  A new direction to understand gravity has recently been explored by
considering classical gravity to be a derived interaction from an underlying
theory. This underlying theory would involve new degrees of freedom at a deeper
level and it would be structurally different from classical gravitation. It may
conceivably be a quantum theory or a non-quantum theory. The relation between
this underlying theory and Einstein's gravity is similar to the connection
between statistical mechanics and thermodynamics. We discuss the apparent lack
of evidence of any quantum nature of gravity in this context.


  We investigate the effect of interactions in the Topological Insulator in 3+1
dimensions. We show that for a particular type of interactions, the
Electrodynamics response is equivalent to the response of non-interacting
Topological Insulator in 4+1 dimensions.


  We investigate the linear stability of topological black hole solutions to
four-dimensional SU(N) Einstein-Yang-Mills theory with a negative cosmological
constant. We here extend recent results in the field which prove the existence
of hairy black hole solutions to such equations, and the stability of their
spherically symmetric analogues. We find the analysis carries over very
similarly, with some important differences in the final stages. Nevertheless,
we establish the existence of non-trivial solutions stable under linear
perturbations, in a sufficiently small neighbourhood of some existing trivial
solutions; in fact, stable topological solutions turn out to be likely more
abundant in the parameter space than their spherically symmetric analogues.


  Let $V$ be an operator space and $\iso(V)$ be the group of all completely
isometric bijective linear mappings on $V$. Let $G$ act on $V$ via a strongly
continuous group homomorphism $\alpha:G \to \iso (V)$. We define the full (and
reduced) operator space crossed product $V\rtimes^{\op}_{\alpha,(r)}G$ and show
that for a $C^*$-algebra with its canonical operator space structure, it
coincides with the corresponding $C^*$-algebra crossed product.
  Unfortunately, the proof of Theorem 4.3 of the paper contains a serious gap,
which leads to the withdrawal of the paper.


  We consider a continuous-time branching random walk on a multidimensional
lattice with two types of particles and an infinite number of initial
particles. The main results are devoted to the study of the generating function
and the limiting behavior of the moments of subpopulations generated by a
single particle of each type. We assume that particle types differ from each
other not only by the laws of branching, as in multi-type branching processes,
but also by the laws of walking. For a critical branching process at each
lattice point and recurrent random walk of particles, the effect of limit
spatial clustering of particles over the lattice is studied. A model
illustrating epidemic propagation is also considered. In this model, we
consider two types of particles: infected and immunity generated. Initially,
there is an infected particle that can infect others. Here, for the local
number of particles of each type at a lattice point, we study the moments and
their limiting behavior. Additionally, the effect of intermittency of the
infected particles is studied for a supercritical branching process at each
lattice point. Simulations are presented to demonstrate the effect of limit
clustering for the epidemiological model.


  The decomposition of nuclear symmetry energy into spin and isospin components
is discussed to elucidate the underlying properties of the NN bare interaction.
This investigation was carried out in the framework of the
Brueckner-Hartree-Fock theory of asymmetric nuclear matter with consistent two
and three body forces. It is shown the interplay among the various two body
channels in terms of isospin singlet and triplet components as well as spin
singlet and triplet ones. The broad range of baryon densities enables to study
the effects of three body force moving from low to high densities.


  This white paper highlights current limitations in the algebraic closure
Unified Form Language (UFL). UFL currently represents forms over finite element
spaces, however finite element problems naturally result in objects in the dual
to a finite element space, and operators mapping between primal and dual finite
element spaces. This document sketches the relevant mathematical areas and
proposes changes to the UFL language to support dual spaces as first class
types in UFL.


  The paper presents the solutions for the two-beam reduction of the dense
soliton gas equations (or Born-Infeld equation) obtained by analytical and
numerical methods. The method proposed by the authors is used. This method
allows to reduce the Cauchy problem for two hyperbolic quasilinear PDEs to the
Cauchy problem for ODEs. In some respect, this method is analogous to the
method of characteristics for two hyperbolic equations. The method is
effectively applicable in all cases when the explicit expression for the
Riemann-Green function for some linear second order PDE, resulting from the use
of the hodograph method for the original equations, is known. The numerical
results for the two-beam reduction of the dense soliton gas equations, and the
shallow water equations (omitting in the previous papers) are presented. For
computing we use the different initial data (periodic, wave packet).


  Piezoresistance is the change in the electrical resistance, or more
specifically the resistivity, of a solid induced by an applied mechanical
stress. The origin of this effect in bulk, crystalline materials like Silicon,
is principally a change in the electronic structure which leads to a
modification of the charge carriers effective mass. The last few years have
seen a rising interest in the piezoresistive properties of semiconductor
nanostructures, motivated in large part by claims of a giant piezoresistance
effect in Silicon nanowires that is more than two orders of magnitude bigger
than the known bulk effect. This review aims to present the controversy
surrounding claims and counter-claims of giant piezoresistance in Silicon
nanostructures by presenting a summary of the major works carried out over the
last 10 years. The main conclusions that can be drawn from the literature are
that i) reproducible evidence for a giant piezoresistance effect in un-gated
Silicon nanowires is limited, ii) in gated nanowires a giant effect has been
reproduced by several authors, iii) the giant effect is fundamentally different
from either the bulk Silicon piezoresistance or that due to quantum confinement
in accumulation layers and heterostructures, the evidence pointing to an
electrostatic origin for the piezoresistance, iv) released nanowires tend to
have slightly larger piezoresistance coefficients than un-released nanowires,
and v) insufficient work has been performed on bottom-up grown nanowires to be
able to rule out a fundamental difference in their properties when compared
with top-down nanowires. On the basis of this, future possible research
directions are suggested.


  We calculate the electronic structure and magnetic properties of hydrogenated
graphite surfaces using van der Waals density functional theory (DFT) and model
Hamiltonians. We find, as previously reported, that the interaction between
hydrogen atoms on graphene favors adsorption on different sublattices along
with an antiferromagnetic coupling of the induced magnetic moments. On the
contrary, when hydrogenation takes place on the surface of graphene multilayers
or graphite (Bernal stacking), the interaction between hydrogen atoms competes
with the different adsorption energies of the two sublattices. This competition
may result in all hydrogen atoms adsorbed on the same sublattice and, thereby,
in a ferromagnetic state for low concentrations. Based on the exchange
couplings obtained from the DFT calculations, we have also evaluated the Curie
temperature by mapping this system onto an Ising-like model with randomly
located spins. Remarkably, the long-range nature of the magnetic coupling in
these systems makes the Curie temperature size dependent and larger than room
temperature for typical concentrations and sizes.


  Surjective homological epimorphisms with stratifying kernel can be used to
construct recollements of derived module categories. These `stratifying'
recollements are derived from recollements of module categories. Can every
recollement be put in this form, up to equivalence? A negative answer will be
given after providing a characterisation of recollements equivalent to
stratifying ones. Moreover, criteria for a ring epimorphism to be `stratifying'
will be presented as well as constructions of such epimorphisms.


  Some new survival distributions are introduced based on a generalised
exponential function. This class of distributions includes heavy-tailed
generalisations of exponential, Weibull and gamma distributions. Properties of
the distributions are described, and R code is available for computation of
pdf, quantiles, inverse quantiles, random numbers, etc. A use of these
distributions for robust inference is suggested, and this is exemplified with a
Monte-Carlo study.


  This paper deals with topos-theoretic truth-value valuations of quantum
propositions. Concretely, a mathematical framework of a specific type of modal
approach is extended to the topos theory, and further, structures of the
obtained truth-value valuations are investigated. What is taken up is the modal
approach based on a determinate lattice $\Dcal(e,R)$, which is a sublattice of
the lattice $\Lcal$ of all quantum propositions and is determined by a quantum
state $e$ and a preferred determinate observable $R$. Topos-theoretic extension
is made in the functor category $\Sets^{\CcalR}$ of which base category
$\CcalR$ is determined by $R$. Each true atom, which determines truth values,
true or false, of all propositions in $\Dcal(e,R)$, generates also a
multi-valued valuation function of which domain and range are $\Lcal$ and a
Heyting algebra given by the subobject classifier in $\Sets^{\CcalR}$,
respectively. All true propositions in $\Dcal(e,R)$ are assigned the top
element of the Heyting algebra by the valuation function. False propositions
including the null proposition are, however, assigned values larger than the
bottom element. This defect can be removed by use of a subobject
semi-classifier. Furthermore, in order to treat all possible determinate
observables in a unified framework, another valuations are constructed in the
functor category $\Sets^{\Ccal}$. Here, the base category $\Ccal$ includes all
$\CcalR$'s as subcategories. Although $\Sets^{\Ccal}$ has a structure
apparently different from $\Sets^{\CcalR}$, a subobject semi-classifier of
$\Sets^{\Ccal}$ gives valuations completely equivalent to those in
$\Sets^{\CcalR}$'s.


  Sunspots on the surface of the Sun are the observational signatures of
intense manifestations of tightly packed magnetic field lines, with
near-vertical field strengths exceeding 6,000 G in extreme cases. It is well
accepted that both the plasma density and the magnitude of the magnetic field
strength decrease rapidly away from the solar surface, making high-cadence
coronal measurements through traditional Zeeman and Hanle effects difficult
since the observational signatures are fraught with low-amplitude signals that
can become swamped with instrumental noise. Magneto-hydrodynamic (MHD)
techniques have previously been applied to coronal structures, with single and
spatially isolated magnetic field strengths estimated as 9-55 G. A drawback
with previous MHD approaches is that they rely on particular wave modes
alongside the detectability of harmonic overtones. Here we show, for the first
time, how omnipresent magneto-acoustic waves, originating from within the
underlying sunspot and propagating radially outwards, allow the spatial
variation of the local coronal magnetic field to be mapped with high precision.
We find coronal magnetic field strengths of 32 +/- 5 G above the sunspot, which
decrease rapidly to values of approximately 1 G over a lateral distance of 7000
km, consistent with previous isolated and unresolved estimations. Our results
demonstrate a new, powerful technique that harnesses the omnipresent nature of
sunspot oscillations to provide magnetic field mapping capabilities close to a
magnetic source in the solar corona.


