  This chapter explores the cognitive mechanisms underlying the emergence and
evolution of cultural novelty. Section Two summarizes the rationale for viewing
the process by which the fruits of the mind take shape as they spread from one
individual to another as a form of evolution, and briefly discusses a computer
model of this process. Section Three presents theoretical and empirical
evidence that the sudden proliferation of human culture approximately two
million years ago began with the capacity for creativity: that is, the ability
to generate novelty strategically and contextually. The next two sections take
a closer look at the creative process. Section Four examines the mechanisms
underlying the fluid, associative thought that constitutes the inspirational
component of creativity. Section Five explores how that initial flicker of
inspiration crystallizes into a solid, workable idea as it gets mulled over in
light of the various constraints and affordances of the world into which it
will be born. Finally, Section Six wraps things up with a few speculative
thoughts about the overall unfolding of this evolutionary process.


  A lot of work has been done to reach the best possible performance of
predictive models on images. There are fewer studies about the resilience of
these models when they are trained on image datasets that suffer modifications
altering their original quality. Yet this is a common problem that is often
encountered in the industry. A good example of that is with earth observation
satellites that are capturing many images. The energy and time of connection to
the earth of an orbiting satellite are limited and must be carefully used. An
approach to mitigate that is to compress the images on board before
downloading. The compression can be regulated depending on the intended usage
of the image and the requirements of this application. We present a new
software tool with the name iquaflow that is designed to study image quality
and model performance variation given an alteration of the image dataset.
Furthermore, we do a showcase study about oriented object detection models
adoption on a public image dataset DOTA Xia_2018_CVPR given different
compression levels. The optimal compression point is found and the usefulness
of iquaflow becomes evident.


  We propose a topological order parameter for interacting topological
insulators, expressed in terms of the full Green's functions of the interacting
system. We show that it is exactly quantized for a time reversal invariant
topological insulator, and it can be experimentally measured through the
topological magneto-electric effect. This topological order parameter can be
applied to both interacting and disordered systems, and used for determining
their phase diagrams.


  We establish the $L^p$ restriction estimates for quasimodes on a smooth curve
in two dimensions. Our estimates are sharp for all smooth curves. As an
application, we address $L^p$ eigenfunction restriction estimates for
Laplace-Beltrami eigenfunctions on $2$-dimensional compact Riemannian manifolds
without boundary and Hermite functions on $\mathbb R^2$. Our method involves a
geometric analysis of the contact order between the curve and the
bicharacteristic flow of the semiclassical pseudodifferential operator.


  We demonstrate that the synergistic effect of a gauge field, Rashba
spin-orbit coupling (SOC), and Zeeman splitting can generate chaotic cyclotron
and Hall trajectories of particles. The physical origin of the chaotic behavior
is that the SOC produces a spin-dependent (so-called anomalous) contribution to
the particle velocity and the presence of Zeeman field reduces the number of
integrals of motion. By using analytical and numerical arguments, we study the
conditions of chaos emergence and report the dynamics both in the regular and
chaotic regimes. {We observe the critical dependence of the dynamic patterns
(such as the chaotic regime onset) on small variations in the initial
conditions and problem parameters, that is the SOC and/or Zeeman constants. The
transition to chaotic regime is further verified by the analysis of phase
portraits as well as Lyapunov exponents spectrum.} The considered chaotic
behavior can occur in solid state systems, weakly-relativistic plasmas, and
cold atomic gases with synthetic gauge fields and spin-related couplings.


  I give a review of the conceptual issues that arise in theories of quantum
cosmology. I start by emphasising some features of ordinary quantum theory that
also play a crucial role in understanding quantum cosmology. I then give
motivations why spacetime cannot be treated classically at the most fundamental
level. Two important issues in quantum cosmology -- the problem of time and the
role of boundary conditions -- are discussed at some length. Finally, I discuss
how classical spacetime can be recovered as an approximate notion. This
involves the application of a semiclassical approximation and the process of
decoherence. The latter is applied to both global degrees of freedom and
primordial fluctuations in an inflationary Universe.


  We obtain an elementary characterization of expected utility based on a
representation of choice in terms of psychological gambles, which requires no
assumption other than coherence between ex-ante and ex-post preferences. Weaker
version of coherence are associated with various attitudes towards complexity
and lead to a characterization of minimax or Choquet expected utility.


  Stochastic partial differential equations (SPDEs) have become a crucial
ingredient in a number of models from economics and the natural sciences. Many
SPDEs that appear in such applications include non-globally monotone
nonlinearities. Solutions of SPDEs with non-globally monotone nonlinearities
are in nearly all cases not known explicitly. Such SPDEs can thus only be
solved approximatively and it is an important research problem to construct and
analyze discrete numerical approximation schemes which converge with positive
strong convergence rates to the solutions of such infinite dimensional SPDEs.
In the case of finite dimensional stochastic ordinary differential equations
(SODEs) with non-globally monotone nonlinearities it has recently been revealed
that exponential integrability properties of the discrete numerical
approximation scheme are a key instrument to establish positive strong
convergence rates for the considered approximation scheme. To the best of our
knowledge, there exists no result in the scientific literature which proves
exponential integrability properties for a time discrete approximation scheme
in the case of an infinite dimensional SPDE. In this paper we propose a new
class of tamed space-time-noise discrete exponential Euler approximation
schemes that admit exponential integrability properties in the case of infinite
dimensional SPDEs. In particular, we establish exponential moment bounds for
the proposed approximation schemes in the case of stochastic Burgers equations,
stochastic Kuramoto-Sivashinsky equations, and two-dimensional stochastic
Navier-Stokes equations.


  Online discussion forum creates an asynchronous conversation environment for
online users to exchange ideas and share opinions through a unique thread-reply
communication mode. Accurately modeling information dynamics under such a mode
is important, as it provides a means of mining latent spread patterns and
understanding user behaviors. In this paper, we design a novel temporal point
process model to characterize information cascades in online discussion forums.
The proposed model views the entire event space as a nested structure composed
of main thread streams and their linked reply streams, and it explicitly models
the correlations between these two types of streams through their intensity
functions. Leveraging the Reddit data, we examine the performance of the
designed model in different applications and compare it with other popular
methods. The experimental results have shown that our model can produce
competitive results, and it outperforms state-of-the-art methods in most cases.


  We study the equilibrium of hyperelastic solids subjected to kinematic
constraints on many small regions, which we call perforations.
  Such constraints on the displacement $u$ are given in the quite general form
$u(x) \in F_x$, where $F_x$ is a closed set, and thus comprise confinement
conditions, unilateral constraints, controlled displacement conditions, etc.,
both in the bulk and on the boundary of the body. The regions in which such
conditions are active are assumed to be so small that they do not produce an
overall rigid constraint, but still large enough so as to produce a non-trivial
effect on the behaviour of the body. Mathematically, this is translated in an
asymptotic analysis by introducing two small parameters: $\varepsilon$,
describing the distance between the elements of the perforation, and $\delta$,
the size of the element of the perforation. We find the critical scale at which
the effect of the perforation is non-trivial and express it in terms of a
$\Gamma$-limit in which the constraints are relaxed so that, in their place, a
penalization term appears in the form of an integral of a function
$\varphi(x,u)$. This function is determined by a blow-up procedure close to the
perforation and depends on the shape of the perforation, the constraint $F_x$,
and the asymptotic behaviour at infinity of the strain energy density $\sigma$.
We give a concise proof of the mathematical result and numerical studies for
some simple yet meaningful geometries.


  This paper proposes the problem of point-and-count as a test case to break
the what-and-where deadlock. Different from the traditional detection problem,
the goal is to discover key salient points as a way to localize and count the
number of objects simultaneously. We propose two alternatives, one that counts
first and then point, and another that works the other way around.
Fundamentally, they pivot around whether we solve "what" or "where" first. We
evaluate their performance on dataset that contains multiple instances of the
same class, demonstrating the potentials and their synergies. The experiences
derive a few important insights that explains why this is a much harder problem
than classification, including strong data bias and the inability to deal with
object scales robustly in state-of-art convolutional neural networks.


  An SO(10) SUSY GUT model was previously presented based on a minimal set of
Higgs fields. The quark and lepton mass matrices derived fitted the data
extremely well and led to large mixing of muon- and tau-neutrinos in agreement
with the atmospheric neutrino data and to the small-angle MSW solution for the
solar neutrinos. Here we show how a slight modification leading to a non-zero
up quark mass can result in bimaximal mixing for the atmospheric and solar
neutrinos. The "just-so" vacuum solution is slightly favored over the
large-angle MSW solution on the basis of the hierarchy required for the
right-handed Majorana matrix and the more nearly-maximal mixing angles
obtained.


  We investigate the expansion dynamics of spin-orbit-coupled Bose-Einstein
condensates subjected to a synthetic magnetic field, after their release from
an external harmonic trap. Our findings reveal that the condensate experiences
a spin-dependent rotation and separation due to the rigid-like rotational
velocity field, which leads to a spin density deflection. The deflection angle
reaches a peak at a time that is inversely related to the frequency of the
harmonic trap. When the detuning gradient is below a critical value for vortex
nucleation, our analytical results derived from a spinor hydrodynamic theory
align closely with numerical results using the coupled Gross-Pitaevskii
equations. Beyond this critical value, we also numerically simulated the
expansion dynamics of the condensates containing vortices with negative
circulation. Our findings highlight the pivotal role of the rigid-like
rotational velocity field on the dynamics of the condensate and may stimulate
further experimental investigations into the rich superfluid dynamics induced
by synthetic magnetic fields.


  This paper presents a study of the effects of proton irradiation on iron
corrosion. Since it is known that in humid atmospheres, iron corrosion is
enhanced by the double influence of air and humidity, we studied the iron
corrosion under irradiation with a 45% relative humidity. Three proton beam
intensities (5, 10 and 20 nA) were used. To characterise the corrosion layer,
we used ion beam methods (Rutherford Backscattering Spectrometry (RBS), Elastic
Recoil Detection Analysis (ERDA)) and X-ray Diffraction (XRD) analysis. The
corrosion kinetics are plotted for each proton flux. A diffusion model of the
oxidant species is proposed, taking into account the fact that the flux through
the surface is dependent on the kinetic factor K. This model provides evidence
for the dependence of the diffusion coefficient, D, and the kinetic factor, K,
on the proton beam intensity. Comparison of the values for D with the diffusion
coefficients for thermal oxygen diffusion in iron at 300 K suggests an
enhancement due to irradiation of 6 orders of magnitude.


