  We review the Baker's method to obtain differential equations of the general
genus hyperelliptic $\wp$ functions. Further, we demonstrate to obtain
differential equations of genus four hyperelliptic differential equations,
which agree with our previous result.


  Computer-Aided Diagnosis (CAD) systems have emerged to support clinicians in
interpreting medical images. CAD systems are traditionally combined with
artificial intelligence (AI), computer vision, and data augmentation to
evaluate suspicious structures in medical images. This evaluation generates
vast amounts of data. Traditional CAD systems belong to a single institution
and handle data access management centrally. However, the advent of CAD systems
for research among multiple institutions demands distributed access management.
This research proposes a blockchain-based solution to enable distributed data
access management in CAD systems. This solution has been developed as a
distributed application (DApp) using Ethereum in a consortium network.


  In recent work we have presented a formal framework for linguistic annotation
based on labeled acyclic digraphs. These `annotation graphs' offer a simple yet
powerful method for representing complex annotation structures incorporating
hierarchy and overlap. Here, we motivate and illustrate our approach using
discourse-level annotations of text and speech data drawn from the CALLHOME,
COCONUT, MUC-7, DAMSL and TRAINS annotation schemes. With the help of domain
specialists, we have constructed a hybrid multi-level annotation for a fragment
of the Boston University Radio Speech Corpus which includes the following
levels: segment, word, breath, ToBI, Tilt, Treebank, coreference and named
entity. We show how annotation graphs can represent hybrid multi-level
structures which derive from a diverse set of file formats. We also show how
the approach facilitates substantive comparison of multiple annotations of a
single signal based on different theoretical models. The discussion shows how
annotation graphs open the door to wide-ranging integration of tools, formats
and corpora.


  This paper describes the use of flexible Bayesian regression models for
estimating a partially identified probability function. Our approach permits
efficient sensitivity analysis concerning the posterior impact of priors on the
partially identified component of the regression model. The new methodology is
illustrated on an important problem where only partially observed data is
available - inferring the prevalence of accounting misconduct among publicly
traded U.S. businesses.


  In the present review different effects related to the orbital degrees of
freedom are discussed. Leaving aside such aspects as the superexchange
mechanism of the cooperative Jahn-Teller distortions and different properties
of "Kugel-Khomskii"-like models, we mostly concentrate on other phenomena,
which are in the focus of the modern condensed matter physics. After a general
introduction we start with the discussion of the concept of effective reduction
of dimensionality due to orbital degrees of freedom and consider such phenomena
as the orbitally-driven Peierls effect and the formation of small clusters of
ions in the vicinity of a Mott transition, which behave like "molecules"
embedded in a solid. The second large section is devoted to the
orbital-selective effects such as the orbital-selective Mott transition and the
suppression of magnetism due to the fact that part of the orbitals start to
form singlet molecular orbitals. At the end the rapidly growing field of the
so-called "spin-orbit-dominated" transition metal compounds is briefly reviewed
including such topics as the interplay between the spin-orbit coupling and the
Jahn-Teller effect, the formation of the spin-orbit driven Mott and Peierls
states, the role of orbital degrees of freedom in generation of the Kitaev
exchange coupling, and the singlet (excitonic) magnetism in $4d$ and $5d$
transition metal compounds.


  Though out-of-sample forecast evaluation is systematically employed with
modern machine learning methods and there exists a well-established classic
inference theory for predictive ability, see, e.g., West (1996, Asymptotic
Inference About Predictive Ability, Econometrica, 64, 1067-1084), such theory
is not directly applicable to modern machine learners such as the Lasso in the
high dimensional setting. We investigate under which conditions such extensions
are possible. Two key properties for standard out-of-sample asymptotic
inference to be valid with machine learning are (i) a zero-mean condition for
the score of the prediction loss function; and (ii) a fast rate of convergence
for the machine learner. Monte Carlo simulations confirm our theoretical
findings. We recommend a small out-of-sample vs in-sample size ratio for
accurate finite sample inferences with machine learning. We illustrate the wide
applicability of our results with a new out-of-sample test for the Martingale
Difference Hypothesis (MDH). We obtain the asymptotic null distribution of our
test and use it to evaluate the MDH of some major exchange rates at daily and
higher frequencies.


  In this paper, we apply a method identified by Puerari & Dottori (1997) to
find the corotation radii (CR) in spiral galaxies. We apply our method to 57
galaxies, 17 of which have already have their CR locations determined using
other methods. The method we adopted entails taking Fourier transforms along
radial cuts in the u, g, r, i, and z wavebands and comparing the phase angles
as a function of radius between them. The radius at which the phase angles
cross indicates the location of the corotation radius. We then calculated the
relative bar pattern speed, $\mathcal{R}$, and classified the bar as "fast",
where $\mathcal{R} < 1.4$, slow, where $\mathcal{R} \geq 1.4$, or intermediate,
where the errors on $\mathcal{R}$ are consistent with the bar being "slow" or
"fast". For the 17 galaxies that had their CR locations previously measured, we
found that our results were consistent with the values of $\mathcal{R}$
obtained by the computer simulations of Rautiainen, Salo & Laurikainen (2008).
For the larger sample, our results indicate that 34 out of 57 galaxies (~60%)
have fast bars. We discuss these results in the context of its implications for
dark matter concentrations in disk galaxies. We also discuss these results in
the context of different models for spiral structure in disk galaxies.


  Dark matter (DM) halos formed in CDM cosmologies seem to be characterized by
a power law phase-space density profile. The density of the DM halos is often
fitted by the NFW profile but a better fit is provided by the Sersic fitting
formula. These relations are empirically derived from cosmological simulations
of structure formation but have not yet been explained on a first principle
basis. Here we solve the Jeans equation under the assumption of a spherical DM
halo in dynamical equilibrium, that obeys a power law phase space density and
either the NFW-like or the Sersic density profile. We then calculate the
velocity anisotropy, beta(r), analytically. Our main result is that for the
NFW-like profile the beta - gamma relation is not a linear one (where gamma is
the logarithmic derivative of the density rho[r]). The shape of beta(r) depends
mostly on the ratio of the gravitational to kinetic energy within the NFW scale
radius R_s. For the Sersic profile a linear beta - gamma relation is recovered,
and in particular for the Sersic index of n = 6.0 case the linear fit of Hansen
& Moore is reproduced. Our main result is that the phase-space density power
law, the Sersic density form and the linear beta - gamma dependence constitute
a consistent set of relations which obey the spherical Jeans equation and as
such provide the framework for the dynamical modeling of DM halos.


  Two signed graphs are called switching isomorphic if one of them is
isomorphic to a switching equivalent of the other. To determine the number of
switching non-isomorphic signed graphs on a specific graph, we will establish a
method based on the action of its automorphism group. As an application and
computational results, we classify all the switching non-isomorphic signed
graphs arising from the complete graph K5 and the generalized Petersen graph
GP(7; 2). Moreover, some results on the automorphism groups of the target
signed graphs are obtained.


  For projection-based linear-subspace model order reduction (MOR), it is well
known that the Kolmogorov n-width describes the best-possible error for a
reduced order model (ROM) of size n. In this paper, we provide approximation
bounds for ROMs on polynomially mapped manifolds. In particular, we show that
the approximation bounds depend on the polynomial degree p of the mapping
function as well as on the linear Kolmogorov n-width for the underlying
problem. This results in a Kolmogorov (n, p)-width, which describes a lower
bound for the best-possible error for a ROM on polynomially mapped manifolds of
polynomial degree p and reduced size n.


  We propose a CP-violating source in the charged Higgs sector of a 3-Higgs
Doublet Model (3HDM) that will contribute to three CP-asymmetry observables for
low energy processes. In the context of such a 3HDM, a measurement of one of
the specific asymmetry observables (i.e., $\bar{B} \to X_{s+d} \gamma$) could
obtain up to 2.5% or more, which would give a 5$\sigma$ evidence for physics
Beyond the SM (BSM) from the full BELLE II data set. In addition to these
CP-violating observables, the current measurements of Electron Dipole Moments
(EDMs) constrain the available parameter region of the CP-violating 3HDM. In
this work, we perform a thorough analysis of the parameter space of it to find
the regions that satisfy EDMs, $\bar{B} \to X_s \gamma$, direct collider
searches for charged Higgs bosons as well as theoretical bounds.


  We show an exact geometric mass formula for superspecial points in the
reduction of any quaternionic Shimura variety modulo at a good prime $p$.


  Evolutions of quantum noise, characterized by quadrature squeezing parameter
and Fano factor, and of mixedness, quantified by quantum von Neumann and linear
entropies, of a pumped dissipative non-linear oscillator are studied. The model
can describe a signal mode interacting with a thermal reservoir in a
parametrically pumped cavity with a Kerr non-linearity. It is discussed that
the initial pure states, including coherent states, Fock states, and finite
superpositions of coherent states evolve into the same steady mixed state as
verified by the quantum relative entropy and the Bures metric. It is shown
analytically and verified numerically that the steady state can be well
approximated by a nonclassical Gaussian state exhibiting quadrature squeezing
and sub-Poissonian statistics for the cold thermal reservoir. A rapid increase
is found in the mixedness, especially for the initial Fock states and
superpositions of coherent states, during a very short time interval, and then
for longer evolution times a decrease in the mixedness to the same, for all the
initial states, and relatively low value of the nonclassical Gaussian state.


  This presentation intends to illustrate the specific capabilities of an
e$^+$e$^-$ sub-TeV collider to provide answers on the basic issues in physics:
origin of mass, hierarchy of masses, cosmological problems. Some foreseeable
scenarios are discussed with a possible synergy with LHC.