  We observed Sedna, Gonggong, and Quaoar with the NIRSpec instrument on the
James Webb Space Telescope (JWST). All three bodies were observed in the
low-resolution prism mode at wavelengths spanning 0.7 to 5.2 $\mu$m. Quaoar was
also observed at 10x higher spectral resolution from 0.97 to 3.16 $\mu$m using
medium-resolution gratings. Sedna's spectrum shows a large number of absorption
features due to ethane (C$_2$H$_6$), as well as acetylene (C$_2$H$_2$),
ethylene (C$_2$H$_4$), H$_2$O, and possibly minor CO$_2$. Gonggong's spectrum
also shows several, but fewer and weaker, ethane features, along with stronger
and cleaner H$_2$O features and CO$_2$ complexed with other molecules. Quaoar's
prism spectrum shows even fewer and weaker ethane features, the deepest and
cleanest H$_2$O features, a feature at 3.2 $\mu$m possibly due to HCN, and
CO$_2$ ice. The higher-resolution medium grating spectrum of Quaoar reveals
several overtone and combination bands of ethane and methane (CH$_4$). Spectra
of all three objects show steep red spectral slopes and strong, broad
absorptions between 2.7 and 3.6 $\mu$m indicative of complex organic molecules.
The suite of light hydrocarbons and complex organic molecules are interpreted
as the products of irradiation of methane. We infer that the differences in
apparent abundances of irradiation products are likely due to their distinctive
orbits, which lead to different timescales of methane retention and to
different charged particle irradiation environments. In all cases, however, the
continued presence of light hydrocarbons implies a resupply of methane to the
surface. We suggest that these three bodies have undergone internal melting and
geochemical evolution similar to the larger dwarf planets and distinct from all
smaller KBOs.


  We present an algorithm to find the determinant and its first and second
derivatives of a rank-one corrected generator matrix of a doubly stochastic
Markov chain. The motivation arises from the fact that the global minimiser of
this determinant solves the Hamiltonian cycle problem. It is essential for
algorithms that find global minimisers to evaluate both first and second
derivatives at every iteration. Potentially the computation of these
derivatives could require an overwhelming amount of work since for the Hessian
$N^2$ cofactors are required. We show how the doubly stochastic structure and
the properties of the objective may be exploited to calculate all cofactors
from a single LU decomposition.


  Despite the massive success of fine-tuning Pre-trained Language Models
(PLMs), they remain susceptible to out-of-distribution input. Dataset
cartography is a simple yet effective dual-model approach that improves the
robustness of fine-tuned PLMs. It involves fine-tuning a model on the original
training set (i.e. reference model), selecting a subset of important training
instances based on the training dynamics, and fine-tuning again only on these
selected examples (i.e. main model). However, this approach requires
fine-tuning the same model twice, which is computationally expensive for large
PLMs. In this paper, we show that (1) training dynamics are highly transferable
across model sizes and pre-training methods, and that (2) fine-tuning main
models using these selected training instances achieves higher training
efficiency than empirical risk minimization (ERM). Building on these
observations, we propose a novel fine-tuning approach: Fine-Tuning by
transFerring Training dynamics (FTFT). Compared with dataset cartography, FTFT
uses more efficient reference models and aggressive early stopping. FTFT
achieves robustness improvements over ERM while lowering the training cost by
up to $\sim 50\%$.


  Navigating complex and dynamic environments requires autonomous vehicles
(AVs) to reason about both visible and occluded regions. This involves
predicting the future motion of observed agents, inferring occluded ones, and
modeling their interactions based on vectorized scene representations of the
partially observable environment. However, prior work on occlusion inference
and trajectory prediction have developed in isolation, with the former based on
simplified rasterized methods and the latter assuming full environment
observability. We introduce the Scene Informer, a unified approach for
predicting both observed agent trajectories and inferring occlusions in a
partially observable setting. It uses a transformer to aggregate various input
modalities and facilitate selective queries on occlusions that might intersect
with the AV's planned path. The framework estimates occupancy probabilities and
likely trajectories for occlusions, as well as forecast motion for observed
agents. We explore common observability assumptions in both domains and their
performance impact. Our approach outperforms existing methods in both occupancy
prediction and trajectory prediction in partially observable setting on the
Waymo Open Motion Dataset.


  We uncover several general phenomenas governing functor homology over
additive categories. In particular, we generalize the strong comparison theorem
of Franjou Friedlander Scorichenko and Suslin to the setting of Fp-linear
additive categories. Our results have a strong impact in terms of explicit
computations of functor homology, and they open the way to new applications to
stable homology of groups or to K-theory. As an illustration, we prove
comparison theorems between cohomologies of classical algebraic groups over
infinite perfect fields, in the spirit of a celebrated result of Cline,
Parshall, Scott et van der Kallen for finite fields.


  Free-standing social conversations constitute a yet underexplored setting for
human behavior forecasting. While the task of predicting pedestrian
trajectories has received much recent attention, an intrinsic difference
between these settings is how groups form and disband. Evidence from social
psychology suggests that group members in a conversation explicitly
self-organize to sustain the interaction by adapting to one another's
behaviors. Crucially, the same individual is unlikely to adapt similarly across
different groups; contextual factors such as perceived relationships,
attraction, rapport, etc., influence the entire spectrum of participants'
behaviors. A question arises: how can we jointly forecast the mutually
dependent futures of conversation partners by modeling the dynamics unique to
every group? In this paper, we propose the Social Process (SP) models, taking a
novel meta-learning and stochastic perspective of group dynamics. Training
group-specific forecasting models hinders generalization to unseen groups and
is challenging given limited conversation data. In contrast, our SP models
treat interaction sequences from a single group as a meta-dataset: we condition
forecasts for a sequence from a given group on other observed-future sequence
pairs from the same group. In this way, an SP model learns to adapt its
forecasts to the unique dynamics of the interacting partners, generalizing to
unseen groups in a data-efficient manner. Additionally, we first rethink the
task formulation itself, motivating task requirements from social science
literature that prior formulations have overlooked. For our formulation of
Social Cue Forecasting, we evaluate the empirical performance of our SP models
against both non-meta-learning and meta-learning approaches with similar
assumptions. The SP models yield improved performance on synthetic and
real-world behavior datasets.


  Simulations of pure-gauge SU(2) lattice gauge theory are performed in the
minimal Coulomb gauge. This leaves a residual or remnant gauge symmetry still
active which is global in three directions but still local in one. Using
averaged fourth-dimension pointing links as a spin-like order parameter, the
remnant symmetry appears to undergo spontaneous symmetry breaking at around
$\beta = 2.6$. Both the Binder cumulant and the magnetization itself exhibit
crossings in this region using lattices up to $20^4$, and a susceptibility peak
is also observed. Finite size scaling indicates a weak first-order transition.
The symmetry breaking is also observed to take place in the fundamental-adjoint
plane, and is coincident with the strong first-order transition that exists
there at large $\beta_{\rm{adjoint}}$. This provides confirmation that this
phase transition is a symmetry-breaking transition. A well-known theorem
concerning the instantaneous Coulomb potential has previously proven that a
transition where such a Coulomb-gauge remnant symmetry breaks is necessarily
deconfining.


  We propose a new contact relation between polytopes. Intuitively, we say that
two polytopes are in strong contact if a small enough object can pass from one
of them to the other while remaining in their union. In the first half of the
paper we prove that this relation is indeed a contact relation between
polytopes, which turns out not to be the case for arbitrary regular closed in
Euclidean spaces sets. In the second half we study the universal fragments of
the logics of the resultant contact algebras. We prove that they all coincide
with the set of theorems of a standard quantifier-free formal system for
connected contact algebras, which also coincides with the universal fragments
of the logics of a variety of (classes of) contact algebras of interest.


  We present a measurement of the branching fractions and charge-parity-(CP-)
violating parameters in B -> omega K decays. The results are obtained from the
final data sample containing 772 x 10^(6) BBbar pairs collected at the Y(4S)
resonance with the Belle detector at the KEKB asymmetric-energy e+e- collider.
We obtain the branching fractions
  B(B0 -> omega K0) = (4.5 +/- 0.4 (stat) +/- 0.3 (syst)) x 10^(-6),
  B(B- -> omega K-) = (6.8 +/- 0.4 (stat) +/- 0.4 (syst)) x 10^(-6),
  which are in agreement with their respective current world averages. For the
CP violating parameters, we obtain
  A(B0 -> omega KS) = -0.36 +/- 0.19 (stat) +/- 0.05 (syst),
  S(B0 -> omega KS) = +0.91 +/- 0.32 (stat) +/- 0.05 (syst),
  A(B- -> omega K-) = -0.03 +/- 0.04 (stat) +/- 0.01 syst), where A and S
represent the direct and mixing-induced CP asymmetry, respectively. We find no
evidence of CP violation in the decay channel B-->omega K-; however, we obtain
the first evidence of CP violation in the B0 -> omega KS decay channel at the
level of 3.1 standard deviations.


  A quantitative theory on the construction and the evolution of the genetic
code is proposed. Through introducing the concept of mutational deterioration
(MD) and developing a theoretical formalism on MD minimization we have proved:
1, the redundancy distribution of codons in the genetic code obeys MD
minimization principle; 2, the hydrophilic-hydrophobic distribution of amino
acids on the code table is global MD (GMD) minimal; 3, the standard genetic
code can be deduced from the adaptive minimization of GMD; 4, the variants of
the standard genetic code can be explained quantitatively by use of GMD
formalism and the general trend of the evolution is GMD non-increasing which
reflects the selection on the code. We have demonstrated that the redundancy
distribution of codons and the hydrophobic-hydrophilic (H-P) distribution of
amino acids are robust in the code relative to the mutational parameter, and
indicated that the GMD can be looked as a non-fitness function on the adaptive
landscape. Finally, an important aspect on the symmetry of the code
construction, the Yin-Yang duality is investigated. The Yin-Yang duality among
codons affords a sound basis for understanding the H-P structure in the genetic
code.


  Deep neural networks are known to achieve superior results in classification
tasks. However, it has been recently shown that they are incapable to detect
examples that are generated by a distribution which is different than the one
they have been trained on since they are making overconfident prediction for
Out-Of-Distribution (OOD) examples. OOD detection has attracted a lot of
attention recently. In this paper, we review some of the most seminal recent
algorithms in the OOD detection field, we divide those methods into training
and post-training and we experimentally show how the combination of the former
with the latter can achieve state-of-the-art results in the OOD detection task.