  We present here the results of an X-ray study of the supernova remnant 3C
400.2 (G53.6-2.2) using the ASCA data. 3C 400.2 has an unusual morphology at
radio wavelengths, suggesting two SNRs superposed along the same line of sight,
whereas its X-ray emission is known to be centrally peaked. We investigated the
X-ray spectral variation across the remnant using the ASCA GIS and the ROSAT
PSPC data. The X-ray spectra can be well fitted by thin thermal plasma models.
However, there is no significant variation in the temperature and the
ionization parameter across the remnant. We conclude that it is a single SNR
rather than two overlapping SNRs. The centrally peaked X-ray morphology and the
thin thermal emission with nearly cosmic abundances indicate that 3C 400.2
belongs to a class of ``mixed-morphology SNRs''. We found that the physical
parameters of 3C 400.2 are similar to those of other mixed-morphology SNRs. The
morphology of 3C 400.2 can be explained by a supernova explosion occurring near
to the edge of an interstellar cloud.


  Analysis of an exactly soluble model of phonons coupled to a carrier in a
quantum dot provides a clear illustration of a phonon bottleneck to relaxation.
The introduction of three-phonon interactions leads to a broad window for
relaxation by the processes of LO phonon scattering and decay.


  This paper presents the first algorithm for model-based offline quantum
reinforcement learning and demonstrates its functionality on the cart-pole
benchmark. The model and the policy to be optimized are each implemented as
variational quantum circuits. The model is trained by gradient descent to fit a
pre-recorded data set. The policy is optimized with a gradient-free
optimization scheme using the return estimate given by the model as the fitness
function. This model-based approach allows, in principle, full realization on a
quantum computer during the optimization phase and gives hope that a quantum
advantage can be achieved as soon as sufficiently powerful quantum computers
are available.


  We study a deformation of a $2$-graded Poisson algebra where the functions of
the phase space variables are complemented by linear functions of parity odd
velocities. The deformation is carried by a $2$-form $B$-field and a bivector
$\Pi$, that we consider as gauge fields of the geometric and non-geometric
fluxes $H$, $f$, $Q$ and $R$ arising in the context of string theory
compactification. The technique used to deform the Poisson brackets is widely
known for the point particle interacting with a $U(1)$ gauge field, but not in
the case of non-abelian or higher spin fields. The construction is closely
related to Generalized Geometry: With an element of the algebra that squares to
zero, the graded symplectic picture is equivalent to an exact Courant algebroid
over the generalized tangent bundle $E \cong TM \oplus T^{*}M$, and to its
higher gauge theory. A particular idempotent graded canonical transformation is
equivalent to the generalized metric. Focusing on the generalized differential
geometry side we construct an action functional with the Ricci tensor of a
connection on covectors, encoding the dynamics of a gravitational theory for a
contravariant metric tensor and $Q$ and $R$ fluxes. We also extract a
connection on vector fields and determine a non-symmetric metric gravity theory
involving a metric and $H$-flux.


  The Airy integral is a well-known contour integral solution of Airy's
equation which has several applications and which has been used for
mathematical illustrations due to its interesting properties. We present and
derive properties of two families of contour integral solutions of linear
differential equations, where one family includes the Airy integral and Airy's
equation, such that the family generalizes known properties of the Airy
integral which include exponential decay growth in a certain sector. The second
family includes a known example and contains a subfamily with interesting
properties where a separate analysis of three pairwise linearly independent
contour integral solutions of a particular equation is given.


  In extreme value statistics for stationary sequences, blocks estimators are
usually constructed by using disjoint blocks because exceedances over high
thresholds of different blocks can be assumed asymptotically independent. In
this paper we focus on the estimation of the extremal index which measures the
degree of clustering of extremes. We consider disjoint and sliding blocks
estimators and compare their asymptotic properties. In particular we show that
the sliding blocks estimator is more efficient than the disjoint version and
has a smaller asymptotic bias. Moreover we propose a method to reduce its bias
when considering sufficiently large block sizes.


  In some recent studies \cite{aman1, aman2, aman3}, Aman {\it et al.} used the
Ruppeiner scalar as a measure of underlying interactions of
Reissner-Nordstr\"{o}m black holes, indicating that it is a non-interacting
statistical system for which classical thermodynamics could be used at any
scale. Here, we show that if we use the complete set of thermodynamic
variables, a non-flat state space will be produced. Furthermore, the Ruppeiner
curvature diverges at extremal limits, as it would for other types of black
holes.


  Much recent work on planet formation has focused on the growth of planets by
accretion of grains whose aerodynamic properties make them marginally coupled
to the nebular gas, a theory commonly referred to as "pebble accretion". While
pebble accretion can ameliorate some of the issues presented by growth by
purely gravitational processes, it has other issues when compared with
observations of exoplanetary systems. A particular concern is the preponderance
of planets that end their growth as "super-Earths" or "sub-Neptunes", with
masses in the range 2-10 $M_\oplus$. Once planets reach this mass scale,
timescales for growth by pebble accretion are so rapid that ubiquitously ending
growth here is difficult. In this work, we highlight this issue in detail using
our previously published model of pebble accretion, and also propose a possible
solution: feedback between the growing planet's atmosphere and the gas disk
inhibits accretion of smaller particle sizes by forcing them to flow around the
growing planet instead of being accreted. For reasonable fiducial disk
parameters this "flow isolation" will inhibit accretion of all available
particle sizes once the planet reaches super-Earth masses. We also demonstrate
that the characteristics of this "flow isolation mass" agree with previously
published trends identified in the \textit{Kepler} planets.


  The Semiotic Interpretation (SI) of QM pushes further the Von Neumann point
of view that `experience only makes statements of this type: an observer has
made a certain observation; and never any like this: a physical quantity has a
certain value.' The supposition that the observables of a system `possess'
objective values is purely idealistic. According to the SI view, the state-
vector collapse cannot result from the Schroedinger evolution of a system (even
with its environment), but only from the empirical production of a mathematical
symbol, irreducible to the quantum level. The production of a symbol always
takes some time. Thus the state-vector collapse cannot be instantaneous
(Schneider 1994), a specific prediction of the present model.
  From this interpretation of Quantum Mechanics, the appearances of the body
are the result of state-vector collapses of several types, i.e. the production
of different kinds of symbols. In fact the universe of symbols is very rich: a
symbol can have a conceptual `value' (like in physics and then give rise to a
measurement), or other qualitative values (like in many human behaviors). In
the latter case, the Semiotic Interpretation of QM gives a way to understand
how a mental representation can modify the state of the body.


  Adversarial training (AT) is one of the most effective strategies for
promoting model robustness. However, recent benchmarks show that most of the
proposed improvements on AT are less effective than simply early stopping the
training procedure. This counter-intuitive fact motivates us to investigate the
implementation details of tens of AT methods. Surprisingly, we find that the
basic settings (e.g., weight decay, training schedule, etc.) used in these
methods are highly inconsistent. In this work, we provide comprehensive
evaluations on CIFAR-10, focusing on the effects of mostly overlooked training
tricks and hyperparameters for adversarially trained models. Our empirical
observations suggest that adversarial robustness is much more sensitive to some
basic training settings than we thought. For example, a slightly different
value of weight decay can reduce the model robust accuracy by more than 7%,
which is probable to override the potential promotion induced by the proposed
methods. We conclude a baseline training setting and re-implement previous
defenses to achieve new state-of-the-art results. These facts also appeal to
more concerns on the overlooked confounders when benchmarking defenses.


  There is no conclusive theoretical argument that would require the
quantization of the gravitational field. A paradox presented by Mari et al.
[Sci. Rep. 6, 22777 (2016)] and its resolution by Belenchia et al. [Phys. Rev.
D 98, 126009 (2018)] did not change anything about this assertion. Despite
being interesting in other respects, efforts of a recent work by Ryding,
Aurell, and Pikovski [arXiv:2107.07514] to further establish the
inconclusiveness of the question of necessity of quantization are futile.


  The renormalized quasiparticle-RPA is reformulated for even-even nuclei using
restrictions imposed by the commutativity of the phonon creation operator with
the total particle number operator. This new version, Fully-Renormalized QRPA
(FR-QRPA), is free from the spurious low-energy solutions. Analytical proof is
given that the Ikeda sum rule is fullfiled within the FR-QRPA.


  We calculate the O($\eps$)--term of the two--loop massive operator matrix
elements for twist 2--operators, which contribute to the heavy flavour Wilson
coefficients in unpolarized deep--inelastic scattering in the asymptotic limit
$Q^2 \gg m^2.$ Our calculation was performed in Mellin space using
Mellin--Barnes integrals and generalized hypergeometric functions. The
O($\eps$)--term contributes in the renormalization at 3--loop order.


  The aim of this paper is to numerically study the performance of a method of
regularization. This technique was developed to solve the illposed problem of
estimating a source-dimensional Poisson equation for two dimensions from
measurements taken over a line inside the domain. The proposed method consists
in adding a regularization term to the equation that depends on a parameter,
which is called regularization parameter. In this paper we show the results for
different values of this parameter as well as for different levels of noise in
the data used for estimation. After analyzing the results some considerations
on its effective implementation are discussed.


  The role of competition and monetary benefits in the design of Content
Delivery Networks (CDNs) is largely an unexplored area. In this paper, we
investigate the effect of competition among the competitive web based CDNs and
show that little difference in their performance may cause significant
financial gain/loss. It turns out that the economy of scale effect is very
significant for the success of a CDN in a competitive market. So CDN peering
might be a good idea. Since performance and conforming to the service level
agreement (SLA) with content providers is very important, we then focus on
designing CDN from this perspective. We provide an asymptotically optimal
static request routing policy for a CDN under a model where a CDN company
guarantees a certain level of user latency to the content providers in the SLA.


