  A frame-independent, thermodynamically exact London equation is presented,
which is especially valid for rotating superconductors. A direct result is the
unexpectedly high accuracy ($\sim10^{-10}$) for the usual expression of the
London moment.


  In this paper, we propose a new method for the construction of
multi-dimensional, wavelet-like families of affine frames, commonly referred to
as framelets, with specific directional characteristics, small and compact
support in space, directional vanishing moments (DVM), and axial symmetries or
anti-symmetries. The framelets we construct arise from readily available
refinable functions. The filters defining these framelets have few non-zero
coefficients, custom-selected orientations and can act as finite-difference
operators.


  The determinantal identities of Hamel and Goulden have recently been shown to
apply to a tableau-based ninth variation of skew Schur functions. Here we
extend this approach and its results to the analogous tableau-based ninth
variation of supersymmetric skew Schur functions. These tableaux are built on
entries taken from an alphabet of unprimed and primed numbers and that may be
ordered in a myriad of different ways, each leading to a determinantal
identity. At the level of the ninth variation the corresponding determinantal
identities are all distinct but the original notion of supersymmetry is lost.
It is shown that this can be remedied at the level of the sixth variation
involving a doubly infinite sequence of factorial parameters. Moreover it is
shown that the resulting factorial supersymmetric skew Schur functions are
independent of the ordering of the unprimed and primed entries in the alphabet.


  The Fuzz programming language [Reed and Pierce, 2010] uses an elegant linear
type system combined with a monad-like type to express and reason about
probabilistic sensitivity properties, most notably $\epsilon$-differential
privacy. We show how to extend Fuzz to capture more general relational
properties of probabilistic programs, with approximate, or $(\epsilon,
\delta)$-differential privacy serving as a leading example. Our technical
contributions are threefold. First, we introduce the categorical notion of
comonadic lifting of a monad to model composition properties of probabilistic
divergences. Then, we show how to express relational properties in terms of
sensitivity properties via an adjunction we call the path construction.
Finally, we instantiate our semantics to model the terminating fragment of Fuzz
extended with types carrying information about other divergences between
distributions.


  Consider a pair of symplectic varieties dual with respect to 3D-mirror
symmetry. The K-theoretic limit of the elliptic duality interface is an
equivariant K-theory class of the product. We show that this class provides
correspondences in the product mapping the K-theoretic stable envelopes to the
K-theoretic stable envelopes. This construction allows us to extend the action
of various representation theoretic objects on K(X), such as action of quantum
groups, quantum Weyl groups, R-matrices etc., to their action on the K-theory
of the variety dual to X. In particular, we relate the wall R-matrices to the
R-matrices of the dual variety.
  As an example, we apply our results to the Hilbert scheme of n points in the
complex plane. In this case we arrive at the conjectures of E.Gorsky and
A.Negut.


  We study the problem of learning to reason in large scale knowledge graphs
(KGs). More specifically, we describe a novel reinforcement learning framework
for learning multi-hop relational paths: we use a policy-based agent with
continuous states based on knowledge graph embeddings, which reasons in a KG
vector space by sampling the most promising relation to extend its path. In
contrast to prior work, our approach includes a reward function that takes the
accuracy, diversity, and efficiency into consideration. Experimentally, we show
that our proposed method outperforms a path-ranking based algorithm and
knowledge graph embedding methods on Freebase and Never-Ending Language
Learning datasets.


  We study a fluid-fluid phase transition of the explicit solvent model
represented as a mixture of the restricted primitive model (RPM) of ionic fluid
and neutral hard spherocylinders (HSC). To this end, we combine two theoretical
approaches, i.e., the scale particle theory (SPT) and the associative mean
spherical approximation (AMSA). Whereas the SPT is sufficient to provide a
rather good description of a reference system taking into account hard-core
interactions, the AMSA is known to be efficient in treating the Coulomb
interactions between the ions. Alternatively, we also use the mean spherical
approximation (MSA) for comparison. In general, both approximations lead to
similar qualitative results for the phase diagrams: the region of coexisting
envelope becomes broader and shifts towards larger densities and higher
temperatures when the pressure increases. However, the AMSA and the MSA produce
different concentration dependences, i.e., contrary to the MSA, the AMSA phase
diagrams show that the high-density phase mostly consists of the ions for all
pressures considered. To demonstrate the effect of asphericity of solvent
molecules on the fluid-fluid phase transition, we consider an "equivalent"
mixture in which the HSC particles are replaced by hard spheres (HS) of the
same volume. It is observed that in the case of HSC solvent (RPM-HSC model),
the region of phase coexistence is wider than for the case of the solvent
molecules being of spherical shape (RPM-HS model). It is also found that the
critical temperature is higher in the RPM-HSC model than in the RPM-HS model,
though it becomes the same at higher pressures in the MSA, while in the AMSA
this difference remains essential.


  This paper proposes online algorithms for dynamic matching markets in power
distribution systems, which at any real-time operation instance decides about
matching -- or delaying the supply of -- flexible loads with available
renewable generation with the objective of maximizing the social welfare of the
exchange in the system. More specifically, two online matching algorithms are
proposed for the following generation-load scenarios: (i) when the mean of
renewable generation is greater than the mean of the flexible load, and (ii)
when the condition (i) is reversed. With the intuition that the performance of
such algorithms degrades with increasing randomness of the supply and demand,
two properties are proposed for assessing the performance of the algorithms.
First property is convergence to optimality (CO) as the underlying randomness
of renewable generation and customer loads goes to zero. The second property is
deviation from optimality, is measured as a function of the standard deviation
of the underlying randomness of renewable generation and customer loads. The
algorithm proposed for the first scenario is shown to satisfy CO and a
deviation from optimal that varies linearly with the variation in the standard
deviation. But the same algorithm is shown to not satisfy CO for the second
scenario. We then show that the algorithm proposed for the second scenario
satisfies CO and a deviation from optimal that varies linearly with the
variation in standard deviation plus an offset.


  As Internet is changing from network of data into network of functionalities,
a federated Internet of applications, that every application can cooperate with
each other smoothly, is a natural trending topic. However, existing integration
techniques did not pay enough attention to multiple control domains for
participants, i.e. application providers and end-users. In this study, we
advocate a global cooperation model for all the participants counts. In
particular, we propose a hybrid model to manage the cooperation among
applications to achieve more optimized allocation of efforts, which means users
perform lighter actions and application providers concerning less
uncontrollable information. In addition, we implement the required system and
show a case study which demonstrates the effectiveness of this model.


  We compiled the systematical measurements of anti-nucleus production in
ultra-relativistic heavy ion collisions as well as those in $pp$, $p\bar{p}$,
$\gamma p$ and $e^{+}e^{-}$ at various beam energies. The anti-baryon phase
space density inferred from $\bar{d}/\bar{p}$ ratio in $A+A$, $p+A$,
$pp(\bar{p})$ and $\gamma p$ collisions is found to follow a universal
distribution as a function of center of mass of beam energy and can be
described in a statistical model. We demonstrated that anti-baryon density in
all the collisions is the highest when the collisions are dominated by the
processes of $g+g$ or $\bar{q}+g$. In $e^+e^-$ collisions at LEP, the cross
section of $q\bar{q}g$ is suppressed by a factor of strong coupling constant
$\alpha_s$ relative to $q\bar{q}$. This can consistently explain the $\bar{d}$
suppression observed by ALEPH relative to that in $e^+e^-\to ggg$ by ARGUS. We
discuss the implications to the baryon enhancement at high transverse momentum
at RHIC when jet is quenched.


  Information retrieval from textual data focuses on the construction of
vocabularies that contain weighted term tuples. Such vocabularies can then be
exploited by various text analysis algorithms to extract new knowledge, e.g.,
top-k keywords, top-k documents, etc. Top-k keywords are casually used for
various purposes, are often computed on-the-fly, and thus must be efficiently
computed. To compare competing weighting schemes and database implementations,
benchmarking is customary. To the best of our knowledge, no benchmark currently
addresses these problems. Hence, in this paper, we present a top-k keywords
benchmark, T${}^2$K${}^2$, which features a real tweet dataset and queries with
various complexities and selectivities. T${}^2$K${}^2$ helps evaluate weighting
schemes and database implementations in terms of computing performance. To
illustrate T${}^2$K${}^2$'s relevance and genericity, we successfully performed
tests on the TF-IDF and Okapi BM25 weighting schemes, on one hand, and on
different relational (Oracle, PostgreSQL) and document-oriented (MongoDB)
database implementations, on the other hand.


  Unusual magnetotransport behaviors such as temperature dependent negative
magnetoresistance(MR) and bowtie-shaped MR have puzzled us for a long time.
Although several mechanisms have been proposed to explain them, the absence of
comprehensive quantitative calculations has made these explanations less
convincing. In our work, we introduce a methodology to study the
magnetotransport behaviors in magnetic materials. This approach integrates
anomalous Hall conductivity induced by Berry curvature, with a multi-band
ordinary conductivity tensor, employing a combination of first-principles
calculations and semi-classical Boltzmann transport theory. Our method
incorporates both the temperature dependency of relaxation time and anomalous
Hall conductivity, as well as the field dependency of anomalous Hall
conductivity. We initially test this approach on two-band models and then apply
it to a Weyl semimetal \CSS. The results, which align well with experimental
observations in terms of magnetic field and temperature dependencies,
demonstrate the efficacy of our approach. Additionally, we have investigated
the distinct behaviors of magnetoresistance (MR) and Hall resistivities across
various types of magnetic materials. This methodology provides a comprehensive
and efficient means to understand the underlying mechanisms of the unusual
behaviors observed in magneto-transport measurements in magnetic materials.


  In the context of global sustainability, buildings are significant consumers
of energy, emphasizing the necessity for innovative strategies to enhance
efficiency and reduce environmental impact. This research leverages extensive
raw data from building infrastructures to uncover energy consumption patterns
and devise strategies for optimizing resource use. We investigate the factors
influencing energy efficiency and cost reduction in buildings, utilizing Lasso
Regression, Decision Tree, and Random Forest models for accurate energy use
forecasting. Our study delves into the factors affecting energy utilization,
focusing on primary fuel and electrical energy, and discusses the potential for
substantial cost savings and environmental benefits. Significantly, we apply
metaheuristic techniques to enhance the Decision Tree algorithm, resulting in
improved predictive precision. This enables a more nuanced understanding of the
characteristics of buildings with high and low energy efficiency potential. Our
findings offer practical insights for reducing energy consumption and
operational costs, contributing to the broader goals of sustainable development
and cleaner production. By identifying key drivers of energy use in buildings,
this study provides a valuable framework for policymakers and industry
stakeholders to implement cleaner and more sustainable energy practices.