  Discrimination in selection problems such as hiring or college admission is
often explained by implicit bias from the decision maker against disadvantaged
demographic groups. In this paper, we consider a model where the decision maker
receives a noisy estimate of each candidate's quality, whose variance depends
on the candidate's group -- we argue that such differential variance is a key
feature of many selection problems. We analyze two notable settings: in the
first, the noise variances are unknown to the decision maker who simply picks
the candidates with the highest estimated quality independently of their group;
in the second, the variances are known and the decision maker picks candidates
having the highest expected quality given the noisy estimate. We show that both
baseline decision makers yield discrimination, although in opposite directions:
the first leads to underrepresentation of the low-variance group while the
second leads to underrepresentation of the high-variance group. We study the
effect on the selection utility of imposing a fairness mechanism that we term
the $\gamma$-rule (it is an extension of the classical four-fifths rule and it
also includes demographic parity). In the first setting (with unknown
variances), we prove that under mild conditions, imposing the $\gamma$-rule
increases the selection utility -- here there is no trade-off between fairness
and utility. In the second setting (with known variances), imposing the
$\gamma$-rule decreases the utility but we prove a bound on the utility loss
due to the fairness mechanism.


  We constructed a model of natural inflation in the context of
$\alpha$-attractor supergravity, in which both the dilaton field and the axion
field are light during inflation, and the inflaton may be a combination of the
two. The T-model version of this theory is defined on the Poincare disk with
radius |Z| = 1. It describes a Mexican hat potential with the flat axion
direction corresponding to a circle of radius |Z| < 1. The axion decay constant
$f_{a}$ in this theory can be exponentially large because of the hyperbolic
geometry of the Poincare disk. Depending on initial conditions, this model may
describe $\alpha$-attractor inflation driven by the radial component of the
inflaton field, natural inflation driven by the axion field, or a sequence of
these two regimes. We also construct the E-model version of this theory, which
has similar properties. In addition, we describe generalized $\alpha$-attractor
models where the potential can be singular at the boundary of the moduli space,
and show that they can provide a simple solution for the problem of initial
conditions for the models with plateau potentials.


  The Shapley value, one of the well-known allocation rules in game theory,
does not take into account information about the structure of the graph, so by
using the Shapley value for each hyperedge, we introduce a new allocation rule
by considering their first-order combination. We proved that some of the
properties that hold for Shapley and Myerson values also hold for our
allocation rule. In addition, we found the relationship between our allocation
rule and the Forman curvature, which plays an important role in discrete
geometry.


  We have carried out mid-infrared spectroscopy of seven Galactic
proto-planetary nebulae (PPNs) using the Spitzer Space Telescope. They were
observed from 10-36 microns at relatively high spectral resolution, R~600. The
sample was chosen because they all gave some evidence in the visible of a
carbon-rich chemistry. All seven of the sources show the broad, unidentified 21
micron emission feature; three of them are new detections (IRAS 06530-0213,
07430+1115, and 19477+2401) and the others are observed at higher S/N than in
previous spectra. These have the same shape and central wavelength (20.1
microns) as found in the ISO spectra of the brighter PPNs. The 30 micron
feature was seen in all seven objects. However, it is not resolved into two
separate features (26 and 33 microns) as was claimed on the basis of ISO
spectra, which presumably suffered from the noisy detector bands in this
region. All showed the infrared aromatic bands (AIB) at 11.3, 12.4, and 13.3
microns. Five of these also appear to have the C2H2 molecular band at 13.7
microns, one in absorption and four in emission. This is extremely rare, with
only one other evolved star, IRC+10216, in which C2H2 emission has been
observed. Four also possessed a broad, unidentified emission feature at 15.8
microns that may possibly be related to the 21 micron feature. Model fits were
made to the spectral energy distributions for these PPNs to determine
properties of the detached circumstellar envelopes. The 21 micron feature has
been seen in all Galactic carbon-rich PPNs observed, and thus its carrier
appears to be a common component of the outflow around these objects.


  Social networks are the fabric of society and the subject of frequent visual
analysis. Closed triads represent triangular relationships between three people
in a social network and are significant for understanding inherent
interconnections and influence within the network. The most common methods for
representing social networks (node-link diagrams and adjacency matrices) are
not optimal for understanding triangles. We propose extending the adjacency
matrix form to 3D for better visualization of network triads. We design a 3D
matrix reordering technique and implement an immersive interactive system to
assist in visualizing and analyzing closed triads in social networks. A user
study and usage scenarios demonstrate that our method provides substantial
added value over node-link diagrams in improving the efficiency and accuracy of
manipulating and understanding the social network triads.


  Human symbol systems such as art and fashion styles emerge from complex
social processes that govern the continuous re-organization of modern
societies. They provide a signaling scheme that allows members of an elite to
distinguish themselves from the rest of society. Efforts to understand the
dynamics of art and fashion cycles have been based on 'bottom-up' and 'top
down' theories. According to 'top down' theories, elite members signal their
superior status by introducing new symbols (e.g., fashion styles), which are
adopted by low-status groups. In response to this adoption, elite members would
need to introduce new symbols to signal their status. According to many
'bottom-up' theories, style cycles evolve from lower classes and follow an
essentially random pattern. We propose an alternative explanation based on
counter-dominance signaling. There, elite members want others to imitate their
symbols; changes only occur when outsider groups successfully challenge the
elite by introducing signals that contrast those endorsed by the elite. We
investigate these mechanisms using a dynamic network approach on data
containing almost 8 million musical albums released between 1956 and 2015. The
network systematically quantifies artistic similarities of competing musical
styles and their changes over time. We formulate empirical tests for whether
new symbols are introduced by current elite members (top-down), randomness
(bottom-up) or by peripheral groups through counter-dominance signals. We find
clear evidence that counter-dominance-signaling drives changes in musical
styles. This provides a quantitative, completely data-driven answer to a
century-old debate about the nature of the underlying social dynamics of
fashion cycles.


  The Hyperspectral Thermal Imager (HyTI) is a technology demonstration mission
that will obtain high spatial, spectral, and temporal resolution long-wave
infrared images of Earth's surface from a 6U cubesat. HyTI science requires
that the pointing accuracy of the optical axis shall not exceed 2.89 arcsec
over the 0.5 ms integration time due to microvibration effects (known as
jitter). Two sources of vibration are a cryocooler that is added to maintain
the detector at 68 K and three orthogonally placed reaction wheels that are a
part of the attitude control system. Both of these parts will introduce
vibrations that are propagated through to the satellite structure while
imaging. Typical methods of characterizing and measuring jitter involve complex
finite element methods and specialized equipment and setups. In this paper, we
describe a novel method of characterizing jitter for small satellite systems
that is low-cost and minimally modifies the subject's mass distribution. The
metrology instrument is comprised of a laser source, a small mirror mounted via
a 3D printed clamp to a jig, and a lateral effect position-sensing detector.
The position-sensing detector samples 1000 Hz and can measure displacements as
little as 0.15 arcsec at distances of one meter. This paper provides an
experimental procedure that incrementally analyzes vibratory sources to
establish causal relationships between sources and the vibratory modes they
create. We demonstrate the capabilities of this metrology system and testing
procedure on HyTI in the Hawaii Space Flight Lab's clean room. Results include
power spectral density plots that show fundamental and higher-order vibratory
modal frequencies. Results from metrology show that jitter from reaction wheels
meets HyTI system requirements within 3$\sigma$.


  We present experimental results on eigenfunctions of a wave chaotic system in
the continuous crossover regime between time-reversal symmetric and
time-reversal symmetry-broken states. The statistical properties of the
eigenfunctions of a two-dimensional microwave resonator are analyzed as a
function of an experimentally determined time-reversal symmetry breaking
parameter. We test four theories of one-point eigenfunction statistics and
introduce a new theory relating the one-point and two-point statistical
properties in the crossover regime. We also find a universal correlation
between the one-point and two-point statistical parameters for the crossover
eigenfunctions.


  We are currently carrying out a K_s band survey for core-collapse supernovae
in the nuclear (central kpc) regions of nearby starburst galaxies with the
INGRID near-IR camera at the WHT. In this article we concentrate in describing
mainly the observations and the real time processing of the SN search data,
which makes use of the ING's integrated data flow system.


  Recently Marcus, Spielman and Srivastava proved Weaver's ${\rm{KS}}_r$
conjecture, which gives a positive solution to the Kadison-Singer problem.
Cohen and Br\"and\'en independently extended this result to obtain the
arbitrary-rank version of Weaver's ${\rm{KS}}_r$ conjecture. In this paper, we
present a new bound in Weaver's ${\rm{KS}}_r$ conjecture for the arbitrary-rank
case. To do that, we introduce the definition of $(k,m)$-characteristic
polynomials and employ it to improve the previous estimate on the largest root
of the mixed characteristic polynomials. For the rank-one case, our bound
agrees with the Bownik-Casazza-Marcus-Speegle's bound when $r=2$ and with the
Ravichandran-Leake's bound when $r>2$. For the higher-rank case, we sharpen the
previous bounds from Cohen and from Br\"and\'en .


  In this paper, we apply the angle-resolved Optically Detected Magnetic
Resonance (ODMR) technique to study series of strained (Cd, Mn)Te/(Cd, Mg)Te
quantum wells (QWs) produced by molecular beam epitaxy. By analyzing
characteristic features of ODMR angular scans, we determine strain-induced
axial-symmetry spin Hamiltonian parameter D with neV precision. Furthermore, we
use low-temperature optical reflectivity measurements and X-ray diffraction
scans to evaluate the local strain present in QW material. In our analysis, we
take into account different thermal expansion coefficients of GaAs substrate
and CdTe buffer. The additional deformation due to the thermal expansion
effects has the same magnitude as deformation origination from the different
compositions of the samples. Based on the evaluated deformations and values of
strain-induced axial-symmetry spin Hamiltonian parameter D, we find strain
spin-lattice coefficient G11 = (72.2 +- 1.9) neV for Mn2+ in CdTe and shear
deformation potential b = (-0.94 +- 0.11) eV for CdTe.