  Java Enterprise Edition (JEE) applications are implemented in terms of a set
of components developed based on several JEE technologies includ- ing, but not
limited to, Servlet, JSP, JSF, EJB, JavaBeans. These JEE technologies rely on a
varied set of communication mechanisms to commu- nicate between each others.
Examples of these communication mechanisms are HTTP requests, Remote Method
Invocation (RMI), Java DateBase Connectivity (JDBC), etc. These communication
mechanisms represent program dependencies between JEE components. However, one
communi- cation mechanism can be implemented following different implementation
ways by different JEE technologies. Therefore, to be able to detect related
dependencies, we identify these implementation ways used by a set of JEE
technologies. In this technical report, we focus on the Web tier technologies
that are Servlets, JSPs and JSFs. Also, we present how these technologies
access the JavaBeans and Manage Beans components.


  Large language models (LLMs) with powerful generalization ability has been
widely used in many domains. A systematic and reliable evaluation of LLMs is a
crucial step in their development and applications, especially for specific
professional fields. In the urban domain, there have been some early
explorations about the usability of LLMs, but a systematic and scalable
evaluation benchmark is still lacking. The challenge in constructing a
systematic evaluation benchmark for the urban domain lies in the diversity of
data and scenarios, as well as the complex and dynamic nature of cities. In
this paper, we propose CityBench, an interactive simulator based evaluation
platform, as the first systematic evaluation benchmark for the capability of
LLMs for urban domain. First, we build CitySim to integrate the multi-source
data and simulate fine-grained urban dynamics. Based on CitySim, we design 7
tasks in 2 categories of perception-understanding and decision-making group to
evaluate the capability of LLMs as city-scale world model for urban domain. Due
to the flexibility and ease-of-use of CitySim, our evaluation platform
CityBench can be easily extended to any city in the world. We evaluate 13
well-known LLMs including open source LLMs and commercial LLMs in 13 cities
around the world. Extensive experiments demonstrate the scalability and
effectiveness of proposed CityBench and shed lights for the future development
of LLMs in urban domain. The dataset, benchmark and source codes are openly
accessible to the research community via
https://github.com/tsinghua-fib-lab/CityBench


  The wavelike processes of crystallisation and melting or crystallisation
waves are well-known to exist at the crystal 4He surface in its rough state.
Below the roughening transition temperature the crystal surface experiences the
transition to the smooth faceted state and the crystallisation waves represent
the propagation of a train of crystalline steps at the velocity depending on
the crystal step height. Here we analyse the transmission and reflection of
crystallisation waves propagating across the crystal edge separating the
crystal surface in the rough and faceted states.


  We develop a simplified method for obtaining higher orders in the
perturbative expansion of the singular term A(\alpha_s)/[1-x]_+ of non-singlet
partonic splitting functions. Our method is based on the calculation of eikonal
diagrams. The key point is the observation that the corresponding cross
sections exponentiate in the case of two eikonal lines, and that the exponent
is directly related to the functions A(\alpha_s) due to the factorization
properties of parton distribution functions. As examples, we rederive the one-
and two-loop coefficients A^(1) and A^(2). We go on to derive the known general
formula for the contribution to A^(n) proportional to N_f^{n-1}, where N_f
denotes the number of flavors. Finally, we determine the previously
uncalculated term proportional to N_f of the three-loop coefficient A^(3) to
illustrate the method. Our answer agrees with the existing numerical estimate.
The exact knowledge of the coefficients A^(n) is important for the resummations
of large logarithmic corrections due to soft radiation. Although only the
singular part of the splitting functions is calculable within our method,
higher-order computations are much less complex than within conventional
methods, and even the calculation of A^(4) may be possible.


  The nonlocal response functions to quantum fluctuations are used to find
asymptotic expressions for the Casimir free energy and entropy at arbitrarily
low temperature in the configuration of two parallel metallic plates. It is
shown that by introducing an alternative nonlocal response to the
off-the-mass-shell fluctuations the Lifshitz theory is brought into agreement
with the requirements of thermodynamics. According to our results, the Casimir
entropy calculated using the nonlocal response functions, which take into
account dissipation of conduction electrons, remains positive and monotonously
goes to zero with vanishing temperature, i.e., satisfies the Nernst heat
theorem. This is true for both plates with perfect crystal lattices and for
lattices with defects of structure. The obtained results are discussed in the
context of the Casimir puzzle.


  Aggregate Risk Analysis is a computationally intensive and a data intensive
problem, thereby making the application of high-performance computing
techniques interesting. In this paper, the design and implementation of a
parallel Aggregate Risk Analysis algorithm on multi-core CPU and many-core GPU
platforms are explored. The efficient computation of key risk measures,
including Probable Maximum Loss (PML) and the Tail Value-at-Risk (TVaR) in the
presence of both primary and secondary uncertainty for a portfolio of property
catastrophe insurance treaties is considered. Primary Uncertainty is the the
uncertainty associated with whether a catastrophe event occurs or not in a
simulated year, while Secondary Uncertainty is the uncertainty in the amount of
loss when the event occurs.
  A number of statistical algorithms are investigated for computing secondary
uncertainty. Numerous challenges such as loading large data onto hardware with
limited memory and organising it are addressed. The results obtained from
experimental studies are encouraging. Consider for example, an aggregate risk
analysis involving 800,000 trials, with 1,000 catastrophic events per trial, a
million locations, and a complex contract structure taking into account
secondary uncertainty. The analysis can be performed in just 41 seconds on a
GPU, that is 24x faster than the sequential counterpart on a fast multi-core
CPU. The results indicate that GPUs can be used to efficiently accelerate
aggregate risk analysis even in the presence of secondary uncertainty.


  We propose an inflationary scenario based on the concurrent presence of
non-minimal coupling (NMC) and generalized non-minimal derivative coupling
(GNMDC), in the context of Higgs inflation. The combined construction maintains
the advantages of the individual scenarios without sharing their disadvantages.
In particular, a long inflationary phase can be easily achieved due to the
gravitational friction effect owed to the GNMDC, without leading to
trans-Planckian values and unitarity violation. Additionally, the
tensor-to-scalar ratio remains to low values due to the NMC contribution.
Finally, the instabilities related to the squared sound-speed of scalar
perturbations, which plague the simple GNMDC scenarios, are now healed due to
the domination of the NMC contribution and the damping of the GNMDC effects
during the reheating era. These features make scenarios with nonminimal and
derivative couplings to gravity successful candidates for the description of
inflation.


  Aiming at a consistent planetary synchronization model of both short-term and
long-term solar cycles, we start with an analysis of Schove's historical data
of cycle maxima. Their deviations (residuals) from the average cycle duration
of 11.07 years show a high degree of regularity, comprising a dominant 200-year
period (Suess-de Vries cycle), and a few periods around 100 years (Gleissberg
cycle). Encouraged by their robustness, we support previous forecasts of an
upcoming grand minimum in the 21st century. To explain the long-term cycles, we
enhance our tidally synchronized solar dynamo model by a modulation of the
field storage capacity of the tachocline with the orbital angular momentum of
the Sun, which is dominated by the 19.86-year periodicity of the Jupiter-Saturn
synodes. This modulation of the 22.14 years Hale cycle leads to a 193-year beat
period of dynamo activity which is indeed close to the Suess-de Vries cycle.
For stronger dynamo modulation, the model produces additional peaks at typical
Gleissberg frequencies, which seem to be explainable by the non-linearities of
the basic beat process, leading to a bi-modality of the Schwabe cycle. However,
a complementary role of beat periods between the Schwabe cycle and the
Jupiter-Uranus/Neptune synodic cycles cannot be completely excluded.


  This work is devoted to the study of relaxation--dissipation processes in
systems described by Quantum Field Theory. In the first part, I focus on the
phi^4 scalar quantum field theory in finite volume in the large N limit. I find
that the zero-mode quantum fluctuations cannot grow macroscopically large
starting from microscopic initial conditions, while the long-wavelength
fluctuations do scale with the linear size of the system, signalling dynamical
infrared properties quite different from the equilibrium ones. I also introduce
a non-gaussian Hartree-Fock approximation (tdHF) and I derive the mean-field
coupled time-dependent Schroedinger equations for the modes of the scalar
field. The dynamical evolution of a uniform condensate is studied in a further
controlled gaussian approximation, for N=1. Results similar to the large N case
show an internal inconsistency of this approximation. I also study the dynamics
of the system in infinite volume in the broken symmetry phase. The data show
that the fixed points of the evolution cover at most the classically metastable
part of the static effective potential. I finally study the dynamical evolution
for the O(N+1) nonlinear sigma model in 1+1 dimensions in the large N limit. I
first of all verify that the large coupling limit of the O(N+1) phi^4 model,
which renders the model non linear, commutes with the large N limit, so that
the O(infty) nonlinear sigma model is uniquely defined. I then study the
evolution of several observables, like the spectrum of produced particles,
finding no evidence for parametric resonance. I conclude with some remarks on
the ``state of art'' in gauge theories and some comments about the open issues
in the subject.


  A simple quantum generalisation of the Liouville-Arnold criterion of
classical integrability is proposed: A system is quantum-integrable if it has
an abelian Lie group of Wigner symmetries of dimension equal to the number of
degrees of freedom. The criterion goes significantly beyond the familiar case
of involutive conserved operators to cover systems with anomalies in which
involutivity is modified by central charges. "Anomalous" quantum integrability
is shown to have all the expected consequences including exact
diagonalisability. The approach throws new light on the origin of Weyl group
invariance.


  In this paper, we seek to answer what-if questions - i.e., given recorded
data of an existing deployed networked system, what would be the performance
impact if we changed the design of the system (a task also known as causal
inference). We make three contributions. First, we expose the complexity of
causal inference in the context of adaptive bit rate video streaming, a
challenging domain where the network conditions during the session act as a
sequence of latent and confounding variables, and a change at any point in the
session has a cascading impact on the rest of the session. Second, we present
Veritas, a novel framework that tackles causal reasoning for video streaming
without resorting to randomised trials. Integral to Veritas is an easy to
interpret domain-specific ML model (an embedded Hidden Markov Model) that
relates the latent stochastic process (intrinsic bandwidth that the video
session can achieve) to actual observations (download times) while exploiting
control variables such as the TCP state (e.g., congestion window) observed at
the start of the download of video chunks. We show through experiments on an
emulation testbed that Veritas can answer both counterfactual queries (e.g.,
the performance of a completed video session had it used a different buffer
size) and interventional queries (e.g., estimating the download time for every
possible video quality choice for the next chunk in a session in progress). In
doing so, Veritas achieves accuracy close to an ideal oracle, while
significantly outperforming both a commonly used baseline approach, and Fugu
(an off-the-shelf neural network) neither of which account for causal effects.