  Recently Maldacena and Strominger found that the calculation of greybody
factors for $D=5$ black holes carrying three U(1) charges gives striking new
evidence for their description as multiply wound effective strings. Here we
show that a similar result holds for $D=4$ black holes with four $U(1)$
charges. In this case the effective string may be thought of as the triple
intersection of the 5-branes in M-theory compactified on $T^7$.


  We will introduce an $\mathbb{N}$-filtration on the negative part of a
quantum group of type $A_n$, such that the associated graded algebra is a
q-commutative polynomial algebra. This filtration is given in terms of the
representation theory of quivers, by realizing the quantum group as the Hall
algebra of a quiver. We show that the induced associated graded module of any
simple finite-dimensional module (of type 1) is isomorphic to a quotient of
this polynomial algebra by a monomial ideal, and we provide a monomial basis
for this associated graded module. This construction can be viewed as a quantum
analog of the classical PBW framework, and in fact, by considering the
classical limit, this basis is the monomial basis provided by Feigin,
Littelmann and the second author in the classical setup.


  Let $K$ be an algebraically closed field of characteristic different from 2,
$g$ a positive integer, $f(x)$ a degree $(2g+1)$ polynomial with coefficients
in $K$ and without multiple roots, $C: y^2=f(x)$ the corresponding genus $g$
hyperelliptic curve over $K$ and $J$ the jacobian of $C$. We identify $C$ with
the image of its canonical embedding into $J$ (the infinite point of $C$ goes
to the zero point of $J$). For each point $P=(a,b)\in C(K)$ there are $2^{2g}$
points $\frac{1}{2}P \in J(K)$. We describe explicitly the Mumford
represesentations of all $\frac{1}{2}P$. The rationality questions for
$\frac{1}{2}P$ are also discussed.


  We establish a Bohr-Sommerfeld type condition for quasi-normal modes of a
slowly rotating Kerr-de Sitter black hole, providing their full asymptotic
description in any strip of fixed width. In particular, we observe a
Zeeman-like splitting of the high multiplicity modes at a=0 (Schwarzschild-de
Sitter), once spherical symmetry is broken. The numerical results presented in
Appendix B show that the asymptotics are in fact accurate at very low energies
and agree with the numerical results established by other methods in the
physics literature. We also prove that solutions of the wave equation can be
asymptotically expanded in terms of quasi-normal modes; this confirms the
validity of the interpretation of their real parts as frequencies of
oscillations, and imaginary parts as decay rates of gravitational waves.


  Vehicle detection and recognition in drone images is a complex problem that
has been used for different safety purposes. The main challenge of these images
is captured at oblique angles and poses several challenges like non-uniform
illumination effect, degradations, blur, occlusion, loss of visibility, etc.
Additionally, weather conditions play a crucial role in causing safety concerns
and add another high level of challenge to the collected data. Over the past
few decades, various techniques have been employed to detect and track vehicles
in different weather conditions. However, detecting vehicles in heavy snow is
still in the early stages because of a lack of available data. Furthermore,
there has been no research on detecting vehicles in snowy weather using real
images captured by unmanned aerial vehicles (UAVs). This study aims to address
this gap by providing the scientific community with data on vehicles captured
by UAVs in different settings and under various snow cover conditions in the
Nordic region. The data covers different adverse weather conditions like
overcast with snowfall, low light and low contrast conditions with patchy snow
cover, high brightness, sunlight, fresh snow, and the temperature reaching far
below -0 degrees Celsius. The study also evaluates the performance of commonly
used object detection methods such as Yolo v8, Yolo v5, and fast RCNN.
Additionally, data augmentation techniques are explored, and those that enhance
the detectors' performance in such scenarios are proposed. The code and the
dataset will be available at https://nvd.ltu-ai.dev


  We discuss some aspects of the pressure (or interaction) driven Mott
transition, in three dimensional transition metal oxides by means of dynami cal
mean field theory. We isolate the universal properties of the transition from
the aspects which depend more on the detailed chemistry of the compounds. In
this light we can understand the main differences and the remarkable
similarities between these systems. Both theory and experiment converge on the
transfer of spectral weight from low energies to high energies as the universal
mechanism underlying the Mott transition, and we comment on the possible
relevance of these ideas to other metal to non metal transitions.


  We consider a class of interacting particle systems in continuous space of
non-gradient type, which are reversible with respect to Poisson point processes
with constant density. For these models, a rate of convergence was recently
obtained in 10.1214/22-AOP1573 for certain finite-volume approximations of the
bulk diffusion matrix. Here, we show how to leverage this to obtain
quantitative versions of a number of results capturing the large-scale
fluctuations of these systems, such as the convergence of two-point correlation
functions and the Green-Kubo formula.


  We prove that the susceptibility of the continuous-time weakly self-avoiding
walk on $\mathbb{Z}^d$, in the critical dimension $d=4$, has a logarithmic
correction to mean-field scaling behaviour as the critical point is approached,
with exponent 1/4 for the logarithm. The susceptibility has been well
understood previously for dimensions $d \geq 5$ using the lace expansion, but
the lace expansion does not apply when $d=4$. The proof begins by rewriting the
walk two-point function as the two-point function of a supersymmetric field
theory. The field theory is then analysed via a rigorous renormalisation group
method developed in a companion series of papers. By providing a setting where
the methods of the companion papers are applied together, the proof also serves
as an example of how to assemble the various ingredients of the general
renormalisation group method in a coordinated manner.


  We suggest novel correlation coefficients which equal the maximum correlation
for a class of bivariate Lancaster distributions while being only slightly
smaller than maximum correlation for a variety of further bivariate
distributions. In contrast to maximum correlation, however, our correlation
coefficients allow for rank and moment-based estimators which are simple to
compute and have tractable asymptotic distributions. Confidence intervals
resulting from these asymptotic approximations and the covariance bootstrap
show good finite-sample coverage. In a simulation, the power of asymptotic as
well as permutation tests for independence based on our correlation measures
compares favorably with competing methods based on distance correlation or rank
coefficients for functional dependence, among others. Moreover, for the
bivariate normal distribution, our correlation coefficients equal the absolute
value of the Pearson correlation, an attractive feature for practitioners which
is not shared by various competitors. We illustrate the practical usefulness of
our methods in applications to two real data sets.


  Even though many existing 3D object detection algorithms rely mostly on
camera and LiDAR, camera and LiDAR are prone to be affected by harsh weather
and lighting conditions. On the other hand, radar is resistant to such
conditions. However, research has found only recently to apply deep neural
networks on radar data. In this paper, we introduce a deep learning approach to
3D object detection with radar only. To the best of our knowledge, we are the
first ones to demonstrate a deep learning-based 3D object detection model with
radar only that was trained on the public radar dataset. To overcome the lack
of radar labeled data, we propose a novel way of making use of abundant LiDAR
data by transforming it into radar-like point cloud data and aggressive radar
augmentation techniques.


  Given a quadruple of finite index subfactors we explicitly compute the
Pimsner-Popa probabilistic constant for the pair of intermediate subfactors and
relate it with the corresponding Connes-St{\o}rmer relative entropy between
them. This generalizes an old result of Pimsner and Popa.


  A proper vertex coloring of a graph is a mapping of its vertices on a set of
colors, such that two adjacent vertices are not mapped to the same color. This
constraint may be interpreted in terms of the distance between to vertices and
so a more general coloring concept can be defined: The strong coloring of a
graph. So a k-strong coloring is a coloring where two vertices may not have the
same color if their distance to each other is at most k. The 2-strong coloring
of the line graph is known as the strong edge coloring. Coloring the kth power
G^k of a graph G is the same as finding a k-strong coloring of G itself. In
order to obtain a graph class on which the 2-strong coloring becomes
efficiently solvable we are looking for a structure that produces induced
cycles in the square of G, so that by excluding this structure we obtain a
graph class with chordal squares, where a chordal graph is a graph without any
induced cycles of length at least 4. Such a structure is called a flower.
Another structure will be found and explained, which is responsible for flowers
to appear in the line graph of G: The sprouts. With this graphs with chordal
line graph squares are described as well. Some attempts in generalizing those
structures to obtain perfect graph squares are being made and the general
concept of chordal graph powers, i.e. the existence of a smallest power for
which a graph becomes chordal, the power of chordality is introduced in order
to solve some coloring related NP-hard problems on graphs with parameterized
algorithms. Some connections to the famous parameter treewidth arise alongside
with some deeper connections between edge and vertex coloring.


  Let $G$ be a finite permutation group on $\Omega.$ An ordered sequence
$(\omega_1,\dots, \omega_t)$ of elements of $\Omega$ is an irredundant base for
$G$ if the pointwise stabilizer is trivial and no point is fixed by the
stabilizer of its predecessors. If all irredundant bases of $G$ have the same
cardinality, $G$ is said to be an IBIS group. In this paper we give a
classification of quasi-primitive soluble irreducible IBIS linear groups, and
we also describe nilpotent and metacyclic IBIS linear groups and IBIS linear
groups of odd order.


  We present a simple argument confirming the spontaneous quantum condensation
of an electromagnetic field in matter in the case of a multi-level atomic
system coupled to a single-mode electromagnetic field in the dipole
approximation. The obtained result disproves the validity of a ``no-go
theorem'' and fully rehabilitates theories of spontaneous quantum condensation
of the electromagnetic field in matter. Peculiar features of the identified
coherent states are outlined.


  We perform a comparative \textit{ab-initio} study of Mn-doped Germanium
semiconductor using the Perdew-Burke-Ernzerhof (PBE) exchange-correlation
functional, DFT+$U$ and Heyd-Scuseria-Ernzerhof hybrid functional (HSE). We
show that the HSE functional is able to correctly account for the relevant
ground state properties of the host matrix as well as of Mn-doped
semiconductor. Although the DFT+$U$ and the HSE description are very similar,
some differences still remain. In particular, the half-metallicity is lost
using DFT+$U$ when a suitable $U$ value, tuned to recover the photoemission
spectra, is employed. For comparison, we also discuss the case of Mn in
Silicon.