  In order to deploy current computer vision (CV) models on
resource-constrained low-power devices, recent works have proposed in-sensor
and in-pixel computing approaches that try to partly/fully bypass the image
signal processor (ISP) and yield significant bandwidth reduction between the
image sensor and the CV processing unit by downsampling the activation maps in
the initial convolutional neural network (CNN) layers. However, direct
inference on the raw images degrades the test accuracy due to the difference in
covariance of the raw images captured by the image sensors compared to the
ISP-processed images used for training. Moreover, it is difficult to train deep
CV models on raw images, because most (if not all) large-scale open-source
datasets consist of RGB images. To mitigate this concern, we propose to invert
the ISP pipeline, which can convert the RGB images of any dataset to its raw
counterparts, and enable model training on raw images. We release the raw
version of the COCO dataset, a large-scale benchmark for generic high-level
vision tasks. For ISP-less CV systems, training on these raw images result in a
7.1% increase in test accuracy on the visual wake works (VWW) dataset compared
to relying on training with traditional ISP-processed RGB datasets. To further
improve the accuracy of ISP-less CV models and to increase the energy and
bandwidth benefits obtained by in-sensor/in-pixel computing, we propose an
energy-efficient form of analog in-pixel demosaicing that may be coupled with
in-pixel CNN computations. When evaluated on raw images captured by real
sensors from the PASCALRAW dataset, our approach results in a 8.1% increase in
mAP. Lastly, we demonstrate a further 20.5% increase in mAP by using a novel
application of few-shot learning with thirty shots each for the novel PASCALRAW
dataset, constituting 3 classes.


  In this paper the failure of Hardy's nonlocality proof for the class of
maximally entangled states is considered. A detailed analysis shows that the
incompatibility of the Hardy equations for this class of states physically
originates from the fact that the existence of quantum perfect correlations for
the three pairs of two-valued observables (D_11,D_21), (D_11,D_22) and
(D_12,D_21) [in the sense of having with certainty equal (different) readings
for a joint measurement of any one of the pairs (D_11,D_21), (D_11,D_22), and
(D_12,D_21)], necessarily entails perfect correlation for the pair of
observables (D_12,D_22) [in the sense of having with certainty equal
(different) readings for a joint measurement of the pair (D_12,D_22)]. Indeed,
the set of these four perfect correlations is found to satisfy the CHSH
inequality, and then no violations of local realism will arise for the
maximally entangled state as far as the four observables D_ij, i,j = 1,2, are
concerned. The connection between this fact and the impossibility for the
quantum mechanical predictions to give the maximum possible theoretical
violation of the CHSH inequality is pointed out. Moreover, it is generally
proved that the fulfillment of all the Hardy nonlocality conditions necessarily
entails a violation of the resulting CHSH inequality. The largest violation of
this latter inequality is determined.


  Object detection or localization is an incremental step in progression from
coarse to fine digital image inference. It not only provides the classes of the
image objects, but also provides the location of the image objects which have
been classified. The location is given in the form of bounding boxes or
centroids. Semantic segmentation gives fine inference by predicting labels for
every pixel in the input image. Each pixel is labelled according to the object
class within which it is enclosed. Furthering this evolution, instance
segmentation gives different labels for separate instances of objects belonging
to the same class. Hence, instance segmentation may be defined as the technique
of simultaneously solving the problem of object detection as well as that of
semantic segmentation. In this survey paper on instance segmentation -- its
background, issues, techniques, evolution, popular datasets, related work up to
the state of the art and future scope have been discussed. The paper provides
valuable information for those who want to do research in the field of instance
segmentation.


  The zero temperature, or quantum, metal-superconductor phase transition is
studied in disordered systems in dimension greater than two. A effective local
field theory is developed that keeps all soft modes or fluctuations explicitly.
A simple renormalization group analysis is used to exactly determine the
quantum critical behavior at this transition.


  In this paper, we investigate the integrability aspects of a physically
important nonlinear oscillator which lacks sufficient number of Lie point
symmetries but can be integrated by quadrature. We explore the hidden symmetry,
construct a second integral and derive the general solution of this oscillator
by employing the recently introduced $\lambda$-symmetry approach and thereby
establish the complete integrability of this nonlinear oscillator equation from
a group theoretical perspective.


  While imitation learning for vision based autonomous mobile robot navigation
has recently received a great deal of attention in the research community,
existing approaches typically require state action demonstrations that were
gathered using the deployment platform. However, what if one cannot easily
outfit their platform to record these demonstration signals or worse yet the
demonstrator does not have access to the platform at all? Is imitation learning
for vision based autonomous navigation even possible in such scenarios? In this
work, we hypothesize that the answer is yes and that recent ideas from the
Imitation from Observation (IfO) literature can be brought to bear such that a
robot can learn to navigate using only ego centric video collected by a
demonstrator, even in the presence of viewpoint mismatch. To this end, we
introduce a new algorithm, Visual Observation only Imitation Learning for
Autonomous navigation (VOILA), that can successfully learn navigation policies
from a single video demonstration collected from a physically different agent.
We evaluate VOILA in the photorealistic AirSim simulator and show that VOILA
not only successfully imitates the expert, but that it also learns navigation
policies that can generalize to novel environments. Further, we demonstrate the
effectiveness of VOILA in a real world setting by showing that it allows a
wheeled Jackal robot to successfully imitate a human walking in an environment
using a video recorded using a mobile phone camera.


  The space of possible grain boundary structures is vast, with 5 macroscopic,
crystallographic degrees of freedom that define the character of a grain
boundary. While numerous datasets of grain boundaries have examined this space
in part or in full, we present a computed dataset of over 7304 unique aluminum
grain boundaries in the 5D crystallographic space. Our sampling also includes a
range of possible microscopic, atomic configurations for each unique 5D
crystallographic structure, which total over 43 million structures. We present
an overview of the methods used to generate this dataset, an initial
examination of the energy trends that follow the Read-Shockley relationship,
hints at trends throughout the 5D space, variations in GB energy when
non-minimum energy structures are examined, and insights gained in machine
learning of grain boundary energy structure-property relationships. This
dataset, which is available for download, has great potential for insight into
GB structure-property relationships.


  The 1950s-- and perhaps also the 1960s-- were very special times for the
development of solid-state/condensed-matter physics. The University of Illinois
at Urbana was at the center of these activities. In areas like NMR and
superconductivity, methods were developed which would form the basis for the
next half century of science and technology. Experimentalists, including
Charlie and John Wheatley, worked hand in hand with theorists, including the
incomparable John Bardeen. They worked cooperatively to develop ideas, often
born in Urbana, but with godparents at Harvard and Moscow and Paris. A
characteristic style of broad collaboration and spirited exchange developed and
spread from Illinois. This development was not an accident but the result of
the vision of leaders like Wheeler Loomis, Fred Seitz, and later Gerald Almy1.
The strong leadership saved the other scientists from expending their time on
departmental decision-making. The style of the scientific activity was set by
Fred, who strongly encouraged joint activities--especially the interaction
between between theory and experiment and between physics and engineering. Fred
encouraged comments from everyone, and helped everyone grow fast


  In this paper we discuss geodesic Witten diagrams in general holographic
conformal field theories with boundary or defect. In boundary or defect
conformal field theory, two-point functions are non-trivial and can be
decomposed into conformal blocks in two distinct ways; ambient channel
decomposition and boundary channel decomposition. In our previous work we only
consider two-point functions of same operators. We generalize our previous work
to a situation where operators in two-point functions are different. We obtain
two distinct decomposition for two-point functions of different operators.


  Ouzo is a well-known drink in Mediterranean countries, with ingredients
water, alcohol and trans-anethole oil. The oil is insoluble in water, but
completely soluble in alcohol, so when water is added to the spirit, the
available alcohol is depleted and the mixture exhibits spontaneous
emulsification. This process is commonly known as the louche or Ouzo effect.
Although the phase boundaries of this archetypal ternary mixture are well
known, the properties of coexisting phases have not previously been studied.
Here, we present a detailed experimental investigation into the phase
behaviour, including tie-lines connecting coexisting phases, determination of
the critical point (also called the plait point in ternary systems) and
measurements of the surface tension and density for varying alcohol
concentrations. Additionally, we present a theory for the thermodynamics and
phase diagram of the system. With suitable selection of the interaction
parameters, the theory captures nearly all features of the experimental work.
This simple model can be used to determine both bulk and non-uniform (e.g.
interfacial) properties, paving the way for a wide range of future applications
of the model to ternary mixtures in general. We show how our accurate
equilibrium phase diagram can be used to provide improved understanding of
non-equilibrium phenomena.


  Monte Carlo (MC) simulations have been carried out to study the adsorption on
square and triangular lattices of particles with two bonding sites that, by
decreasing temperature or increasing density, polymerize reversibly into chains
with a discrete number of allowed directions and, at the same time, undergo a
continuous isotropic-nematic (IN) transition. The process has been monitored by
following the behavior of the adsorption isotherms for different values of
lateral interaction energy/temperature. The numerical data were compared with
mean-field analytical predictions and exact functions for noninteracting and 1D
systems. The obtained results revealed the existence of three adsorption
regimes in temperature. (1) At high temperatures, above the critical one
characterizing the IN transition at full coverage Tc(\theta=1), the particles
are distributed at random on the surface and the adlayer behaves as a
noninteracting 2D system. (2) At very low temperatures, the asymmetric monomers
adsorb forming chains over almost the entire range of coverage, and the
adsorption process behaves as a 1D problem. (3) In the intermediate regime, the
system exhibits a mixed regime and the filling of the lattice proceeds
according to two different processes. In the first stage, the monomers adsorb
isotropically on the lattice until the IN transition occurs in the system and,
from this point, particles adsorb forming chains so that the adlayer behaves as
a 1D fluid. The two adsorption processes are present in the adsorption
isotherms, and a marked singularity can be observed that separates both
regimes. Thus, the adsorption isotherms appear as sensitive quantities with
respect to the IN phase transition, allowing us (i) to reproduce the phase
diagram of the system for square lattices and (ii) to obtain an accurate
determination of the phase diagram for triangular lattices.


  Time series forecasting is a demanding task ranging from weather to failure
forecasting with black-box models achieving state-of-the-art performances.
However, understanding and debugging are not guaranteed. We propose TS-MULE, a
local surrogate model explanation method specialized for time series extending
the LIME approach. Our extended LIME works with various ways to segment and
perturb the time series data. In our extension, we present six sampling
segmentation approaches for time series to improve the quality of surrogate
attributions and demonstrate their performances on three deep learning model
architectures and three common multivariate time series datasets.


