves to the classical legacy, and investigate
Newton's intellectual intercourse with it.


  Let E/k(T) be an elliptic curve defined over a rational function field of
characteristic zero. Fix a Weierstrass equation for E. For points R in E(k(T)),
write x_R=A_R/D_R^2 with relatively prime polynomials A_R(T) and D_R(T) in
k[T]. The sequence {D_{nR}) for n \ge 1 is called the ``elliptic divisibility
sequence of R.'' Let P,Q in E(k(T)) be independent points. We conjecture that
deg (gcd(D_{nP},D_{mQ})) is bounded for m,n \ge 1, and that gcd(D_{nP},D_{nQ})
= gcd(D_{P},D_{Q}) for infinitely many n \ge 1. We prove these conjectures in
the case that j(E) is in k. More generally, we prove analogous statements with
k(T) replaced by the function field of any curve and with P and Q allowed to
lie on different elliptic curves. If instead k is a finite field of
characteristic p, and again assuming that j(E) is in k, we show that deg
(gcd(D_{nP},D_{nQ})) > n + O(sqrt{n}) for infinitely many n satisfying gcd(n,p)
= 1.


  The Internet and its current information culture of preserving all kinds of
data cause severe problems with privacy. Most of today's Internet users,
especially teenagers, publish various kinds of sensitive information, yet
without recognizing that revealing this information might be detrimental to
their future life and career. Unflattering images that can be openly accessed
now and in the future, e.g., by potential employers, constitute a particularly
important such privacy concern. We have developed a novel, fast, and scalable
system called X-pire! that allows users to set an expiration date for images in
social networks (e.g., Facebook and Flickr) and on static websites, without
requiring any form of additional interaction with these web pages. Once the
expiration date is reached, the images become unavailable. Moreover, the
publishing user can dynamically prolong or shorten the expiration dates of his
images later, and even enforce instantaneous expiration. Rendering the approach
possible for social networks crucially required us to develop a novel technique
for embedding encrypted information within JPEG files in a way that survives
JPEG compression, even for highly optimized implementations of JPEG
post-processing with their various idiosyncrasies as commonly used in such
networks. We have implemented our system and conducted performance measurements
to demonstrate its robustness and efficiency.


  In recent years, Low Earth Orbit (LEO) satellites have witnessed rapid
development, with inference based on Deep Neural Network (DNN) models emerging
as the prevailing technology for remote sensing satellite image recognition.
However, the substantial computation capability and energy demands of DNN
models, coupled with the instability of the satellite-ground link, pose
significant challenges, burdening satellites with limited power intake and
hindering the timely completion of tasks. Existing approaches, such as
transmitting all images to the ground for processing or executing DNN models on
the satellite, is unable to effectively address this issue. By exploiting the
internal hierarchical structure of DNNs and treating each layer as an
independent subtask, we propose a satellite-ground collaborative computation
partial offloading approach to address this challenge. We formulate the problem
of minimizing the inference task execution time and onboard energy consumption
through offloading as an integer linear programming (ILP) model. The complexity
in solving the problem arises from the combinatorial explosion in the discrete
solution space. To address this, we have designed an improved optimization
algorithm based on branch and bound. Simulation results illustrate that,
compared to the existing approaches, our algorithm improve the performance by
10%-18%


  We propose a generic confidence-based approximation that can be plugged in
and simplify the auto-regressive generation process with a proved convergence.
We first assume that the priors of future samples can be generated in an
independently and identically distributed (i.i.d.) manner using an efficient
predictor. Given the past samples and future priors, the mother AR model can
post-process the priors while the accompanied confidence predictor decides
whether the current sample needs a resampling or not. Thanks to the i.i.d.
assumption, the post-processing can update each sample in a parallel way, which
remarkably accelerates the mother model. Our experiments on different data
domains including sequences and images show that the proposed method can
successfully capture the complex structures of the data and generate the
meaningful future samples with lower computational cost while preserving the
sequential relationship of the data.


  A longstanding mystery about Jupiter has been the straightness and steadiness
of its weather-layer jets, quite unlike terrestrial strong jets with their
characteristic unsteadiness and long-wavelength meandering. The problem is
addressed in two steps. The first is to take seriously the classic
Dowling-Ingersoll (DI) 1-1/2-layer scenario and its supporting observational
evidence, pointing toward deep, massive, zonally-symmetric zonal jets in the
underlying dry-convective layer. The second is to improve the realism of the
model stochastic forcing used to represent the effects of Jupiter's moist
convection as far as possible within the 1-1/2-layer dynamics. The real moist
convection should be strongest in the belts where the interface to the deep
flow is highest and coldest, and should generate cyclones as well as
anticyclones with the anticyclones systematically stronger. The new model
forcing reflects these insights. Also, it acts quasifrictionally on large
scales to produce statistically steady turbulent weather-layer regimes without
any need for explicit large-scale dissipation, and with weather-layer jets that
are approximately straight thanks to the influence of the deep jets, allowing
shear stability despite nonmonotonic potential-vorticity gradients when the
Rossby deformation lengthscale is not too large. Moderately strong forcing
produces chaotic vortex dynamics and realistic belt-zone contrasts in the
model's convective activity, through an eddy-induced sharpening and
strengthening of the weather-layer jets relative to the deep jets, tilting the
interface between them. Weak forcing, for which the only jet-sharpening
mechanism is the passive (Kelvin) shearing of vortices (as in the "CE2" or
"SSST" theories), produces unrealistic belt-zone contrasts.


  In a recent paper published in Ecosphere, their authors suggest that
extending the logistic growth model in its usual r - K parametrization to a
multi-patch environment results in undesirable properties, that were referred
to as the "perfect mixing paradox". This led the authors to recommend using the
Verhulst r - {\alpha} parametrization of the logistic model instead and
abandoning the term "carrying capacity" in the context of population dynamics.
In this study we show that the use of the logistic equation in its traditional
r - K parametrization is appropriate for representing the dynamics of
populations in a simple spatial context with passive migration among patches.
Furthermore, we show that the conclusions of the mentioned paper depend on the
specific functional form for migration rates used for their analyses. In
addition, we suggest that their specific migration model was not the best
choice since biologically realistic options exist. Moreover, these alternatives
require the same number of parameters. The model we present here is free of the
paradoxical behaviors presented previously. This allows us to conclude that the
logistic growth in its usual r - K parametrization is useful in a spatial
context if extended appropriately to a multi-patch scenario and consequently
there are no reasons to abandon the concept of carrying capacity. Ecologists
should pay great attention when using models in scenarios that are more complex
or just different from the ones for which the models were created.