  In this research we study the effect of matter-wave instability on electron
beam transport with arbitrary degree of degeneracy. Particular class of
solutions of the Schr\"{o}dinger-Poisson system is used to model the
electron-beam transport at constant speed. It is shown that such electron-beam
is described by a coupled driven pseudoforce system solution of which leads to
plasmon excitations with dual wave-particle character. The fundamental quantum
mechanical de Broglie relation is found to be due to the resonant interaction
of particle-like plasmon excitation branch with the electron beam drift. We
further obtain a generalized double lengthscale de Broglie wave-particle
relation through which various beam-plasmon instability is studied in this
model. The quantum charge screening and the chemical potential effects on the
matter-wave formation and instabilities are discussed in detail and the
well-known Aharonov-Bohm effect is revisited in current quantum hydrodynamic
model. Current research may further illuminate the origin of matter-wave in
quantum mechanics and lead to clear understanding of novel wave-particle
interactions.


  Relational lattice is a formal mathematical model for Relational algebra. It
reduces the set of six classic relational algebra operators to two: natural
join and inner union. We continue to investigate Relational lattice properties
with emphasis onto axiomatic definition. New results include additional axioms,
equational definition for set difference (more generally anti-join), and case
study demonstrating application of the relational lattice theory for query
transformations.


  We study the decay rate $\theta(a)$ that characterizes the late time
exponential decay of the first-passage probability density $F_a(t|0) \sim
e^{-\theta(a)\, t}$ of a diffusing particle in a one dimensional confining
potential $U(x)$, starting from the origin, to a position located at $a>0$. For
general confining potential $U(x)$ we show that $\theta(a)$, a measure of the
barrier (located at $a$) crossing rate, has three distinct behaviors as a
function of $a$, depending on the tail of $U(x)$ as $x\to -\infty$. In
particular, for potentials behaving as $U(x)\sim |x|$ when $x\to -\infty$, we
show that a novel freezing transition occurs at a critical value $a=a_c$, i.e,
$\theta(a)$ increases monotonically as $a$ decreases till $a_c$, and for $a \le
a_c$ it freezes to $\theta (a)=\theta(a_c)$. Our results are established using
a general mapping to a quantum problem and by exact solution in three
representative cases, supported by numerical simulations. We show that the
freezing transition occurs when in the associated quantum problem, the gap
between the ground state (bound) and the continuum of scattering states
vanishes.


  Given a task of predicting $Y$ from $X$, a loss function $L$, and a set of
probability distributions $\Gamma$ on $(X,Y)$, what is the optimal decision
rule minimizing the worst-case expected loss over $\Gamma$? In this paper, we
address this question by introducing a generalization of the principle of
maximum entropy. Applying this principle to sets of distributions with marginal
on $X$ constrained to be the empirical marginal from the data, we develop a
general minimax approach for supervised learning problems. While for some loss
functions such as squared-error and log loss, the minimax approach rederives
well-knwon regression models, for the 0-1 loss it results in a new linear
classifier which we call the maximum entropy machine. The maximum entropy
machine minimizes the worst-case 0-1 loss over the structured set of
distribution, and by our numerical experiments can outperform other well-known
linear classifiers such as SVM. We also prove a bound on the generalization
worst-case error in the minimax approach.


  Explaining how and why some species evolved to have more complex social
structures than others has been a long-term goal for many researchers in animal
behavior because it would provide important insight into the links between
evolution and ecology, sociality, and cognition. However, despite long-standing
interest, the evolution of social complexity is still poorly understood. This
may be due in part to researchers focusing on the feasibility of quantifying
aspects of sociality, rather than what features are characteristic of animal
social complexity in the first place. Any given approach to studying complexity
can tell us some things about animal sociality, but may miss others, so it is
critical to decide first how to conceptualize complexity before jumping in to
quantifying it. Here, we briefly summarize five existing approaches to
measuring social complexity. Then, we highlight three fundamental concepts that
are commonly used in the field of complex systems: (1) scales of organization,
(2) compression, and (3) emergence. All of these concepts are applicable to the
study of animal social systems, but are not often explicitly addressed in
existing social complexity measures. We discuss how these concepts can provide
a rigorous foundation for conceptualizing social complexity, the potential
benefits of incorporating them, and how existing measures do (or do not)
include them. Ultimately, researchers need to critically evaluate any measure
of animal social complexity in order to balance the biological relevance of the
aspect of sociality they are quantifying with the feasibility of obtaining
enough data.


  This paper describes our multiclass classification system developed as part
of the LTEDI@RANLP-2023 shared task. We used a BERT-based language model to
detect homophobic and transphobic content in social media comments across five
language conditions: English, Spanish, Hindi, Malayalam, and Tamil. We
retrained a transformer-based crosslanguage pretrained language model,
XLMRoBERTa, with spatially and temporally relevant social media language data.
We also retrained a subset of models with simulated script-mixed social media
language data with varied performance. We developed the best performing
seven-label classification system for Malayalam based on weighted macro
averaged F1 score (ranked first out of six) with variable performance for other
language and class-label conditions. We found the inclusion of this
spatio-temporal data improved the classification performance for all language
and task conditions when compared with the baseline. The results suggests that
transformer-based language classification systems are sensitive to
register-specific and language-specific retraining.


  The source NRAO150 is a very prominent millimeter to radio emitting quasar at
redshift z=1.52 for which previous millimeter VLBI observations revealed a fast
counterclockwise rotation of the innermost regions of the jet. Here we present
new polarimetric multi-epoch VLBI-imaging observations of NRAO150 performed at
8, 15, 22, 43, and 86GHz with the VLBA and GMVA between 2006 and 2010. All new
and previous observational evidence are consistent with an interpretation of
the source behavior where the jet is seen at an extremely small angle to the
line of sight, and the high frequency emitting regions in NRAO150 rotate at
high speeds on the plane of the sky with respect to a reference point that does
not need to be related to any particularly prominent jet feature. The observed
polarization angle distribution at 22, 43, and 86 GHz during observing epochs
with high polarization degree suggests that we have detected the toroidal
component of the magnetic field threading the innermost jet plasma regions.
This is also consistent with the lower degree of polarization detected at
progressively poorer angular resolutions, where the integrated polarization
intensity produced by the toroidal field is explained by polarization
cancellation inside the observing beam. All this evidence is fully consistent
with a kinematic scenario where the main kinematic and polarization properties
of the 43 GHz emitting structure of NRAO150 are explained by the internal
rotation of such emission regions around the jet axis when the jet is seen
almost face on. A simplified model developed to fit helical trajectories to the
observed kinematics of the 43 GHz features fully supports this hypothesis. This
explains the kinematics of the innermost regions of the jet in NRAO150 in terms
of internal jet rotation.


  We present a new model for the Galactic population of close double white
dwarfs. The model accounts for the suggestion of the avoidance of a substantial
spiral-in during mass transfer between a giant and a main-sequence star of
comparable mass and for detailed cooling models. It agrees well with the
observations of the local sample of white dwarfs if the initial binary fraction
is close to 50% and an ad hoc assumption is made that white dwarfs with mass
less than about 0.3 solar mass cool faster than the models suggest. About 1000
white dwarfs brighter than V=15 have to be surveyed for detection of a pair
which has total mass greater than the Chandrasekhar mass and will merge within
10 Gyr.


  We revisit the geometrical meaning of statistical isotropy that is manifest
in excursion sets of smooth random fields in two dimensions. Using the contour
Minkowski tensor, $\W_1$, as our basic tool we first examine geometrical
properties of single structures. For simple closed curves in two dimensions we
show that $\W_1$ is proportional to the identity matrix if the curve has
$m$-fold symmetry, with $m\ge 3$. Then we elaborate on how $\W_1$ maps any
arbitrary shaped simple closed curve to an ellipse that is unique up to
translations of its centroid. We also carry out a comparison of the shape
parameters, $\alpha$ and $\beta$, defined using $\W_1$, with the filamentarity
parameter defined using two scalar Minkowski functionals - area and contour
length. We show that they contain complementary shape information, with $\W_1$
containing additional information of orientation of structures. Next, we apply
our method to boundaries of excursion sets of random fields and examine what
statistical isotropy means for the geometry of the excursion sets. Focusing on
Gaussian isotropic fields, and using a semi-numerical approach we quantify the
effect of finite sampling of the field on the geometry of the excursion sets.
In doing so we obtain an analytic expression for $\alpha$ which takes into
account the effect of finite sampling. Finally we derive an analytic expression
for the ensemble expectation of $\W_1$ for Gaussian anisotropic random fields.
Our results provide insights that are useful for designing tests of statistical
isotropy using cosmological data.


  A major issue for the implementation of large scale superconducting quantum
circuits is the interaction with interfacial two-level system defects (TLS)
that leads to qubit relaxation and impedes qubit operation in certain frequency
ranges that also drift in time. Another major challenge comes from
non-equilibrium quasiparticles (QPs) that result in qubit dephasing and
relaxation. In this work we show that such QPs can also serve as a source of
TLS. Using spectral and temporal mapping of TLS-induced fluctuations in
frequency tunable resonators, we identify a subset of the general TLS
population that are highly coherent TLS with a low reconfiguration temperature
$\sim$ 300 mK, and a non-uniform density of states. These properties can be
understood if these TLS are formed by QPs trapped in shallow subgap states
formed by spatial fluctutations of the superconducting order parameter
$\Delta$. Magnetic field measurements of one such TLS reveals a link to
superconductivity. Our results imply that trapped QPs can induce qubit
relaxation.


  We study multivariate polynomials over `structured' grids. We begin by
proposing an interpretation as to what it means for a finite subset of a field
to be structured; we do so by means of a numerical parameter, the nullity. We
then extend several results--notably, the Combinatorial Nullstellensatz and the
Coefficient Theorem--to polynomials over structured grids. The main point is
that the structure of a grid allows the degree constraints on polynomials to be
relaxed.


  Edward C. Tolman found reinforcement learning unsatisfactory for explaining
intelligence and proposed a clear distinction between learning and behavior.
Tolman's ideas on latent learning and cognitive maps eventually led to what is
now known as conceptual space, a geometric representation where concepts and
ideas can form points or shapes.Active navigation between ideas - reasoning -
can be expressed directly as purposive navigation in conceptual space.
Assimilating the theory of conceptual space from modern neuroscience, we
propose autonomous navigation as a valid approach for emulated cognition.
However, achieving autonomous navigation in high-dimensional Euclidean spaces
is not trivial in technology. In this work, we explore whether neoRL navigation
is up for the task; adopting Kaelbling's concerns for efficient robot
navigation, we test whether the neoRL approach is general across navigational
modalities, compositional across considerations of experience, and effective
when learning in multiple Euclidean dimensions. We find neoRL learning to be
more resemblant of biological learning than of RL in AI, and propose neoRL
navigation of conceptual space as a plausible new path toward emulated
cognition.