  Strongly interacting two dimensional electron systems (2DESs) host a complex
landscape of broken symmetry states. The possible ground states are further
expanded by internal degrees of freedom such as spin or valley-isospin. While
direct probes of spin in 2DESs were demonstrated two decades ago, the valley
quantum number has only been probed indirectly in semiconductor quantum wells,
graphene mono- and bilayers, and transition-metal dichalcogenides. Here, we
present the first direct experimental measurement of valley polarization in a
two dimensional electron system, effected via the direct mapping of the valley
quantum number onto the layer polarization in bilayer graphene at high magnetic
fields. We find that the layer polarization evolves in discrete steps across 32
electric field-tuned phase transitions between states of different valley,
spin, and orbital polarization. Our data can be fit by a model that captures
both single particle and interaction induced orbital, valley, and spin
anisotropies, providing the most complete model of this complex system to date.
Among the newly discovered phases are theoretically unanticipated orbitally
polarized states stabilized by skew interlayer hopping. The resulting roadmap
to symmetry breaking in bilayer graphene paves the way for deterministic
engineering of fractional quantum Hall states, while our layer-resolved
technique is readily extendable to other two dimensional materials where layer
polarization maps to the valley or spin quantum numbers, providing an essential
direct probe that is a prerequisite for manipulating these new quantum degrees
of freedom.


  Instruction tuning is a burgeoning method to elicit the general intelligence
of Large Language Models (LLMs). However, the creation of instruction data is
still largely heuristic, leading to significant variation in quantity and
quality across existing datasets. While some research advocates for expanding
the number of instructions, others suggest that a small set of well-chosen
examples is adequate. To better understand data construction guidelines, our
research provides a granular analysis of how data volume, parameter size, and
data construction methods influence the development of each underlying ability
of LLM, such as creative writing, code generation, and logical reasoning. We
present a meticulously curated dataset with over 40k instances across ten
abilities and examine instruction-tuned models with 7b to 33b parameters. Our
study reveals three primary findings: (i) Despite the models' overall
performance being tied to data and parameter scale, individual abilities have
different sensitivities to these factors. (ii) Human-curated data strongly
outperforms synthetic data from GPT-4 in efficiency and can constantly enhance
model performance with volume increases, but is unachievable with synthetic
data. (iii) Instruction data brings powerful cross-ability generalization, as
evidenced by out-of-domain evaluations. Furthermore, we demonstrate how these
findings can guide more efficient data constructions, leading to practical
performance improvements on two public benchmarks.


  Human decision making is well known to be imperfect and the ability to
analyse such processes individually is crucial when attempting to aid or
improve a decision-maker's ability to perform a task, e.g. to alert them to
potential biases or oversights on their part. To do so, it is necessary to
develop interpretable representations of how agents make decisions and how this
process changes over time as the agent learns online in reaction to the accrued
experience. To then understand the decision-making processes underlying a set
of observed trajectories, we cast the policy inference problem as the inverse
to this online learning problem. By interpreting actions within a potential
outcomes framework, we introduce a meaningful mapping based on agents choosing
an action they believe to have the greatest treatment effect. We introduce a
practical algorithm for retrospectively estimating such perceived effects,
alongside the process through which agents update them, using a novel
architecture built upon an expressive family of deep state-space models.
Through application to the analysis of UNOS organ donation acceptance
decisions, we demonstrate that our approach can bring valuable insights into
the factors that govern decision processes and how they change over time.


  The ``Little Higgs'' opens up a new avenue for natural electroweak symmetry
breaking in which the standard model Higgs particle is realized as a
pseudo-Goldstone boson and thus is generically light. The symmetry breaking
structure of the Little Higgs models predicts a large multiplet of
(pseudo-)Goldstone bosons and their low energy interactions below the
ultraviolet (UV) completion scale $\Lambda \sim 4\pi f \sim O(10)$ TeV, where
$f$ is the Goldstone decay constant. We study unitarity of the Little Higgs
models by systematically analyzing the high energy scatterings of these
(pseudo-)Goldstone bosons. We reveal that the collective effect of the
Goldstone scatterings via coupled channel analysis tends to push the unitarity
violation scale $\Lambda_U$ significantly below the conventional UV scale
$\Lambda \sim 4\pi f$ as estimated by naive dimensional analysis (NDA).
Specifically, $\Lambda_U \sim (3-4)f$, lying in the multi-TeV range for $f\sim
1$ TeV. We interpret this as an encouraging sign that the upcoming LHC may
explore aspects of Little Higgs UV completions, and we discuss some potential
signatures. The meanings of the two estimated UV scales $\Lambda_U$ (from
unitarity violation) and $\Lambda$ (from NDA) together with their implications
for an effective field theory analysis of the Little Higgs models are also
discussed.


  In even spacetime dimensions, the interacting bosonic conformal higher-spin
(CHS) theory can be realised as an induced action. The main ingredient in this
definition is the model $\mathcal{S}[\varphi,h]$ describing a complex scalar
field $\varphi$ coupled to an infinite set of background CHS fields $h$, with
$\mathcal{S}[\varphi,h]$ possessing a non-abelian gauge symmetry. Two
characteristic features of the perturbative constructions of
$\mathcal{S}[\varphi , h]$ given in the literature are: (i) the background
spacetime is flat; and (ii) conformal invariance is not manifest. In the
present paper we provide a new derivation of this action in four dimensions
such that (i) $\mathcal{S}[\varphi , h]$ is defined on an arbitrary
conformally-flat background; and (ii) the background conformal symmetry is
manifestly realised. Next, our results are extended to the $\mathcal{N}=1$
supersymmetric case. Specifically, we construct, for the first time, a model
$\mathcal{S}[\Phi, H]$ for a conformal scalar/chiral multiplet $\Phi$ coupled
to an infinite set of background higher-spin superfields $H$. Our action
possesses a non-abelian gauge symmetry which naturally generalises the
linearised gauge transformations of conformal half-integer superspin
multiplets. The other fundamental features of this model are: (i)
$\mathcal{S}[\Phi, H]$ is defined on an arbitrary conformally-flat superspace
background; and (ii) the background $\mathcal{N}=1$ superconformal symmetry is
manifest. Making use of $\mathcal{S}[\Phi, H]$, an interacting superconformal
higher-spin theory can be defined as an induced action.


  Ionization profile monitors (IPMs) are widely used in particle accelerators
for fast evaluation of parameters of high energy beams. Due to the space-charge
effects and several other physical reasons, as well as due to instrumental
effects, the measured IPM profiles differ from the those of the beams.
Empirical mathematical models are commonly used for reconstruction of the
profiles. Here we present proper correction algorithm based on the space-charge
dynamics of the secondaries in IPMs. We also demonstrate efficiency of the beam
size reconstruction from experimentally measured profiles and discuss practical
aspects limiting the IPM accuracy.


  Thermalization of chaotic quantum many-body systems under unitary time
evolution is related to the growth in complexity of initially simple Heisenberg
operators. Operator growth is a manifestation of information scrambling and can
be diagnosed by out-of-time-order correlators (OTOCs). However, the behavior of
OTOCs of local operators in generic chaotic local Hamiltonians remains poorly
understood, with some semiclassical and large N models exhibiting exponential
growth of OTOCs and a sharp chaos wavefront and other random circuit models
showing a diffusively broadened wavefront. In this paper we propose a unified
physical picture for scrambling in chaotic local Hamiltonians. We construct a
random time-dependent Hamiltonian model featuring a large N limit where the
OTOC obeys a Fisher-Kolmogorov-Petrovsky-Piskunov (FKPP) type equation and
exhibits exponential growth and a sharp wavefront. We show that quantum
fluctuations manifest as noise (distinct from the randomness of the couplings
in the underlying Hamiltonian) in the FKPP equation and that the noise-averaged
OTOC exhibits a cross-over to a diffusively broadened wavefront. At small N we
demonstrate that operator growth dynamics, averaged over the random couplings,
can be efficiently simulated for all time using matrix product state
techniques. To show that time-dependent randomness is not essential to our
conclusions, we push our previous matrix product operator methods to very large
size and show that data for a time-independent Hamiltonian model are also
consistent with a diffusively-broadened wavefront.


  The Effelsberg-Bonn HI Survey (EBHIS) covers the whole sky north of Dec(2000)
= -5 deg. on a fully sampled angular grid. Using state-of-the-art
FPGA-spectrometers we perform a Milky Way and an extragalactic HI survey in
parallel. Moreover, the high dynamic range and short dump time of the HI
spectra allow to overcome the vast majority of all radio-frequency-interference
(RFI) events. The Milky Way data will be corrected for the stray-radiation bias
which warrants a main-beam efficiency of 99%. Towards the whole survey area we
exceed the sensitivity limit of HIPASS, while towards the
Sloan-Digital-Sky-Survey (SDSS) area EBHIS offers an order of magnitude higher
mass sensitivity. The Milky Way data will be a cornerstone for multi-frequency
astrophysics, while the extragalactic part will disclose detailed information
on the structure formation of the local universe.


  The momentum distribution of the electron in the reaction p+He $\rightarrow$
H + He$^{2+}$ + $e$ is measured for projectile energies $E_p$=300 and 630 keV/u
at very small scattering angles of hydrogen. We mainly present two dimensional
distributions parallel $(k_{||})$ and perpendicular $(k_{\perp})$ to the
projectile beam. Theoretical calculations were carried out within the Plane
Wave First Born Approximation (PWFBA), which includes both electron emission
mechanisms, shake-off and sequential capture and ionization. It is shown that
electron correlations in the target wave function play the most important role
in the explanation of experimentally observed backward emission. Second order
effects have to be involved to correctly describe the forward emission of the
electron.


  The significance of zero modes in the path-integral quantization of some
solitonic models is investigated. In particular a Skyrme-like theory with
topological vortices in (1+2) dimensions is studied, and with a BRST invariant
gauge fixing a well defined transition amplitude is obtained in the one loop
approximation. We also present an alternative method which does not necessitate
evoking the time-dependence in the functional integral, but is equivalent to
the original one in dealing with the quantization in the background of the
static classical solution of the non-linear field equations. The considerations
given here are particularly useful in - but also limited to - the one-loop
approximation.


  We describe a perfect correspondence between skew monoidal categories and
certain generalised multicategories, called skew multicategories, that arise in
nature.