  We introduce a prescription to compute the entanglement entropy of Galilean
conformal field theories by combining gravitational anomalies and an
\.{I}n\"{o}n\"{u}-Wigner contraction. We find that our expression for the
entanglement entropy in the thermal limit reproduces the Cardy formula for
Galilean conformal field theories. Using this proposal, we calculate the
entanglement entropy for a class of Galilean conformal field theories, which
are believed to be dual to three-dimensional flat-space cosmological solutions.
These geometries describe expanding (contracting) universes and can be viewed
as the flat-space limit of rotating Ba\~nados-Teitelboim-Zanelli black holes.
We show that our finding reduces, in the appropriate limits, to the results
discussed in the literature and provide interpretations for the previously
unexplored regimes, such as flat-space chiral gravity.


  The theory of the quantum Coulomb field associates with each Lorentz frame,
i. e., with each unit, future oriented time-like vector $u$, the operator of
the number of transversal infrared photons $N(u)$ and the phase $S(u)$ which is
the coordinate canonically conjugated with the total charge $Q: [Q, S(u)] = ie,
e$ being the elementary charge. It is shown that the operators $N(u), Q/e S(u)$
and $Q^2$ form an infinite Lie algebra. One can conclude from this algebra that
$\DeltaN(u) = (4/\pi) Q^2$, where $\Delta$ is the Laplace operator in the
Lobachevsky space of four-velocities $u$, thus relating the total charge $Q$
with the number of infrared photons.


  In this work, we introduce a generalization of the well-known Vehicle Routing
Problem for a specific application in the monitoring of a Water Distribution
Network (WDN). In this problem, multiple technicians must visit a sequence of
nodes in the WDN and perform a series of tests to check the quality of water.
Some special nodes (i.e., wells) require technicians to first collect a key
from a key center. The key must then be returned to the same key center after
the test has been performed, thus introducing precedence constraints and
multiple visits in the routes. To solve the problem, three mathematical models
and an Iterated Local Search have been implemented. The efficiency of the
proposed methods is demonstrated by means of extensive computational tests on
randomly created instances, as well as on instances derived from a real-world
case study.


  Recently, stereo vision based on lightweight RGBD cameras has been widely
used in various fields. However, limited by the imaging principles, the
commonly used RGB-D cameras based on TOF, structured light, or binocular vision
acquire some invalid data inevitably, such as weak reflection, boundary
shadows, and artifacts, which may bring adverse impacts to the follow-up work.
In this paper, we propose a new model for depth image completion based on the
Attention Guided Gated-convolutional Network (AGG-Net), through which more
accurate and reliable depth images can be obtained from the raw depth maps and
the corresponding RGB images. Our model employs a UNet-like architecture which
consists of two parallel branches of depth and color features. In the encoding
stage, an Attention Guided Gated-Convolution (AG-GConv) module is proposed to
realize the fusion of depth and color features at different scales, which can
effectively reduce the negative impacts of invalid depth data on the
reconstruction. In the decoding stage, an Attention Guided Skip Connection
(AG-SC) module is presented to avoid introducing too many depth-irrelevant
features to the reconstruction. The experimental results demonstrate that our
method outperforms the state-of-the-art methods on the popular benchmarks
NYU-Depth V2, DIML, and SUN RGB-D.


  We investigate the function-space optimality (specifically, the Banach-space
optimality) of a large class of shallow neural architectures with multivariate
nonlinearities/activation functions. To that end, we construct a new family of
Banach spaces defined via a regularization operator, the $k$-plane transform,
and a sparsity-promoting norm. We prove a representer theorem that states that
the solution sets to learning problems posed over these Banach spaces are
completely characterized by neural architectures with multivariate
nonlinearities. These optimal architectures have skip connections and are
tightly connected to orthogonal weight normalization and multi-index models,
both of which have received recent interest in the neural network community.
Our framework is compatible with a number of classical nonlinearities including
the rectified linear unit (ReLU) activation function, the norm activation
function, and the radial basis functions found in the theory of
thin-plate/polyharmonic splines. We also show that the underlying spaces are
special instances of reproducing kernel Banach spaces and variation spaces. Our
results shed light on the regularity of functions learned by neural networks
trained on data, particularly with multivariate nonlinearities, and provide new
theoretical motivation for several architectural choices found in practice.


  Clustering bipartite graphs is a fundamental task in network analysis. In the
high-dimensional regime where the number of rows $n_1$ and the number of
columns $n_2$ of the associated adjacency matrix are of different order,
existing methods derived from the ones used for symmetric graphs can come with
sub-optimal guarantees. Due to increasing number of applications for bipartite
graphs in the high dimensional regime, it is of fundamental importance to
design optimal algorithms for this setting. The recent work of Ndaoud et al.
(2022) improves the existing upper-bound for the misclustering rate in the
special case where the columns (resp. rows) can be partitioned into $L = 2$
(resp. $K = 2$) communities. Unfortunately, their algorithm cannot be extended
to the more general setting where $K \neq L \geq 2$. We overcome this
limitation by introducing a new algorithm based on the power method. We derive
conditions for exact recovery in the general setting where $K \neq L \geq 2$,
and show that it recovers the result in Ndaoud et al. (2022). We also derive a
minimax lower bound on the misclustering error when $K = L$ under a symmetric
version of our model, which matches the corresponding upper bound up to a
factor depending on $K$.


  Ma-Minda class (of starlike functions) consists of all normalized analytic
functions $f$ on the unit disk for which the image of $zf'(z)/f(z)$ is
contained in the some starlike region in the right-half plane. We obtain the
best possible bounds on the second and third coefficient for the inverse
functions of functions in the Ma-Minda class. The bounds on the Fekete-Szeg\"o
functional and the second Hankel determinant of the inverse functions of the
functions belonging to the Ma-Minda class are also determined. Further, the
bounds on the first five coefficients of the inverse functions are investigated
for two particular subclasses of the Ma-Minda class. In addition, some radius
estimates associated with the two subclasses are also computed.


  The Projected Configuration Interaction (PCI) method starts from a collection
of mean-field wave functions, and builds up correlated wave functions of good
symmetry. It relies on the Generator Coordinator Method (GCM) techniques, but
it improves the past approaches by a very efficient method of selecting the
basis states. We use the same realistic Hamiltonians and model spaces as the
Configuration Interaction (CI) method, and compare the results with the full CI
calculations in the sd and pf shell. Examples of 24Mg, 28Si, 48Cr, 52Fe and
56Ni are discussed.


