  Label placement in maps is a very challenging task that is critical for the
overall map quality. Most previous work focused on designing and implementing
fully automatic solutions, but the resulting visual and aesthetic quality has
not reached the same level of sophistication that skilled human cartographers
achieve. We investigate a different strategy that combines the strengths of
humans and algorithms. In our proposed method, first an initial labeling is
computed that has many well-placed labels but is not claiming to be perfect.
Instead it serves as a starting point for an expert user who can then
interactively and locally modify the labeling where necessary. In an iterative
human-in-the-loop process alternating between user modifications and local
algorithmic updates and refinements the labeling can be tuned to the user's
needs. We demonstrate our approach by performing different possible
modification steps in a sample workflow with a prototypical interactive
labeling editor. Further, we report computational performance results from a
simulation experiment in QGIS, which investigates the differences between exact
and heuristic algorithms for semi-automatic map labeling. To that end, we
compare several alternatives for recomputing the labeling after local
modifications and updates, as a major ingredient for an interactive labeling
editor.


  Anonymity networks like Tor significantly enhance online privacy but are
vulnerable to correlation attacks by state-level adversaries. While covert
channels encapsulated in media protocols, particularly WebRTC-based
encapsulation, have demonstrated effectiveness against passive traffic
correlation attacks, their resilience against active correlation attacks
remains unexplored, and their compatibility with Tor has been limited. This
paper introduces TorKameleon, a censorship evasion solution designed to protect
Tor users from both passive and active correlation attacks. TorKameleon employs
K-anonymization techniques to fragment and reroute traffic through multiple
TorKameleon proxies, while also utilizing covert WebRTC-based channels or TLS
tunnels to encapsulate user traffic.


  In this contribution we present the superfield T-duality rules relating type
IIA and type IIB supergravity potentials for the case when both type IIA and
type IIB superspaces have (at least) one isometry direction. We also give a
brief review of T-duality and discuss the main steps of our approach to the
derivation of the superfield T-duality rules, including the treatment of
T-duality as an operation acting on differential forms rather than on the
superspace coordinates.


  To improve user experience, Alexa now allows users to consent to data sharing
via voice rather than directing them to the companion smartphone app. While
verbal consent mechanisms for voice assistants (VAs) can increase usability,
they can also undermine principles core to informed consent. We conducted a
Delphi study with experts from academia, industry, and the public sector on
requirements for verbal consent in VAs. Candidate requirements were drawn from
the literature, regulations, and research ethics guidelines that participants
rated based on their relevance to the consent process, actionability by
platforms, and usability by end-users, discussing their reasoning as the study
progressed. We highlight key areas of (dis)agreement between experts, deriving
recommendations for regulators, skill developers, and VA platforms towards
crafting meaningful verbal consent mechanisms. Key themes include approaching
permissions according to the user's ability to opt-out, minimising consent
decisions, and ensuring platforms follow established consent principles.


  Given a symmetric nonnegative matrix $A$, symmetric nonnegative matrix
factorization (symNMF) is the problem of finding a nonnegative matrix $H$,
usually with much fewer columns than $A$, such that $A \approx HH^T$. SymNMF
can be used for data analysis and in particular for various clustering tasks.
In this paper, we propose simple and very efficient coordinate descent schemes
to solve this problem, and that can handle large and sparse input matrices. The
effectiveness of our methods is illustrated on synthetic and real-world data
sets, and we show that they perform favorably compared to recent
state-of-the-art methods.


  In ring theory, the lifting idempotent property (LIP) is related to some
important classes of rings: clean rings, exchange rings, local and semilocal
rings, Gelfand rings,maximal rings, etc. Inspired by LIP, there were defined
lifting properties for other algebraic structures: MV-algebras, BL- algebras,
residuated lattices, abelian l-groups, congruence distributive universal
algebras,etc. In this paper we define a lifting property (LP) in quantales,
structures that constitute a good abstraction of the lattices of ideals,
filters or congruences. LP generalizes all the lifting properties existing in
literature. The main tool in the study of LP in a quantale A is the
reticulation of A, a bounded distributive lattice whose prime spectrum is
homeomorphic to the prime spectrum os A. The principal results of the paper
include a characterization theorem for quantales with LP, a structure theorem
for semilocal quantales with LP and a charaterization theorem for
hyperarhimedean quantales.


  We revisit a concept that has been central in some early stages of computer
science, that of structured programming: a set of rules that an algorithm must
follow in order to acquire a structure that is desirable in many aspects. While
much has been written about structured programming, an important issue has been
left unanswered: given an arbitrary, compiled program, describe an algorithm to
decide whether or not it is structured, that is, whether it conforms to the
stated principles of structured programming. We refer to the classical concept
of structured programming, as described by Dijkstra. By employing a graph model
and graph-theoretic techniques, we formulate an efficient algorithm for
answering this question. To do so, we first introduce the class of graphs which
correspond to structured programs, which we call Dijkstra Graphs. Our problem
then becomes the recognition of such graphs, for which we present a greedy
$O(n)$-time algorithm. Furthermore, we describe an isomorphism algorithm for
Dijkstra graphs, whose complexity is also linear in the number of vertices of
the graph. Both the recognition and isomorphism algorithms have potential
important applications, such as in code similarity analysis.