  We study conformal symmetry breaking differential operators which map
differential forms on $\mathbb{R}^n$ to differential forms on a codimension one
subspace $\mathbb{R}^{n-1}$. These operators are equivariant with respect to
the conformal Lie algebra of the subspace $\mathbb{R}^{n-1}$. They correspond
to homomorphisms of generalized Verma modules for ${\mathfrak so}(n,1)$ into
generalized Verma modules for ${\mathfrak so}(n+1,1)$ both being induced from
fundamental form representations of a parabolic subalgebra. We apply the
F-method to derive explicit formulas for such homomorphisms. In particular, we
find explicit formulas for the generators of the intertwining operators of the
related branching problems restricting generalized Verma modules for
${\mathfrak so}(n+1,1)$ to ${\mathfrak so}(n,1)$. As consequences, we find
closed formulas for all conformal symmetry breaking differential operators in
terms of the first-order operators $d$, $\delta$, $\bar{d}$ and $\bar{\delta}$
and certain hypergeometric polynomials. A dominant role in these studies will
be played by two infinite sequences of symmetry breaking differential operators
which depend on a complex parameter $\lambda$. These will be termed the
conformal first and second type symmetry breaking operators. Their values at
special values of $\lambda$ appear as factors in two systems of factorization
identities which involve the Branson-Gover operators of the Euclidean metrics
on $\mathbb{R}^n$ and $\mathbb{R}^{n-1}$ and the operators $d$, $\delta$,
$\bar{d}$ and $\bar{\delta}$ as factors, respectively. Moreover, they are shown
to naturally recover the gauge companion and $Q$-curvature operators of the
Euclidean metric on the subspace $\mathbb{R}^{n-1}$, respectively.


  Performing reliability analysis on complex systems is often computationally
expensive. In particular, when dealing with systems having high input
dimensionality, reliability estimation becomes a daunting task. A popular
approach to overcome the problem associated with time-consuming and expensive
evaluations is building a surrogate model. However, these computationally
efficient models often suffer from the curse of dimensionality. Hence, training
a surrogate model for high-dimensional problems is not straightforward.
Henceforth, this paper presents a framework for solving high-dimensional
reliability analysis problems. The basic premise is to train the surrogate
model on a low-dimensional manifold, discovered using the active subspace
algorithm. However, learning the low-dimensional manifold using active subspace
is non-trivial as it requires information on the gradient of the response
variable. To address this issue, we propose using sparse learning algorithms in
conjunction with the active subspace algorithm; the resulting algorithm is
referred to as the sparse active subspace (SAS) algorithm. We project the
high-dimensional inputs onto the identified low-dimensional manifold identified
using SAS. A high-fidelity surrogate model is used to map the inputs on the
low-dimensional manifolds to the output response. We illustrate the efficacy of
the proposed framework by using three benchmark reliability analysis problems
from the literature. The results obtained indicate the accuracy and efficiency
of the proposed approach compared to already established reliability analysis
methods in the literature.


  This paper presents results of a fully automated search for multiperiodic RR
Lyrae stars in the center of the Galaxy. The search was carried out on OGLE-II
database created by means of image subtraction method. I found more than 2700
RR Lyrae stars with about 600 showing various kinds of multiperiodic behavior.
Previous OGLE-I database contained only about 200 RR Lyrae stars in the
Galactic Bulge, that is twelve times less than the current sample. There are
two most interesting outcomes for Bulge: very high percentage of Blazhko stars
and very low percentage of RRd stars. Blazhko effect was confirmed in about 25
percent of all RRab stars. This incidence rate is almost 2.5 times greater than
in the Large Magellanic Cloud. On the other hand I discovered only 3 RRd stars,
which implies that the incidence rate of this type of variables is much smaller
in Bulge than in the Magellanic Clouds.


  Lock-in Thermography (LIT) is a type of Infrared Thermography (IRT) that can
be used as a useful non-destructive testing (NDT) technique for the detection
of subsurface anomalies in objects. Currently, LIT fails to estimate the
thickness at a point on the tested object. This makes LIT unable to figure out
the 3-dimensional geometry of an object. In this project, two techniques of
identifying the geometry of an object using LIT are discussed. The main idea of
both techniques is to find a relationship between the parameters obtained from
LIT and the thickness at each data point. Technique I builds a numerical
function that models the relationship between thickness, Lock-In phase, and
other parameters. The function is then inverted for thickness estimation.
Technique II is a quantitative method, in which a database is created with six
dimensions - thickness, Lock-In phase, Lock-In amplitude and three other
parameters, based on data obtained from LIT experiments or simulations.
Estimated thickness is obtained by retrieving data from the database. The
database can be improved based on Principal Component Analysis. Evaluation of
the techniques is done by measuring root-mean-square deviation, and calculating
successful rate with different tolerances. Moreover, during the application of
the techniques, Stochastic Gradient Descent can be used to determine the time
when sufficient data have been collected from LIT measurement to generate the
estimated geometry accurately.


  The supernova yields of r-process elements are obtained as a function of the
mass of their progenitor stars from the abundance patterns of extremely
metal-poor stars on the left-side [Ba/Mg]-[Mg/H] boundary with a procedure
proposed by Tsujimoto and Shigeyama. The ejected masses of r-process elements
associated with stars of progenitor mass $M_{ms}\leq18M_{\odot}$ are infertile
sources and the SNe II with 20$M_{\odot}\leq M_{ms}\leq 40M_{\odot}$are the
dominant source of r-process nucleosynthesis in the Galaxy. The ratio of these
stars 20$M_{\odot}\leq M_{ms}\leq40M_{\odot}$ with compared to the all massive
stars is about $\sim$18%. In this paper, we present a simple model that
describes a star's [r/Fe] in terms of the nucleosynthesis yields of r-process
elements and the number of SN II explosions. Combined the r-process yields
obtained by our procedure with the scatter model of the Galactic halo, the
observed abundance patterns of the metal-poor stars can be well reproduced


  We consider a system of particles subjected to a uniform external force E and
undergoing random collisions with "virtual" fixed obstacles, as in the Drude
model of conductivity. The system is maintained in a nonequilibrium stationary
state by a Gaussian thermostat. In a suitable limit the system is described by
a self consistent Boltzmann equation for the one particle distribution function
f. We find that after a long time f(v,t) approaches a stationary velocity
distribution f(v) which vanishes for large speeds, i.e. f(v)=0 for |v|>vmax(E),
with vmax(E)~1/|E| as |E| -> 0. In that limit f(v)~exp(-c|v|^3) for fixed v,
where c depends on mean free path of the particle. f(v) is computed explicitly
in one dimension.


  We establish radiative stability of generalized Proca effective field
theories. While standard powercounting arguments would conclude otherwise, we
find non-trivial cancellations of leading order corrections by explicit
computation of divergent one-loop diagrams up to four-point. These results are
crosschecked against an effective action based generalized Schwinger-DeWitt
method. Further, the cancellations are understood as coming from the specific
structure of the theory through a decoupling limit analysis which at the same
time allows for an extension of the results to higher orders.


  Transition disks with large dust cavities around young stars are promising
targets for studying planet formation. Previous studies have revealed the
presence of gas cavities inside the dust cavities hinting at recently formed,
giant planets. However, many of these studies are biased towards the brightest
disks in the nearby star forming regions, and it is not possible to derive
reliable statistics that can be compared with exoplanet populations. We present
the analysis of 11 transition disks with large cavities (>20 AU radius) from a
complete disk survey of the Lupus star forming region, using ALMA Band 7
observations at 0.3" (22-30 AU radius) resolution of the 345 GHz continuum,
13CO and C18O 3-2 observations and the Spectral Energy Distribution of each
source. Gas and dust surface density profiles are derived using the
physical-chemical modeling code DALI. This is the first study of transition
disks of large cavities within a complete disk survey within a star forming
region. The dust cavity sizes range from 20-90 AU radius and in three cases, a
gas cavity is resolved as well. The deep drops in gas density and large dust
cavity sizes are consistent with clearing by giant planets. The fraction of
transition disks with large cavities in Lupus is ~11%, which is inconsistent
with exoplanet population studies of giant planets at wide orbits. Furthermore,
we present a hypothesis of an evolutionary path for large massive disks
evolving into transition disks with large cavities.


  We propose a new framework to facilitate dynamic assurance within a safety
case approach by associating safety performance measurement with the core
assurance artifacts of a safety case. The focus is mainly on the safety
architecture, whose underlying risk assessment model gives the concrete link
from safety measurement to operational risk. Using an aviation domain example
of autonomous taxiing, we describe our approach to derive safety indicators and
revise the risk assessment based on safety measurement. We then outline a
notion of consistency between a collection of safety indicators and the safety
case, as a formal basis for implementing the proposed framework in our tool,
AdvoCATE.


  The thermodynamic properties of gases have been understood primarily through
phase diagrams of bulk gases. However, observations of gases confined in a
nanometer space have posed a challenge to the principles of classical
thermodynamics. Here, we investigated interfacial structures comprising either
O2 or N2 between water and a hydrophobic solid surface by using advanced atomic
force microscopy techniques. Ordered epitaxial layers and cap-shaped
nanostructures were observed. In addition, pancake-shaped disordered layers
that had grown on top of the epitaxial base layers were observed in
oxygen-supersaturated water. We propose that hydrophobic solid surfaces provide
low-chemical-potential sites at which gas molecules dissolved in water can be
adsorbed. The structures are further stabilized by interfacial water. Gas
molecules can agglomerate into a condensed form when confined in a sufficiently
small space under ambient conditions. The ordering and thermodynamic properties
of the confined gases are determined primarily according to interfacial
interactions. The crystalline solid surface may even induce a solid-gas state.


  Human-Object Interaction (HOI) detection is a challenging computer vision
task that requires visual models to address the complex interactive
relationship between humans and objects and predict HOI triplets. Despite the
challenges posed by the numerous interaction combinations, they also offer
opportunities for multimodal learning of visual texts. In this paper, we
present a systematic and unified framework (RmLR) that enhances HOI detection
by incorporating structured text knowledge. Firstly, we qualitatively and
quantitatively analyze the loss of interaction information in the two-stage HOI
detector and propose a re-mining strategy to generate more comprehensive visual
representation.Secondly, we design more fine-grained sentence- and word-level
alignment and knowledge transfer strategies to effectively address the
many-to-many matching problem between multiple interactions and multiple
texts.These strategies alleviate the matching confusion problem that arises
when multiple interactions occur simultaneously, thereby improving the
effectiveness of the alignment process. Finally, HOI reasoning by visual
features augmented with textual knowledge substantially improves the
understanding of interactions. Experimental results illustrate the
effectiveness of our approach, where state-of-the-art performance is achieved
on public benchmarks. We further analyze the effects of different components of
our approach to provide insights into its efficacy.