  We present a framework to segregate the roles of elastic and non-elastic
deformations in the examination of real-space experiments of solid-solid
Martensitic transitions. The Martensitic transformation of a
body-centred-tetragonal(BCT) to a body-centred-orthorhombic(BCO) crystal
structure has been studied in a model system of micron-scale ionic microgel
colloids. Non-affine fluctuations, i.e., displacement fluctuations that do not
arise from purely elastic(affine) deformations, are detected in particle
configurations acquired from the experiment. Tracking these fluctuations serves
as a highly sensitive tool in signaling the onset of the Martensitic transition
and precisely locating particle rearrangements occurring at length scales of a
few particle diameters. Particle rearrangements associated with non-affine
displacement modes become increasingly favorable during the transformation
process. The nature of the displacement fluctuation modes that govern the
transformation are shown to be different from those predominant in an
equilibrium crystal. We show that BCO crystallites formed through shear may,
remarkably, co-exist with those resulting from local rearrangements within the
same sample.


  The objective of trajectory optimization algorithms is to achieve an optimal
collision-free path between a start and goal state. In real-world scenarios
where environments can be complex and non-homogeneous, a robot needs to be able
to gauge whether a state will be in collision with various objects in order to
meet some safety metrics. The collision detector should be computationally
efficient and, ideally, analytically differentiable to facilitate stable and
rapid gradient descent during optimization. However, methods today lack an
elegant approach to detect collision differentiably, relying rather on
numerical gradients that can be unstable. We present DiffCo, the first, fully
auto-differentiable, non-parametric model for collision detection. Its
non-parametric behavior allows one to compute collision boundaries on-the-fly
and update them, requiring no pre-training and allowing it to update
continuously in dynamic environments. It provides robust gradients for
trajectory optimization via backpropagation and is often 10-100x faster to
compute than its geometric counterparts. DiffCo also extends trivially to
modeling different object collision classes for semantically informed
trajectory optimization.


  In recent work, it was shown that velocity-dependent forces between parallel
fundamental strings moving apart in a D-dimensional spacetime implied an
expanding universe in D-1-dimensional spacetime. Here we expand on this work to
obtain exact solutions for various string/brane cosmological toy models.


  Feed-forward, fully-connected Artificial Neural Networks (ANNs) or the
so-called Multi-Layer Perceptrons (MLPs) are well-known universal
approximators. However, their learning performance varies significantly
depending on the function or the solution space that they attempt to
approximate. This is mainly because of their homogenous configuration based
solely on the linear neuron model. Therefore, while they learn very well those
problems with a monotonous, relatively simple and linearly separable solution
space, they may entirely fail to do so when the solution space is highly
nonlinear and complex. Sharing the same linear neuron model with two additional
constraints (local connections and weight sharing), this is also true for the
conventional Convolutional Neural Networks (CNNs) and, it is, therefore, not
surprising that in many challenging problems only the deep CNNs with a massive
complexity and depth can achieve the required diversity and the learning
performance. In order to address this drawback and also to accomplish a more
generalized model over the convolutional neurons, this study proposes a novel
network model, called Operational Neural Networks (ONNs), which can be
heterogeneous and encapsulate neurons with any set of operators to boost
diversity and to learn highly complex and multi-modal functions or spaces with
minimal network complexity and training data. Finally, a novel training method
is formulated to back-propagate the error through the operational layers of
ONNs. Experimental results over highly challenging problems demonstrate the
superior learning capabilities of ONNs even with few neurons and hidden layers.


  The aim of this paper is to define and study Drinfeld twists for monoidal
Hom-bialgebras. We show that a new Hom-bialgebra could be constructed by
changing the coproduct of a monoidal Hom-bialgebra via a Drinfeld twist, and
this construction preserves $R$-matrixes if there exist one. Moreover, their
representation categories are monoidal isomorphic.


  Monocular 3D object detection (Mono3D) has achieved unprecedented success
with the advent of deep learning techniques and emerging large-scale autonomous
driving datasets. However, drastic performance degradation remains an
unwell-studied challenge for practical cross-domain deployment as the lack of
labels on the target domain. In this paper, we first comprehensively
investigate the significant underlying factor of the domain gap in Mono3D,
where the critical observation is a depth-shift issue caused by the geometric
misalignment of domains. Then, we propose STMono3D, a new self-teaching
framework for unsupervised domain adaptation on Mono3D. To mitigate the
depth-shift, we introduce the geometry-aligned multi-scale training strategy to
disentangle the camera parameters and guarantee the geometry consistency of
domains. Based on this, we develop a teacher-student paradigm to generate
adaptive pseudo labels on the target domain. Benefiting from the end-to-end
framework that provides richer information of the pseudo labels, we propose the
quality-aware supervision strategy to take instance-level pseudo confidences
into account and improve the effectiveness of the target-domain training
process. Moreover, the positive focusing training strategy and dynamic
threshold are proposed to handle tremendous FN and FP pseudo samples. STMono3D
achieves remarkable performance on all evaluated datasets and even surpasses
fully supervised results on the KITTI 3D object detection dataset. To the best
of our knowledge, this is the first study to explore effective UDA methods for
Mono3D.


  We present new algorithms to perform fast probabilistic collision queries
between convex as well as non-convex objects. Our approach is applicable to
general shapes, where one or more objects are represented using Gaussian
probability distributions. We present a fast new algorithm for a pair of convex
objects, and extend the approach to non-convex models using hierarchical
representations. We highlight the performance of our algorithms with various
convex and non-convex shapes on complex synthetic benchmarks and trajectory
planning benchmarks for a 7-DOF Fetch robot arm.


  In this note, I review a recent approach to quantum gravity that "gravitizes"
quantum mechanics by emerging geometry and gravity from complex quantum states.
Drawing further insights from tensor network toy models in AdS/CFT, I propose
that approximate quantum error correction codes, when re-adapted into the
aforementioned framework, also has promise in emerging gravity in near-flat
geometries.