  In this short note, we present a construction for the log-log blow up
solutions to focusing mass-critical stochastic nonlinear Schr\"oidnger
equations with multiplicative noises. The solution is understood in the sense
of controlled rough path as in \cite{SZ20}.


  Quark and pole models of nonleptonic decays of charmed baryons are analysed
from the point of view of their symmetry properties. The symmetry structure of
the parity conserving amplitudes that corresponds to the contribution of the
ground-state intermediate baryons is shown to differ from the one hitherto
employed in the symmetry approach. It is pointed out that the "subtraction" of
sea quark effects in hyperon decays leads to an estimate of $W$-exchange
contributions in charmed baryon decays that is significantly smaller than
naively expected on the basis of $SU(4)$. An $SU(2)_{W}$ constraint questioning
the reliability of the factorization technique is exhibited. Finally, a
successful fit to the available data is presented.


  The localization of teeth and segmentation of periapical lesions in cone-beam
computed tomography (CBCT) images are crucial tasks for clinical diagnosis and
treatment planning, which are often time-consuming and require a high level of
expertise. However, automating these tasks is challenging due to variations in
shape, size, and orientation of lesions, as well as similar topologies among
teeth. Moreover, the small volumes occupied by lesions in CBCT images pose a
class imbalance problem that needs to be addressed. In this study, we propose a
deep learning-based method utilizing two convolutional neural networks: the
SpatialConfiguration-Net (SCN) and a modified version of the U-Net. The SCN
accurately predicts the coordinates of all teeth present in an image, enabling
precise cropping of teeth volumes that are then fed into the U-Net which
detects lesions via segmentation. To address class imbalance, we compare the
performance of three reweighting loss functions. After evaluation on 144 CBCT
images, our method achieves a 97.3% accuracy for teeth localization, along with
a promising sensitivity and specificity of 0.97 and 0.88, respectively, for
subsequent lesion detection.


  We re-visit the classical problem of optimal payment of dividends and
determine the degree to which the diffusion approximation serves as a valid
approximation of the classical risk model for this problem. Our results
parallel some of those in B\"auerle (2004), but we obtain sharper results
because we use a different technique for obtaining them. Specifically,
B\"auerle (2004) uses probabilistic techniques and relies on convergence in
distribution of the underlying processes. By contrast, we use comparison
results from the theory of differential equations, and these methods allow us
to determine the rate of convergence of the value functions in question.


  Quantum Darwinism is a compelling theory that describes the quantum-to
classical transition as the emergence of objectivity of quantum systems.
Spectrum broadcast structure and strong quantum Darwinism are two extensions of
this theory with emphasis on state structure and information respectively. The
complete experimental verification of these three frameworks, however, requires
quantum state tomography over both the system and accessible environments, thus
limiting the feasibility and scalability of experimental tests. Here, we
introduce a subspace-dependent objectivity operation and construct a witness
that detects non-objectivity by comparing the dynamics of the
system-environment state with and without the objectivity operation. We then
propose a photonic experimental simulation that implements the witnessing
scheme. Our work proposes a route to further experimental exploration of the
quantum to classical transition.


  Using the properties of SDSS DR7 QSOs catalog from Shen et al., the Baldwin
effect, its slope evolution, the underlying drive for a large sample of 35019
QSOs with reliable spectral analysis are investigated. We find that the Baldwin
effect exists in this large QSOs sample, which is almost the same in 11
different redshift bins, up to $z\sim 5$. The slope is -0.238 by the BCES
(\civ\ EW depends on the continuum), -0.787 by the BCES bisector. For 11
redshift-bins, there is an increasing of the Baldwin effect slope from
$z\sim1.5$ to $z\sim2.0$. From $z\sim2.0$ to $z\sim5.0$, the slope change is
not clear considering their uncertainties or larger redshift bins. There is a
strong correlation between the rest-frame \civ\ EW and \civ-based \mbh while
the relation between the \civ\ EW and \mgii-based \mbh is very weak. With the
correction of \civ-based \mbh from the \civ\ blueshift relative to \mgii, we
suggest that this strong correlation is due to the bias of the \civ-based \mbh,
with respect to that from the \mgii\ line. Considering the \mgii-based \mbh, a
medium strong correlation is found between the \civ\ EW and the Eddington
ratio, which implies that the Eddington ratio seems to be a better underlying
physical parameter than the central black hole mass.


  A noncommutative Feynman graph is a ribbon graph and can be drawn on a genus
$g$ 2-surface with a boundary. We formulate a general convergence theorem for
the noncommutative Feynman graphs in topological terms and prove it for some
classes of diagrams in the scalar field theories. We propose a noncommutative
analog of Bogoliubov-Parasiuk's recursive subtraction formula and show that the
subtracted graphs from a class $\Omega_d$ satisfy the conditions of the
convergence theorem. For a generic scalar noncommutative quantum field theory
on $\re^d$, the class $\Omega_d$ is smaller than the class of all diagrams in
the theory. This leaves open the question of perturbative renormalizability of
noncommutative field theories. We comment on how the supersymmetry can improve
the situation and suggest that a noncommutative analog of Wess-Zumino model is
renormalizable.


  Jet energy calibration is an important aspect of many measurements and
searches at the LHC. Currently, these calibrations are performed on a per-jet
basis, i.e. agnostic to the properties of other jets in the same event. In this
work, we propose taking advantage of the correlations induced by momentum
conservation between jets in order to improve their jet energy calibration. By
fitting the $p_T$ asymmetry of dijet events in simulation, while remaining
agnostic to the $p_T$ spectra themselves, we are able to obtain
correlation-improved maximum likelihood estimates. This approach is
demonstrated with simulated jets from the CMS Detector, yielding a $3$-$5\%$
relative improvement in the jet energy resolution, corresponding to a
quadrature improvement of approximately 35\%.


  Transparent media exhibiting anomalous dispersion have been of considerable
interest since Wang, Kuzmich, and Dogariu [Nature {\bf 406}, 277 (2000)] first
observed light propagate with superluminal and negative group velocities
without absorption. Here, we propose an atomic model exhibiting these
properties, based on a generalization of amplification without inversion in a
five-level DIGS system. The system consists of a $\Lambda$ atom prepared as in
standard electromagnetically induced transparency (EIT), with two additional
metastable ground states coupled to the $\Lambda$ atom ground states by two
RF/microwave fields. We consider two configurations by which population is
incoherently pumped into the ground states of the atom. Under appropriate
circumstances, we predict a pair of new gain lines with tunable width,
separation, and height. Between these lines, absorption vanishes but dispersion
is large and anomalous. The system described here is a significant improvement
over other proposals in the anomalous dispersion literature in that it permits
additional coherent control over the spectral properties of the anomalous
region, including a possible $10^4$-fold increase over the group delay observed
by Wang, Kuzmich, and Dogariu.


  CountSketch is a popular dimensionality reduction technique that maps vectors
to a lower dimension using randomized linear measurements. The sketch supports
recovering $\ell_2$-heavy hitters of a vector (entries with $v[i]^2 \geq
\frac{1}{k}\|\boldsymbol{v}\|^2_2$). We study the robustness of the sketch in
adaptive settings where input vectors may depend on the output from prior
inputs. Adaptive settings arise in processes with feedback or with adversarial
attacks. We show that the classic estimator is not robust, and can be attacked
with a number of queries of the order of the sketch size. We propose a robust
estimator (for a slightly modified sketch) that allows for quadratic number of
queries in the sketch size, which is an improvement factor of $\sqrt{k}$ (for
$k$ heavy hitters) over prior work.


  We apply a meron cluster algorithm to the XY spin chain, which describes a
quantum rotor. This is a multi-cluster simulation supplemented by an improved
estimator, which deals with objects of half-integer topological charge. This
method is powerful enough to provide precise results for the model with a
theta-term - it is therefore one of the rare examples, where a system with a
complex action can be solved numerically. In particular we measure the
correlation length, as well as the topological and magnetic susceptibility. We
discuss the algorithmic efficiency in view of the critical slowing down. Due to
the excellent performance that we observe, it is strongly motivated to work on
new applications of meron cluster algorithms in higher dimensions.


  A new nanoscale ordered perovskite cobaltite, which consists of 90 degree
ordered domains of the layered-112 LaBaCo2O6 has been evidenced by high
resolution- transmission electron microscopy. This new form, like the
disordered La0.5Ba0.5CoO3 and ordered LaBaCo2O6, exhibits a ferromagnetic
transition at TC around 179 K. However, it differs from the two previous forms
by its strong magnetic anisotropy, and correlatively by its high value of
coercivity (0.42 Tesla) at low temperature. We suggest that this behaviour
originates from the locking of magnetic spins in the 90 degree oriented
nano-domain. Moreover, one observes a semi-metal/semi-metal transition at TC
with a maximum magnetoresistance of 6.5 % at this temperature.


  We examine the space-time properties of the distribution (dbar - ubar) and
dbar/ubar in the proton. The difference of the antiquark distributions shows
the expected peak at the approximate pion Compton wavelength and is
supportative of the thesis that the meson cloud of the nucleon is at the origin
of the asymmetry of (dbar - ubar), with the pion cloud playing a dominant role.


  The relation between X-ray and UV/optical variability in AGNs has been
explored in many individual sources, however a large sample study is yet
absent. Through matching the XMM-Newton serendipitous X-ray and UV source
catalogs with SDSS quasars, we build a sample of 802 epoch-pairs of 525 quasars
showing clear variability in logFx-logFuv space. After correcting for the
effect of photometric noise, we find 35.6\pm2.1% of the epoch-pairs show
asynchronous variability between X-ray and UV (brightening in one band but
dimming in the other). This indicates only in 28.8\pm4.2% of the epoch-pairs
the X-ray and UV variability are intrinsically coordinated. The variability
synchronicity exhibits no dependence on physical parameters of quasars or the
time lag of the epoch-pairs, except for stronger variability tends to have
stronger synchronicity. Switches between synchronous and asynchronous
variability are also seen in individual sources. The poor coordination clearly
contradicts both the X-ray reprocessing model and the accretion rate variation
model for AGN variability. The ratios of the observed X-ray variability
amplitude to that in UV span a broad range and peak at ~ 2. The dominant
fraction of the ratios appear too small to be attributed to X-ray reprocessing,
and too large for accretion rate variation. The inhomogeneous disk model which
incorporates both X-ray and UV/optical variability in AGNs is favored by the
observed stochastic relation between X-ray and UV variations.