  In this paper we present a fast method based on successive convexification
for generating fuel-optimized spacecraft rendezvous trajectories in the
presence of mixed-integer constraints. A recently developed paradigm of
state-triggered constraints allows to efficiently embed a subset of discrete
decision constraints into the continuous optimization framework of successive
convexification. As a result, we are able to solve difficult trajectory
optimization problems at interactive speeds, as opposed to a mixed-integer
programming approach that would require significantly more solution time and
computing power. Our method is applied to the real problem of transposition and
docking of the Apollo command and service module with the lunar module. We
demonstrate that, within seconds, we are able to obtain trajectories that are
up to 90 percent more fuel efficient (saving up to 45 kg of fuel) than
non-optimization based Apollo-era design targets. Our trajectories take
explicit account of minimum thrust pulse width and plume impingement
constraints. Both of these constraints are naturally mixed-integer, but we
handle them as state-triggered constraints. In its current state, our algorithm
will serve as a useful off-line design tool for rapid trajectory trade studies.


  Leukemia (blood cancer) is an unusual spread of White Blood Cells or
Leukocytes (WBCs) in the bone marrow and blood. Pathologists can diagnose
leukemia by looking at a person's blood sample under a microscope. They
identify and categorize leukemia by counting various blood cells and
morphological features. This technique is time-consuming for the prediction of
leukemia. The pathologist's professional skills and experiences may be
affecting this procedure, too. In computer vision, traditional machine learning
and deep learning techniques are practical roadmaps that increase the accuracy
and speed in diagnosing and classifying medical images such as microscopic
blood cells. This paper provides a comprehensive analysis of the detection and
classification of acute leukemia and WBCs in the microscopic blood cells.
First, we have divided the previous works into six categories based on the
output of the models. Then, we describe various steps of detection and
classification of acute leukemia and WBCs, including Data Augmentation,
Preprocessing, Segmentation, Feature Extraction, Feature Selection (Reduction),
Classification, and focus on classification step in the methods. Finally, we
divide automated detection and classification of acute leukemia and WBCs into
three categories, including traditional, Deep Neural Network (DNN), and mixture
(traditional and DNN) methods based on the type of classifier in the
classification step and analyze them. The results of this study show that in
the diagnosis and classification of acute leukemia and WBCs, the Support Vector
Machine (SVM) classifier in traditional machine learning models and
Convolutional Neural Network (CNN) classifier in deep learning models have
widely employed. The performance metrics of the models that use these
classifiers compared to the others model are higher.


  (Abridged) We infer the velocity distribution of radio pulsars by modelling
their birth, evolution, and detection in large-scale 0.4 GHz pulsar surveys,
and by comparing model distributions of measurable pulsar properties with
survey data using a likelihood function. We test models that characterize a
population's birth rate, luminosity, shutoff of radio emission, birth
locations, and birth velocities. We infer that the radio beam luminosity (i) is
comparable to the energy flux of relativistic particles in models for
spin-driven magnetospheres, signifying that radio emission losses reach nearly
100% for the oldest pulsars; and (ii) scales approximately as sqrt(Edot) which,
in magnetosphere models, is proportional to the voltage drop available for
acceleration of particles. We find that a two-component velocity distribution
with characteristic velocities of 90 km/s and 500 km/s is greatly preferred to
any one-component distribution. We explore some consequences of the preferred
birth velocity distribution: (i) roughly 50% of pulsars in the solar
neighborhood will escape the Galaxy, while ~15% have velocities greater than
1000 km/s; (ii) an important low-velocity population exists that increases the
fraction of neutron stars retained by globular clusters and is consistent with
the number of old objects that accrete from the interstellar medium; (iii)
under standard assumptions for supernova remnant expansion and pulsar
spin-down, ~10% of pulsars younger than 20 kyr will appear to lie outside of
their host remnants. Finally, we comment on the ramifications of our birth
velocity distribution for binary survival and the population of inspiraling
binary neutron stars relevant to some GRB models and potential sources for
LIGO.


  We study the fractional Schr\"odinger equation with quasilocal perturbations.
These are a family of nonlocal perturbations vanishing at infinity, which
include e.g. convolutions against Schwartz functions. We show that the
qualitative unique continuation and Runge approximation properties hold in the
assumption of sufficient decay. Quantitative versions of both results are also
obtained via a propagation of smallness analysis for the Caffarelli-Silvestre
extension. The results are then used to show uniqueness in the inverse problem
of retrieving a quasilocal perturbation from DN data under suitable geometric
assumptions. Our work generalizes recent results regarding the locally
perturbed fractional Calder\'on problem.


  We propose and use a technique to measure the transverse emittance of a
laser-wakefield accelerated beam of relativistic electrons. The technique is
based on the simultaneous measurements of the electron beam divergence given by
$v_{\perp}/v_{\parallel}$, the measured longitudinal spectrum
$\gamma_\parallel$ and the transverse electron bunch size in the bubble
$r_{\perp}$. The latter is obtained via the measurement of the source size of
the x-rays emitted by the accelerating electron bunch in the bubble. We measure
a \textit{normalised} RMS beam transverse emittance $<0.5$ $\pi$ mm$\:$mrad as
an upper limit for a spatially gaussian, spectrally quasi-monoenergetic
electron beam with 230 MeV energy in agreement with numerical modeling and
analytic theory in the bubble regime.


  Emergence of hierarchies is investigated by Monte Carlo simulation in a timid
society where all individuals are pacifist. The self-organiztion of hierarchies
is shown to occur in two steps as the population is increased, i.e. there are
three states, one egalitarian and two hierarchical states;the transition from
the egalitarian to the first hierarchical state is continuous and the
transition from the first hierachical state to the second one is discontinuous.
In the first hierarchical society, all individuals belong to either middle
class or losers and no winners appear. In the second hierarchical society, many
winners emerge and the population of the middle class is reduced. The hierarchy
in the second hierarchical society is stronger than the hierachy in a
no-preference society studied by Bonabeau et al [ Physica A{\bf 217}, 373
(1995)]


  In this work, we present a logic based on first-order CTL, namely Game
Analysis Logic (GAL), in order to reason about games. We relate models and
solution concepts of Game Theory as models and formulas of GAL, respectively.
Precisely, we express extensive games with perfect in- formation as models of
GAL, and Nash equilibrium and subgame perfect equilibrium by means of formulas
of GAL. From a practical point of view, we provide a GAL model checker in order
to analyze games automatically. We use our model checker in at least two
directions: to find solution con- cepts of Game Theory; and, to analyze players
that are based on standard algorithms of the AI community, such as the minimax
procedure.


  We derive the microcanonical partition function of the ideal relativistic
quantum gas with fixed intrinsic angular momentum as an expansion over fixed
multiplicities. We developed a group theoretical approach by generalizing known
projection techniques to the Poincare' group. Our calculation is carried out in
a quantum field framework and applies to particles with any spin. It extends
known results in literature in that it does not introduce any large volume
approximation and it takes particle spin fully into account. We provide
expressions of the microcanonical partition function at fixed multiplicities in
the limiting classical case of large volumes and large angular momenta and in
the grand-canonical ensemble. We also derive the microcanonical partition
function of the ideal relativistic quantum gas with fixed parity.


  The nonlinear response of stochastic models obeying a master equation is
calculated up to fifth-order in the external field thus extending the
third-order results obtained earlier (G. Diezemann, Phys. Rev. E{\bf 85},
051502 (2012)). For sinusoidal fields the $5\om$-component of the
susceptibility is computed for the model of dipole reorientations in an
asymmetric double well potential and for a trap model with a Gaussian density
of states. For most realizations of the models a hump is found in the
higher-order susceptibilities. In particular, for the asymmetric double well
potential model there are two characteristic temperature regimes showing the
occurence of such a hump as compared to a single characteristic regime in case
of the third-order response. In case of the trap model the results strongly
depend on the variable coupled to the field. As for the third-order response,
the low-frequency limit of the susceptibility plays a crucial role with respect
to the occurence of a hump. The findings are discussed in light of recent
experimental results obtained for supercooled liquids. The differences found
for the third-order and the fifth-order response indicate that nonlinear
response functions might serve as a powerful tool to discriminate among the
large number of existing models for glassy relaxation.


  This paper addresses the problem of determining the minimum set of state
variables in a network that need to be blocked from direct measurements in
order to protect functional privacy with respect to {\emph{any}} output
matrices. The goal is to prevent adversarial observers or eavesdroppers from
inferring a linear functional of states, either vector-wise or entry-wise. We
prove that both problems are NP-hard. However, by assuming a reasonable
constant bound on the geometric multiplicities of the system's eigenvalues, we
present an exact algorithm with polynomial time complexity for the vector-wise
functional privacy protection problem. Based on this algorithm, we then provide
a greedy algorithm for the entry-wise privacy protection problem. Our approach
is based on relating these problems to functional observability and leveraging
a PBH-like criterion for functional observability. Finally, we provide an
example to demonstrate the effectiveness of our proposed approach.


  Semilinear stochastic evolution equations with multiplicative L\'evy noise
and monotone nonlinear drift are considered. Unlike other similar works, we do
not impose coercivity conditions on coefficients. We establish the continuous
dependence of the mild solution with respect to initial conditions and also on
coefficients which as far as we know, has not been proved before. As
corollaries of the continuity result, we derive sufficient conditions for
asymptotic stability of the solutions, we show that Yosida approximations
converge to the solution and we prove that solutions have Markov property.
Examples on stochastic partial differential equations and stochastic delay
differential equations are provided to demonstrate the theory developed. The
main tool in our study is an inequality which gives a pathwise bound for the
norm of stochastic convolution integrals.