  Monte Carlo simulation study of a classical spin model with
Dzylosinskii-Moriya interaction and the spin anisotropy under the magnetic
field is presented. We found a rich phase diagram containing the multiple spin
spiral (or skyrme crystal) phases of square, rectangular, and hexagonal
symmetries in addition to the spiral spin state. The Hall conductivity
$\sigma_{xy}$ is calculated within the $sd$ model for each of the phases. While
$\sigma_{xy}$ is zero in the absence of external magnetic field, applying a
field strength $H$ larger than a threshold value $H_c$ leads to the
simultaneous onset of nonzero chirality and Hall conductivity. We find $H_c =
0$ for the multiple spin spiral states, but $H_c > 0$ for a single spin spiral
state regardless of the field orientation. Relevance of the present results to
MnSi is discussed.


  The KLOE-2 experiment at the INFN Laboratori Nazionali di Frascati (LNF)
completed its data-taking at the $e^+ e^-$ DA$\Phi$NE collider, which
implements an innovative collision scheme based on a crab-waist configuration,
and achieved the integrated luminosity of more than 5 fb$^-1$. KLOE-2
represents the continuation of KLOE with an upgraded detector and an extended
physics program which includes, among the main topics, neutral kaon
interferometry and test of discrete symmetries . Entangled neutral kaon pairs
produced at DA$\Phi$NE are a unique tool to test discrete symmetries and
quantum coherence at the utmost sensitivity, strongly motivating the
experimental searches of possible CPT violating effects, which would constitute
an unambiguous signal of New Physics. The status of the test of Time reversal
and CPT simmetry in $\phi \to \mbox{K}_S \mbox{K}_L \to \pi\nu,3\pi^0,(2\pi)$
decays with KLOE and KLOE-2 data will be discussed.


  In the future International Linear Collider (ILC) experiment, high
performance tracking is essential to its physics program including precision
Higgs studies. One of major challenges for a detector such as the proposed
International Large Detector (ILD) is to provide excellent momentum resolution
in a magnetic filed with small (but non-negligible) non-uniformity. The
non-uniform magnetic field implies deviation from a helical track and hence
requires the extension of a helical track model used for track fitting in a
uniform magnetic field. In this paper, a segment-wise helical track model is
introduced as such an extension. The segment-wise helical track model
approximates the magnetic field between two nearby measurement sites to be
uniform and steps between the two sites along a helix. The helix frame is then
transformed according to the new magnetic field direction for the next step, so
as to take into account the non-uniformity of the magnetic field. Details of
the algorithm and mathematical aspects of the segment-wise helical track model
in a Kalman-filter-based track fitting in the non-uniform magnetic field are
elaborated. The new track model is implemented and successfully tested in the
framework of the Kalman filter tracking software package, KalTest, which was
originally developed for tracking in a uniform magnetic field.


  A cosmological model dominated at the beginning by a dark radiation followed
by a period of inflation is presented. This model is based on a Randall-Sundrum
II type brane-world. Current observational data are used to fix the parameters
associated to the dark radiation.


  We propose a novel pipeline for unknown object grasping in shared robotic
autonomy scenarios. State-of-the-art methods for fully autonomous scenarios are
typically learning-based approaches optimised for a specific end-effector, that
generate grasp poses directly from sensor input. In the domain of assistive
robotics, we seek instead to utilise the user's cognitive abilities for
enhanced satisfaction, grasping performance, and alignment with their high
level task-specific goals. Given a pair of stereo images, we perform unknown
object instance segmentation and generate a 3D reconstruction of the object of
interest. In shared control, the user then guides the robot end-effector across
a virtual hemisphere centered around the object to their desired approach
direction. A physics-based grasp planner finds the most stable local grasp on
the reconstruction, and finally the user is guided by shared control to this
grasp. In experiments on the DLR EDAN platform, we report a grasp success rate
of 87% for 10 unknown objects, and demonstrate the method's capability to grasp
objects in structured clutter and from shelves.


  Using data recorded by the CLEO-II detector at CESR, we report new
measurements of the branching fractions for the decays of the charmed baryon
$\Lambda_c^+$ into $pK^-\pi^+\pi^0$, $p\bar{K}^0$, $p\bar{K}^0\pi^+\pi^-$, and
$p\bar{K}^0\pi^0$, all measured relative to $pK^-\pi^+$. The relative branching
fractions are $0.67\pm0.04\pm0.11, 0.46\pm0.02\pm0.04,0.52\pm0.04\pm0.05$, and
$0.66\pm0.05\pm0.07$ respectively.


  We compute the second order transport coefficients of a hydrodynamic theory
with Einstein-Gauss-Bonnet gravity dual. We show the breakdown of the universal
hydrodynamic relation $ -2 \lambda_0 + 4 \lambda_1 - \lambda_2 = 0 $ for the
general values of the Gauss-Bonnet coupling.


  An optimal protocol for the current-induced switching of a perpendicularly
magnetized nanoelement placed on the surface of a topological insulator is
presented. The time dependence of both in-plane components of the surface
current that induces the magnetization reversal via Dirac spin-orbit torque
with minimal Joule heating is derived analytically as a function of the
required switching time and material properties. It is demonstrated that a
particularly energy-efficient switching is realized for vanishing dampinglike
torque. The optimal reversal time providing a tradeoff between the switching
speed and energy efficiency is derived. The obtained switching protocol is
contrasted with the one realized in heavy-metal systems. Topological insulators
provide a highly tunable platform for the realization of energy-efficient
magnetization switching.


  We resume the study initiated in \cite{CL}. For a generic curve $C$ in an
ample linear system $\vert \mathcal{L} \vert$ on a toric surface $X$, a
vanishing cycle of $C$ is an isotopy class of simple closed curve that can be
contracted to a point along a degeneration of $C$ to a nodal curve in $\vert
\mathcal{L} \vert$. The obstructions that prevent a simple closed curve in $C$
from being a vanishing cycle are encoded by the adjoint line bundle $K_X
\otimes \mathcal{L}$. In this paper, we consider the linear systems carrying
the two simplest types of obstruction. Geometrically, these obstructions
manifest on $C$ respectively as an hyperelliptic involution and as a Spin
structure. In both cases, we determine all the vanishing cycles by
investigating the associated monodromy maps, whose target space is the mapping
class group $MCG(C)$. We show that the image of the monodromy is the subgroup
of $MCG(C)$ preserving respectively the hyperelliptic involution and the Spin
structure. In particular, we provide an explicit finite set of generators for
the Spin mapping class group. The results obtained here support the Conjecture
$1$ in \cite{CL} aiming to describe all the vanishing cycles for any pair $(X,
\mathcal{L})$.