  In this paper, we study quantitative properties of quantum programs.
Properties of interest include (positive) almost-sure termination, expected
runtime or expected cost, that is, for example, the expected number of
applications of a given quantum gate, etc. After studying the completeness of
these problems in the arithmetical hierarchy over the Clifford+T fragment of
quantum mechanics, we express these problems using a variation of a quantum
pre-expectation transformer, a weakest precondition based technique that allows
to symbolically compute these quantitative properties. Under a smooth
restriction-a restriction to polynomials of bounded degree over a real closed
field-we show that the quantitative problem, which consists in finding an
upper-bound to the pre-expectation, can be decided in time double-exponential
in the size of a program, thus providing, despite its great complexity, one of
the first decidable results on the analysis and verification of quantum
programs. Finally, we sketch how the latter can be transformed into an
efficient synthesis method.


  We introduce a novel method to design and implement a tunable dynamical
tissue phantom for laser speckle-based in-vivo blood flow imaging. This
approach relies on Stochastic Differential Equations (SDE) to control a
piezoelectric actuator which, upon illuminated with a laser source, generates
speckles of pre-defined probability density function and auto-correlation. The
validation experiments show that the phantom can generate dynamic speckles that
closely replicate both surfaces as well as deep tissue blood flow for a
reasonably wide range and accuracy.


  This paper focuses on two main issues; first one is the impact of Similarity
Search to learning the training sample in metric space, and searching based on
supervised learning classi-fication. In particular, four metrics space
searching are based on spatial information that are introduced as the
following; Cheby-shev Distance (CD); Bray Curtis Distance (BCD); Manhattan
Distance (MD) and Euclidean Distance(ED) classifiers. The second issue
investigates the performance of combination of mul-ti-sensor images on the
supervised learning classification accura-cy. QuickBird multispectral data (MS)
and panchromatic data (PAN) have been used in this study to demonstrate the
enhance-ment and accuracy assessment of fused image over the original images.
The supervised classification results of fusion image generated better than the
MS did. QuickBird and the best results with ED classifier than the other did.


  We classify the lattice by elementary 3-cubes which are associated to dual
links occupied by, or free of monopoles. We then compute the quark condensate,
the quark charge and the chiral density on those cubes. By looking at
distributions we demonstrate that monopole trajectories carry considerably more
chirality with respect to the free vacuum.


  In this note we present some recent results for Kirchhoff equations in
generalized Gevrey spaces. We show that these spaces are the natural framework
where classical results can be unified and extended. In particular we focus on
existence and uniqueness results for initial data whose regularity depends on
the continuity modulus of the nonlinear term, both in the strictly hyperbolic
case, and in the degenerate hyperbolic case.


  Crystal faceting can emerge via two broad physical mechanisms: anisotropic
attachment kinetics on growing crystals and anisotropic surface energies on
near-equilibrium crystals. For the case of the ice/vapor system, anisotropic
attachment kinetics is the dominant faceting mechanism, while the possible
occurrence of equilibrium faceting has been debated for many decades. In this
investigation we examine ice/vapor faceting at low supersaturations over the
temperature range -15C<T<0C, where evidence of a roughening transition has been
previously reported. Our findings indicate that a comprehensive attachment
kinetics model can explain all the experimental data to date, while assuming an
essentially isotropic surface energy (which is supported by other
considerations). Specifically, our kinetic model naturally explains the
observed disappearance of prism faceting on slowly growing ice crystals in
vacuum at T>-2C, thus suggesting that snow crystal faceting is caused by
anisotropic attachment kinetics even at extremely slow growth rates.


  In this paper, we consider the concept of $C$-star body in a fixed pointed
closed convex cone $C$ and study the dual mixed volume for $C$-star bodies. For
$C$-star bodies, we establish the corresponding dual Brunn-Minkowski
inequality, the dual Minkowski inequality and the dual Aleksandrov-Fenchel
inequality. Our dual Brunn-Minkowski inequality for $C$-star bodies strengthens
Schneider's Brunn-Minkowski inequality for $C$-coconvex sets.


  Network embedding methods aim at learning low-dimensional latent
representation of nodes in a network. These representations can be used as
features for a wide range of tasks on graphs such as classification,
clustering, link prediction, and visualization. In this survey, we give an
overview of network embeddings by summarizing and categorizing recent
advancements in this research field. We first discuss the desirable properties
of network embeddings and briefly introduce the history of network embedding
algorithms. Then, we discuss network embedding methods under different
scenarios, such as supervised versus unsupervised learning, learning embeddings
for homogeneous networks versus for heterogeneous networks, etc. We further
demonstrate the applications of network embeddings, and conclude the survey
with future work in this area.


  A general problem of $2\rightarrow N_f$ scattering is addressed with all the
states being wave packets with arbitrary phases. Depending on these phases, one
deals with coherent states in $(3+1)$ D, vortex particles with orbital angular
momentum, the Airy beams, and their generalizations. A method is developed in
which a number of events represents a functional of the Wigner functions of
such states. Using width of a packet $\sigma_p/\langle p\rangle$ as a small
parameter, the Wigner functions, the number of events, and a cross section are
represented as power series in this parameter, the first non-vanishing
corrections to their plane-wave expressions are derived, and generalizations
for beams are made. Although in this regime the Wigner functions turn out to be
everywhere positive, the cross section develops new specifically quantum
features, inaccessible in the plane-wave approximation. Among them is
dependence on an impact parameter between the beams, on phases of the incoming
states, and on a phase of the scattering amplitude. A model-independent
analysis of these effects is made. Two ways of measuring how a Coulomb phase
and a hadronic one change with a transferred momentum $t$ are discussed.


  We present CCD broad band photometric observations in the fields of the Third
Galactic Quadrant open clusters NGC 2580 and NGC 2588 ($V(I)_C$ and $UBV(RI)_C$
respectively). From the analysis of our data we found that NGC 2580 is located
at a distance of about 4 kpc and its age is close to 160 Myr. As for NGC 2588,
it is placed at about 5 kpc from the Sun and is 450 Myr old. This means that
NGC 2588 belongs to the extension of the Perseus arm, whereas NGC 2580 is
closer to the local arm structure. The luminosity functions (LFs) have been
constructed for both clusters down to $V \sim 20$ together with their initial
mass functions (IMFs) for stars with masses above $M \sim 1-1.5 M_{\sun}$. The
IMF slopes for the most massive bins yielded values of $x \approx 1.3$ for NGC
2580 and $x \approx 2$ for NGC 2588. In the case of this latter cluster we
found evidence of a core-corona structure produced probably by dynamical
effect. In the main sequences of both clusters we detected gaps, which we
suggest could be real features.


  Based on the technique previously developed by the author, we present a
conjecture which claims that the reciprocal of the n-th largest (in absolute
value) eigenvalue of the Gauss-Kuzmin-Wirsing operator is equal to the sum of a
certain infinite series. This series is constructed recurrently. It consists of
rational functions with integer coefficients in two variables X, Y, specialized
at X=n and Y=2^n. This gives a strong evidence to the conjecture of Mayer and
Roepstorff that eigenvalues have alternating sign. Further, a very similar
recursion yields a series for the dominant eigenvalue of the Mayer-Ruelle
operator.


  Using NRQCD b quarks and HISQ light, strange and charm quarks we have
calculated B meson masses and B^*-B splittings. We quote results for a range of
lattice spacings and sea quark masses, enabling controlled extrapolation to the
physical point. Since the $b$ quark masses and lattice spacing are fixed from
the \Upsilon and other meson masses, this allows accurate, parameter-free tests
of B, B_s, and B_c masses against experiment. We can also predict the mass of
the B^*_c meson.


  Studies of disks around young brown dwarfs are of paramount importance to our
understanding of the origin, diversity and early evolution of sub-stellar
objects. Here we present first results from a systematic search for disk
emission in a spectroscopically confirmed sample of young objects near or below
the sub-stellar boundary in a variety of star-forming regions. Our VLT and Keck
L'-band observations of the sigma Orionis and TW Hydrae associations suggest
that if a majority of brown dwarfs are born with disks, at least the inner
regions of those disks evolve rapidly, possibly clearing out within a few
million years.


  Spatial resolution of most imaging devices is fundamentally restricted by
diffraction. This limitation is manifested in the loss of high spatial
frequency information contained in evanescent waves. As a result, conventional
far-field optics yields no information about an object's subwavelength
features. Here we propose a novel approach to recovering evanescent waves in
the far field, thereby enabling subwavelength-resolved imaging and spatial
spectroscopy. Our approach relies on shifting the frequency and the wave vector
of near-field components via scattering on acoustic phonons. This process
effectively removes the spatial frequency cut-off for unambiguous far field
detection. A straightforward extension of this technique, which we call spatial
Fourier transform infrared spectroscopy, allows to preserve phase information,
making it possible to perform 3D subwavelength imaging. We discuss the
implementation of such a system in the mid-IR and THz bands, with possible
extension to other spectral regions.


  The solution of a two level system driven by a Laser in the adiabatic limit
is determined using third order Magnus expansion. We made the assumption that
the laser is on resonance or close to resonance with the Bohr transition. As a
consequence of which we are able to obtain a Hamiltonian which commute with
itself at different times. We solve the problem using the Sylvester Formula
where we make use of the eigenvalues.


  We consider a broad class of systems of nonlinear integro-differential
equations posed on the real line that arise as Euler-Lagrange equations to
energies involving nonlinear nonlocal interactions. Although these equations
are not readily cast as dynamical systems, we develop a calculus that yields a
natural Hamiltonian formalism. In particular, we formulate Noether's theorem in
this context, identify a degenerate symplectic structure, and derive
Hamiltonian differential equations on finite-dimensional center manifolds when
those exist. Our formalism yields new natural conserved quantities. For
Euler-Lagrange equations arising as traveling-wave equations in gradient flows,
we identify Lyapunov functions. We provide several applications to
pattern-forming systems including neural field and phase separation problems.