  We prove that Kobayashi isometries between strongly convex domains are
holomorphic or anti-holomorphic.
  More precisely, let $n_1, n_2$ be positive integers and let $\Omega_i \subset
\C^{n_i}, \ i=1,2$, be bounded $C^3$ strongly convex domains. If $\phi:
(\Omega_1, d^K_{\Omega_1}) \rightarrow (\Omega_2, d^K_{\Omega_2})$ is an
isometry, i.e. $ d^K_\Omega_{n_2}(f(\zeta),f(\eta)) = d^K_{n_1} (\zeta,\eta)$
for all $\zeta,\eta \in \Omega_1,$ then $\phi$ is either holomorphic or
anti-holomorphic.


  This paper shows how abstract resolvent estimates imply local smoothing for
solutions to the Schr\"odinger equation. If the resolvent estimate has a loss
when compared to the optimal, non-trapping estimate, there is a corresponding
loss in regularity in the local smoothing estimate. As an application, we apply
well-known techniques to obtain well-posedness results for the semi-linear
Schr\"odinger equation.


  In this paper we analyze a broad class of abstract doubly nonlinear evolution
equations in Banach spaces, driven by nonsmooth and nonconvex energies. We
provide some general sufficient conditions, on the dissipation potential and
the energy functional,for existence of solutions to the related Cauchy problem.
We prove our main existence result by passing to the limit in a
time-discretization scheme with variational techniques. Finally, we discuss an
application to a material model in finite-strain elasticity.


  The color matrix elements of the ghost triangle diagram that appears in the
triple gluon vertex and the ghost-ghost-gluon triangle diagram that appears in
the ghost-gluon-ghost vertex are calculated. The ghost-ghost-gluon triangle
contains a loop consisting of two color diagonal ghosts and one gluon and a
loop consisting of two color antisymmetric ghosts and one gluon. Consequently,
the pQCD argument in the infrared region based on the one particle irreducible
diagram should be modified. Implications for the Kugo-Ojima color confinement
and the QCD running coupling are discussed.


  We report the discovery of a sample of 19 low redshift (z<0.22)
spectroscopically non-Seyfert galaxies that show slow declining mid-infrared
(MIR) light-curves (LCs), similar to those of tidal disruption event (TDE)
candidates with extreme coronal lines. Two sources also showed a relatively
fast rising MIR LCs. They consist of 61% sample of the WISE MIR variable
non-Seyfert galaxies with SDSS spectra. In a comparison sample of optically
selected Seyfert galaxies, the fraction of sources with such a LC is only 15%.
After rejecting 5 plausible obscured Seyfert galaxies with red MIR colours,
remaining 14 objects are studied in detail in this paper. We fit the declining
part of LC with an exponential law, and the decay time is typically one year.
The observed peak MIR luminosities ($\nu L_\nu$) after subtracting host
galaxies are in the range of a few 10^42 to 10^44 erg~s^-1 with a median of
5x10^43 erg~s^-1 in the W2 band. The black hole masses distribute in a wide
range with more than half in between 10^7 to 10^8 ~M_sun, but significantly
different from that of optical/UV selected TDEs. Furthermore, MIR luminosities
are correlated with black hole masses, the stellar mass or luminosity of their
host bulges. Most galaxies in the sample are red and luminous with an absolute
magnitude of r between -20 to -23. We estimate the rate of event about 10^-4
gal^-1~yr^-1 among luminous red galaxies. We discuss several possibilities for
the variable infrared sources, and conclude that most likely, they are caused
by short sporadic fueling to the supermassive black holes via either the
instability of accretion flows or tidal disruption of stars.


  For the binary discs packed in two dimensions, the packing fraction of disc
assembly becomes lower than that of the monodisperse system when the size ratio
is close to unity. We show that the suppressed packing fraction is caused by an
increase of the adjacent neighbours with long bonds where the adjacent
neighbours is defined on the basis of the Laguerre (radical) tessellation. For
the poly-disperse systems in two and three dimensions, the packing fraction is
shown to have a minimuma as a function of the poly-dispersity. Percolation
process in the densely packed discs and spheres is also studied. The critical
area (volume) fraction in two (three) dimensions is shown to be a monotonically
increasing (decreasing) function of the poly-dispersity.


  This paper presents a multi-view distributed video coding framework for
independent camera encoding and centralized decoding. Spatio-temporal-view
concealment methods are developed that exploit the interleaved nature of the
employed hybrid KEY/Wyner-Ziv frames for block-wise generation of the side
information (SI). We study a number of view concealment methods and develop a
joint approach that exploits all available correlation for forming the side
information. We apply a diversity technique for fusing multiple such
predictions thereby achieving more reliable results. We additionally introduce
systems enhancements for further improving the rate distortion performance
through selective feedback, inter-view bitplane projection and frame
subtraction. Results show a significant improvement in performance relative to
H.264 intra coding of up to 25% reduction in bitrate or equivalently 2.5 dB
increase in PSNR.


  We examine the execution of general U(1) transformations on programmable
quantum processors. We show that, with only the minimal assumption of
availability of copies of the one-qubit program state, that the apparent
advantage of existing schemes proposed by G.Vidal it et al. [Phys. Rev. Lett.
88, 047905 (2002)] and M.Hillery et al. [Phys. Rev. A. 65, 022301 (2003)] to
execute a general U(1) transformation with greater probability using complex
program states appears not to hold.


  Thomas has recently derived scaling laws for X-ray radiation from electrons
accelerated in plasma bubbles, as well as a threshold for the self-injection of
background electrons into the bubble [A. G. R. Thomas, Phys. Plasmas 17, 056708
(2010)]. To obtain this threshold, the equations of motion for a test electron
are studied within the frame of the bubble model, where the bubble is described
by prescribed electromagnetic fields and has a perfectly spherical shape. The
author affirms that any elliptical trajectory of the form x'^2/{\gamma}_p^2 +
y'^2 = R^2 is solution of the equations of motion (in the bubble frame), within
the approximation p'_y^2/p'_x^2 \ll 1. In addition, he highlights that his
result is different from the work of Kostyukov et al. [Phys. Rev. Lett. 103,
175003 (2009)], and explains the error committed by
Kostyukov-Nerush-Pukhov-Seredov (KNPS). In this comment, we show that
numerically integrated trajectories, based on the same equations than the
analytical work of Thomas, lead to a completely different result for the
self-injection threshold, the result published by KNPS [Phys. Rev. Lett. 103,
175003 (2009)]. We explain why the analytical analysis of Thomas fails and we
provide a discussion based on numerical simulations which show exactly where
the difference arises. We also show that the arguments of Thomas concerning the
error of KNPS do not hold, and that their analysis is mathematically correct.
Finally, we emphasize that if the KNPS threshold is found not to be verified in
PIC (Particle In Cell) simulations or experiments, it is due to a deficiency of
the model itself, and not to an error in the mathematical derivation.


  "Propellers" are features in Saturn's A ring associated with moonlets that
open partial gaps. They exhibit non-Keplerian motion (Tiscareno 2010); the
longitude residuals of the best-observed propeller, "Bl\'eriot," appear
consistent with a sinusoid of period ~4 years. Pan and Chiang (2010) proposed
that propeller moonlets librate in "frog resonances" with co-orbiting ring
material. By analogy with the restricted three-body problem, they treated the
co-orbital material as stationary in the rotating frame and neglected
non-co-orbital material. Here we use simple numerical experiments to extend the
frog model, including feedback due to the gap's motion, and drag associated
with the Lindblad disk torques that cause Type I migration. Because the moonlet
creates the gap, we expect the gap centroid to track the moonlet, but only
after a time delay t_diff, the time for a ring particle to travel from
conjunction with the moonlet to the end of the gap. We find that frog
librations can persist only if t_diff exceeds the frog libration period P_lib,
and if damping from Lindblad torques balances driving from co-orbital torques.
If t_diff << P_lib, then the libration amplitude damps to zero. In the case of
Bl\'eriot, the frog resonance model can reproduce the observed libration period
P_lib ~ 4 yr. However, our simple feedback prescription suggests that
Bl\'eriot's t_diff ~ 0.01P_lib, which is inconsistent with the observed
libration amplitude of 260 km. We urge more accurate treatments of feedback to
test the assumptions of our toy models.


  We define Schwartz functions, tempered functions and tempered distributions
on (possibly singular) real algebraic varieties. We prove that all classical
properties of these spaces, defined previously on affine spaces and on Nash
manifolds, also hold in the case of affine real algebraic varieties, and give
partial results for the non-affine case.


  We present an information-theoretic framework to learn fixed-dimensional
embeddings for tasks in reinforcement learning. We leverage the idea that two
tasks are similar if observing an agent's performance on one task reduces our
uncertainty about its performance on the other. This intuition is captured by
our information-theoretic criterion which uses a diverse agent population as an
approximation for the space of agents to measure similarity between tasks in
sequential decision-making settings. In addition to qualitative assessment, we
empirically demonstrate the effectiveness of our techniques based on task
embeddings by quantitative comparisons against strong baselines on two
application scenarios: predicting an agent's performance on a new task by
observing its performance on a small quiz of tasks, and selecting tasks with
desired characteristics from a given set of options.


  We simulate the central reactions of $^{20}$Ne+$^{20}$Ne,
$^{40}$Ar+$^{45}$Sc, $^{58}$Ni+$^{58}$Ni, $^{86}$Kr+$^{93}$Nb,
$^{129}$Xe+$^{118}$Sn, $^{86}$Kr+$^{197}$Au and $^{197}$Au+$^{197}$Au at
different incident energies for different equations of state (EOS), binary
cross sections and different widths of Gaussians. A rise and fall behaviour of
the multiplicity of intermediate mass fragments (IMFs) is observed. The system
size dependence of peak center-of-mass energy E$_{c.m.} ^{max}$ and peak IMF
multiplicity $<$N$_{IMF}>^{max}$ is also studied, where it is observed that
E$_{c.m.}^{max}$ follows a linear behaviour and $<$N$_{IMF}>^{max}$ shows a
power law dependence. A comparison between two clusterization methods, the
minimum spanning tree and the minimum spanning tree method with binding energy
check (MSTB) is also made. We find that MSTB method reduces the
$<$N$_{IMF}>^{max}$ especially in heavy systems. The power law dependence is
also observed for fragments of different sizes at E$_{c.m.} ^{max}$ and power
law parameter $\tau$ is found to be close to unity in all cases except
A$^{max}$.