  Assessing the influence of a scholar's work is an important task for funding
organizations, academic departments, and researchers. Common methods, such as
measures of citation counts, can ignore much of the nuance and
multidimensionality of scholarly influence. We present an approach for
generating dynamic visualizations of scholars' careers. This approach uses an
animated node-link diagram showing the citation network accumulated around the
researcher over the course of the career in concert with key indicators,
highlighting influence both within and across fields. We developed our design
in collaboration with one funding organization---the Pew Biomedical Scholars
program---but the methods are generalizable to visualizations of scholarly
influence. We applied the design method to the Microsoft Academic Graph, which
includes more than 120 million publications. We validate our abstractions
throughout the process through collaboration with the Pew Biomedical Scholars
program officers and summative evaluations with their scholars.


  The ~200 m/s impact of a single 400-kg Bjurb\"ole L/LL ordinary chondrite
meteorite onto sea ice resulted in the catastrophic disruption of the
projectile. This resulted in a significant fraction of decimeter-sized
fragments that exhibit power law cumulative size and mass distributions. This
size range is underrepresented in impact experiments and asteroid boulder
studies. The Bjurb\"ole projectile fragments share similarities in shape
(sphericity, and roughness at small and large scale) with asteroid boulders.
However, the mean aspect ratio (3D measurement) and apparent aspect ratio (2D
measurement) of Bjurb\"ole fragment is 0.83 and 0.77, respectively, indicating
that Bjurb\"ole fragments are more equidimensional compared to both fragments
produced in smaller scale impact experiments and asteroid boulders. These
differences may be attributed either to the fragment source (projectile vs.
target), to the high porosity and low strength of Bjurb\"ole, to the lower
impact velocity compared with typical asteroid collision velocities, or
potentially to fragment erosion during sea sediment penetration or cleaning.


  The goal of compressed sensing is to estimate a high dimensional vector from
an underdetermined system of noisy linear equations. In analogy to classical
compressed sensing, here we assume a generative model as a prior, that is, we
assume the vector is represented by a deep generative model $G: \mathbb{R}^k
\rightarrow \mathbb{R}^n$. Classical recovery approaches such as empirical risk
minimization (ERM) are guaranteed to succeed when the measurement matrix is
sub-Gaussian. However, when the measurement matrix and measurements are
heavy-tailed or have outliers, recovery may fail dramatically. In this paper we
propose an algorithm inspired by the Median-of-Means (MOM). Our algorithm
guarantees recovery for heavy-tailed data, even in the presence of outliers.
Theoretically, our results show our novel MOM-based algorithm enjoys the same
sample complexity guarantees as ERM under sub-Gaussian assumptions. Our
experiments validate both aspects of our claims: other algorithms are indeed
fragile and fail under heavy-tailed and/or corrupted data, while our approach
exhibits the predicted robustness.


  We study paycheck optimization, which examines how to allocate income in
order to achieve several competing financial goals. For paycheck optimization,
a quantitative methodology is missing, due to a lack of a suitable problem
formulation. To deal with this issue, we formulate the problem as a utility
maximization problem. The proposed formulation is able to (i) unify different
financial goals; (ii) incorporate user preferences regarding the goals; (iii)
handle stochastic interest rates. The proposed formulation also facilitates an
end-to-end reinforcement learning solution, which is implemented on a variety
of problem settings.


  In this paper, we address the Online Unsupervised Domain Adaptation (OUDA)
problem, where the target data are unlabelled and arriving sequentially. The
traditional methods on the OUDA problem mainly focus on transforming each
arriving target data to the source domain, and they do not sufficiently
consider the temporal coherency and accumulative statistics among the arriving
target data. We propose a multi-step framework for the OUDA problem, which
institutes a novel method to compute the mean-target subspace inspired by the
geometrical interpretation on the Euclidean space. This mean-target subspace
contains accumulative temporal information among the arrived target data.
Moreover, the transformation matrix computed from the mean-target subspace is
applied to the next target data as a preprocessing step, aligning the target
data closer to the source domain. Experiments on four datasets demonstrated the
contribution of each step in our proposed multi-step OUDA framework and its
performance over previous approaches.


  In numerous papers, the behaviour of stochastic population models is
investigated through the sign of a real quantity which is the growth rate of
the population near the extinction set. In many cases, it is proven that when
this growth rate is positive, the process is persistent in the long run, while
if it is negative, the process converges to extinction. However, the critical
case when the growth rate is null is rarely treated. The aim of this paper is
to provide a method that can be applied in many situations to prove that in the
critical case, the process congerves in temporal average to extinction. A
number of applications are given, for Stochastic Differential Equations and
Piecewise Deterministic Markov Processes modelling prey-predator,
epidemilogical or structured population dynamics.


  Interference of double moire patterns of graphene (G) encapsulated by
hexagonal boron nitride (BN) can alter the electronic structure features near
the primary/secondary Dirac points and the electron-hole symmetry introduced by
a single G/BN moire pattern depending on the relative stacking arrangements of
the top/bottom BN layers. We show that strong interference effects are found in
nearly aligned BN/G/BN and BN/G/NB and obtain the evolution of the associated
density of states as a function of moire superlattice twist angles. For equal
moire periods and commensurate patterns with $\Delta \phi = 0^{\circ}$ modulo
$60^{\circ}$ angle differences the patterns can add up constructively leading
to large pseudogaps of about $\sim 0.5$ eV on the hole side or cancel out
destructively depending on their relative sliding, e.g. partially recovering
electron-hole symmetry. The electronic structure of moire quasicrystals for
$\Delta \phi =30^{\circ}$ differences reveal double moire features in the
density of states with almost isolated van Hove singularities where we can
expect strong correlations.


  We demonstrated that the spin injection/extraction efficiency is enhanced by
an ultrathin Mg insertion layer (<= 2 nm) in Fe/Mg/MgO/n+-Si tunnel junctions.
In diode-type vertical three-terminal devices fabricated on a Si substrate, we
observed the narrower three-terminal Hanle (N-3TH) signals indicating true spin
injection into Si, and estimated the spin polarization in Si to be 16% when the
thickness of the Mg insertion layer is 1 nm, whereas no N-3TH signal was
observed without Mg insertion. This means that the spin injection/extraction
efficiency is enhanced by suppressing the formation of a magnetically-dead
layer at the Fe/MgO interface. We have also observed clear spin transport
signals, such as non-local Hanle signals and spin-valve signals, in a lateral
four-terminal device with the same Fe/Mg/MgO/n+-Si tunnel junctions fabricated
on a Si-on-insulator substrate. It was found that both the intensity and
linewidth of the spin signals are affected by the geometrical effects (device
geometry and size). We have derived analytical functions taking into account
the device structures, including channel thickness and electrode size, and
estimated important parameters; spin lifetime and spin polarizations. Our
analytical functions well explain the experimental results. Our study shows the
importance of suppressing a magnetically-dead layer, and provides a unified
understanding of spin injection/detection signals in different device
geometries.