  Conventionally, the observed charged leptons are regarded the simultaneous
eigenstates of "mass" and "family". Against this view, we discuss a possibility
that the observed charged leptons $e_i=(e, \mu, \tau)$ are not identical with
the eigenstates of family $e^0_\alpha =(e_1^0, e_2^0, e_3^0)$. Here, we define
the eigenstates of family, $e^0_\alpha$, as the states which interact with
family gauge bosons in the mass eigenstates of the broken U(3)$_{family}$ gauge
symmetry. Although there is at present not any experimental evidence for
$e^0_1$-$e^0_2$ mixing, and we have only an upper limit for the mixing from the
present experimental data. We will conclude that the $e$-$\mu$ mixing angle
$\theta$ must be $\theta \lesssim 10^{-3}$. Thus, we can not exclude a
possibility $\theta\neq 0$. If we want more small upper limit of $\theta$, a
rare decay search $\mu \rightarrow e + \gamma$ will be useful.


  Dirac-Coulomb type differential equation and its solution relativistic
exponential-type spinor orbitals are introduced. They provide a revised form
for operator invariants, namely Dirac invariants, simplifying the treatment of
the angular components in calculation of many-electron systems. The
relativistic Coulomb energy is determined by employing a spectral solution to
Poisson's equation for the one-electron potential, which is expressed in terms
of radial functions involving incomplete gamma functions. The computation for
incomplete gamma functions posses challenges due to slow convergence rate
associated with their series representation. Such difficulties are eliminated
through use of the bi-directional method along with hyper-radial functions. A
new formulation for relativistic auxiliary functions that improve the
efficiency in Coulomb energy calculations is presented. These formulations also
contribute to inquiring into orthogonal expansions for solutions to Poisson's
equation using complete orthonormal sets of exponential orbitals with
non-integer principal quantum numbers. They may provide a meaningful
alternative series representations.


  Developers often try to find occurrences of a certain term in a software
system. Traditionally, a text search is limited to static source code files. In
this paper, we introduce a simple approach, RuntimeSearch, where the given term
is searched in the values of all string expressions in a running program. When
a match is found, the program is paused and its runtime properties can be
explored with a traditional debugger. The feasibility and usefulness of
RuntimeSearch is demonstrated on a medium-sized Java project.


  Long-lived, high-frequency phonons are valuable for applications ranging from
optomechanics to emerging quantum systems. For scientific as well as
technological impact, we seek high-performance oscillators that offer a path
towards chip-scale integration. Confocal bulk acoustic wave resonators have
demonstrated an immense potential to support long-lived phonon modes in
crystalline media at cryogenic temperatures. So far, these devices have been
macroscopic with cm-scale dimensions. However, as we push these oscillators to
high frequencies, we have an opportunity to radically reduce the footprint as a
basis for classical and emerging quantum technologies. In this paper, we
present novel design principles and simple fabrication techniques to create
high performance chip-scale confocal bulk acoustic wave resonators in a wide
array of crystalline materials. We tailor the acoustic modes of such resonators
to efficiently couple to light, permitting us to perform a non-invasive
laser-based phonon spectroscopy. Using this technique, we demonstrate an
acoustic $Q$-factor of 28 million (6.5 million) for chip-scale resonators
operating at 12.7 GHz (37.8 GHz) in crystalline $z$-cut quartz ($x$-cut
silicon) at cryogenic temperatures.


  Exact and approximate expressions are established for dissipation, the power
of the shear stress at the wall and the boundary layer thickness corresponding
to the motion of an Oldroyd-B fluid induced by a constantly accelerating plate.
The similar expressions for Maxwell, Newtonian and second grade fluids,
performing the same motion, are obtained as limiting cases of our general
results. The specific features of the four models are emphasized by means of
the asymptotic approximations.


  Lithium Sulfide, Li2S, is an anti-fluorite semiconductor with a band-gap of
3.865 eV. It also has exactly the same valence electron count, Ne, and atomic
number, Z, as magnesium diboride, MgB2. Both have almost the same formula
weight. This qualifies Li2S as a magnesium-diboride like material. Li2S passes
the same computational material specific test for superconductivity as MgB2.
Using our recently developed symmetry rules for searching for superconductors,
we predict that Li2S, with electronegativity of 1.5, will be superconducting
with a Tc of 33.8K, if double-gapped or 16.9K if single gapped.


  In this paper, the problem of approximating hidden chaotic attractors of a
general class of nonlinear systems is investigated. The Parameter Switching
(PS) algorithm is utilized, which switches the control parameter within a given
set of values with the initial value problem numerically solved. The
PS-generated generated attractor approximates the attractor obtained by
averaging the control parameter with the switched values, which represents the
hidden chaotic attractor. The hidden chaotic attractors of a generalized Lorenz
system and the Rabinovich-Fabrikant system are simulated for illustration


  We have used neutron scattering and muon spin relaxation (muSR) to
investigate the structural and magnetic properties of the beta-phase of
elemental manganese doped with dilute amounts of indium. beta-Mn is an example
of a topologically frustrated antiferromagnetically correlated metal - but
which remains paramagnetic at all temperatures. The addition of In to beta-Mn
results in a vast volume expansion of the lattice, and would therefore be
expected to have a major effect on the stability and localization of the Mn
moment - as observed in, for example, Ru and Al doped beta-Mn alloys. We find
that In doping in beta-Mn results in a short-range ordered spin-glass like
ground state, similar to that of Al-doped beta-Mn but with residual low
frequency spin fluctuations. This is in contrast to Ru doping which results in
the stabilization of a long-range ordered Mn moment


  Characterizing the tissue morphology and anatomy of seagrasses is essential
to predicting their acoustic behavior. In this pilot study, we use histology
techniques and whole slide imaging (WSI) to describe the composition and
topology of the aerenchyma of an entire leaf blade in an automatic way
combining the advantages of X-ray microtomography and optical microscopy.
Paraffin blocks are prepared in such a way that microtome slices contain an
arbitrarily large number of cross sections distributed along the full length of
a blade. The sample organization in the paraffin block coupled with whole slide
image analysis allows high throughput data extraction and an exhaustive
characterization along the whole blade length. The core of the work are image
processing algorithms that can identify cells and air lacunae (or void) from
fiber strand, epidermis, mesophyll and vascular system. A set of specific
features is developed to adequately describe the convexity of cells and voids
where standard descriptors fail. The features scrutinize the local curvature of
the object borders to allow an accurate discrimination between void and cell
through machine learning. The algorithm allows to reconstruct the cells and
cell membrane features that are relevant to tissue density, compressibility and
rigidity. Size distribution of the different cell types and gas spaces, total
biomass and total void volume fraction are then extracted from the high
resolution slices to provide a complete characterization of the tissue along
the leave from its base to the apex.


  The classical Landau--Lifshitz equation -- the simplest model of a
ferromagnet -- provides an archetypal example for studying transport phenomena.
In one-spatial dimension, integrability enables the classification of the
spectrum of linear and nonlinear modes. An exact characterization of
finite-temperature thermodynamics and transport has nonetheless remained
elusive. We present an exact description of thermodynamic equilibrium states in
terms of interacting modes. This is achieved by retrieving the classical
Landau--Lifschitz model through the semiclassical limit of the integrable
quantum spin-$S$ anisotropic Heisenberg chain at the level of the thermodynamic
Bethe ansatz description. In the axial regime, the mode spectrum comprises
solitons with unconventional statistics, whereas in the planar regime we
additionally find two special types of modes of radiative and solitonic type.
The obtained framework paves the way for analytical study of unconventional
transport properties: as an example we study the finite-temperature spin Drude
weight, finding excellent agreement with Monte Carlo simulations.


  Sensor network attitude problem consists in retrieving the attitude of each
sensor of a network knowing some relative orientations between pairs of
sensors. The attitude of a sensor is its orientation in an absolute axis
system. We present in this paper a method for solving the sensor network
attitude problem using quaternion formalism which allows to apply linear
algebra tools. The proposed algorithm solves the problem when all of the
relative attitudes are known. A complete characterisation of the algorithm is
established: spatial complexity, time complexity and robustness. Our algorithm
is validated in simulations and with real experiments.


  We have analyzed the [Fe II] and [Ni II] emission lines in the bipolar
planetary nebula Mz~3. We find that the [Fe II] and [Ni II] lines arise
exclusively from the central regions. Fluorescence excitation in the formation
process of these lines is negligible for this low-excitation nebula. From the
[Fe II]/[Ni II] ratio, we obtain a higher Fe/Ni abundance ratio with respect to
the solar value. The current result provides further supporting evidence for Mz
3 as a symbiotic Mira.


  The metamagnetic transition between the antiferromagnetic and paramagnetic
state in UIrGe has been studied at various temperatures by magnetization, heat
capacity and magnetocaloric-effect measurements on a single crystal in static
and pulsed magnetic fields applied along the orthorhombic b-axis. A first-order
transition is observed at temperatures below 13 K and a second-order one at
higher temperatures up to the N\'eel temperature (TN = 16.5 K). The first-order
transition is accompanied by a dramatic increase of the Sommerfeld coefficient.
Magnetization measurements extended to the paramagnetic range revealed an
anomalous S-shape (inflection point at a magnetic field Hm) in magnetization
isotherms at temperatures above 13 K and a temperature dependence of
susceptibility with a maximum at Tmax well above TN. The lines representing the
temperature-induced evolution of Hm and field-induced evolution of Tmax,
respectively, are bound for the point in the magnetic phase diagram at which
the order of metamagnetic transition changes. A tentative scenario explaining
these anomalies by antiferromagnetic correlations or short-range order in the
paramagnetic state is discussed.