  This article is a survey of classical and quantum completely integrable
systems from the viewpoint of local ``phase space'' analysis. It advocates the
use of normal forms and shows how to get global information from glueing local
pieces. Many crucial phenomena such as monodromy or eigenvalue concentration
are shown to arise from the presence of non-degenerate critical points.


  We prove that the space of traces $\text{T}(A)$ of the unital full free
product $A=A_1*A_2$ of two unital, separable $C^*$-algebras $A_1$ and $A_2$ is
typically a Poulsen simplex, i.e., a simplex whose extreme points are dense. We
deduce that $\text{T}(A)$ is a Poulsen simplex whenever $A_1$ and $A_2$ have no
$1$-dimensional representations, e.g., if $A_1$ and $A_2$ are finite
dimensional with no $1$-dimensional direct summands. Additionally, we
characterize when the space of traces of a free product of two countable groups
is a Poulsen simplex. Our main technical contribution is a new perturbation
result for pairs of von Neumann subalgebras $(M_1,M_2)$ of a tracial von
Neumann algebra $M$ which gives necessary conditions ensuring that $M_1$ and a
small unitary perturbation of $M_2$ generate a II$_1$ factor.


  We use a modified directed path algorithm to study the finite temperature
chiral singularities of two color lattice QCD with staggered fermions at strong
coupling. Our lattice calculations are done at a fixed finite temperature in
the broken phase with a variety of different quark masses. We find that to the
lowest order, the behavior of our observables, namely the condensates and the
decay constants are all consistent with the predictions of the low energy
effective theory of our model. We further notice that in order to see
consistency, the quark masses used in our lattice calculations need to be quite
small than typically used.


  In this article, we study the De Rham cohomology of the first cover in the
Drinfel'd tower. In particular, we get a purely local proof that the
supercuspidal part realizes the local Jacquet-Langlands correspondence for
${\rm GL}_n$ by comparing it to the rigid cohomology of some Deligne-Lusztig
varieties. The representations obtained are analogous to the ones appearing in
the $\ell$-adic cohomology if we forget the action of the Weil group. The proof
relies on the generalization of an excision result of Grosse-Kl\"onne and on
the explicit description of the first cover as a cyclic cover obtained by the
author on a previous work.


  The general expression with the physical significance and positive definite
condition of the eigenvalues of $4\times 4$ Hermitian and trace-one matrix are
obtained. This implies that the eigenvalue problem of the $4\times 4$ density
matrix is generally solved. The obvious expression of Peres' separability
condition for an arbitrary state of two qubits is then given out and it is very
easy to use. Furthermore, we discuss some applications to the calculation of
the entanglement, the upper bound of the entanglement, and a model of the
transfer of entanglement in a qubit chain through a noisy channel.


  We extend Lerner's recent approach to sparse domination of
Calder\'on--Zygmund operators to upper doubling (but not necessarily doubling),
geometrically doubling metric measure spaces. Our domination theorem is
different from the one obtained recently by Conde-Alonso and Parcet and yields
a weighted estimate with the sharp power $\max(1,1/(p-1))$ of the $A_p$
characteristic of the weight.


  From detailed spectral analysis of a large sample of low-redshift active
galactic nuclei (AGNs) selected from the Sloan Digital Sky Survey, we
demonstrate---statistically for the first time---that narrow optical Fe II
emission lines, both permitted and forbidden, are prevalent in type 1 AGNs.
Remarkably, these optical lines are completely absent in type 2 AGNs, across a
wide luminosity range, from Seyfert 2 galaxies to type 2 quasars. We suggest
that the narrow FeII-emitting gas is confined to a disk-like geometry in the
innermost regions of the narrow-line region on physical scales smaller than the
obscuring torus.


  Hyperon-nucleons interactions constructed by two frameworks, the
Kyoto-Niigata SU$_6$ quark model and the chiral effective field theory, are
compared by investigating equivalent interactions in a low-momentum space and
in addition by calculating hyperon single-particle potentials in the
lowest-order Brueckner theory in symmetric nuclear matter. Two descriptions are
shown to give similar matrix elements in most channels after renormalizing high
momentum components. Although the range of the $\Lambda N$ interaction is
different in two potentials, the $\Lambda$ single-particle potential in nuclear
matter is very similar. The $\Sigma$-nucleus and $\Xi$-nucleus potentials are
also found to be similar. These predictions are to be confronted with
forthcoming experimental data.


  We explore non-classical correlations in n-cycle setting. In particular, we
focus on correlations manifested by Kochen-Specker-Klyachko box (KS box),
scenarios involving n-cycle non-contextuality inequalities and Popescu-Rohlrich
boxes (PR box). We provide the criteria for optimal classical simulation of a
KS box of arbitrary n dimension. The non-contextuality inequalities are
analysed for n-cycle setting, and the condition for the quantum violation for
odd as well as even n-cycle is discussed. We offer a simple extension of even
cycle non-contextuality inequalities to the continuous variable case.
Furthermore, we simulate a generalized PR box using KS box and provide some
interesting insights. Towards the end, we discuss a few possible interesting
open problems for future research.


  In these latest years, the detection of Wolf-Rayet (WR) stars in Giant HII
Regions (GHRs) has yielded several questions about our current understanding of
massive stars evolution and hot expanding atmospheres, the age of the ionizing
populations and their impact onto the physical properties of GHRs. Here, we
present spectrophotometric observations of 4 extragalactic GHRs which show WR
features in their spectra. Our goal is to reproduce simultaneously the observed
WR properties and the emission line spectra with the help of current
evolutionary synthesis models. Finally, we address the main advantages that GTC
will provide to our better understanding of massive star forming regions.


  The intrinsic volumes of a convex body are fundamental invariants that
capture information about the average volume of the projection of the convex
body onto a random subspace of fixed dimension. The intrinsic volumes also play
a central role in integral geometry formulas that describe how moving convex
bodies interact. Recent work has demonstrated that the sequence of intrinsic
volumes concentrates sharply around its centroid, which is called the central
intrinsic volume. The purpose of this paper is to derive finer concentration
inequalities for the intrinsic volumes and related sequences. These
concentration results have striking implications for high-dimensional integral
geometry. In particular, they uncover new phase transitions in formulas for
random projections, rotation means, random slicing, and the kinematic formula.
In each case, the location of the phase transition is determined by reducing
each convex body to a single summary parameter.


  We consider the general problem of utilizing both labeled and unlabeled data
to improve data representation performance. A new semi-supervised learning
framework is proposed by combing manifold regularization and data
representation methods such as Non negative matrix factorization and sparse
coding. We adopt unsupervised data representation methods as the learning
machines because they do not depend on the labeled data, which can improve
machine's generation ability as much as possible. The proposed framework forms
the Laplacian regularizer through learning the affinity graph. We incorporate
the new Laplacian regularizer into the unsupervised data representation to
smooth the low dimensional representation of data and make use of label
information. Experimental results on several real benchmark datasets indicate
that our semi-supervised learning framework achieves encouraging results
compared with state-of-art methods.


  Prominences, or filaments, are a striking phenomenon in the solar atmosphere.
Besides their own rich features and dynamics, they are related to many other
activities, such as solar flares and coronal mass ejections (CMEs). In the past
several years we have been investigating the prominence formation,
oscillations, and eruptions through both data analysis and radiative
hydrodynamic and magnetohydrodynamic (MHD) simulations. This paper reviews our
progress on these topics, which includes: (1) With updated radiative cooling
function, the coronal condensation becomes a little faster than previous work;
(2) Once a seed condensation is formed, it can grow via siphon flow
spontaneously even if the evaporation stops; (3) A scaling law was obtained to
relate the length of the prominence thread to various parameters, indicating
that higher prominences tend to have shorter threads, which is consistent with
the fact that threads are long in active region prominences and short in
quiescent prominences; (4) It was proposed that long-time prominence
oscillations out of phase might serve as a precursor for prominence eruptions
and CMEs; (5) An ensemble of oscillating prominence threads may explain the
counter-streaming motion.


  We study the response of a semi-bounded one-component fully degenerate
electron plasma to an initial perturbation in the electrostatic limit. We show
that the part of the electric potential corresponding to surface waves in such
plasma can be represented, at large times, as the sum of two terms, one term
corresponding to "conventional" (Langmuir) surface waves and the other term
representing a new type of surface waves resulting from specific analytic
properties of degenerate plasma's dielectric response function. These two terms
are characterized by different oscillation frequencies (for a given wave
number), and, while the "conventional" term's amplitude decays exponentially
with time, the new term is characterized by a slower, power-law decay of the
oscillation amplitude and is therefore dominant at large times.


  According to recent reports, the last loopholes in testing Bell's inequality
are closed. It is argued that the really important task in this field has not
been tackled yet and that the leading experiments claiming to close locality
and detection efficiency loopholes, although making a very significant
progress, have conceptual drawbacks. The important task is constructing quantum
devices which will allow winning games of certain correlated replies against
any classical team. A novel game of this type is proposed.


  The Schroedinger functional treatment of 2+1 D Yang-Mills theory is
recapitulated, in great calculational detail, by following three papers of
Karabali, Kim and Nair in 1998/99. The notes include the Hermitean WZW model,
regularization, the functional Hamiltonian, the string tension and the magnetic
mass problem of 4D hot gluons.


  We show the emergence of fractional quantum Hall states in dry-transferred
chemical vapor deposition (CVD) derived graphene assembled into
heterostructures for magnetic fields from below 3 T to 35 T. Effective
composite-fermion filling factors up to $\nu^* = 4$ are visible and higher
order composite-fermion states (with four flux quanta attached) start to emerge
at the highest fields. Our results show that the quantum mobility of CVD-grown
graphene is comparable to that of exfoliated graphene and, more specifically,
that the $p/3$ fractional quantum Hall states have energy gaps of up to 30 K,
well comparable to those observed in other silicon-gated devices based on
exfoliated graphene.