  We are able to clearly distinguish the processes responsible for enhanced
low-intensity atomic Kerr nonlinearity, namely coherent population trapping and
coherent population oscillations in experiments performed on the Rb D1 line,
where one or the other process dominates under appropriate conditions. The
potential of this new approach based on wave mixing for probing coherent atomic
media is discussed. It allows the new spectral components to be detected with
sub-kHz resolution, which is well below the laser linewidth limit. Spatial
selectivity and enhanced sensitivity make this method useful for testing dilute
cold atomic samples.


  We construct four dimensional three generation non-supersymmetric $SU(3)_c
\times SU(2)_L \times U(1)_Y$ intersecting D6-brane models with $\nu_R$\rq{s}.
At three stacks we find exactly the MSSM chiral fermion matter spectrum. At 4-,
5-stacks we find models with the massless fermion spectrum of the N=1 Standard
Model and massive exotic non-chiral matter; these models flow also to only the
SM. At 8-stacks we find MSSM-like models, with minimal massless exotics, made
from two different N=1 sectors. Exotic triplet masses put a lower bound on the
string scale of $2.79/2.89 \times 10^6$ GeV for a Higgs 124/126 GeV. It\rq{}s
the first appearance of N=0 stringy quivers with the MSSM and matter in
antisymmetric representations and perturbatively missing Yukawa couplings. The
present models are based on orientifolds of ${\bf T^6/(Z_3 \times Z_3)}$
compactifications of IIA theory based on the torus lattice AAA; all complex
moduli are fixed by the orbifold symmetry. We also present the spectrum rules +
GS anomaly cancellation for the ABB lattice. Moreover, we point out the
relevance of intersecting/and present D6-brane constructions on ideas related
to existence of split supersymmetry in nature. In this context we present
non-susy models with only the SM-matter and also MSSM-matter dominated models,
with massive gauginos and light higgsinos, that achieve the correct
supersymmetric GUT value for the Weinberg angle $sin^2 \theta = \frac{3}{8}$ at
a string scale $5 \cdot 10^{13} \ GeV < M_{S} < 1.4 \cdot 10^{17}$ GeV. It
appears that if only the SM survives at low energy the unification scale is
preserved at $5.03 \times 10^{13}$ GeV when n$_H$ =1, 3, 6. These models
support the existence of split supersymmetry scenario in string theory.


  There is no consensus on the state-of-the-art approach to historical text
normalization. Many techniques have been proposed, including rule-based
methods, distance metrics, character-based statistical machine translation, and
neural encoder--decoder models, but studies have used different datasets,
different evaluation methods, and have come to different conclusions. This
paper presents the largest study of historical text normalization done so far.
We critically survey the existing literature and report experiments on eight
languages, comparing systems spanning all categories of proposed normalization
techniques, analysing the effect of training data quantity, and using different
evaluation methods. The datasets and scripts are made publicly available.


  A proper orthogonal decomposition-based B-splines B\'ezier elements method
(POD-BSBEM) is proposed as a non-intrusive reduced-order model for uncertainty
propagation analysis for stochastic time-dependent problems. The method uses a
two-step proper orthogonal decomposition (POD) technique to extract the reduced
basis from a collection of high-fidelity solutions called snapshots. A third
POD level is then applied on the data of the projection coefficients associated
with the reduced basis to separate the time-dependent modes from the stochastic
parametrized coefficients. These are approximated in the stochastic parameter
space using B-splines basis functions defined in the corresponding B\'ezier
element. The accuracy and the efficiency of the proposed method are assessed
using benchmark steady-state and time-dependent problems and compared to the
reduced order model-based artificial neural network (POD-ANN) and to the
full-order model-based polynomial chaos expansion (Full-PCE). The POD-BSBEM is
then applied to analyze the uncertainty propagation through a flood wave flow
stemming from a hypothetical dam-break in a river with a complex bathymetry.
The results confirm the ability of the POD-BSBEM to accurately predict the
statistical moments of the output quantities of interest with a substantial
speed-up for both offline and online stages compared to other techniques.


  We examine the effect on cosmological evolution of adding a string motivated
Gauss-Bonnet term to the traditional Einstein-Hilbert action for a (1 + 3) + d
dimensional Friedman-Robertson- Walker (FRW) metric. By assuming that the
additional dimensions compactify as the usual 3 spatial dimensions expand, we
find that the Gauss Bonnet terms give perturbative corrections to the FRW
equations. We find corrections that appear in the calculation of both the
Hubble constant, H0, and the acceleration parameter, q0, for a variety of cases
that are consistent with a dark energy equation of state.


  We review the history of the discovery of field subgiant stars and their
importance in the age dating of the Galactic disk. We use the cataloged data
from the Hipparcos satellite in this latter capacity. Based on Hipparcos
parallaxes accurate to 10% or better, the absolute magnitude of the lower
envelope of the nearly horizontal subgiant sequence for field stars in the H-R
diagram for B-V colors between 0.85 and 1.05 is measured to be M_V = 4.03 +/-
0.06. The age of the field stars in the solar neighborhood is found to be 7.9
+/- 0.7 Gyr by fitting the theoretical isochrones for [Fe/H] = +0.37 to the
lower envelope of the Hipparcos subgiants. The same grid of isochrones yields
ages, in turn, of 4.0 +/- 0.2 Gyr, 6.2 +/- 0.5 Gyr, and 7.5 to 10 Gyr for the
old Galactic clusters M67, NGC188, and NGC6791. The ages of both the Galactic
disk in the solar neighborhood and of NGC6791 are, nevertheless, likely between
3 and 5 Gyr younger than the oldest halo globular clusters, which have ages of
13.5 Gyr. The most significant results are (1) the supermetallicity of the
oldest local disk stars, and (2) the large age difference between the most
metal-poor component of the halo and the thick and thin disk in the solar
neighborhood. These facts are undoubtedly related and pose again the problem of
the proper scenario for the timing of events in the formation of the halo and
the Galactic disk in the solar neighborhood. [Abstract Abridged]


  For any fixed $p>2$, a necessary and sufficient condition is obtained for the
boundedness of the Riesz transforms associated with second order elliptic
operators with real, symmetric, bounded measurable coefficients.