  With the growth and accessibility of mobile devices and internet, the ease of
posting and sharing content on social media networks (SMNs) has increased
exponentially. Many users post images that contain "privacy leaks" regarding
themselves or someone else. Privacy leaks include any instance in which a
transfer of personal identifying visual content is shared on SMNs. Private
visual content (images and videos) exposes intimate information that can be
detrimental to your finances, personal life, and reputation. Private visual
content can include baby faces, credit cards, social security cards, house keys
and others. The Hawaii Emergency Agency example provides evidence that visual
content privacy leaks can happen on an individual or organization level. We
find that monitoring techniques are essential for the improvement of private
life and the development of future techniques. More extensive and enduring
techniques will allow typical users, organizations, and the government to have
a positive social media footprint.


  Motivated by the fundamental question of the fate of interacting bosons in
flat bands, we consider a two-dimensional Bose gas at zero temperature with an
underlying quartic single-particle dispersion in one spatial direction. This
type of band structure can be realized using the NIST scheme of spin-orbit
coupling [Y.-J. Lin, K. Jim\'{e}nez-Garcia, and I. B. Spielman, Nature
$\textbf{471}$, 83 (2011)], in the regime where the lower band dispersion has
the form $\varepsilon_{\textbf{k}} \sim k_{x}^{4}/4+k_{y}^{2}+\ldots$, or using
the shaken lattice scheme of Parker $\textit{et al.}$ [C. V. Parker, L.-C. Ha
and C. Chin, Nature Physics $\textbf{9}$, 769 (2013)]. We numerically compare
the ground state energies of the mean-field Bose-Einstein condensate (BEC) and
various trial wave-functions, where bosons avoid each other at short distances.
We discover that, at low densities, several types of strongly correlated states
have an energy per particle ($\epsilon$), which scales with density ($n$) as
$\epsilon \sim n^{4/3}$, in contrast to $\epsilon \sim n$ for the weakly
interacting Bose gas. These competing states include a Wigner crystal,
quasi-condensates described in terms properly symmetrized fermionic states, and
variational wave-functions of Jastrow type. We find that one of the latter has
the lowest energy among the states we consider. This Jastrow-type state has a
strongly reduced, but finite condensate fraction, and true off-diagonal long
range order, which suggests that the ground state of interacting bosons with
quartic dispersion is a strongly-correlated condensate reminiscent of
superfluid Helium-4. Our results show that even for weakly-interacting bosons
in higher dimensions, one can explore the crossover from a weakly-coupled BEC
to a strongly-correlated condensate by simply tuning the single particle
dispersion or density.


  We present high energy spectra and zenith-angle distributions of the
atmospheric muons computed for the depths of the locations of the underwater
neutrino telescopes. We compare the calculations with the data obtained in the
Baikal and the AMANDA muon experiments. The prompt muon contribution to the
muon flux underwater due to recent perturbative QCD-based models of the charm
production is expected to be observable at depths of the large underwater
neutrino telescopes. This appears to be probable even at rather shallow depths
(1-2 km), provided that the energy threshold for muon detection is raised above
$\sim 100$ TeV.


  Conventional quantum annealing does not sample all ground states fairly. We
demonstrate that fair sampling can be achieved by performing simulated
annealing on a quantum annealer. We discuss the problems that occur when
implementing this method and propose an alternative way to overcome them. We
numerically verify the fair sampling ability of our method in a small-scale toy
model.


  We have studied the magnetic field dependence of the thermal conductivity
$\kappa(T,B)$ of highly oriented pyrolytic graphite samples at temperatures
0.2K$ \le T < 10$K and fields 0T$ \le B \le 9$T. The samples show clear
deviations from the Wiedemann-Franz law with a kink behavior at fields $B \sim
0.1 $T near the metal-insulator transition observed in electrical resistivity
measurements. We further show that the oscillations in the thermal conductivity
at the quantum limit $B > 1 $T, which are correlated with the Landau
quantization observed in Hall measurements, increase in amplitude with
temperature following a $\sim T^3$ law at $T > 0.2 $K and show a maximum at $T
\sim 6 $K, suggesting that they are phonons mediated.


  We investigate unique continuation properties and asymptotic behaviour at
boundary points for solutions to a class of elliptic equations involving the
spectral fractional Laplacian. An extension procedure leads us to study a
degenerate or singular equation on a cylinder, with a homogeneous Dirichlet
boundary condition on the lateral surface and a non homogeneous Neumann
condition on the basis. For the extended problem, by an Almgren-type
monotonicity formula and a blow-up analysis, we classify the local asymptotic
profiles at the edge where the transition between boundary conditions occurs.
Passing to traces, an analogous blow-up result and its consequent strong unique
continuation property is deduced for the nonlocal fractional equation.


  Weak labeling is a popular weak supervision strategy for Named Entity
Recognition (NER) tasks, with the goal of reducing the necessity for
hand-crafted annotations. Although there are numerous remarkable annotation
tools for NER labeling, the subject of integrating weak labeling sources is
still unexplored. We introduce a web-based tool for text annotation called
SciAnnotate, which stands for scientific annotation tool. Compared to
frequently used text annotation tools, our annotation tool allows for the
development of weak labels in addition to providing a manual annotation
experience. Our tool provides users with multiple user-friendly interfaces for
creating weak labels. SciAnnotate additionally allows users to incorporate
their own language models and visualize the output of their model for
evaluation. In this study, we take multi-source weak label denoising as an
example, we utilized a Bertifying Conditional Hidden Markov Model to denoise
the weak label generated by our tool. We also evaluate our annotation tool
against the dataset provided by Mysore which contains 230 annotated materials
synthesis procedures. The results shows that a 53.7% reduction in annotation
time obtained AND a 1.6\% increase in recall using weak label denoising. Online
demo is available at https://sciannotate.azurewebsites.net/(demo account can be
found in README), but we don't host a model server with it, please check the
README in supplementary material for model server usage.


  . As Supervisory Control and Data Acquisition (SCADA) systems control several
critical infrastructures, they have connected to the internet. Consequently,
SCADA systems face different sophisticated types of cyber adversaries. This
paper suggests a Probability Risk Identification based Intrusion Detection
System (PRI-IDS) technique based on analysing network traffic of Modbus TCP/IP
for identifying replay attacks. It is acknowledged that Modbus TCP is usually
vulnerable due to its unauthenticated and unencrypted nature. Our technique is
evaluated using a simulation environment by configuring a testbed, which is a
cus- tom SCADA network that is cheap, accurate and scalable. The testbed is
exploited when testing the IDS by sending individual packets from an attacker
located on the same LAN as the Modbus master and slave. The experimental
results demonstrated that the proposed technique can effectively and
efficiently recognise replay attacks.


  We define zonal polynomials of quaternion matrix argument and deduce some
important formulae of zonal polynomials and hypergeometric functions of
quaternion matrix argument. As an application, we give the distributions of the
largest and smallest eigenvalues of a quaternion central Wishart matrix
$W\sim\mathbb{Q}W(n,\Sigma)$, respectively.


  Comprehensive Monte Carlo simulations of the short-time dynamic behaviour are
reported for the three-dimensional Ising model at criticality. Besides the
exponent $\theta$ of the critical initial increase and the dynamic exponent
$z$, the static critical exponents $\nu$ and $\beta$ as well as the critical
temperature are determined from the power-law scaling behaviour of observables
at the beginning of the time evolution. States of very high temperature as well
as of zero temperature are used as initial states for the simulations.


  The twenty years since the announcement of the proton spin crisis by the
European Muon Collaboration has seen tremendous progress in our knowledge of
the distribution of spin within the proton. The problem is reviewed, beginning
with the original data and the suggestion that polarized gluons may play a
crucial role in resolving the problem through the U(1) axial anomaly. The
discussion continues to the present day where not only have strong limits have
been placed on the amount of polarized glue in the proton but the experimental
determination of the spin content has become much more precise. It is now clear
that the origin of the discrepancy between experiment and the naive expectation
of the fraction of spin carried by the quarks and anti-quarks in the proton
lies in the non-perturabtive structure of the proton. We explain how the
features expected in a modern, relativistic and chirally symmetric description
of nucleon structure naturally explain the current data.


  We established a method on measuring the $\dzdzb$ mixing parameter $y$ for
BESIII experiment at the BEPCII $e^+e^-$ collider. In this method, the doubly
tagged $\psi(3770) \to D^0 \overline{D^0}$ events, with one $D$ decays to
CP-eigenstates and the other $D$ decays semileptonically, are used to
reconstruct the signals. Since this analysis requires good $e/\pi$ separation,
a likelihood approach, which combines the $dE/dx$, time of flight and the
electromagnetic shower detectors information, is used for particle
identification. We estimate the sensitivity of the measurement of $y$ to be
0.007 based on a $20fb^{-1}$ fully simulated MC sample.


  We report millisecond-range spin memory of resident electrons in an ensemble
of InP quantum dots (QDs) under a small magnetic field of 0.1 T applied along
the optical excitation axis at temperatures up to about 5 K. A pump-probe
photoluminescence (PL) technique is used for optical orientation of electron
spins by the pump pulses and for study of spin relaxation over the long time
scale by measuring the degree of circular polarization of the probe PL as a
function of pump-probe delay. Dependence of spin decay rate on magnetic field
and temperature suggests two-phonon processes as the dominant spin relaxation
mechanism in this QDs at low temperatures.


  There is an increasing demand for intelligent processing on emerging
ultra-low-power internet of things (IoT) devices, and recent works have shown
substantial efficiency boosts by executing inference tasks directly on the IoT
device (node) rather than merely transmitting sensor data. However, the
computation and power demands of Deep Neural Network (DNN)-based inference pose
significant challenges for nodes in an energy-harvesting wireless sensor
network (EH-WSN). Moreover, these tasks often require responses from multiple
physically distributed EH sensor nodes, which imposes crucial system
optimization challenges in addition to per-node constraints.
  To address these challenges, we propose \emph{Seeker}, a novel approach to
efficiently execute DNN inferences for Human Activity Recognition (HAR) tasks,
using both an EH-WSN and a host mobile device. Seeker minimizes communication
overheads and maximizes computation at each sensor without violating the
quality of service. \emph{Seeker} uses a \emph{store-and-execute} approach to
complete a subset of inferences on the EH sensor node, reducing communication
with the mobile host. Further, for those inferences unfinished because of
harvested energy constraints, it leverages an \emph{activity aware coreset}
(AAC) construction to efficiently communicate compact features to the host
device where ensemble techniques are used to efficiently finish the inferences.
\emph{Seeker} performs HAR with $86.8\%$ accuracy, surpassing the $81.2\%$
accuracy of a state of the art approach. Moreover, by using AAC, it lowers the
communication data volume by $8.9\times$.