  We compute the number counts of clusters of galaxies, the logN-logS relation,
in several X-ray and submm bands on the basis of the Press-Schechter theory. We
pay particular attention to a set of theoretical models which well reproduce
the ROSAT 0.5-2 keV band logN-logS, and explore possibilities to further
constrain the models from future observations with ASCA and/or at submm bands.
The latter is closely related to the European PLANCK mission and the Japanese
Large Millimeter and Submillimeter Array (LMSA) project. We exhibit that one
can break the degeneracy in an acceptable parameter region on the $\Omega_0 -
\sigma_8$ plane by combining the ROSAT logN-logS and the submm number counts.
Models which reproduce the ROSAT band logN-logS will have $N(>S) \sim (150-300)
(S/10^{-12} erg cm^{-2} s^{-1})^{-1.3}$ str$^{-1}$ at $S > 10^{-12} erg cm^{-2}
s^{-1}$ in the ASCA 2-10 keV band, and $N(>S_\nu) \sim (10^2-10^4) (S_\nu/100
mJy)^{-1.5} str^{-1}$ at $S_\nu > 100 mJy$ in the submm (0.85mm) band. The
amplitude of the logN-logS is very sensitive to the model parameters in the
submm band. We also compute the redshift evolution of the cluster number counts
and compare with that of the X-ray brightest Abell-type clusters. The results,
although still preliminary, point to low density ($\Omega_0\sim 0.3$)
universes. The contribution of clusters to the X-ray and submm background
radiations is shown to be insignificant in any model compatible with the ROSAT
logN-logS.


  We consider how superconducting microwave detector technology might be
applied to the readout of cavity-axion haloscopes and similar fundamental
physics experiments. Expressions for the sensitivity of two detection schemes
are derived: 1) a dispersive spectrometer, and 2) a direct-conversion/homodyne
receiver using detectors as mixing elements. In both cases the
semi-classical/Poisson-mixture approach is used to account for quantum effects.
Preliminary sensitivity calculations are performed to guide future development
work. These suggest the homodyne scheme offers a near-term solution for
realising near-quantum-noise limited receivers with improved usability compared
with parametric amplifiers. Similarly, they show that the dispersive
spectrometer offers a potential way to beat the quantum noise limit, but that
significant technological development work is needed to do so.


  Miscommunication and communication challenges between instructors and
students represents one of the primary barriers to post-secondary learning.
Students often avoid or miss opportunities to ask questions during office hours
due to insecurities or scheduling conflicts. Moreover, students need to work at
their own pace to have the freedom and time for the self-contemplation needed
to build conceptual understanding and develop creative thinking skills. To
eliminate barriers to student engagement, academic institutions need to
redefine their fundamental approach to education by proposing flexible
educational pathways that recognize continuous learning. To this end, we
developed an AI-augmented intelligent educational assistance framework based on
a power language model (i.e., GPT-3) that automatically generates
course-specific intelligent assistants regardless of discipline or academic
level. The virtual intelligent teaching assistant (TA) system will serve as a
voice-enabled helper capable of answering course-specific questions concerning
curriculum, logistics and course policies. It is envisioned to improve access
to course-related information for the students and reduce logistical workload
for the instructors and TAs. Its GPT-3-based knowledge discovery component as
well as the generalized system architecture is presented accompanied by a
methodical evaluation of the system accuracy and performance.


  Staring from the Lagrangian density that foots on the meson-propagated
picture of nuclear force, the full Hamiltonian, that contains both mean field
and pairing contributions, is derived by quantizing the Dirac spinor field in
the Bogoliubov quasi-particle space, and the expectation with respect to the
Bogoliubov ground state gives the full energy functional. As an extension of
the D-RHF model, the degree of freedom associated with the $\rho$-tensor
($\rho$-T) coupling is implemented, and incorporating with the Bogoliubov
scheme the finite-range Gogny force D1S is utilized as the pairing force.
Moreover, qualitative analysis on the nature of the $\pi$-PV and $\rho$-T
couplings are presented for better understanding their enhancements on the
deformation effects.
  Space convergence related to the spherical DWS base is confirmed for the
D-RHFB model by taking light nucleus $^{24}$Mg and mid-heavy one $^{156}$Sm as
candidates. Compared to light nuclei, extraordinary more negative energy states
are necessitated to keep the expansion completeness on the spherical DWS base
for mid-heavy and heavy nuclei, due to the enhanced correlations between the
expansion components with large $\kappa$-quantity as indicated by the nature of
the $\pi$-PV and $\rho$-T couplings. Furthermore, because of the enhanced
deformation effects by the $\pi$-PV and $\rho$-T couplings, the RHF Lagrangian
PKA1 presents deeper bound ground state for $^{24}$Mg than the other selected
Lagrangians, in addition to predicting a fairly deep bound local minimum with
large oblate deformation.


  The control of complex networks has generated a lot of interest in a variety
of fields from traffic management to neural systems. A commonly used metric to
compare two particular control strategies that accomplish the same task is the
control energy, the integral of the sum of squares of all control inputs. The
minimum control energy problem determines the control input that lower bounds
all other control inputs with respect to their control energies. Here, we focus
on the infinite lattice graph with linear dynamics and analytically derive the
expression for the minimum control energy in terms of the modified Bessel
function. We then demonstrate that the control energy of the infinite lattice
graph accurately predicts the control energy of finite lattice graphs.


  The recent detection of possible neutrino emission from the blazar TXS
0506+056 was the first high-energy neutrino associated with an astrophysical
source, making this special type of active galaxies promising neutrino
emitters. The fact that two distinct episodes of neutrino emission were
detected with a separation of around 3 years suggests that emission could be
periodic. Periodic emission is expected from supermassive binary black hole
systems due to jet precession close to the binary's merger. Here we show that
if TXS 0506+056 is a binary source then the next neutrino flare could occur
before the end of 2021. We derive the binary properties that would lead to the
detection of gravitational waves from this system by LISA. Our results for the
first time quantify the time scale of these correlations for the example of TXS
0506+056, providing clear predictions for both the neutrino and
gravitational-wave signatures of such sources.


  Channel linear Weingarten surfaces in space forms are investigated in a Lie
sphere geometric setting, which allows for a uniform treatment of different
ambient geometries. We show that any channel linear Weingarten surface in a
space form is isothermic and, in particular, a surface of revolution in its
ambient space form. We obtain explicit parametrisations for channel surfaces of
constant Gauss curvature in space forms, and thereby for a large class of
linear Weingarten surfaces up to parallel transformation.


  Nonlinear magneto-optical (NMO) resonances occurring for near-zero magnetic
field are studied in Rb vapor using light-noise spectroscopy. With a balanced
detection polarimeter, we observe high contrast variations of the noise power
(at fixed analysis frequency) carried by diode laser light resonant with the
5S$_{1/2}(F=2) \to 5$P$_{1/2}(F=1) $ transition of $^{87}$Rb and transmitted
through a rubidium vapor cell, as a function of magnetic field $B$. A symmetric
resonance doublet of anti-correlated noise is observed for orthogonal
polarizations around $B=0 $ as a manifestation of ground state coherence. We
also observe sideband noise resonances when the magnetic field produces an
atomic Larmor precession at a frequency corresponding to one half of the
analysis frequency. The resonances on the light fluctuations are the
consequence of phase to amplitude noise conversion owing to nonlinear coherence
effects in the response of the atomic medium to the fluctuating field. A
theoretical model (derived from linearized Bloch equations) is presented that
reproduces the main qualitative features of the experimental signals under
simple assumptions.


  In this work we study the increasing resolution of linear inverse scattering
problems at a large fixed frequency. We consider the problem of recovering the
density of a Herglotz wave function, and the linearized inverse scattering
problem for a potential. It is shown that the number of features that can be
stably recovered (stable region) becomes larger as the frequency increases,
whereas one has strong instability for the rest of the features (unstable
region). To show this rigorously, we prove that the singular values of the
forward operator stay roughly constant in the stable region and decay
exponentially in the unstable region. The arguments are based on structural
properties of the problems and they involve the Courant min-max principle for
singular values, quantitative Agmon-H\"ormander estimates, and a Schwartz
kernel computation based on the coarea formula.


  The homotopy theory of higher categorical structures has become a relevant
part of the machinery of algebraic topology and algebraic K-theory, and this
paper contains contributions to the study of the relationship between
B\'enabou's bicategories and the homotopy types of their classifying spaces.
Mainly, we state and prove an extension of Quillen's Theorem B by showing,
under reasonable necessary conditions, a bicategory-theoretical interpretation
of the homotopy-fibre product of the continuous maps induced on classifying
spaces by a diagram of bicategories $\mathcal{A}\to\mathcal{B}\leftarrow
\mathcal{A}'$. Applications are given for the study of homotopy pullbacks of
monoidal categories and of crossed modules.


  We introduce strong left ideals of skew braces and prove that they produce
non-trivial decomposition of set-theoretic solutions of the Yang-Baxter
equation. We study factorization of skew left braces through strong left ideals
and we prove analogs of It\^{o}'s theorem in the context of skew left braces.
As a corollary, we obtain applications to the retractability problem of
involutive non-degenerate solutions of the Yang-Baxter equation. Finally, we
classify skew braces that contain no non-trivial proper ideals.


  The main objective of this paper is to study the effect of a cold, vertical,
arc-shaped control plate on the flow characteristics and forced convective heat
transfer mechanism across a rotary oscillating, isothermally heated circular
cylinder. Two-dimensional, unsteady, incompressible, laminar, and viscous flow
of a Newtonian, constant property fluid is considered across the cylinder. The
simulations are performed with an in-house code for various gap ratios between
the control plate and the cylinder ($0\leq d/R_0 \leq 3$), maximum angular
velocity ($0.5\leq \alpha_m \leq 4$) and frequency ratio of oscillation
($f/f_0=0.5,\ 3$) at Prandtl number $0.7$ and Reynolds number $150$. Here, $d$
denotes the gap between the surface of the cylinder and the leading surface of
the control plate, $R_0$ denotes the radius of the cylinder, $f$ is the
frequency of oscillation and $f_0$ is the frequency of natural vortex shedding.
$d/R_0=0$ corresponds to the no plate case. Heat transfer and vortex shedding
phenomena are discussed in relation to one another. A significant increase in
heat transmission is observed for all $\alpha_m$ with the gap ratio of
$d/R_0=0.5$ and $f/f_0=0.5$. The heat absorption on the surface of the control
plate decreases to zero with increasing gap ratio when $\alpha_m=0.5$ and
$f/f_0=0.5$ but never becomes zero when $\alpha_m=4$ and $f/f_0=3$.
Additionally, when compared to the no plate case with $(\alpha_m,\
f/f_0)=(0.5,\ 0.5)$, the maximum peak of the drag coefficient is decreased by
$9.877\%$ for the gap ratio of $d/R_0=3$. For $\alpha_m=4$ and $f/f_0=3$, the
smallest gap ratio of $d/R_0=0.5$ is found to significantly increase the lift
coefficient relative to other cases.