  Hybrid quantum-classical algorithms based on variational circuits are a
promising approach to quantum machine learning problems for near-term devices,
but the selection of the variational ansatz is an open issue. Recently, tensor
network-inspired circuits have been proposed as a natural choice for such
ansatz. Their employment on binary classification tasks provided encouraging
results. However, their effectiveness on more difficult tasks is still unknown.
Here, we present numerical experiments on multi-class classifiers based on tree
tensor network and multiscale entanglement renormalization ansatz circuits. We
conducted experiments on image classification with the MNIST dataset and on
quantum phase recognition with the XXZ model by Cirq and TensorFlow Quantum. In
the former case, we reduced the number of classes to four to match the aimed
output based on 2 qubits. The quantum data of the XXZ model consist of three
classes of ground states prepared by a checkerboard circuit used for the ansatz
of the variational quantum eigensolver, corresponding to three distinct quantum
phases. Test accuracy turned out to be 59%-93% and 82%-96% respectively,
depending on the model architecture and on the type of preprocessing.


  We prove that nonnegative almost minimizers of the horizontal Bernoulli-type
functional
  $$ J(u,\Omega):=\int_{\Omega}\Big(|\nabla_{\mathbb{G}}
u(x)|^2+\chi_{\{u>0\}}(x)\Big)\,dx$$
  are Lipschitz continuous in the intrinsic sense.


  We often wish to classify objects by their shapes. Indeed, the study of
shapes is an important part of many scientific fields such as evolutionary
biology, structural biology, image processing, and archaeology. The most
widely-used method of shape analysis, Geometric Morphometrics, assumes that
that the mathematical space in which shapes are represented is linear. However,
it has long been known that shape space is, in fact, rather more complicated,
and certainly non-linear. Diffeomorphic methods that take this non-linearity
into account, and so give more accurate estimates of the distances among
shapes, exist but have rarely been applied to real-world problems. Using a
machine classifier, we tested the ability of several of these methods to
describe and classify the shapes of a variety of organic and man-made objects.
We find that one method, the Square-Root Velocity Function (SRVF), is superior
to all others, including a standard Geometric Morphometric method
(eigenshapes). We also show that computational shape classifiers outperform
human experts, and that the SRVF shortest-path between shapes can be used to
estimate the shapes of intermediate steps in evolutionary series. Diffeomorphic
shape analysis methods, we conclude, now provide practical and effective
solutions to many shape description and classification problems in the natural
and human sciences.


  The appeal of serverless (FaaS) has triggered a growing interest on how to
use it in data-intensive applications such as ETL, query processing, or machine
learning (ML). Several systems exist for training large-scale ML models on top
of serverless infrastructures (e.g., AWS Lambda) but with inconclusive results
in terms of their performance and relative advantage over "serverful"
infrastructures (IaaS). In this paper we present a systematic, comparative
study of distributed ML training over FaaS and IaaS. We present a design space
covering design choices such as optimization algorithms and synchronization
protocols, and implement a platform, LambdaML, that enables a fair comparison
between FaaS and IaaS. We present experimental results using LambdaML, and
further develop an analytic model to capture cost/performance tradeoffs that
must be considered when opting for a serverless infrastructure. Our results
indicate that ML training pays off in serverless only for models with efficient
(i.e., reduced) communication and that quickly converge. In general, FaaS can
be much faster but it is never significantly cheaper than IaaS.


  In this paper, we study the asymptotic behavior of supremum distribution of
some classes of iterated stochastic processes $\{X(Y(t)) : t \in [0,
\infty)\}$, where $\{X(t) : t \in \mathbb{R} \}$ is a centered Gaussian process
and $\{Y(t): t \in [0, \infty)\}$ is an independent of $\{X(t)\}$ stochastic
process with a.s. continuous sample paths. In particular, the asymptotic
behavior of $\mathbb{P}\left(\sup_{s \in [0,T]} X(Y(s)) > u\right)$ as $u \to
\infty$, where $T > 0$, as well as $\lim_{u\to\infty} \mathbb{P}\left(\sup_{s
\in [0, h(u)]} X(Y(s)) > u\right)$, for some suitably chosen function $h(u)$
are analyzed. As an illustration, we study the asymptotic behavior of the
supremum distribution of iterated fractional Brownian motion process.


  Algebraic Riccati equations with indefinite quadratic terms play an important
role in applications related to robust controller design. While there are many
established approaches to solve these in case of small-scale dense
coefficients, there is no approach available to compute solutions in the
large-scale sparse setting. In this paper, we develop an iterative method to
compute low-rank approximations of stabilizing solutions of large-scale sparse
continuous-time algebraic Riccati equations with indefinite quadratic terms. We
test the developed approach for dense examples in comparison to other
established matrix equation solvers, and investigate the applicability and
performance in large-scale sparse examples.


  The ground state of a spinor Bose liquid is ferromagnetic, while the softest
excitation above the ground state is the magnon mode. The dispersion relation
of the magnon in a one-dimensional liquid is periodic in the wavenumber q with
the period 2\pi n, determined by the density n of the liquid. Dynamic
correlation functions, such as e.g. spin-spin correlation function, exhibit
power-law singularities at the magnon spectrum, $\omega\to\omega_m(q,n)$.
Without using any specific model of the inter-particle interactions, we relate
the corresponding exponents to independently measurable quantities
$\partial\omega_m/\partial q$ and $\partial\omega_m/\partial n$.


  We study the influence of the cosmic expansion on the size of the shadow of a
spinning black hole observed by a comoving observer. We first consider that the
expansion is driven by a cosmological constant only and build the connection
between the Kerr-de Sitter metric and the FLRW metric. We clarify that the
notion of a comoving observer is well defined in the spacetime of a spinning
black hole only in the sense of being asymptotic. The angular size of the
shadow for a comoving observer is calculated. Significantly we find that the
angular size approaches a non-zero finite value for a distant comoving
observer, while it vanishes for a distant static observer. Furthermore, by
adopting the approximate method proposed in \cite{Bisnovatyi-Kogan:2018vxl} we
extend the study to the general multi-component universe case. The results show
that the difference between the horizontal and vertical angular size changes a
lot, while their ratio, i.e. the oblateness, keeps unchanged when the
supermassive spinning black hole is at a high redshift, due to the common
amplification factor exerted by the cosmic expansion. In addition, when $a=0$,
our results agree with the previous studies in
\cite{Perlick:2018iye,Bisnovatyi-Kogan:2018vxl}.


  Ordinary least squares (OLS) linear regression is one of the most basic
statistical techniques for data analysis. In the main stream literature and the
statistical education, the study of linear regression is typically restricted
to the case where the covariates are fixed, errors are mean zero Gaussians with
variance independent of the (fixed) covariates. Even though OLS has been
studied under misspecification from as early as the 1960's, the implications
have not yet caught up with the main stream literature and applied sciences.
The present article is an attempt at a unified viewpoint that makes the various
implications of misspecification stand out.


  The electronic properties of antimonene, single-layer Sb, are attracting
great attention. In this paper, spin transport in armchair antimonene
nanoribbon (ASbNR) is investigated. Following the tight-binding model, we
calculate both the transmission probability and the conductance by means of the
non-equilibrium Green's function (NEGF) method. The effects of an external
electric field vertical to the ribbon plane are explored. Our results indicate
that the spin-flip rate increases with the vertical electric field. Disorder
effects on spin transport are addressed by considering the presence of charged
impurities. It is found that charged impurities also enhance the spin-flip rate
but to a lesser extent than the out-of-plane electric field.


We determine the Cox ring of the space of complete rank two collineations.


  Sensing electric fields with high sensitivity, high spatial resolution and at
radio frequencies can be challenging to realize. Recently, point defects in
silicon carbide have shown their ability to measure local electric fields by
optical charge conversion of their charge state. Here we report the combination
of heterodyne detection with charge-based electric field sensing, solving many
of the previous limitations of this technique. Owing to the non-linear response
of the charge conversion to electric fields, the application of a separate
"pump" electric field results in a detection sensitivity as low as 1.1
(V/cm)/$\sqrt{Hz}$, with near-diffraction limited spatial resolution and
tunable control of the sensor dynamic range. In addition, we show both
incoherent and coherent heterodyne detection, allowing measurements of either
unknown random fields or synchronized fields with higher sensitivities.
Finally, we demonstrate in-plane vector measurements of the electric field by
combining orthogonal pump electric fields. Overall, this work establishes
charge-based measurements as highly relevant for solid-state defect sensing.


  The possibility of realizing lattice analogs of fractional quantum Hall (FQH)
states, so-called fractional Chern insulators (FCIs), in nearly flat
topological (Chern) bands has attracted a lot of recent interest. Here, we make
the connection between Abelian as well as non-Abelian FQH states and FCIs more
precise. Using a gauge-fixed version of Qi's Wannier basis representation of a
Chern band, we demonstrate that the interpolation between several FCI states,
obtained by short-range lattice interactions in a spin-orbit-coupled kagome
lattice model, and the corresponding continuum FQH states is smooth: the gap
remains approximately constant and extrapolates to a finite value in the
thermodynamic limit, while the low-lying part of the orbital entanglement
spectrum remains qualitatively unaltered. The orbital entanglement spectra also
provide a first glimpse of the edge physics of FCIs via the bulk-boundary
correspondence. Corroborating these results, we find that the squared overlaps
between the FCI and FQH ground states are as large as 98.7% for the 8-electron
Laughlin state at $\nu=1/3$ (consistent with an earlier study) and 97.8% for
the 10-electron Moore-Read state at $\nu=1/2$. For the bosonic analogs of these
states, the adiabatic continuity is also shown to hold, albeit with somewhat
smaller associated overlaps, etc. Although going between the Chern bands to the
Landau level problem is often smooth, we show that this is not always the case
by considering fermions at filling fraction $\nu=4/5$, where the interpolation
between Hamiltonians describing the two systems results in a phase transition.


  The cosmic no hair conjecture is tested for a large class of inhomogeneous
cosmologies with a positive cosmological constant. Firstly, we derive a new
class of exact inhomogeneous cosmological solutions whose matter content of the
models is formed by a mixture of two interacting simple fluids plus a
cosmological Lambda-term. These models generalize the de Sitter spacetime and
the inhomogeneous two-fluid Szekeres-type cosmologies derived by Lima and
Tiomno. Finally, we show that the late time behaviour of our solutions is in
agreement with the "cosmic no hair theorem" of Hawking and Moss.