  In this work, we revisit the global average pooling layer proposed in [13],
and shed light on how it explicitly enables the convolutional neural network to
have remarkable localization ability despite being trained on image-level
labels. While this technique was previously proposed as a means for
regularizing training, we find that it actually builds a generic localizable
deep representation that can be applied to a variety of tasks. Despite the
apparent simplicity of global average pooling, we are able to achieve 37.1%
top-5 error for object localization on ILSVRC 2014, which is remarkably close
to the 34.2% top-5 error achieved by a fully supervised CNN approach. We
demonstrate that our network is able to localize the discriminative image
regions on a variety of tasks despite not being trained for them


  Let $\Omega\subset\mathbb{R}^n$ be a bounded domain. We perturb it to a
domain $\Omega^\varepsilon$ attaching a family of small protuberances with
"room-and-passage"-like geometry ($\varepsilon>0$ is a small parameter).
Peculiar spectral properties of Neumann problems in so perturbed domains were
observed for the first time by R. Courant and D. Hilbert. We study the case,
when the number of protuberances tends to infinity as $\varepsilon\to 0$ and
they are $\varepsilon$-periodically distributed along a part of
$\partial\Omega$. Our goal is to describe the behaviour of the spectrum of the
operator
$\mathcal{A}^\varepsilon=-(\rho^\varepsilon)^{-1}\Delta_{\Omega^\varepsilon}$,
where $\Delta_{\Omega^\varepsilon}$ is the Neumann Laplacian in
$\Omega^\varepsilon$, and the positive function $\rho^\varepsilon$ is equal to
$1$ in $\Omega$. We prove that the spectrum of $\mathcal{A}^\varepsilon$
converges as $\varepsilon\to 0$ to the "spectrum" of a certain boundary value
problem for the Neumann Laplacian in $\Omega$ with boundary conditions
containing the spectral parameter in a nonlinear manner. Its eigenvalues may
accumulate to a finite point.


  Sun like stars are born from the collapse of fragment of molecular clouds.
During the first embedded phase (the so called class 0/1), the protostar is
surrounded by a collapsing envelope, whose physical and chemical structure
would set up the initial conditions of the proto-stellar disk which may
eventually form planets. In this contribution, we show how spectroscopic far
infrared to millimeter observations can be a powerful diagnostic to derive the
chemical and physical structure of the innermost regions of envelopes
collapsing around solar type protostars, where disk are believe to form. Our
claim is based on the simultaneous modeling of the dynamics, chemistry and
radiative transfer in a protostellar envelope. Here we present a study of a
class 0 protostar NGC1333-IRAS4, obtained using ISO-LWS observations of water
far-infrared lines. We show the derived physical and chemical structure of the
protostar, namely the density and temperature profiles, as well as the water
abundance across the envelope. Besides, the mass of the central protostar and
its accretion rate can be constrained by these observations and modeling,
yielding an alternative method to measure these two poorly know parameters.


  We describe a system composed of two coupled optical cavity modes with a
coupling modulated by a bulk mechanical resonator. In addition, one of the
cavity modes is irreversibly coupled to a single photon source. Our scheme is
an opto-mechanical realisation of the Jaynes-Cummings model where the qubit is
a dual rail optical qubit while the bosonic degree of freedom is a matter
degree of freedom realised as the bulk mechanical excitation. We show the
possibility of engineering phonon number states of the mechanical oscillator in
such a system by computing the conditional state of the mechanics after
successive photon counting measurements.


  Ultra dense cloud small cell network (UDCSNet), which combines cloud
computing and massive deployment of small cells, is a promising technology for
the fifth-generation (5G) LTE-U mobile communications because it can
accommodate the anticipated explosive growth of mobile users' data traffic. As
a result, fronthauling becomes a challenging problem in 5G LTE-U UDCSNet. In
this article, we present an overview of the challenges and requirements of the
fronthaul technology in 5G \mbox{LTE-U} UDCSNets. We survey the advantages and
challenges for various candidate fronthaul technologies such as optical fiber,
millimeter-wave based unlicensed spectrum, Wi-Fi based unlicensed spectrum, sub
6GHz based licensed spectrum, and free-space optical based unlicensed spectrum.


  Since it was realized that the Curry-Howard isomorphism can be extended to
the case of classical logic as well, several calculi have appeared as
candidates for the encodings of proofs in classical logic. One of the most
extensively studied among them is the $\lambda\mu$-calculus of Parigot. In this
paper, based on the result of Xi presented for the $\lambda$-calculus Xi, we
give an upper bound for the lengths of the reduction sequences in the
$\lambda\mu$-calculus extended with the $\rho$- and $\theta$-rules.
Surprisingly, our results show that the new terms and the new rules do not add
to the computational complexity of the calculus despite the fact that
$\mu$-abstraction is able to consume an unbounded number of arguments by virtue
of the $\mu$-rule.


  Extinction is the elephant in the room that almost everyone tries to avoid
when analyzing optical/IR data: astronomers tend to find a quick fix for it
that the referee will accept, but that does not mean such a solution is correct
or even optimal. In this contribution I address three important issues related
to extinction that are commonly ignored and present current and future
solutions for them: [1] Extinction produces non-linear photometric effects, [2]
the extinction law changes between sightlines, and [3] not all families of
extinction laws have the same accuracy.


  Dynamical properties of 2D antiferromagnets with hole doping are investigated
to see the effects of short range local magnetic order on the temperature
dependence of the dynamical magnetic susceptibility. We show the pseudo-gap
like behavior of the temperature dependence of the NMR relaxation rate. We also
discuss implications of the results in relations to the observed spin gap like
behavior of low-doped copper oxide high-$T_c$ superconductors.


  We investigate the potential of the model `CP in the Dark' for providing a
strong first-order electroweak phase transition (SFOEWPT) by taking into
account all relevant theoretical and experimental constraints. For the
derivation of the strength of the phase transition we use the one-loop
corrected, daisy-resummed effective potential at finite temperature,
implemented in the C++ code BSMPT, to determine the global minimum at the
critical temperature. The model `CP in the Dark' provides a dark matter (DM)
candidate as well as explicit CP violation in the dark sector. We find a broad
range of viable parameter points providing an SFOEWPT. They are within the
reach of XENON1T and future invisible Higgs decay searches for DM. `CP in the
Dark' also offers SFOEWPT points that feature spontaneous CP violation at
finite temperature. Having not only an SFOEWPT that provides the necessary
departure from thermal equilibrium, but also a source of additional
non-standard CP violation, opens a promising gate towards enabling the
generation of the baryon asymmetry of the universe (BAU) through electroweak
baryogenesis.


  We present calculations of the charge density profile, subband occupancy and
ellipsometry spectra of the electron gas at the LaAlO3/SrTiO3 interface. The
calculations employ self-consistent Hartree and random phase approximations, a
tight binding parametrization of the band structure and a model for the optical
phonon of SrTiO3. The dependence of the spatial structure and occupancy of
subbands on the magnitude of the polarization charge at the interface and the
dielectric function is determined. The interface-confined subbands may be
labelled by the symmetry (xy, xz, or yz) of the Ti d-orbitals from which they
mainly derive. The xy-derived band nearest the interface contains the major
proportion of the electronic charge, but a large number of more distant,
slightly occupied xy-derived bands are also found. Depending on the magnitude
of the polarization charge, zero, one, or two xz/yz derived subbands are found.
When present, these xz/yz bands give the dominant contribution to the
long-distance tail of the interface charge. The response to applied ac electric
fields polarized parallel and perpendicular to the interface is calculated and
the results are presented in terms of ellipsometry angles. Two features are
found: a dip in the spectrum near the LO feature of the STO phonon and a peak
at the higher energy. We show that the form and magnitude of the dip is related
to the Drude response of carriers moving in the plane of the interface while
the peak arises from the plasmon excitation of the xz and yz electrons. The
relation of the features of the subband occupancies and the in-plane
conductivities is given.


  For the calculation of Springer numbers (of root systems) of type $B_n$ and
$D_n$, Arnold introduced a signed analogue of alternating permutations, called
$\beta_n$-snakes, and derived recurrence relations for enumerating the
$\beta_n$-snakes starting with $k$. The results are presented in the form of
double triangular arrays ($v_{n,k}$) of integers, $1\le |k|\le n$. An Arnold
family is a sequence of sets of such objects as $\beta_n$-snakes that are
counted by $(v_{n,k})$. As a refinement of Arnold's result, we give analogous
arrays of polynomials, defined by recurrence, for the calculation of the
polynomials associated with successive derivatives of $\tan x$ and $\sec x$,
established by Hoffman. Moreover, we provide some new Arnold families of
combinatorial objects that realize the polynomial arrays, which are signed
variants of Andr\'{e} permutations and Simsun permutations.


  In this paper, we investigate the stability problem of subelliptic harmonic
maps with potential. First, we derive the first and second variation formulas
for subelliptic harmonic maps with potential. As a result, it is proved that a
subelliptic harmonic map with potential is stable if the target manifold has
nonpositive curvature and the Hessian of the potential is nonpositive definite.
We also give Leung type results which involve the instability of subelliptic
harmonic maps with potential when the target manifold is a sphere of dimension
$\geq 3$.


  We show algorithmic randomness versions of the two classical theorems on
subsequences of normal numbers. One is Kamae-Weiss theorem (Kamae 1973) on
normal numbers, which characterize the selection function that preserves normal
numbers. Another one is the Steinhaus (1922) theorem on normal numbers, which
characterize the normality from their subsequences. In van Lambalgen (1987), an
algorithmic analogy to Kamae-Weiss theorem is conjectured in terms of
algorithmic randomness and complexity. In this paper we consider two types of
algorithmic random sequence; one is ML-random sequences and the other one is
the set of sequences that have maximal complexity rate. Then we show
algorithmic randomness versions of corresponding theorems to the above
classical results.