  Control reserves are power generation or consumption entities that ensure
balance of supply and demand of electricity in real-time. In many countries,
they are operated through a market mechanism in which entities provide bids.
The system operator determines the accepted bids based on an optimization
algorithm. We develop the Vickrey-Clarke-Groves (VCG) mechanism for these
electricity markets. We show that all advantages of the VCG mechanism including
incentive compatibility of the equilibria and efficiency of the outcome can be
guaranteed in these markets. Furthermore, we derive conditions to ensure
collusion and shill bidding are not profitable. Our results are verified with
numerical examples.


  Let \q be a simple algebraic group of type A or C over a field of good
positive characteristic. We show for any x \in \q =\Lie(Q) that the invariant
algebra S(\q_x)^{\q_x} is generated by the p^{th} power subalgebra and the mod
p reduction of the characteristic zero invariant algebra. The latter algebra is
known to be polynomial \cite{PPY} and we show that it remains so after
reduction. Using a theory of symmetrisation in positive characteristic we prove
the analogue of this result in the enveloping algebra, where the p-centre plays
the role of the p^{th} power subalgebra. In Zassenhaus' foundational work
\cite{Zas}, the invariant theory and representation theory of modular Lie
algebras were shown to be explicitly intertwined. We exploit his theory to give
a precise upper bound for the dimensions of simple \q_x-modules.
  When \g is of type A and \g = \k \oplus \p is a symmetric decomposition of
orthogonal type we use similar methods to show that for every nilpotent e \in
\k the invariant algebra S(\p_e)^{\k_e} is generated by the p^{th} power
subalgebra and S(\p_e)^{K_e} which is also shown to be polynomial.


  We present our recent results for the pion elastic form factor [1] obtained
within a local-duality three-point sum rule (a Borel sum rule in the limit of
an infinite Borel parameter). Our analysis includes the O(1) and O(\alpha_s)
contributions and is therefore applicable in a broad range of spacelike
momentum transfers. Our results demonstrate in essentially model-independent
way that the O(1) term, which provides the subleading 1/Q^4 power correction at
asymptotically large momentum transfers, contributes more than half of the pion
form factor in the region Q^2 \le 20 GeV^2. To probe the accuracy of
local-duality sum rules for form factors, we apply precisely the same
procedures to extract the form factor in a quantum-mechanical potential model.
Comparison of the exact form factor known in this model with the result of the
sum-rule calculation gives a probe of the systematic error of the method. In
our example this error is found to be at the level of 10-20%. We expect similar
systematic errors for form factors obtained from local-duality sum rules in
QCD.


  OpenStreetMap (OSM) is currently the richest publicly available information
source on geographic entities (e.g., buildings and roads) worldwide. However,
using OSM entities in machine learning models and other applications is
challenging due to the large scale of OSM, the extreme heterogeneity of entity
annotations, and a lack of a well-defined ontology to describe entity semantics
and properties. This paper presents GeoVectors - a unique, comprehensive
world-scale linked open corpus of OSM entity embeddings covering the entire OSM
dataset and providing latent representations of over 980 million geographic
entities in 180 countries. The GeoVectors corpus captures semantic and
geographic dimensions of OSM entities and makes these entities directly
accessible to machine learning algorithms and semantic applications. We create
a semantic description of the GeoVectors corpus, including identity links to
the Wikidata and DBpedia knowledge graphs to supply context information.
Furthermore, we provide a SPARQL endpoint - a semantic interface that offers
direct access to the semantic and latent representations of geographic entities
in OSM.


  Educational achievement distributions for Australian indigenous and
nonindigenous populations in the years 2001, 2006, 2014 and 2017 are
considered. Bayesian inference is used to analyse how these ordinal categorical
distributions have changed over time and to compare indigenous and
nonindigenous distributions. Both the level of educational achievement and
inequality in educational achievement are considered. To compare changes in
levels over time, as well as inequality between the two populations, first
order stochastic dominance and an index of educational poverty are used. To
examine changes in inequality over time, two inequality indices and generalised
Lorenz dominance are considered. Results are presented in terms of posterior
densities for the indices and posterior probabilities for dominance for the
dominance comparisons. We find some evidence of improvement over time,
especially in the lower parts of the indigenous distribution and that
inequality has significantly increased from 2001 to 2017.


  We show explicit estimates on the number of $q$--rational points of an
$F_q$--definable affine absolutely irreducible variety of the algebraic closure
of the finite field $F_q$ of $q$ elements. Our estimates for a hypersurface
significantly improve previous estimates of W. Schmidt and M.-D. Huang and
Y.-C. Wong, while in the case of a variety our estimates improve those of S.
Ghorpade and G. Lachaud in several important cases. Our proofs rely on
elementary methods of effective elimination theory and suitable effective
versions of the first Bertini theorem.


  Vector Quantization, VQ is a popular image compression technique with a
simple decoding architecture and high compression ratio. Codebook designing is
the most essential part in Vector Quantization. LindeBuzoGray, LBG is a
traditional method of generation of VQ Codebook which results in lower PSNR
value. A Codebook affects the quality of image compression, so the choice of an
appropriate codebook is a must. Several optimization techniques have been
proposed for global codebook generation to enhance the quality of image
compression. In this paper, a novel algorithm called IDE-LBG is proposed which
uses Improved Differential Evolution Algorithm coupled with LBG for generating
optimum VQ Codebooks. The proposed IDE works better than the traditional DE
with modifications in the scaling factor and the boundary control mechanism.
The IDE generates better solutions by efficient exploration and exploitation of
the search space. Then the best optimal solution obtained by the IDE is
provided as the initial Codebook for the LBG. This approach produces an
efficient Codebook with less computational time and the consequences include
excellent PSNR values and superior quality reconstructed images. It is observed
that the proposed IDE-LBG find better VQ Codebooks as compared to IPSO-LBG,
BA-LBG and FA-LBG.


  We present a novel technique for learning semantic representations, which
extends the distributional hypothesis to multilingual data and joint-space
embeddings. Our models leverage parallel data and learn to strongly align the
embeddings of semantically equivalent sentences, while maintaining sufficient
distance between those of dissimilar sentences. The models do not rely on word
alignments or any syntactic information and are successfully applied to a
number of diverse languages. We extend our approach to learn semantic
representations at the document level, too. We evaluate these models on two
cross-lingual document classification tasks, outperforming the prior state of
the art. Through qualitative analysis and the study of pivoting effects we
demonstrate that our representations are semantically plausible and can capture
semantic relationships across languages without parallel data.


  When answering a question, humans utilize the information available across
different modalities to synthesize a consistent and complete chain of thought
(CoT). This process is normally a black box in the case of deep learning models
like large-scale language models. Recently, science question benchmarks have
been used to diagnose the multi-hop reasoning ability and interpretability of
an AI system. However, existing datasets fail to provide annotations for the
answers, or are restricted to the textual-only modality, small scales, and
limited domain diversity. To this end, we present Science Question Answering
(ScienceQA), a new benchmark that consists of ~21k multimodal multiple choice
questions with a diverse set of science topics and annotations of their answers
with corresponding lectures and explanations. We further design language models
to learn to generate lectures and explanations as the chain of thought (CoT) to
mimic the multi-hop reasoning process when answering ScienceQA questions.
ScienceQA demonstrates the utility of CoT in language models, as CoT improves
the question answering performance by 1.20% in few-shot GPT-3 and 3.99% in
fine-tuned UnifiedQA. We also explore the upper bound for models to leverage
explanations by feeding those in the input; we observe that it improves the
few-shot performance of GPT-3 by 18.96%. Our analysis further shows that
language models, similar to humans, benefit from explanations to learn from
fewer data and achieve the same performance with just 40% of the data. The data
and code are available at https://scienceqa.github.io.


  Most early Universe scenarios predict negligible magnetic fields on
cosmological scales if they are unprocessed during subsequent expansion of the
Universe. We present a new numerical treatment of the evolution of primordial
fields and apply it to weakly helical seeds as they occur in certain early
Universe scenarios. We find that initial helicities not much larger than the
baryon to photon number can lead to fields of about 10^{-13} Gauss with
coherence scales slightly below a kilo-parsec today.


  Extracting a proper dynamic network for modelling a time-dependent complex
system is an important issue. Building a correct model is related to finding
out critical time points where a system exhibits considerable change. In this
work, we propose to measure network similarity to detect proper time intervals.
We develop three similarity metrics, node, link, and neighborhood similarities,
for any consecutive snapshots of a dynamic network. Rather than a label or a
user-defined threshold, we use statistically expected values of proposed
similarities under a null-model to state whether the system changes critically.
We experimented on two different data sets with different temporal dynamics:
The Wi-Fi access points logs of a university campus and Enron emails. Results
show that, first, proposed similarities reflect similar signal trends with
network topological properties with less noisy signals, and their scores are
scale invariant. Second, proposed similarities generate better signals than
adjacency correlation with optimal noise and diversity. Third, using
statistically expected values allows us to find different time intervals for a
system, leading to the extraction of non-redundant snapshots for dynamic
network modelling.


  Micro/nano porous polymeric material is considered a unique industrial
material due to its extremely low thermal conductivity, low density, and high
surface area. Therefore, it is necessary to establish an accurate thermal
conductivity prediction model suiting their applicable conditions and provide a
theoretical basis for expanding of their applications. In this work, the
development of the calculation model of equivalent thermal conductivity of
micro/nano porous polymeric materials in recent years was summarized. Firstly,
it reviews the process of establishing the overall equivalent thermal
conductivity calculation model for micro/nano porous polymers. Then, the
predicted calculation models of thermal conductivity are introduced according
to the conductive thermal conductivity models and the radiative thermal
conductivity models separately. In addition, the thermal conduction part is
divided into the gaseous thermal conductivity model, solid thermal conductivity
model and gas-solid coupling model. Finally, it is concluded that, compared
with other porous materials, there are few studies on heat transfer of
micro/nano porous polymers, especially on the special heat transfer mechanisms
such as scale effects at the micro/nanoscale. In particular, the following
aspects of porous polymers still need to be further studied: micro scaled
thermal radiation, heat transfer characteristics of special morphologies at the
nanoscale, heat transfer mechanism and impact factors of micro/nano porous
polymers. Such studies would provide a more accurate prediction of thermal
conductivity and a wider application in energy conversion and storage systems.