  Let $f:R\to C$ be the characteristic function of a probability measure. We
study the following question: Is it true that for any closed interval $I$ on
$R$, which does not contain the origin, there exists a characteristic function
$g$ such that $g$ coincides with $f$ on $I$ but $g \not\equiv f$ on $R$?


  Tunneling processes through black hole horizons have recently been
investigated in the framework of WKB theory discovering interesting interplay
with the Hawking radiation. In this paper we instead adopt the point of view
proper of QFT in curved spacetime, namely, we use a suitable scaling limit
technique to obtain the leading order of the correlation function related with
some tunneling process through a Killing horizon. The computation is done for
certain large class of reference quantum states for scalar fields. In the limit
of sharp localization either on the external side or on opposite sides of the
horizon, the quantum correlation functions appear to have thermal nature, where
in both cases the characteristic temperature is the Hawking one. Our approach
is valid for every stationary charged rotating non extremal black hole,
however, since the computation is completely local, it covers the case of a
Killing horizon which just temporarily exists in some finite region too. These
results give a strong support to the idea that the Hawking radiation, which is
detected at future infinity and needs some global structures to be defined, is
actually related to a local phenomenon taking place even for local geometric
structures (local Killing horizons) existing just for a while.


  In the paper the so-called modified Yamaguchi function for the Bethe-Salpeter
equation with a separable kernel is discussed. The type of the functions is
defined by the analytic stucture of the hadron current with breakup - the
reactions with interacting nucleon-nucleon pair in the final state (electro-,
photo-, and nucleon-disintegration of the deuteron).


  EBEX is a balloon-borne polarimeter designed to measure the intensity and
polarization of the cosmic microwave background radiation. The measurements
would probe the inflationary epoch that took place shortly after the big bang
and would significantly improve constraints on the values of several
cosmological parameters. EBEX is unique in its broad frequency coverage and in
its ability to provide critical information about the level of polarized
Galactic foregrounds which will be necessary for all future CMB polarization
experiments. EBEX consists of a 1.5 m Dragone-type telescope that provides a
resolution of less than 8 arcminutes over four focal planes each of 4 degree
diffraction limited field of view at frequencies up to 450 GHz. The experiment
is designed to accommodate 330 transition edge bolometric detectors per focal
plane, for a total of up to 1320 detectors. EBEX will operate with frequency
bands centered at 150, 250, 350, and 450 GHz. Polarimetry is achieved with a
rotating achromatic half-wave plate. EBEX is currently in the design and
construction phase, and first light is scheduled for 2008.


  We obtain iso-spectral Euler-Bernoulli beams by using factorization and Lie
symmetry techniques. The canonical Euler-Bernoulli beam operator is factorized
as the product of a second-order linear differential operator and its adjoint.
The factors are then reversed to obtain iso-spectral beams. The factorization
is possible provided the coefficients of the factors satisfy a system of
non-linear ordinary differential equations . The uncoupling of this system
yields a single non-linear third-order ordinary differential equation. This
ordinary differential equation, refer to as the {\it principal equation}, is
analyzed and solved using Lie group methods. We show that the principal
equation may admit a one-dimensional or three-dimensional symmetry Lie algebra.
When the principal system admits a unique symmetry, the best we can do is to
depress its order by one. We obtain a one-parameter family of solutions in this
case. The maximally symmetric case is shown to be isomorphic to a Chazy
equation which is solved in closed form to derive the general solution of the
principal equation.


  We present a measurement of neutral pion production in charged-current
interactions using data recorded with the MicroBooNE detector exposed to
Fermilab's booster neutrino beam. The signal comprises one muon, one neutral
pion, any number of nucleons, and no charged pions. Studying neutral pion
production in the MicroBooNE detector provides an opportunity to better
understand neutrino-argon interactions, and is crucial for future
accelerator-based neutrino oscillation experiments. Using a dataset
corresponding to $6.86 \times 10^{20}$ protons on target, we present
single-differential cross sections in muon and neutral pion momenta, scattering
angles with respect to the beam for the outgoing muon and neutral pion, as well
as the opening angle between the muon and neutral pion. Data extracted cross
sections are compared to generator predictions. We report good agreement
between the data and the models for scattering angles, except for an
over-prediction by generators at muon forward angles. Similarly, the agreement
between data and the models as a function of momentum is good, except for an
underprediction by generators in the medium momentum ranges, $200-400$ MeV for
muons and $100-200$ MeV for pions.


  A novel route to a one-dimensional Fulde-Ferrell-Larkin-Ovchinnikov (1D-FFLO)
state in the absence of broken time-reversal symmetry is proposed in this
paper. At present such a state may be encouraged in a clean AlAs quantum wire.
Using the AlAs quantum wire as an example it is shown using bosonization and
the renormalization group approach that the 1D-FFLO state can arise due to a
combination of Coulomb interactions and the unique bandstructure arrangement of
the AlAs quantum wire. The present theoretical proposal is very general and is
applicable to other systems with similar fermionic interaction terms.


  In this paper, we introduce a class of $(P, \omega)$-partitions that we call
periodic $(P, \omega)$-partitions, then prove that such $(P,
\omega)$-partitions satisfy a homogeneous first-order matrix difference
equation. After defining an appropriate counting problem for the above $(P,
\omega)$-partitions, we show that as a consequence of this equation, periodic
$(P, \omega)$-partitions can be enumerated with constant coefficient linear
recurrence relations. By analysing the above matrix difference equation, we
also prove a result for the asymptotic growth rate for the number of periodic
$(P, \omega)$-partitions. The results of this paper generalizes and strengthens
the constant coefficient linear recurrence results proved by Sun and by
L\'opez, Mart\'inez, P\'erez, P\'erez, and Basova for enumerating standard
Young tableaux on shifted strips with constant width.


  The strong geomagnetic influences on mechanical properties of crystals due to
their exposure to ultralow crossed magnetic fields, the Earth's field (approx.
50 microTesla) and the AC field (approx. 3 microTesla) in the electron
paramagnetic resonance scheme, are discussed. Resonance relaxation
displacements of dislocations in NaCl crystals are found both for a harmonic
pump field and for a pulse AC field of resonance duration approx. 0.5 microsec.
Resonant changes have been also detected in the microhardness of ZnO,
triglycine sulfate, and potassium acid phthalate crystals after their exposure
in the same EPR scheme. The both effects manifest new strongly anisotropic
properties. In particular, the frequency of the resonance is very sensitive to
the mutual orientation of the sample and the Earth's field. Physical mechanisms
and practical significance of the phenomenon are discussed.