  Semantic communications can reduce the resource consumption by transmitting
task-related semantic information extracted from source messages. However, when
the source messages are utilized for various tasks, e.g., wireless sensing data
for localization and activities detection, semantic communication technique is
difficult to be implemented because of the increased processing complexity. In
this paper, we propose the inverse semantic communications as a new paradigm.
Instead of extracting semantic information from messages, we aim to encode the
task-related source messages into a hyper-source message for data transmission
or storage. Following this paradigm, we design an inverse semantic-aware
wireless sensing framework with three algorithms for data sampling,
reconfigurable intelligent surface (RIS)-aided encoding, and self-supervised
decoding, respectively. Specifically, on the one hand, we propose a novel RIS
hardware design for encoding several signal spectrums into one MetaSpectrum. To
select the task-related signal spectrums for achieving efficient encoding, a
semantic hash sampling method is introduced. On the other hand, we propose a
self-supervised learning method for decoding the MetaSpectrums to obtain the
original signal spectrums. Using the sensing data collected from real-world, we
show that our framework can reduce the data volume by 95% compared to that
before encoding, without affecting the accomplishment of sensing tasks.
Moreover, compared with the typically used uniform sampling scheme, the
proposed semantic hash sampling scheme can achieve 67% lower mean squared error
in recovering the sensing parameters. In addition, experiment results
demonstrate that the amplitude response matrix of the RIS enables the
encryption of the sensing data.


  We present a novel approach for measuring the two-point correlation function
of galaxies in narrow pencil beam surveys with varying depths. Our methodology
is utilized to expand high-redshift galaxy clustering investigations up to $z
\sim 8$ by analyzing a comprehensive sample consisting of $N_g = 160$ Lyman
break galaxy candidates obtained through optical and near-infrared photometric
data within the CANDELS GOODS datasets from the Hubble Space Telescope Legacy
Fields. For bright sources with $M_{UV} < -19.8$, we determine a galaxy bias of
$b = 9.33\pm4.90$ at $\overline{z} = 7.7$ and a correlation length of $r_0 =
10.74\pm7.06$ $h^{-1}Mpc$. We obtain similar results for the XDF, with a galaxy
bias measurement of $b = 8.26\pm3.41$ at the same redshift for a slightly
fainter sample with a median luminosity of $M_{UV} = -18.4$. By comparing with
dark-matter halo bias and employing abundance matching, we deduce a
characteristic halo mass of $M_h \sim 10^{11.5} M_{\odot}$ and a duty cycle
close to unity. To validate our approach for variable-depth datasets, we
replicate the analysis in a region with near-uniform depth using a standard
two-point correlation function estimator, yielding consistent outcomes. Our
study not only provides a valuable tool for future utilization in JWST datasets
but also suggests that the clustering of early galaxies continues to increase
with redshift beyond $z \gtrsim 8$, potentially contributing to the existence
of protocluster structures observed in early JWST imaging and spectroscopic
surveys at $z \gtrsim 8$.


  The combination of complex networks and dynamic systems research is poised to
yield some of the most interesting theoretic and applied scientific results
along the forthcoming decades. The present work addresses a particularly
important related aspect, namely the quantification of how well separated can
the attractors be in dynamic systems underlined by four types of complex
networks (Erd\H{o}s-R\'enyi, Barab\'asi-Albert, Watts-Strogatz and as well as a
geographic model). Attention is focused on grandmother dynamic systems, where
each state variable (associated to each node) is used to represent a specific
prototype pattern (attractor). By assuming that the attractors spread their
influence among its neighboring nodes through a diffusive process, it is
possible to overlook the specific details of specific dynamics and focus
attention on the separability among such attractors. This property is defined
in terms of two separation indices (one individual to each prototype and the
other considering also the immediate neighborhood) reflecting the balance and
proximity to attractors revealed by the activation of the network after a
diffusive process. The separation index considering also the neighborhood was
found to be much more informative, while the best separability was observed for
the Watts-Strogatz and the geographic models. The effects of the involved
parameters on the separability were investigated by correlation and path
analyses. The obtained results suggest the special importance of some
measurements in underlying the relationship between topology and dynamics.


  In this work, we extend the model of contact angles that we have previously
developed for sessile drops on a wetted surface to the case of a meniscus in a
capillary. The underlying physics of our model describe the intermolecular
forces between the fluid and the surface of the capillary that result in the
formation of a thin, non-removable fluid layer that coats the capillary wall.
We describe the shape of the meniscus using a Young-Laplace equation and an
incompressible, two-phase, CFD calculation, both modified to take into account
intermolecular forces using the disjoining pressure model. We find that our
numerical solutions of the Young-Laplace equation and equilibrium meniscus
shapes obtained by CFD agree well with each other. Furthermore, for capillaries
that are sufficiently larger than the thickness of the non-removable film, our
numerical solutions agree well with the effective contact angle model that we
previously developed for sessile drops. Finally, we observe that it is possible
to tune the disjoining pressure model parameters so that the intermolecular
forces between the liquid and solid molecules becomes so strong compared to the
surface tension that our formula for effective contact angle gives an imaginary
solution. We analyze this situation using CFD and find that it corresponds to
dewetting, where the bulk liquid detaches from the walls of the capillary
leaving behind the non-removable thin liquid film.


  Reinforcement learning is commonly associated with training of
reward-maximizing (or cost-minimizing) agents, in other words, controllers. It
can be applied in model-free or model-based fashion, using a priori or online
collected system data to train involved parametric architectures. In general,
online reinforcement learning does not guarantee closed loop stability unless
special measures are taken, for instance, through learning constraints or
tailored training rules. Particularly promising are hybrids of reinforcement
learning with "classical" control approaches. In this work, we suggest a method
to guarantee practical stability of the system-controller closed loop in a
purely online learning setting, i.e., without offline training. Moreover, we
assume only partial knowledge of the system model. To achieve the claimed
results, we employ techniques of classical adaptive control. The implementation
of the overall control scheme is provided explicitly in a digital, sampled
setting. That is, the controller receives the state of the system and computes
the control action at discrete, specifically, equidistant moments in time. The
method is tested in adaptive traction control and cruise control where it
proved to significantly reduce the cost.


  Quantum State Tomography is the task of determining an unknown quantum state
by making measurements on identical copies of the state. Current algorithms are
costly both on the experimental front -- requiring vast numbers of measurements
-- as well as in terms of the computational time to analyze those measurements.
In this paper, we address the problem of analysis speed and flexibility,
introducing \textit{Neural Adaptive Quantum State Tomography} (NA-QST), a
machine learning based algorithm for quantum state tomography that adapts
measurements and provides orders of magnitude faster processing while retaining
state-of-the-art reconstruction accuracy. Our algorithm is inspired by particle
swarm optimization and Bayesian particle-filter based adaptive methods, which
we extend and enhance using neural networks. The resampling step, in which a
bank of candidate solutions -- particles -- is refined, is in our case learned
directly from data, removing the computational bottleneck of standard methods.
We successfully replace the Bayesian calculation that requires computational
time of $O(\mathrm{poly}(n))$ with a learned heuristic whose time complexity
empirically scales as $O(\log(n))$ with the number of copies measured $n$,
while retaining the same reconstruction accuracy. This corresponds to a factor
of a million speedup for $10^7$ copies measured. We demonstrate that our
algorithm learns to work with basis, symmetric informationally complete (SIC),
as well as other types of POVMs. We discuss the value of measurement adaptivity
for each POVM type, demonstrating that its effect is significant only for basis
POVMs. Our algorithm can be retrained within hours on a single laptop for a
two-qubit situation, which suggests a feasible time-cost when extended to
larger systems. It can also adapt to a subset of possible states, a choice of
the type of measurement, and other experimental details.


  Based on the concept of curved spacetime in Einsteinian General Relativity,
the field theories and their quantum theories in the curved octonion spaces etc
are discussed. The research results discover the close relationships of the
curved spacetimes with the field theories and quantum theories. In the field
theories of curved spacetimes, the curvatures have direct effect on field
strength and field source etc. While the curvatures have direct impact on wave
functions and quantum equations etc in the quantum theories of curved
spacetimes. The research results discover that some abnormal phenomena of field
source particles could be explained by the field theories or quantum theories
in the curved spacetimes.


  Tracker detectors can be used to identify charged particles based on their
global chi value obtained during track fitting with the Kalman filter. This
approach builds upon the knowledge of detector material and local position
resolution, using the known physics of multiple scattering and energy loss. The
proposed method is independent of the traditional way of identification using
deposited energy. The performance for present LHC experiments is demonstrated.


  We calculate the rates for lepton number violating processes via the exchange
of the Z' boson occuring in top-color assisted technicolor. The current
experimental limits on muon electron conversion in Ti nuclei allow for a mass
of the new gauge boson around 1 TeV and the magnitudes of the mixing angles
turn out to lie roughly between the analogous elements of the CKM matrix and
its square root.


  An accurate and efficient epileptic seizure onset detection can significantly
benefit patients. Traditional diagnostic methods, primarily relying on
electroencephalograms (EEGs), often result in cumbersome and non-portable
solutions, making continuous patient monitoring challenging. The video-based
seizure detection system is expected to free patients from the constraints of
scalp or implanted EEG devices and enable remote monitoring in residential
settings. Previous video-based methods neither enable all-day monitoring nor
provide short detection latency due to insufficient resources and ineffective
patient action recognition techniques. Additionally, skeleton-based action
recognition approaches remain limitations in identifying subtle seizure-related
actions. To address these challenges, we propose a novel Video-based Seizure
detection model via a skeleton-based spatiotemporal Vision Graph neural network
(VSViG) for its efficient, accurate and timely purpose in real-time scenarios.
Our experimental results indicate VSViG outperforms previous state-of-the-art
action recognition models on our collected patients' video data with higher
accuracy (5.9% error), lower FLOPs (0.4G), and smaller model size (1.4M).
Furthermore, by integrating a decision-making rule that combines output
probabilities and an accumulative function, we achieve a 5.1 s detection
latency after EEG onset, a 13.1 s detection advance before clinical onset, and
a zero false detection rate. The project homepage is available at:
https://github.com/xuyankun/VSViG/


  We are concerned with the existence of ground states for nonlinear Choquard
equations involving a critical nonlinearity in the sense of
Hardy-Littlewood-Sobolev. Our result complements previous results by Moroz and
Van Schaftingen where the subcritical case was considered. Then, we focus on
the existence of semi-classical states and by using a truncation argument
approach, we establish the existence and concentration of single peak solutions
concentrating around minima of the Schr\"odinger potential, as the Planck
constant goes to zero. The result is robust in the sense that the nonlinearity
is not required to satisfy monotonicity conditions nor the
Ambrosetti-Rabinowitz condition.