  It was recently advanced the argument that Unruh effect emerges from the
study of quantum field theory in quantum space-time. Quantum space-time is
identified with the Hilbert space of a new kind of quantum fields, the
accelerated fields, which are defined in momentum space. In this work, we argue
that the interactions between such fields offer a clear distinction between
flat and curved space-times. Free accelerated fields are associated with flat
spacetime, while interacting accelerated fields with curved spacetimes. Our
intuition that quantum gravity arises via field interactions is verified by
invoking quantum statistics. Studying the Unruh-like effect of accelerated
fields, we show that any massive object behaves as a black body at temperature
which is inversely proportional to its mass, radiating space-time quanta. With
a heuristic argument, it is shown that Hawking radiation naturally arises in a
theory in which space-time is quantized. Finally, in terms of thermodynamics,
gravity can be identified with an entropic force guaranteed by the second law
of thermodynamics.


  Entanglement in symmetric quantum states and the theory of copositive
matrices are intimately related concepts. For the simplest symmetric states,
i.e., the diagonal symmetric (DS) states, it has been shown that there exists a
correspondence between exceptional (non-exceptional) copositive matrices and
non-decomposable (decomposable) Entanglement Witnesses (EWs). Here we show that
EWs of symmetric, but not DS, states can also be constructed from extended
copositive matrices, providing new examples of bound entangled symmetric
states, together with their corresponding EWs, in arbitrary odd dimensions.


  Deep image denoising networks have achieved impressive success with the help
of a considerably large number of synthetic train datasets. However, real-world
denoising is a still challenging problem due to the dissimilarity between
distributions of real and synthetic noisy datasets. Although several real-world
noisy datasets have been presented, the number of train datasets (i.e., pairs
of clean and real noisy images) is limited, and acquiring more real noise
datasets is laborious and expensive. To mitigate this problem, numerous
attempts to simulate real noise models using generative models have been
studied. Nevertheless, previous works had to train multiple networks to handle
multiple different noise distributions. By contrast, we propose a new
generative model that can synthesize noisy images with multiple different noise
distributions. Specifically, we adopt recent contrastive learning to learn
distinguishable latent features of the noise. Moreover, our model can generate
new noisy images by transferring the noise characteristics solely from a single
reference noisy image. We demonstrate the accuracy and the effectiveness of our
noise model for both known and unknown noise removal.


  Cloud computing systems promise to offer subscription-oriented,
enterprise-quality computing services to users worldwide. With the increased
demand for delivering services to a large number of users, they need to offer
differentiated services to users and meet their quality expectations. Existing
resource management systems in data centers are yet to support Service Level
Agreement (SLA)-oriented resource allocation, and thus need to be enhanced to
realize cloud computing and utility computing. In addition, no work has been
done to collectively incorporate customer-driven service management,
computational risk management, and autonomic resource management into a
market-based resource management system to target the rapidly changing
enterprise requirements of Cloud computing. This paper presents vision,
challenges, and architectural elements of SLA-oriented resource management. The
proposed architecture supports integration of marketbased provisioning policies
and virtualisation technologies for flexible allocation of resources to
applications. The performance results obtained from our working prototype
system shows the feasibility and effectiveness of SLA-based resource
provisioning in Clouds.


  By an additive action on an algebraic variety $X$ we mean a regular effective
action $\mathbb{G}_a^n\times X\to X$ with an open orbit of the commutative
unipotent group $\mathbb{G}_a^n$. In this paper, we give a classification of
additive actions on complete toric surfaces.


  We present and interpret the observations of extreme ultraviolet (EUV) waves
associated with a filament eruption on 2011 May 11.The filament eruption also
produces a small B-class two ribbon flare and a coronal mass ejection (CME).
The event is observed by the Solar Dynamic Observatory (SDO) with high
spatio-temporal resolution data recorded by Atmospheric Imaging Assembly (AIA).
As the filament erupts, we observe two types of EUV waves (slow and fast)
propagating outwards. The faster EUV wave has a propagation velocity of ~ 500
km/s and the slower EUV wave has an initial velocity of ~ 120 km/s. We report
for the first time that not only the slower EUV wave stops at a magnetic
separatrix to form bright stationary fronts, but also the faster EUV wave
transits a magnetic separatrix, leaving another stationary EUV front behind.


  We present results of a dark matter search performed with a 0.6 kg day
exposure of the DAMIC experiment at the SNOLAB underground laboratory. We
measure the energy spectrum of ionization events in the bulk silicon of
charge-coupled devices down to a signal of 60 eV electron equivalent. The data
are consistent with radiogenic backgrounds, and constraints on the
spin-independent WIMP-nucleon elastic-scattering cross section are accordingly
placed. A region of parameter space relevant to the potential signal from the
CDMS-II Si experiment is excluded using the same target for the first time.
This result obtained with a limited exposure demonstrates the potential to
explore the low-mass WIMP region (<10 GeV/$c^{2}$) of the upcoming DAMIC100, a
100 g detector currently being installed in SNOLAB.


  Deep learning has been demonstrated its effectiveness and efficiency in music
genre classification. However, the existing achievements still have several
shortcomings which impair the performance of this classification task. In this
paper, we propose a hybrid architecture which consists of the paralleling CNN
and Bi-RNN blocks. They focus on spatial features and temporal frame orders
extraction respectively. Then the two outputs are fused into one powerful
representation of musical signals and fed into softmax function for
classification. The paralleling network guarantees the extracting features
robust enough to represent music. Moreover, the experiments prove our proposed
architecture improve the music genre classification performance and the
additional Bi-RNN block is a supplement for CNNs.


  In this paper we introduce the concept of Hamiltonian system in the canonical
and Poisson settings. We will discuss the quantization of the Hamiltonian
systems in the Poisson context, using formal deformation quantization and
quantum group theories.


  The problem of light propagation of frequency corresponding to half of the
energy difference between a metastable excited state and the ground state of
atoms is examined, and solved for coherent medium by analytic means. We
demonstrate that the non-linear system of Maxwell-Bloch equation for the
effective model of the $\Lambda-$type three levels is integrable in the
mathematical sense. Analytic solutions thus obtained describe pulse splitting
accompanied by compression, indicating a kind of non-linear instability of
propagating pulses. The instability is eventually terminated by coherent two
photon emission (called paired superradiance or PSR in short). These results
are displayed by numerical outputs for visual understanding, as well. It is
further shown that the integrable system allows a new class of soliton
solutions. Solitons, implying the phenomenon of seff-induced transparancy at
non-resonant frequencies, are stable against PSR. One of our goals of the
present work is construction of a calculable theoretical framework for PSR
rates associated with a trigger pulse propagation, which is achieved by
combining analytic results with perturbative methods. PSR photon spectrum and
its rate $\propto$(target number density)$^2$, along with their time structure,
are clarified this way. These results may open a new path for interesting
technological applications such as quantum entanglement and for solving the
remaining problems of the still mysterious neutrino. Some basic strategy for
realistic experiments of PSR detection and soliton production is also outlined.


  CaV$_2$O$_4$ is a spin-1 antiferromagnet, where the magnetic vanadium ions
are arranged on quasi-one-dimensional (1D) zig-zag chains with potentially
frustrated antiferromagnetic exchange interactions. High temperature
susceptibility and single-crystal neutron diffraction measurements are used to
deduce the non-collinear magnetic structure, dominant exchange interactions and
orbital configurations. The results suggest that at high temperatures
CaV$_2$O$_4$ behaves as a Haldane chain, but at low temperatures, orbital
ordering lifts the frustration and it becomes a spin-1 ladder.


  Deep, near-infrared imaging surveys have been motivated by the desire to
study the rest-frame optical properties and stellar content of galaxies at high
redshift. Here we briefly review their history, and illustrate one application,
using HST NICMOS imaging of the Hubble Deep Field North to examine the
rest-frame optical luminosities and colors of galaxies at 2 < z < 3, and to
constrain their stellar masses. The rest-frame B-band luminosity density at z =
2.5 is similar to that in the local universe, but the galaxies are evidently
less massive, with rapid star formation and low mass-to-light ratios. There are
few candidates for red, non-star-forming galaxies at these redshifts to the
HDF/NICMOS limits. We estimate a stellar mass density at 2 < z < 3 that is ~5%
of the present-day value, with an upper bound of <= 30%. Future headway will
come from wide-field ground-based surveys, multiplexing infrared spectrographs,
and new space-based facilities such as HST/WFC3 and SIRTF/IRAC.


  An adjoint-based variational optimal mixed model (VOMM) is proposed for
subgrid-scale (SGS) closure in large-eddy simulation (LES) of turbulence. The
stabilized adjoint LES equations are formulated by introducing a minimal
regularization to address the numerical instabilities of the long-term gradient
evaluations in chaotic turbulent flows. The VOMM model parameters are optimized
by minimizing the discrepancy of energy dissipation spectra between LES
calculations and a priori knowledge of direct numerical simulation (DNS) using
the gradient-based optimization. The a posteriori performance of the VOMM model
is comprehensively examined in LES of three turbulent flows, including the
forced homogeneous isotropic turbulence, decaying homogenous isotropic
turbulence, and temporally evolving turbulent mixing layer. The VOMM model
outperforms the dynamic Smagorinsky model (DSM), dynamic mixed model (DMM) and
approximate deconvolution model (ADM) in predictions of various turbulence
statistics, including the velocity spectrum, structure functions, statistics of
velocity increments and vorticity, temporal evolutions of the turbulent kinetic
energy, dissipation rate, momentum thickness and Reynolds stress, as well as
the instantaneous vortex structures at different grid resolutions and times. In
addition, the VOMM model only takes up 30% time of the DMM model for all flow
scenarios. These results demonstrate that the proposed VOMM model improves the
numerical stability of LES and has high a posteriori accuracy and computational
efficiency by incorporating the a priori information of turbulence statistics,
highlighting that the VOMM model has a great potential to develop advanced SGS
models in the LES of turbulence.