  We present the first detailed chemical abundances for distant RR Lyrae stars
members of the Virgo Stellar Stream (VSS), derived from X-Shooter
medium-resolution spectra. Sixteen elements from carbon to barium have been
measured in six VSS RR Lyrae stars, sampling all main nucleosynthetic channels.
For the first time we will be able to compare in detail the chemical evolution
of the VSS progenitor with those of Local Group dwarf spheroidal galaxies (LG
dSph) as well as the one of the smooth halo.


  The definition of a pseudo-dualizing complex is obtained from that of a
dualizing complex by dropping the injective dimension condition, while
retaining the finite generatedness and homothety isomorphism conditions. In the
specific setting of a pair of associative rings, we show that the datum of a
pseudo-dualizing complex induces a triangulated equivalence between a
pseudo-coderived category and a pseudo-contraderived category. The latter terms
mean triangulated categories standing "in between" the conventional derived
category and the coderived or the contraderived category. The constructions of
these triangulated categories use appropriate versions of the Auslander and
Bass classes of modules. The constructions of derived functors providing the
triangulated equivalence are based on a generalization of a technique developed
in our previous paper arXiv:1503.05523.


  We study the effect of thermal fluctuations on a sourced quench in a system
with $Z_2$ symmetry. By ignoring the fluctuation of finite momentum modes and
tracing the dynamics of zero momentum mode driven by a spatially homogeneous
source near the critical point, we map out a phase diagram for the quench
dynamics. The phase diagram consists of three different phases. Phase I occurs
for large fluctuations with the relaxation time set by fluctuation induced
inverse effective mass square. Phase II occurs for small fluctuation and slow
quench rate. The dynamics is characterized by a modified Kibble-Zurek scaling.
Phase III corresponds to small fluctuations and rapid quench rate. The
relaxation time tends to a finite value in the rapid quench limit. We also
estimate the fluctuations of finite momentum modes, finding significant
enhancement of the effective mass square. We speculate the qualitative features
of the phase diagram may remain the same, but enhanced fluctuations can lead to
shrinkage of phase II and III.


  In this short note, we examine the relationship between the string coupling
constant, $\gstring{}$, and the grand unified gauge coupling constant,
$\alphagut{}$, in a highly successful class of models based on anisotropic
orbifold compactifications of the weakly coupled heterotic string. These models
represent a stringy embedding of SU(6) gauge-Higgs unification in a five
dimensional orbifold GUT. We find that the requirement that the theory be
perturbative provides a non-trivial constraint on these models. Interestingly,
there is a correlation between the proton decay rate (due to dimension six
operators) and the string coupling constant. Finally, we make some comments
concerning the extension of these models to the six (and higher) dimensional
case.


  Imaging biological molecules in the gas-phase requires novel sample delivery
methods, which generally have to be characterized and optimized to produce
high-density particle beams. A non-destructive characterization method of the
transverse particle beam profile is presented. It enables the characterization
of the particle beam in parallel to the collection of, for instance,
x-ray-diffraction patterns. As a rather simple experimental method, it requires
the generation of a small laser-light sheet using a cylindrical telescope and a
microscope. The working principle of this technique was demonstrated for the
characterization of the fluid-dynamic-focusing behavior of 220 nm polystyrene
beads as prototypical nanoparticles. The particle flux was determined and the
velocity distribution was calibrated using Mie-scattering calculations.


  Zero-shot learning for visual recognition, e.g., object and action
recognition, has recently attracted a lot of attention. However, it still
remains challenging in bridging the semantic gap between visual features and
their underlying semantics and transferring knowledge to semantic categories
unseen during learning. Unlike most of the existing zero-shot visual
recognition methods, we propose a stagewise bidirectional latent embedding
framework to two subsequent learning stages for zero-shot visual recognition.
In the bottom-up stage, a latent embedding space is first created by exploring
the topological and labeling information underlying training data of known
classes via a proper supervised subspace learning algorithm and the latent
embedding of training data are used to form landmarks that guide embedding
semantics underlying unseen classes into this learned latent space. In the
top-down stage, semantic representations of unseen-class labels in a given
label vocabulary are then embedded to the same latent space to preserve the
semantic relatedness between all different classes via our proposed
semi-supervised Sammon mapping with the guidance of landmarks. Thus, the
resultant latent embedding space allows for predicting the label of a test
instance with a simple nearest-neighbor rule. To evaluate the effectiveness of
the proposed framework, we have conducted extensive experiments on four
benchmark datasets in object and action recognition, i.e., AwA, CUB-200-2011,
UCF101 and HMDB51. The experimental results under comparative studies
demonstrate that our proposed approach yields the state-of-the-art performance
under inductive and transductive settings.


  Monotone systems preserve a partial ordering of states along system
trajectories and are often amenable to separable Lyapunov functions that are
either the sum or the maximum of a collection of functions of a scalar
argument. In this paper, we consider constructing separable Lyapunov functions
for monotone systems that are also contractive, that is, the distance between
any pair of trajectories exponentially decreases. The distance is defined in
terms of a possibly state-dependent norm. When this norm is a weighted
one-norm, we obtain conditions which lead to sum-separable Lyapunov functions,
and when this norm is a weighted infinity-norm, symmetric conditions lead to
max-separable Lyapunov functions. In addition, we consider two classes of
Lyapunov functions: the first class is separable along the system's state, and
the second class is separable along components of the system's vector field.
The latter case is advantageous for many practically motivated systems for
which it is difficult to measure the system's state but easier to measure the
system's velocity or rate of change. In addition, we present an algorithm based
on sum-of-squares programming to compute such separable Lyapunov functions. We
provide several examples to demonstrate our results.


  In this article, we propose and study several discrete versions of
homogeneous and inhomogeneous one-dimensional Fokker-Planck equations. In
particular, for these discretizations of velocity and space, we prove the
exponential convergence to the equilibrium of the solutions, for
time-continuous equations as well as for time-discrete equations. Our method
uses new types of discrete Poincar\'e inequalities for a "two-direction"
discretization of the derivative in velocity. For the inhomogeneous problem, we
adapt hypocoercive methods to the discrete cases.


  We establish a large deviation principle (LDP) for a class of stochastic
porous media equations driven by L\'{e}vy-type noise on a $\sigma$-finite
measure space $(E,\mathcal{B}(E),\mu)$, with the Laplacian replaced by a
negative definite self-adjoint operator. One of the main contributions of this
paper is that we do not assume the compactness of embeddings in the
corresponding Gelfand triple, and to compensate for this generalization, a new
procedure is provided. This is the first paper to deal with LDPs for stochastic
evolution equations with L\'evy noise without compactness conditions. The
coefficient $\Psi$ is assumed to satisfy nondecreasing Lipschitz nonlinearity,
so an important physical problem covered by this case is the Stefan problem.
Numerous examples of negative definite self-adjoint operators are applicable to
our results, for example, for open $E\subset\Bbb{R}^d$, $L=$ Laplacian or
fractional Laplacians, i.e., $L=-(-\Delta)^\alpha,\ \alpha\in(0,1]$,
generalized Schr\"{o}dinger operators, i.e., $L=\Delta+2\frac{\nabla
\rho}{\rho}\cdot\nabla$, Laplacians on fractals is also included.


  Recently it was shown that if a given state fulfils the reduction criterion
it must also satisfy the known entropic inequalities. Now the questions arises
whether on the assumption that stronger criteria based on positive but not
completely positive maps are satisfied, it is possible to derive some scalar
inequalities stronger than the entropic ones. In this paper we show that under
some assumptions the extended reduction criterion [H.-P. Breuer, Phys. Rev.
Lett 97, 080501 (2006); W. Hall, J. Phys. A 40, 6183 (2007)] leads to some
entropic--like inequalities which are much stronger than their entropic
counterparts. The comparison of the derived inequalities with other
separability criteria shows that such approach might lead to strong scalar
criteria detecting both distillable and bound entanglement. In particular, in
the case of SO(3)-invariant states it is shown that the present inequalities
detect entanglement in regions in which entanglement witnesses based on
extended reduction map fail. It should be also emphasized that in the case of
$2\otimes N$ states the derived inequalities detect entanglement efficiently,
while the extended reduction maps are useless when acting on the qubit
subsystem. Moreover, there is a natural way to construct a many-copy
entanglement witnesses based on the derived inequalities so, in principle,
there is a possibility of experimental realization. Some open problems and
possibilities for further studies are outlined.


  We investigate the influence of new GRAAL Sigma-beam asymmetry measurements
on the neutron in multipole fits to the single-pion photoproduction database.
Results are compared to those found with the addition of a double-polarization
quantity associated with the sum rule.


  We report on measurements of quantum many-body modes in ballistic wires and
their dependence on Coulomb interactions, obtained from tunneling between two
parallel wires in a GaAs/AlGaAs heterostructure while varying electron density.
We observe two spin modes and one charge mode of the coupled wires, and map the
dispersion velocities of the modes down to a critical density, at which
spontaneous localization is observed. Theoretical calculations of the charge
velocity agree well with the data, although they also predict an additional
charge mode that is not observed. The measured spin velocity is found to be
smaller than theoretically predicted.


  In this note we study the power of so called query-limited computers. We
compare the strength of a classical computer that is allowed to ask two
questions to an NP-oracle with the strength of a quantum computer that is
allowed only one such query. It is shown that any decision problem that
requires two parallel (non-adaptive) SAT-queries on a classical computer can
also be solved exactly by a quantum computer using only one SAT-oracle call,
where both computations have polynomial time-complexity. Such a simulation is
generally believed to be impossible for a one-query classical computer. The
reduction also does not hold if we replace the SAT-oracle by a general
black-box. This result gives therefore an example of how a quantum computer is
probably more powerful than a classical computer. It also highlights the
potential differences between quantum complexity results for general oracles
when compared to results for more structured tasks like the SAT-problem.