  Let G be a unitary group over the rationals, associated to a CM-field F with
totally real part F^+, with signature (1,1) at all the archimedean places of
F^+. Under certain hypotheses on F^+, we show that Jacquet-Langlands
correspondences between certain automorphic representations of G and
representations of a group G' isomorphic to G except at infinity can be
realized in the cohomology of Shimura varieties attached to G and G'.
  We obtain these Jacquet-Langlands correspondences by studying the bad
reduction of a Shimura variety X attached to G at a prime p for which X has
maximal parabolic level structure. We construct a "Deligne-Rapoport" model for
X and show that the irreducible components of its special fiber have a global
structure that can be explicitly described in terms of Shimura varieties X' for
unitary groups G' isomorphic to G except at infinity.
  The weight spectral sequence of Rapoport-Zink then yields an expression for
certain pieces of the weight filtration on the etale cohomology of X in terms
of the cohomology of a suitable X'. This identifies a piece of this weight
filtration with a space of algebraic modular forms for G'. A consequence is
certain cases of the Jacquet-Langlands correspondence between G and G' in terms
of a canonical isomorphism between spaces of arithmetic interest, rather than
simply as an abstract bijection between isomorphism classes of representations.


  The success of adiabatic quantum computation (AQC) depends crucially on the
ability to maintain the quantum computer in the ground state of the evolution
Hamiltonian. The computation process has to be sufficiently slow as restricted
by the minimal energy gap. However, at finite temperatures, it might need to be
fast enough to avoid thermal excitations. The question is, how fast does it
need to be? The structure of evolution Hamiltonians for AQC is generally too
complicated for answering this question. Here we model an adiabatic quantum
computer as a (parametrically driven) harmonic oscillator. The advantages of
this model are (1) it offers high flexibility for quantitative analysis on the
thermal effect, (2) the results qualitatively agree with previous numerical
calculation, and (3) it could be experimentally verified with quantum
electronic circuits.


  We use the Galaxy And Mass Assembly (GAMA) survey to measure the local
Universe mass dependent merger fraction and merger rate using galaxy pairs and
the CAS structural method, which identifies highly asymmetric merger candidate
galaxies. Our goals are to determine which types of mergers produce highly
asymmetrical galaxies, and to provide a new measurement of the local galaxy
major merger rate. We examine galaxy pairs at stellar mass limits down to
$M_{*} = 10^{8}M_{\odot}$ with mass ratios of $<$100:1 and line of sight
velocity differences of $\Delta V<500$ km s$^{-1}$. We find a significant
increase in mean asymmetries for projected separations less than the sum of the
individual galaxy's Petrosian 90 radii. For systems in major merger pairs with
mass ratios of $<$4:1 both galaxies in the pair show a strong increase in
asymmetry, while in minor merger systems (with mass ratios of $>$4:1) the lower
mass companion becomes highly asymmetric, while the larger galaxy is much less
affected. The fraction of highly asymmetric paired galaxies which have a major
merger companion is highest for the most massive galaxies and drops
progressively with decreasing mass. We calculate that the mass dependent major
merger fraction is fairly constant at $\sim1.3-2\%$ between
$10^{9.5}<M_{*}<10^{11.5} M_{\odot}$, and increases to $\sim4\%$ at lower
masses. When the observability time scales are taken into consideration, the
major merger rate is found to approximately triple over the mass range we
consider. The total co-moving volume major merger rate over the range
$10^{8.0}<M_{*}<10^{11.5} M_{\odot}$ is $(1.2 \pm 0.5) \times 10^{-3}$
$h^{3}_{70}$ Mpc$^{-3}$ Gyr$^{-1}$.


  We study the uniform random graph $\mathsf{C}_n$ with $n$ vertices drawn from
a subcritical class of connected graphs. Our main result is that the rescaled
graph $\mathsf{C}_n / \sqrt{n}$ converges to the Brownian Continuum Random Tree
$\mathcal{T}_{\mathsf{e}}$ multiplied by a constant scaling factor that depends
on the class under consideration. In addition, we provide subgaussian tail
bounds for the diameter $\text{D}(\mathsf{C}_n)$ and height
$\text{H}(\mathsf{C}_n^\bullet)$ of the rooted random graph
$\mathsf{C}_n^\bullet$. We give analytic expressions for the scaling factor of
several classes, including for example the prominent class of outerplanar
graphs. Our methods also enable us to study first passage percolation on
$\mathsf{C}_n$, where we show the convergence to $\mathcal{T}_{\mathsf{e}}$
under an appropriate rescaling.


  A numerical method for the quasi-neutral two-fluid (QNTF) plasma model is
described. The basic equations are ion and electron fluid equations and the
Maxwell equations without displacement current. The neglect of displacement
current is consistent with the assumption of charge neutrality. It thus reduces
to the ideal magnetohydrodynamic (MHD) equations in the long wavelength limit,
but the two-fluid effect appearing at ion and electron inertial scales is fully
taken into account. It is shown that the basic equations may be rewritten in a
form that has formally the same structure as the MHD equations. The total mass,
momentum, and energy are all written in the conservative form. A new
three-dimensional numerical simulation code has been developed for the QNTF
equations. The HLL (Harten-Lax-van Leer) approximate Riemann solver combined
with the upwind constrained transport (UCT) scheme is applied. The method was
originally developed for MHD (Londrillo & Del Zanna, 2004), but works quite
well for the present model as well. The simulation code is able to capture
sharp multidimensional discontinuities as well as dispersive waves arising from
the two-fluid effect at small scales without producing $\nabla \cdot
\mathbf{B}$ errors. It is well known that conventional Hall-MHD codes often
suffer a numerical stability issue associated with short wavelength whistler
waves. On the other hand, since finite electron inertia introduces an upper
bound to the phase speed of whistler waves in the present model, our code is
free from the issue even without explicit dissipation terms or implicit time
integration. Numerical experiments have confirmed that there is no need to
resolve characteristic time scales such as plasma frequency or cyclotron
frequency for numerical stability. Consequently, the QNTF model offers a better
alternative to the Hall-MHD or fully electromagnetic two-fluid models.