  We show continuity of solutions $u \in W^{1,n}(B^n,\mathbb{R}^N)$ to the
system \[
  -{\rm div} (|\nabla u|^{n-2} \nabla u) = \Omega \cdot |\nabla u|^{n-2} \nabla
u \] when $\Omega$ is an $L^n$-antisymmetric potential -- and additionally
satisfies a Lorentz-space assumption.
  To obtain our result we study a rotated n-Laplace system \[
  -{\rm div} (Q|\nabla u|^{n-2} \nabla u) = \tilde{\Omega} \cdot |\nabla
u|^{n-2} \nabla u, \] where $Q \in W^{1,n}(B^n,SO(N))$ is the Coulomb gauge
which ensures improved Lorentz-space integrability of $\tilde{\Omega}$. Because
of the matrix-term $Q$, this system does not fall directly into
Kuusi-Mingione's vectorial potential theory. However, we adapt ideas of their
theory together with Iwaniec' stability result to obtain
$L^{(n,\infty)}$-estimates of the gradient of a solution which, by an iteration
argument leads to the regularity of solutions. As a corollary of our argument
we see that $n$-harmonic maps into manifolds are continuous if their gradient
belongs to the Lorentz-space $L^{(n,2)}$ -- which is a trivial and optimal
assumption if $n=2$, and the weakest assumption to date for the regularity of
critical $n$-harmonic maps, without any added differentiability assumption. We
also discuss an application to H systems.


  It is suggested that the center vortex confinement mechanism, familiar in
hadronic physics, may have some relevance to high-T$_\text{c}$ phenomena. We
focus specifically on the transition from the superconducting phase to the
pseudogap phase. There is evidence of a vortex liquid in the latter phase, in
which the pairing responsible for superconductivity still exists, but
superconductivity itself does not. An analogy, drawn from particle physics, may
be the Higgs to confinement phase transition in an SU(N) gauge theory, where
the confined phase is a vortex liquid, and the Higgs phase is a phase of a
broken global $Z_N$ symmetry. We illustrate this idea with numerical
simulations of a spatially asymmetric U(1) gauge-Higgs model, with lattice
artifact monopoles suppressed. We show the existence of a Higgs
(superconductor) to confinement (vortex liquid) phase, explicitly identifying
vortices in lattice configurations generated in the confined phase, and showing
that they produce an area-law falloff in planar Wilson loops, which may be
measurable experimentally. The superconducting phase is a phase of broken
global Z$_\text{2}$ symmetry.


  Given two {0,1}-sequences X and Y of lengths m and n, respectively, we write
L(X,Y) to denote the length of the longest common subsequence (LCS) of X and Y,
and write L(m,n) to denote the expected value of L(X,Y) when X and Y are random
sequences. We study the value of the function z -> lim L(nz,n)/n (as n ->
infinity) and the relation of this function to the outstanding problem of
computing the Chvatal-Sankoff constant lim L(n,n)/n.


  We consider two theoretical scenarios, each including a $\mathbb{Z}_{2}$-odd
sector and leading to an elementary dark matter candidate. The first one is a
variant of the Type-III seesaw model where one lepton triplet is
$\mathbb{Z}_{2}$-odd, together with a heavy sterile neutrino. It leads to a
fermionic dark matter, together with the charged component of the triplet being
a quasi-stable particle which decays only via a higher-dimensional operator
suppressed by a high scale. The second model consists of an inert scalar
doublet together with a $\mathbb{Z}_{2}$-odd right-handed Majorana neutrino
dark matter. A tiny Yukawa coupling delays the decay of the charged component
of the inert doublet into the dark matter candidate, making the former
long-lived on the scale of collider detectors. The parameter space of each
model has been constrained by big-bang nucleosynthesis constraints, and also by
estimating the contribution to the relic density through freeze-out of the
long-lived charged particle as well the freeze-in production of the dark matter
candidate. We consider two kinds of signals at the Large Hadron Collider for
the first kind of models, namely two charged tracks and single track + MET. For
the second kind, the characteristic signals are opposite as well as same-sign
charged track pairs. We perform a detailed analysis using event selection
criteria consistent with the current experimental programmes. It is found that
the scenario with a lepton triplet can be probed upto 960(1190) GeV with an
integrated luminosity of 300(3000) $fb^{-1}$, while the corresponding numbers
for the inert doublet scenario are 630(800) GeV. Furthermore, the second kind
of signal mentioned in each case allows us to differentiate different dark
matter scenarios from each other.


  This work presents the suspicious code at a finer granularity of call stack
rather than code region, which was being returned by Orion. Call stack based
comparison returns call stacks that are most impacted by the bug and save
developer time to debug from scratch. This solution has polynomial complexity
and hence can be implemented practically.


  We study the topology of a complete asymptotically hyperbolic Einstein
manifold such that its conformal boundary has positive Yamabe invariant. We
proved that all maps from such manifold into any nonpositively curved manifold
are homotopically trivial. Our proof is based on a Bochner type argument on
harmonic maps.


  In the current epoch of neutrino physics, many experiments are aiming for
precision measurements of oscillation parameters. Thus, various new physics
scenarios which alter the neutrino oscillation probabilities in matter deserve
careful investigation. In this context, we study the effect of a vector
leptoquark which induces non-standard neutrino interactions (NSI) that modify
the oscillation probabilities of neutrinos in matter. We show that such
interactions provide a relatively large value of NSI parameter $\varepsilon_{e
\mu}$. Considering this NSI parameter, we successfully explain the recent
discrepancy between the observed $\delta_{CP}$ results of T2K and NOvA.


  We present strategies based upon extremization principles, in the case of the
axisymmetric equations of magnetohydrodynamics (MHD). We study the equilibrium
shape by using a minimum energy principle under the constraints of the MHD
axisymmetric equations. We also propose a numerical algorithm based on a
maximum energy dissipation principle to compute in a consistent way the
equilibrium states. Then, we develop the statistical mechanics of such flows
and recover the same equilibrium states giving a justification of the minimum
energy principle. We find that fluctuations obey a Gaussian shape and we make
the link between the conservation of the Casimirs on the coarse-grained scale
and the process of energy dissipation.


  A method is presented for achieving entanglement-free teleportation of a
quantum state subject to any quantum noise. We apply this as a light-speed
noise-resistant communicator, but also treat the possibility of a quantum
ansible, a device for effectively superluminal communication and quantum
broadcasting. The results suggest a "no-projector theorem" analogous to the
no-cloning theorem. We then show how to build a pseudo-ansible for
connection-free light-speed communication.


  Using the QUIJOTE line survey in the 32.0-50.4 GHz range, we report the
discovery of the molecule CH2CCHC4H towards the prestellar cold core TMC-1 in
the Taurus region. We also present a rigorous detection of CH2CCHC3N, along
with its detailed analysis. We identified a total of twenty rotational
transitions for each one of these molecules. The rotational quantum numbers
range from Ju=17 up to 24 and Ka<=3. The column density for CH2CCHC4H is
N=(2.2+/-0.2)x 1E12 cm-2, while for CH2CCHC3N, we derived N=(1.2+/-0.15) x 1E11
cm-2. The rotational temperature is 9.0+/-0.5 K for both species. The abundance
ratio between CH2CCHC4H and CH2CCHC3N is 18+/-4. We also compared the column
densities of these species with those of their isomers CH3C6H and CH3C5N,
derived from their J=20-19 up to J=30-29 rotational transitions observed with
the QUIJOTE line survey. The observed abundances for all these species are
reasonably well explained by state-of-the-art chemical models of TMC-1. The
observed astronomical frequencies were merged with laboratory frequencies from
the literature to derive improved spectroscopic parameters.


  We show that for every $r\ge 3$, the maximal running time of the
$K^{r}_{r+1}$-bootstrap percolation in the complete $r$-uniform hypergraph on
$n$ vertices $K_n^r$ is $\Theta(n^r)$. This answers a recent question of Noel
and Ranganathan in the affirmative, and disproves a conjecture of theirs.
Moreover, we show that the prefactor is of the form $r^{-r} \mathrm{e}^{O(r)}$
as $r\to\infty$.


  Manipulating the strain induced poly-domains and phase transition in
correlated oxide material are important for high performance devices
fabrication. Though the electronic transport in the strained oxide film at
macroscopic scales can be directly measured, the anisotropic electronic state
and the controllable phase separation cross the insulator-to-metal transition
within nanoscale size are still elusive. Here, we selected VO2 crystal film as
a prototypical oxide and achieved the manipulation of anisotropy electronic
phase separation via injecting He+ nanobeam into VO2 film at room temperature.
In addition, this nanoscale phase separation was directly visualized by
infrared near-field imaging measurements, showing the pronounced and unique
cR-axis dependent anisotropy on VO2 surface. Our results offered new insights
towards understanding the anisotropic nanoscale phase separation in strained
metal oxide films.


  In this paper we investigate the polarization property of the radiation
amplified by astronomical masers in the presence of a strong magnetic field.
Our model explicitly takes into account the broadband nature of the radiation
field and the interaction of the radiation with the maser transition J=1--0.
The amplification of different realisations of the background continuum
radition by the maser is directly simulated and the Stokes parameters of the
radiation field are then obtained by averaging over the ensemble of emerging
maser radiation. For isotropic pumping and partially saturated masers we find
that the maser radiation is linearly polarized in two representative cases
where the magnetic field {\bf B} makes an angle $\theta$=30$^0$ and
$\theta$=90$^0$ to the maser axis. The linear polarization for maser radiation
obtained in our simulations for both cases are in agreement with the results of
the standard model. Furthermore, no instability during amplification is seen in
our simulations. Therefore, we conclude that there is no problem with the
previous numerical investigations of maser polarization in the unsaturated and
partially saturated regime.


  Monitoring changes in the Earth's surface is crucial for understanding
natural processes and human impacts, necessitating precise and comprehensive
interpretation methodologies. Remote sensing satellite imagery offers a unique
perspective for monitoring these changes, leading to the emergence of remote
sensing image change interpretation (RSICI) as a significant research focus.
Current RSICI technology encompasses change detection and change captioning,
each with its limitations in providing comprehensive interpretation. To address
this, we propose an interactive Change-Agent, which can follow user
instructions to achieve comprehensive change interpretation and insightful
analysis, such as change detection and change captioning, change object
counting, change cause analysis, etc. The Change-Agent integrates a multi-level
change interpretation (MCI) model as the eyes and a large language model (LLM)
as the brain. The MCI model contains two branches of pixel-level change
detection and semantic-level change captioning, in which the BI-temporal
Iterative Interaction (BI3) layer is proposed to enhance the model's
discriminative feature representation capabilities. To support the training of
the MCI model, we build the LEVIR-MCI dataset with a large number of change
masks and captions of changes. Experiments demonstrate the SOTA performance of
the MCI model in achieving both change detection and change description
simultaneously, and highlight the promising application value of our
Change-Agent in facilitating comprehensive interpretation of surface changes,
which opens up a new avenue for intelligent remote sensing applications. To
facilitate future research, we will make our dataset and codebase of the MCI
model and Change-Agent publicly available at
https://github.com/Chen-Yang-Liu/Change-Agent


  Using time-adaptive probabilistic shaped 64QAM driven by a simple SNR
prediction algorithm, we demonstrate $>$450 Gbps transmission over a 55-m
free-space optics link with enhanced resilience towards rainy weather
conditions. Through continuous measurement over 3-hours, we demonstrate
$\sim$40~Gbps average bit-rate gain over unsupervised fixed modulation.