  In the present paper we review the progress of the project of classification
and construction of invariant differential operators for non-compact semisimple
Lie groups. Our starting points is the class of algebras, which we called
earlier 'conformal Lie algebras' (CLA), which have very similar properties to
the conformal algebras of Minkowski space-time, though our aim is to go beyond
this class in a natural way. For this we introduced recently the new notion of
{\it parabolic relation} between two non-compact semisimple Lie algebras $\cal
G$ and $\cal G'$ that have the same complexification and possess maximal
parabolic subalgebras with the same complexification. Thus, we consider the
exceptional algebra $E_{7(7)}$ which is parabolically related to the CLA
$E_{7(-25)}$. Other interesting examples are the orthogonal algebras $so(p,q)$
all of which are parabolically related to the conformal algebra $so(n,2)$ with
$p+q=n+2$, the parabolic subalgebras including the Lorentz subalgebra
$so(n-1,1)$ and its analogs $so(p-1,q-1)$. Further we consider the algebras
$sl(2n,R)$ and for $n=2k$ the algebras $su^*(4k)$ which are parabolically
related to the CLA $su(n,n)$. Further we consider the algebras $sp(r,r)$ which
are parabolically related to the CLA $sp(2r,R)$. We consider also $E_{6(6)}$
and $E_{6(2)}$ which are parabolically related to the hermitian symmetric case
$E_{6(-14)}$.


  In this paper we consider a fragment of the first-order theory of the real
numbers that includes systems of equations of continuous functions in bounded
domains, and for which all functions are computable in the sense that it is
possible to compute arbitrarily close piece-wise interval approximations. Even
though this fragment is undecidable, we prove that there is a (possibly
non-terminating) algorithm for checking satisfiability such that (1) whenever
it terminates, it computes a correct answer, and (2) it always terminates when
the input is robust. A formula is robust, if its satisfiability does not change
under small perturbations. As a basic tool for our algorithm we use the notion
of degree from the field of (differential) topology.


  It is assumed that HXR sources map to the primary energy release site in
flares where particle acceleration occurs. Strong HXR sources are mostly
observed at confined regions along the reconnecting magnetic arcade. We make a
general approach on how the geometry of the reconnecting current sheet (CS) may
influence the strength and localization of observed HXR sources. For this we
use results from an analysis on the 3B/X3.8 flare on January 17, 2005 (Temmer
et al., 2007), as well as measurements from the associated CME. Due to the
close match of the CME acceleration profile and the flare HXR flux, we suppose
that the CME might play a certain role in modifying the geometry of the CS
('symmetric' versus 'asymmetric' vertically stretched CS). This could be the
driver for 'guiding' the accelerated particles to confined areas along the
flaring arcade and might explain the spatially limited occurrence of strong HXR
sources in comparison to elongated ribbons as seen in H-alpha and UV.


  We present the first application of data-driven techniques for dynamical
system analysis based on Koopman theory to variable stars. We focus on light
curves of RRLyrae type variables, in the Galactic globular cluster $\omega$
Centauri. Light curves are thus summarized by a handful of complex eigenvalues,
corresponding to oscillatory or fading dynamical modes. We find that variable
stars of the RRc subclass can be summarized in terms of fewer ($\approx 8$)
eigenvalues, while RRab need comparatively more ($\approx 12$). This result can
be leveraged for classification and reflects the simpler structure of RRc light
curves. We then consider variable stars displaying secular variations due to
the Tseraskaya-Blazhko effect and find a change in relevant eigenvalues with
time, with possible implications for the physical interpretation of the effect.


  The discovery of novel substrate materials has been dominated by trial and
error, opening the opportunity for a systematic search. To identify stable
crystal surfaces, we generate bonding networks for materials from the Materials
Project database with one to five atoms in the primitive unit cell. For
three-dimensional crystals in this set, we systematically break up to three
bonds in the bonding network of the primitive cell. Successful cleavage reduces
the bonding network to two periodic dimensions, creating a layer of the cleaved
crystal. We identify 4,693 unique cleavage surfaces across 2,133 bulk crystals,
4,626 of which have a maximum Miller index of 1. To characterize the likelihood
of cleavage and the thermodynamic stability of the cleaved surfaces, we create
monolayers of these surfaces and calculate the work of cleavage and the
partially-relaxed surface energy using density functional theory to discover
3,991 potential substrates, 2,307 of which do not contain f-valence electrons
and 2,183 of which are derived from a bulk precursor with an entry in the
Inorganic Crystal Structure Database. Following, we identify distinct trends in
the work of cleavage of these layers and relate them to metallic and
covalent/ionic bonding of the three-dimensional precursor. We also assembled a
database of commercially available substrates and show that the database of
predicted substrates significantly enhances the diversity and range of the
distribution of electronic properties and lattice parameters, providing
opportunities for the epitaxial growth of many materials. We illustrate the
potential impact of the substrate database by identifying several new epitaxial
substrates for the transparent conductor BaSnO3, which exhibit low cleavage
energies and result in strains an order of magnitude lower than currently used
substrates.


  In this note we provide a simple formula of general term of recurrent
sequence.


  The spectral classification of Algol C, the third star in the Algol triple
system, has long been a matter of some uncertainty. There is good reason to
suspect that it should be a metallic-line A-type star, and one study in
particular showed that this was so, but further studies have cast doubt on that
assessment. We utilized a simple spectral subtraction method between spectra
taken in and out of primary eclipse to reveal the light of Algol C in the
absence of the light from the brightest star. Our resultant spectrum is
well-matched to an F1 V spectroscopic standard and shows no evidence of
metallic-line spectral anomalies. We note that this classification matches
recent abundance determinations for this source.


  We study the thermal transport properties in three-dimensional disordered
systems close to the metal-insulator transition within linear response. Using a
suitable form for the energy-dependent conductivity $\sigma$, we show that the
value of the dynamical scaling exponent for noninteracting disordered systems
such as the Anderson model of localization can be reproduced. Furthermore, the
values of the thermopower S have the right order of magnitude close to the
transition as compared to the experimental results. A sign change in the
thermoelectric power S - as is often observed in experiments - can also be
modeled within the linear response formulation using modified experimental
$\sigma$ data as input.


  Three great theorems of Thurston read: Haken manifolds are hyperbolic; big
ramified coverings are hyperbolic; big surgeries are hyperbolic. Recent
developments indicate that the later two theorems are essentially a corollary
of the first, that is there are much more Haken manifolds than expected by
Thurston. In fact Freedman showed very recently that big ramified coverings are
Haken. A version of his proof with various improvements was obtained by
Cooper-Long and Cooper-Long-Reid.
  The two main contributions of the present paper are the following. I give an
analytic proof of Freedman's result and the improved version of
Cooper-Long-Reid. This proof is based on fundamentally different approach than
Freedman's and is 10 times shorter, but uses the full forse of the
hyperbolization theorem.
  Secondly, I prove that ANY ramified covering of a tight knot is Haken.
Morover any knot becomes tight after a big surgery. So any ramified covering of
a big surgery is Haken.
  Many other results of the paper are better seen from the introduction.
  The paper uses many different techniques and may be difficult to read for a
beginner.


  The current literature on AI-advised decision making -- involving explainable
AI systems advising human decision makers -- presents a series of inconclusive
and confounding results. To synthesize these findings, we propose a simple
theory that elucidates the frequent failure of AI explanations to engender
appropriate reliance and complementary decision making performance. We argue
explanations are only useful to the extent that they allow a human decision
maker to verify the correctness of an AI's prediction, in contrast to other
desiderata, e.g., interpretability or spelling out the AI's reasoning process.
Prior studies find in many decision making contexts AI explanations do not
facilitate such verification. Moreover, most tasks fundamentally do not allow
easy verification, regardless of explanation method, limiting the potential
benefit of any type of explanation. We also compare the objective of
complementary performance with that of appropriate reliance, decomposing the
latter into the notions of outcome-graded and strategy-graded reliance.


  Differential cross sections for exclusive 16O(e,e'pp)14C processes are
computed within a distorted-wave framework which includes central short-range
correlations and intermediate \Delta+ excitations. The cross sections are
compared to high-resolution data from the MAMI facility at Mainz for a central
energy and momentum transfer of \omega=215 MeV and q=316 MeV respectively. A
fair agreement between the numerical calculations and data is reached when
using spectroscopic information extracted from a 15N(d,3He)14C experiment. The
comparison between the calculations and the data provides additional evidence
that short-range correlations exclusively affect nucleon pairs with a small
center-of-mass momentum residing in a relative S state.


  This introduction to Green's functions is based on their role as kernels of
differential equations. The procedures to construct solutions to a differential
equation with an external source or with an inhomogeneity term are put together
to derive the Dyson equation for the Green's function of the inhomogeneous
system. Very different areas of physics such as, for example, electrodynamics
and quantum transport, can profit from this Green's function formalism. The
fundamental homogeneous-medium Green's tensor of electrodynamics is deduced
from the field of a dipole. Based upon that a numerical procedure is presented
to solve the wave-equation for the near-field in a scattering setup for
arbitrary material distributions. The full inhomogeneous system's Green's
function is not explicitly needed to get the fields, although it can be
obtained by a very similar calculation and in optics can be interpreted as a
density of states. It is demonstrated how the transport problem for two open
free-electron gas reservoirs with arbitrary coupling can be solved by finding
the system's Green's function. In this sense the article is an introduction on
Green's functions for treating interaction. A very detailed discussion of the
current formula is given on an elementary basis.


  The efficacy of data decoding in contemporary ultrafast fiber transmission
systems is greatly determined by the capabilities of the signal processing
tools that are used. The received signal must not exceed a certain level of
complexity, beyond which the applied signal processing solutions become
insufficient or slow. Moreover, the required signal-to-noise ratio of the
received signal can be challenging, especially when adopting modulation formats
with multi-level encoding. Lately, photonic reservoir computing (RC) - a
hardware machine learning technique with recurrent connectivity - has been
proposed as a post-processing tool that deals with deterministic distortions
from fiber transmission. Here we show that RC post-processing is remarkably
efficient for multilevel encoding and for the use of very high launched optical
peak power for fiber transmission up to 14dBm. Higher power levels provide the
desired high signal-to-noise ratio (SNR) values at the receiver end, at the
expense of a complex nonlinear transformation of the transmission signal. Our
demonstration evaluates a direct fiber communication link with 4-level pulse
amplitude modulation (PAM-4) encoding and direct detection, without including
optical amplification, dispersion compensation, pulse shaping or other digital
signal processing (DSP) techniques. By applying RC post-processing on the
distorted signal, we numerically estimate fiber transmission distances of 27km
at 56Gb/s and of 5.5 km at 112Gb/s data encoding rates, while fulfilling the
hard-decision forward error correction (HD-FEC) bit-error-rate (BER) limit for
data recovery. In an experimental equivalent demonstration of our photonic
reservoir, the achieved distances are 21km and 4.6km respectively.