  In recent years, a study by environmental organizations in the world and
Vietnam shows that weather change is quite complex. global warming has become a
serious problem in the modern world, which is a concern for scientists. last
century, it was difficult to forecast the weather due to missing weather
monitoring stations and technological limitations. this made it hard to collect
data for building predictive models to make accurate simulations. in Vietnam,
research on weather forecast models is a recent development, having only begun
around 2000. along with advancements in computer science, mathematical models
are being built and applied with machine learning techniques to create more
accurate and reliable predictive models. this article will summarize the
research and solutions for applying recurrent neural networks to forecast urban
temperatures.


  Outflows are inevitably driven from the disk if the vertical component of the
black hole (BH) gravity cannot resist the radiation force. We derive the mass
loss rate in the outflows by solving a dynamical equation for the vertical gas
motion in the disk. The structure of a supercritical accretion disk is
calculated with the radial energy advection included. We find that most
inflowing gas is driven into outflows if the disk is accreting at a moderate
Eddington-scaled rate (up to $\sim 100$) at its outer edge, i.e., only a small
fraction of gas is accreted by the BH, which is radiating at several Eddington
luminosities, while it reaches around ten for extremely high accretion rate
cases ($\dot{m}\equiv\dot{M}/\dot{M}_{\rm Edd}\sim 1000$). Compared with a
normal slim disk, the disk luminosity is substantially suppressed due to the
mass loss in the outflows. We apply the model to the light curves of the tidal
disruption events (TDEs), and find that the disk luminosity declines very
slowly with time even if a typical accretion rate $\dot{m}\propto t^{-5/3}$ is
assumed at the outer edge of the disk, which is qualitatively consistent with
the observed light curves in some TDEs, and helps understanding the energy
deficient phenomenon observed in the TDEs. Strong outflows from supercritical
accretion disks surrounding super massive BHs may play crucial roles on their
host galaxies, which can be taken as an ingredient in the mechanical feedback
models. The implications of the results on the growth of supper-massive BHs are
also discussed.


  We investigate extensions of the N=2 super Virasoro algebra by one additional
super primary field and its charge conjugate. Using a supersymmetric covariant
formalism we construct all N=2 super W-algebras up to spin 5/2 of the
additional generator. Led by these first examples we close with some
conjectures on the classification of N=2 ${\cal SW}(1,\Dt)$ algebras.


  This paper describes some biologically-inspired processes that could be used
to build the sort of networks that we associate with the human brain. New to
this paper, a 'refined' neuron will be proposed. This is a group of neurons
that by joining together can produce a more analogue system, but with the same
level of control and reliability that a binary neuron would have. With this new
structure, it will be possible to think of an essentially binary system in
terms of a more variable set of values. The paper also shows how recent
research associated with the new model, can be combined with established
theories, to produce a more complete picture. The propositions are largely in
line with conventional thinking, but possibly with one or two more radical
suggestions. An earlier cognitive model can be filled in with more specific
details, based on the new research results, where the components appear to fit
together almost seamlessly. The intention of the research has been to describe
plausible 'mechanical' processes that can produce the appropriate brain
structures and mechanisms, but that could be used without the magical
'intelligence' part that is still not fully understood. There are also some
important updates from an earlier version of this paper.


  The Ising one-dimensional (1D) chain with spin $S=1/2$ and magnetoelastic
interactions is studied with the lattice contribution included in the form of
elastic interaction and thermal vibrations simultaneously taken into account.
The magnetic energy term and the elastic (static) energy term based on the
Morse potential are calculated exactly. The vibrational energy is calculated in
the Debye approximation, in which the anharmonicity is introduced by the
Gr{\"u}neisen parameter. The total Gibbs potential, including both the magnetic
field, as well as the external force term, is constructed and from its minimum
the equation of state is derived.
  From the Gibbs energy all the thermodynamic properties are calculated in a
self-consistent manner. The comprehensive numerical calculations are performed
in a full temperature range, i.e., from zero temperature up to the vicinity of
melting. In particular, a role of magneto-elastic coupling is emphasized and
examined. The numerical results are illustrated in figures and discussed.


  It is well known that chaotic dynamic systems (such as three-body system,
turbulent flow and so on) have the sensitive dependence on initial conditions
(SDIC). Unfortunately, numerical noises (such as truncation error and round-off
error) always exist in practice. Thus, due to the SDIC, long-term accurate
prediction of chaotic dynamic systems is practically impossible. In this paper,
a new strategy for chaotic dynamic systems, i.e. the Clean Numerical Simulation
(CNS), is briefly described, together with its applications to a few
Hamiltonian chaotic systems. With negligible numerical noises, the CNS can
provide convergent (reliable) chaotic trajectories in a long enough interval of
time. This is very important for Hamiltonian systems such as three-body
problem, and thus should have many applications in various fields. We find that
the traditional numerical methods in double precision cannot give not only
reliable trajectories but also reliable Fourier power spectra and
autocorrelation functions. In addition, it is found that even statistic
properties of chaotic systems can not be correctly obtained by means of
traditional numerical algorithms in double precision, as long as these
statistics are time-dependent. Thus, our CNS results strongly suggest that one
had better to be very careful on DNS results of statistically unsteady
turbulent flows, although DNS results often agree well with experimental data
when turbulent flows are in a statistical stationary state.


  Control of open quantum systems is an essential ingredient to the realization
of contemporary quantum science and technology. We demonstrate such control by
employing a thermodynamically consistent framework, taking into account the
fact that the drive can modify the interaction with environment. Such an effect
is incorporated within the dynamical equation, leading to control dependent
dissipation, this relation serves as the key element for open system control.
Thermodynamics of the control process is reflected by a unidirectional flow of
energy to the environment resulting in large entropy production. The control
paradigm is displayed by analyzing entropy changing state to state
transformations, such as heating and cooling. In addition, the generation of
quantum gates under dissipative conditions is demonstrated for both non-unitary
reset maps with complete memory loss and a universal set of single and double
qubit unitary gates.


  Strongly correlated metals close to the Mott transition display unusual
transport regimes, together with large spectral weight transfers in optics and
photoemission. We briefly review the theoretical understanding of these
effects, based on the dynamical mean-field theory, and emphasize the key role
played by the two energy scales associated with quasiparticle coherence scale
and with the Mott gap. Recent experimental results on two-dimensional organic
compounds and transition metal oxides are considered in this perspective. The
liquid-gas critical behaviour at the Mott critical endpoint is also discussed.
Transport calculations using the numerical renormalization group are presented.


  In this paper we reveal an additional new cause for decreasing of particles
interference. We found that particle which, transmits kinetic energy to the
detector decrease its wave packet area size. A detector that transmits kinetic
energy to the particle increases the particle's wave packet area. We found
these phenomena cause decrease in the interference pattern. We show that the
interference pattern decrease is graduate and proportional to the amount of the
particle's kinetic energy change. We show that our findings are in agreement
with the results of different experiments like the two slits experiment and the
two paths interferometer experiment. We conclude the wave like behavior of the
particle, is not have to lost in the detection process, it changes its area
size.


  Rademacher theorem asserts that Lipschitz continuous functions between
Euclidean spaces are differentiable almost everywhere. In this work we extend
this result to set-valued maps using an adequate notion of set-valued
differentiability relating to convex processes. Our approach uses Rademacher
theorem but also recovers it as a special case.


  Neutron diffraction and thermodynamics techniques were used to probe the
evolution of the magnetic properties of Tb(Co_{x}Ni_{1-x})_{2}B_{2}C. A
succession of magnetic modes was observed as x is varied: the longitudinal
modulated k=(0.55,0,0) state at x=0 is transformed into a collinear
k=([nicefrac]<LaTeX>\nicefrac{1}{2}</LaTeX>,0,[nicefrac]<LaTeX>\nicefrac{1}{2}</LaTeX>)
antiferromagnetic state at x= 0.2, 0.4; then into a transverse c-axis modulated
k=(0,0,[nicefrac]<LaTeX>\nicefrac{1}{3}</LaTeX>) mode at x= 0.6, and finally
into a simple ferromagnetic structure at x= 0.8 and 1. Concomitantly, the
low-temperature orthorhombic distortion of the tetragonal unit cell at x=0 is
reduced smoothly such that for x >= 0.4 only a tetragonal unit cell is
manifested. Though predicted theoretically earlier, this is the first
observation of the k=(0,0,[nicefrac]<LaTeX>\nicefrac{1}{3}</LaTeX>) mode in
borocarbides; our findings of a succession of magnetic modes upon increasing x
also find support from a recently proposed theoretical model. The implication
of these findings and their interpretation on the magnetic structure of the
RM_{2}B_{2}C series are also discussed.


  For an inclined accretion flow around a rotating black hole, the combined
effect of the Lense-Thirring precession and viscous torque tends to align the
inner part of the flow with the black hole spin, leading to the formation of a
warped disc, known as the Bardeen-Petterson effect (Bardeen & Petterson 1975).
In tidal disruption events (TDEs) in which a super-massive black hole starts to
accrete the bound debris, if the black hole is spinning, in general the stellar
orbit is inclined with the black hole spin. So is the accretion disc formed
following circularization and radiative cooling of the debris. Xiang-Gruess et
al. (2016) studied in detail the stellar debris evolution and disc formation in
TDEs when the stellar orbit is inclined, and found that a warped disc would
form under certain conditions. In this work we investigate properties of
time-resolved fluorescent iron line originating from a warped disc that is
irradiated by the initial X-ray flare. We find that the time-resolved spectrum
shows distinct features before and after a critical time. This critical time
depends on the Bardeen-Petterson radius $r_{\rm BP}$, i.e., the outer boundary
of the inner aligned disc; while the line width during the later stage of the
X-ray flare is sensitive to the inclination of the outer disc flow. This
demonstrates that time-resolved X-ray spectroscopy can be a powerful tool to
probe the Bardeen-Petterson effect in TDE flares and can be used to measure the
Bardeen-Petterson radius as well as put constraint on the black hole mass and
spin.


  Feedback effects due to spin fluctuation induced precursors in the fermionic
quasiparticle spectrum are taken into account in the description of a quantum
critical point of itinerant spin systems. A correlation length dependent spin
damping occurs, leading to a dynamical scaling with z\approx 1 which
non-trivially competes with the conventional spin wave behavior. We obtain,
within a one loop renormalization group approach, a quantitative explanation
for the scaling behavior seen in underdoped cuprate superconductors.