  In a preceding paper we examined the question whether the spin-spin repulsion
and the gravitational attraction of two aligned sub-extremal black holes can
balance each other. Based on the solution of a boundary value problem for two
separate (Killing-) horizons and a novel black hole criterion we were able to
prove the non-existence of the equilibrium configuration in question. In this
paper we extend the non-existence proof to extremal black holes.


  Accurate modeling of the correlation between the sources plays a crucial role
in the efficiency of distributed source coding (DSC) systems. This correlation
is commonly modeled in the binary domain by using a single binary symmetric
channel (BSC), both for binary and continuous-valued sources. We show that
"one" BSC cannot accurately capture the correlation between continuous-valued
sources; a more accurate model requires "multiple" BSCs, as many as the number
of bits used to represent each sample. We incorporate this new model into the
DSC system that uses low-density parity-check (LDPC) codes for compression. The
standard Slepian-Wolf LDPC decoder requires a slight modification so that the
parameters of all BSCs are integrated in the log-likelihood ratios (LLRs).
Further, using an interleaver the data belonging to different bit-planes are
shuffled to introduce randomness in the binary domain. The new system has the
same complexity and delay as the standard one. Simulation results prove the
effectiveness of the proposed model and system.


  We investigate the consecutive primes $p$ and $q$ ($p > q$) for which there
exists a pair of natural numbers $(x,y)$ such that $p^x-q^y$ is a perfect
square and make some conjectures.


  We review the latest advances in the generation of quantum light with
nonlinear nanoresonators in metasurfaces, which act both as sources of quantum
states and nanoantennas shaping the emitted photons. We outline a general
quantum theory of spontaneous photon-pair generation in arbitrary nonlinear
photonic structures, including nanoresonators and metasurfaces, which provides
an explicit analytical solution for the photon state expressed through the
classical Green function. We formulate the correspondence between the quantum
photon-pair generation and classical sum-frequency process in nonlinear media,
and discuss its application in various contexts, including waveguide circuits
and nanostructures. We also discuss the first experimental results
demonstrating photon-pair generation in a single nonlinear nanoantenna.


  The generalized seniority approach proposed by us to understand the
B(E1)/B(E2)/B(E3) properties of semi-magic nuclei has been widely successful in
the explanation of the same and has led to an expansion in the scope of
seniority isomers. In the present paper, we apply the generalized seniority
scheme to understand the behavior of g-factors in semi-magic nuclei. We find
that the magnetic moment and the gfactors do show a particle number independent
behavior as expected and the understanding is consistent with the explanation
of transition probabilities.


  This paper presents a simulation-based framework for sequential inference
from partially and discretely observed point process (PP's) models with static
parameters. Taking on a Bayesian perspective for the static parameters, we
build upon sequential Monte Carlo (SMC) methods, investigating the problems of
performing sequential filtering and smoothing in complex examples, where
current methods often fail. We consider various approaches for approximating
posterior distributions using SMC. Our approaches, with some theoretical
discussion are illustrated on a doubly stochastic point process applied in the
context of finance.


  Pairing of fermions is ubiquitous in nature and it is responsible for a large
variety of fascinating phenomena like superconductivity, superfluidity of
$^3$He, the anomalous rotation of neutron stars, and the BEC-BCS crossover in
strongly interacting Fermi gases. When confined to two dimensions, interacting
many-body systems bear even more subtle effects, many of which lack
understanding at a fundamental level. Most striking is the, yet unexplained,
effect of high-temperature superconductivity in cuprates, which is intimately
related to the two-dimensional geometry of the crystal structure. In
particular, the questions how many-body pairing is established at high
temperature and whether it precedes superconductivity are crucial to be
answered. Here, we report on the observation of pairing in a harmonically
trapped two-dimensional atomic Fermi gas in the regime of strong coupling. We
perform momentum-resolved photoemission spectroscopy, analogous to ARPES in the
solid state, to measure the spectral function of the gas and we detect a
many-body pairing gap above the superfluid transition temperature. Our
observations mark a significant step in the emulation of layered
two-dimensional strongly correlated superconductors using ultracold atomic
gases.


  We study the static black hole solutions of generalized two-dimensional
dilaton-gravity theories generated by pointlike mass sources, in the hypothesis
that the matter is conformally coupled. We also discuss the motion of test
particles. Due to conformal coupling, these follow the geodesics of a metric
obtained by rescaling the canonical metric with the dilaton.


  We review the mechanisms of low-temperature electron transport across a
quantum dot weakly coupled to two conducting leads. Conduction in this case is
controlled by the interaction between electrons. At temperatures moderately
lower than the single-electron charging energy of the dot, the linear
conductance is suppressed by the Coulomb blockade. Upon further lowering of the
temperature, however, the conductance may start to increase again due to the
Kondo effect. This increase occurs only if the dot has a non-zero spin S. We
concentrate on the simplest case of S=1/2, and discuss the conductance across
the dot in a broad temperature range, which includes the Kondo temperature.
Temperature dependence of the linear conductance in the Kondo regime is
discussed in detail. We also consider a simple (but realistic) limit in which
the differential conductance at a finite bias can be fully investigated.


  From a three-dimensional boundary value problem for the time harmonic
classical Maxwell equations, we derive the dispersion relation for a surface
wave, the edge plasmon-polariton (EP), that is localized near and propagates
along the straight edge of a planar, semi-infinite sheet with a spatially
homogeneous, scalar conductivity. The sheet lies in a uniform and isotropic
medium; and serves as a model for some two-dimensional (2D) conducting
materials such as the doped monolayer graphene. We formulate a homogeneous
system of integral equations for the electric field tangential to the plane of
the sheet. By the Wiener-Hopf method, we convert this system to coupled
functional equations on the real line for the Fourier transforms of the fields
in the surface coordinate normal to the edge, and solve these equations
exactly. The derived EP dispersion relation smoothly connects two regimes: a
low-frequency regime, where the EP wave number, $q$, can be comparable to the
propagation constant, $k_0$, of the ambient medium; and the nonretarded
frequency regime in which $|q|\gg |k_0|$. Our analysis indicates two types of
2D surface plasmon-polaritons on the sheet away from the edge. We extend the
formalism to the geometry of two coplanar sheets.


  We introduce and study the new concepts of cosilting complexes, cosilting
modules and AIR-cotilting modules. We prove that the three concepts
AIR-cotilting modules, cosilting modules and quasi-cotilting modules coincide
with each other, in contrast with the dual fact that AIR-tilting modules,
silting modules and quasi-tilting modules are different. Further, we show that
there are bijections between the following four classes (1) equivalent classes
of AIR-cotilting (resp., cosilting, quasi-cotilting) modules, (2) equivalent
classes of 2-term cosilting complexes, (3) torsion-free cover classes and (4)
torsion-free special precover classes. We also extend a classical result of
Auslander and Reiten on the correspondence between certain contravariantly
finite subcategories and cotilting modules to the case of cosilting complexes.


  In boundary element methods, the method of using double nodes at corners is a
useful approach to uniquely define the normal direction of boundary elements.
However, matrix equations constructed by conventional boundary integral
equations (CBIE) become singular under certain combinations of double node
boundary conditions. In this paper, we analyze the singular conditions of the
CBIE formulation for cases where the boundary conditions at the double node are
imposed by combinations of Dirichlet, Neumann, Robin, and interface conditions.
To address this singularity we propose the use of hypersingular integral
equations (HBIE) for wave propagation problems that obey Helmholtz equation. To
demonstrate the applicability of HBIE, we compare three types of simultaneous
equations: (i) CBIE, (ii) partial-HBIE in which HBIE is only applied to the
double nodes at corners while CBIE is applied to the other nodes, and (iii)
full-HBIE in which HBIE is applied to all nodes. Based on our numerical
results, we observe the following results. The singularity of the matrix
equations for problems with any combination of boundary conditions can be
resolved by both full-HBIE and partial-HBIE, and partial-HBIE exhibits better
accuracy than full-HBIE. Furthermore, the computational cost of partial-HBIE is
smaller than that of full-HBIE.


  We provide a very general argument showing that the Universe must have kept
its quantum memories from an epoch much earlier than $60$ e-foldings before the
end of inflation. The point is that a generic system of enhanced memory storage
capacity exhibits a phenomenon of memory burden. Due to its universal nature
this effect must be applicable to de Sitter since the latter has a maximal
memory storage capacity thanks to its Gibbons-Hawking entropy. The primordial
information pattern encoded in de Sitter memory initially costs very little
energy. However, because of Gibbons-Hawking evaporation, the memory burden of
the pattern grows in time and increasingly back reacts on the evaporation
process. After a finite time the memory burden becomes unbearable and de Sitter
quantum breaks. If inflation ended not long before its quantum break-time, the
imprints of the primordial memory pattern can be observable. This provides a
qualitatively new type of window in the Universe's beginning, a sort of cosmic
quantum hair.


  This work is devoted to an analysis of exact penalty functions and optimality
conditions for nonsmooth two-stage stochastic programming problems. To this
end, we first study the co-/quasi-differentiability of the expectation of
nonsmooth random integrands and obtain explicit formulae for its co- and
quasidifferential under some natural assumptions on the integrand. Then we
analyse exact penalty functions for a variational reformulation of two-stage
stochastic programming problems and obtain sufficient conditions for the global
exactness of these functions with two different penalty terms. In the end of
the paper, we combine our results on the co-/quasi-differentiability of the
expectation of nonsmooth random integrands and exact penalty functions to
derive optimality conditions for nonsmooth two-stage stochastic programming
problems in terms of codifferentials.