  The rate, selectivity and efficiency of plasma-based conversion processes is
strongly affected by nonequilibrium phenomena. High concentrations of
vibrationally excited molecules are such a plasma-induced effect. It is
frequently assumed that vibrationally excited molecules are important in plasma
catalysis because their presence lowers the apparent activation energy of
dissociative chemisorption reactions and thus increases the conversion rate. A
detailed atomic-level understanding of vibrationally stimulated catalytic
reactions in the context of plasma catalysis is however lacking. Here, we
couple a recently developed statistical model of a plasma-induced vibrational
nonequilibrium to molecular dynamics simulations, enhanced sampling methods,
and machine learning techniques. We quantify the impact of a vibrational
nonequilibrium on the dissociative chemisorption barrier of H2 and CH4 on
nickel catalysts over a wide range of vibrational temperatures. We investigate
the effect of surface structure and compare the role of different vibrational
modes of methane in the dissociation process. For low vibrational temperatures,
very high vibrational efficacies are found, and energy in bend vibrations
appears to dominate the dissociation of methane. The relative impact of
vibrational nonequilibrium is much higher on terrace sites than on surface
steps. We then show how our simulations can help to interpret recent
experimental results, and suggest new paths to a better understanding of plasma
catalysis.


  In this work we present a dual-mode mid-infrared workflow [6], for detecting
sub-superficial mural damages in frescoes artworks. Due to the large nature of
frescoes, multiple thermal images are recorded. Thus, the experimental setup
may introduce measurements errors, seen as inter-frame changes in the image
contrast, after mosaicking. An approach to lowering errors is to post-process
the mosaic [10] via osmosis partial differential equation (PDE) [12, 13], which
preserves details, mass and balance the lights: efficient numerical study for
osmosis on large images is proposed [2, 11], based on operator splitting [8].
Our range of Cultural Heritage applications include the detection of
sub-superficial voids in Monocromo (L. Da Vinci, Castello Sforzesco, Milan)
[5], the light-balance for multi-spectral imaging and the data integration on
the Archimedes Palimpsest [10].


  There has recently been an increasing interest in declarative data analysis,
where analytic tasks are specified using a logical language, and their
implementation and optimisation are delegated to a general-purpose query
engine. Existing declarative languages for data analysis can be formalised as
variants of logic programming equipped with arithmetic function symbols and/or
aggregation, and are typically undecidable. In prior work, the language of
$\mathit{limit\ programs}$ was proposed, which is sufficiently powerful to
capture many analysis tasks and has decidable entailment problem. Rules in this
language, however, do not allow for negation. In this paper, we study an
extension of limit programs with stratified negation-as-failure. We show that
the additional expressive power makes reasoning computationally more demanding,
and provide tight data complexity bounds. We also identify a fragment with
tractable data complexity and sufficient expressivity to capture many relevant
tasks.


  In this short note, we use classic computations for K\"ahler-Ricci flow to
achieve scalar curvature bound for minimal manifold of general type.


  We obtain a necessary and sufficient condition on a polynomial $P(t_1,t_2)$
for the $\ell^{p}$ boundedness of the discrete double Hilbert transforms
associated with $P(t)$ for $1 < p < \infty$. The proof is based on the
multi-parameter circle method treating the cases of $|t_1|\not\approx |t_2|$
arising from $1/t_1$ and $1/t_2$.


  Markov Chains offer ideal conditions for the study and mathematical modelling
of a certain kind of situations depending on random variables. The basic
concepts of the corresponding theory were introduced by Markov in 1907 on
coding literary texts. Since then, the Markov Chain theory was developerd by a
number of leading mathematicians, such as Kolmogorov, Feller etc. However, only
from the 1960's the importance of this theory to the Natural, Social and most
of the other Applied Sciences has been recognized. In this review paper we
present applications of finite Markov Chains to management problems, which can
be solved, as most of the problems concerning applications of Markov chains in
general do, by distinguishing between two types of Chains, the Ergodic and the
Absorbing ones.


  It is shown that when in a higher order variational principle one fixes
fields at the boundary leaving the field derivatives unconstrained, then the
variational principle (in particular the solution space) is not invariant with
respect to the addition of boundary terms to the action, as it happens instead
when the correct procedure is applied. Examples are considered to show how
leaving derivatives of fields unconstrained affects the physical interpretation
of the model. This is justified in particularl by the need of clarifying the
issue for the purpose of applications to relativistic gravitational theories,
where a bit of confusion still exists. On the contrary, as it is well known for
variational principles of order k, if one fixes variables together with their
derivatives (up to order k-1) on the boundary then boundary terms leave
solution space invariant.


  The sparsity of reward feedback remains a challenging problem in online deep
reinforcement learning (DRL). Previous approaches have utilized offline
demonstrations to achieve impressive results in multiple hard tasks. However,
these approaches place high demands on demonstration quality, and obtaining
expert-like actions is often costly and unrealistic. To tackle these problems,
we propose a simple and efficient algorithm called Policy Optimization with
Smooth Guidance (POSG), which leverages a small set of state-only
demonstrations (where expert action information is not included in
demonstrations) to indirectly make approximate and feasible long-term credit
assignments and facilitate exploration. Specifically, we first design a
trajectory-importance evaluation mechanism to determine the quality of the
current trajectory against demonstrations. Then, we introduce a guidance reward
computation technology based on trajectory importance to measure the impact of
each state-action pair, fusing the demonstrator's state distribution with
reward information into the guidance reward. We theoretically analyze the
performance improvement caused by smooth guidance rewards and derive a new
worst-case lower bound on the performance improvement. Extensive results
demonstrate POSG's significant advantages in control performance and
convergence speed in four sparse-reward environments, including the grid-world
maze, Hopper-v4, HalfCheetah-v4, and Ant maze. Notably, the specific metrics
and quantifiable results are investigated to demonstrate the superiority of
POSG.


  Density functional calculations have performed to study the band structures
of $Bi_2Te_3$-related binary ($Bi_2Te_3$, $Sb_2Te_3$, $Bi_2Se_3$, and
$Sb_2Se_3$) and $Sb$/$Se$ doped ternary compounds [$(Bi_{1-x}Sb_x)_2Te_3$ and
$Bi_2(Te_{1-y}Se_y)_3$]. It is found that the band gap can be increased by $Sb$
doping and it is monotonically increased by $Se$ doping. In ternary compounds,
the change of the conduction band structure is more significant, as compared to
the change of valence band. The band degeneracy of valence band maximum is
maintained to be 6 in binaries and ternaries. However, as going from $Bi_2Te_3$
to $Sb_2Te_3$ ($Bi_2Se_3$), the degeneracy of conduction band minimum is
reduced from 6 to 2(1). Based on the results of band structures, we suggest the
suitable stoichiometries of ternary compounds for high thermoelectric
performance.


  Although tidal dissipation in binary stars has been studied for over a
century, theoretical predictions have yet to match the observed properties of
binary populations. This work quantitatively examines the recent proposal of
tidal circularization by resonance locking, where tidal dissipation arises from
resonances between the star's natural oscillation frequencies and harmonics of
the orbital frequency, and where resonances are `locked' for an extended period
of time due to concurrent stellar evolution. We focus on tidal resonances with
axi-symmetric gravity-modes, and examine binaries with primary masses from one
to two solar masses. We find that orbital evolution via resonance locking
occurs primarily during the star's pre-main-sequence phase, with the
main-sequence phase contributing negligibly. Resonance locking, ignoring
non-linearity, can circularize binaries with peri-centre distances out to $\sim
10$ stellar radii, corresponding to circular periods of $\sim 4-6$ days.
However, we find resonantly excited gravity-modes will become nonlinear in
stellar cores, which prevents them from reaching their full, linear amplitudes.
We estimate that such a `saturated resonance lock' reduces the circularization
period by about a third, but resonance locking remains much more effective than
the cumulative actions of equilibrium tides. In a companion paper, we examine
recent binary data to compare against theory.


  In this paper, we propose PanoViT, a panorama vision transformer to estimate
the room layout from a single panoramic image. Compared to CNN models, our
PanoViT is more proficient in learning global information from the panoramic
image for the estimation of complex room layouts. Considering the difference
between a perspective image and an equirectangular image, we design a novel
recurrent position embedding and a patch sampling method for the processing of
panoramic images. In addition to extracting global information, PanoViT also
includes a frequency-domain edge enhancement module and a 3D loss to extract
local geometric features in a panoramic image. Experimental results on several
datasets demonstrate that our method outperforms state-of-the-art solutions in
room layout prediction accuracy.


  Understanding the astrophysical processes acting within galaxy groups and
their effects on the evolution of the galaxy population is one of the crucial
topic of modern cosmology, as almost 60% of galaxies in the Local Universe are
found in groups. We imaged in the far (FUV 1539 A) and near ultraviolet (NUV
2316 A) with GALEX three nearby groups, namely LGG93, LGG127 and LGG225. We
obtained the UV galaxy surface photometry and, for LGG225, the only group
covered by the SDSS, the photometry in u, g, r, i, z bands. We discuss galaxy
morphologies looking for interaction signatures and we analyze the SED of
galaxies to infer their luminosity-weighted ages. The UV and optical photometry
was also used to perform a kinematical and dynamical analysis of each group and
to evaluate the stellar mass. A few member galaxies in LGG225 show a distorted
UV morphology due to ongoing interactions. (FUV-NUV) colors suggest that
spirals in LGG93 and LGG225 host stellar populations in their outskirts younger
than that of M31 and M33 in the LG or with less extinction. The irregular
interacting galaxy NGC3447A has a significantly younger stellar population (few
Myr old) than the average of the other irregular galaxies in LGG225 suggesting
that the encounter triggered star formation. The early-type members of LGG225,
NGC3457 and NGC3522, have masses of the order of a few 10^9 Mo, comparable to
the Local Group ellipticals. For the most massive spiral in LGG225, we estimate
a stellar mass of ~4x10$^{10}$ Mo, comparable to M33 in the LG. Ages of stellar
populations range from a few to ~7 Gyr for the galaxies in LGG225. The
kinematical and dynamical analysis indicates that LGG127 and LGG225 are in a
pre-virial collapse phase, i.e. still undergoing dynamical relaxation, while
LGG93 is likely virialized. (Abridged)