  Optical spectroscopic observations of white dwarf stars selected from
catalogs based on the Gaia DR2 database reveal nine new gaseous debris disks
that orbit single white dwarf stars, about a factor of two increase over the
previously known sample. For each source we present gas emission lines
identified and basic stellar parameters, including abundances for lines seen
with low-resolution spectroscopy. Principle discoveries include: (1) the
coolest white dwarf (Teff~12,720 K) with a gas disk; this star, WD0145+234, has
been reported to have undergone a recent infrared outburst; (2) co-location in
velocity space of gaseous emission from multiple elements, suggesting that
different elements are well-mixed; (3) highly asymmetric emission structures
toward SDSSJ0006+2858, and possibly asymmetric structures for two other
systems; (4) an overall sample composed of approximately 25% DB and 75% DA
white dwarfs, consistent with the overall distribution of primary atmospheric
types found in the field population; and (5) never-before-seen emission lines
from Na in the spectra of GaiaJ0611-6931, semi-forbidden Mg, Ca, and Fe lines
toward WD0842+572, and Si in both stars. The currently known sample of gaseous
debris disk systems is significantly skewed towards northern hemisphere stars,
suggesting a dozen or so emission line stars are waiting to be found in the
southern hemisphere.


  Given a finitely generated algebra $A$, it is a fundamental question whether
$A$ has a full rank discrete (Krull) valuation $\mathfrak{v}$ with finitely
generated value semigroup. We give a necessary and sufficient condition for
this, in terms of tropical geometry of $A$. In the course of this we introduce
the notion of a Khovanskii basis for $(A, \mathfrak{v})$ which provides a
framework for far extending Gr\"obner theory on polynomial algebras to general
finitely generated algebras. In particular, this makes a direct connection
between the theory of Newton-Okounkov bodies and tropical geometry, and toric
degenerations arising in both contexts. We also construct an associated
compactification of $Spec(A)$. Our approach includes many familiar examples
such as the Gel'fand-Zetlin degenerations of coordinate rings of flag varieties
as well as wonderful compactifications of reductive groups. We expect that many
examples coming from cluster algebras naturally fit into our framework.


  We present a new algorithm to solve polynomial equations, and publish its
code, which is 1.6-3 times faster than the ZROOTS subroutine that is
commercially available from Numerical Recipes, depending on application. The
largest improvement, when compared to naive solvers, comes from a fail-safe
procedure that permits us to skip the majority of the calculations in the great
majority of cases, without risking catastrophic failure in the few cases that
these are actually required. Second, we identify a discriminant that enables a
rational choice between Laguerre's Method and Newton's Method (or a new
intermediate method) on a case-by-case basis. We briefly review the history of
root solving and demonstrate that "Newton's Method" was discovered neither by
Newton (1671) nor by Raphson (1690), but only by Simpson (1740). Some of the
arguments leading to this conclusion were first given by the British historian
of science Nick Kollerstrom in 1992, but these do not appear to have penetrated
the astronomical community. Finally, we argue that Numerical Recipes should
voluntarily surrender its copyright protection for non-profit applications,
despite the fact that, in this particular case, such protection was the major
stimulant for developing our improved algorithm.


  This tutorial article provides a concise and pedagogical overview on
negatively-charged nitrogen-vacancy (NV) centers in diamond. The research on
the NV centers has attracted enormous attention for its application to quantum
sensing, encompassing the areas of not only physics and applied physics but
also chemistry, biology and life sciences. Nonetheless, its key technical
aspects can be understood from the viewpoint of magnetic resonance. We focus on
three facets of this ever-expanding research field, to which our viewpoint is
especially relevant: microwave engineering, materials science, and
magnetometry. In explaining these aspects, we provide a technical basis and
up-to-date technologies for the research on the NV centers.


  It is suggested that the outflowing plasma in the jets of active galactic
nuclei (AGNs) is inhomogeneous and consists of separate clouds. These clouds
are strongly magnetized and move away from the central engine at relativistic
speeds. The clouds interact with an ambient medium which is assumed to be at
rest. In the process of this interaction, particles of the ambient medium are
accelerated to high energies at the cloud front and flow ahead of the front. It
is shown that the radiation of the accelerated particles may be responsible for
the X-ray and $\gamma$-ray emission from AGN jets. TeV $\gamma$-ray emission is
generated in the inner parts of AGN jets where the Lorentz factor of the cloud
fronts is $\Gamma_0\geq 30$, while GeV $\gamma$-ray emission emanates from the
outer parts of AGN jets where $\Gamma_0$ is $\sim 10$.


  We study the limits of accuracy for weak lensing maps of dark matter using
diffuse 21-cm radiation from the pre-reionization epoch using simulations. We
improve on previous "optimal" quadratic lensing estimators by using shear and
convergence instead of deflection angles. We find that non-Gaussianity provides
a limit to the accuracy of weak lensing reconstruction, even if instrumental
noise is reduced to zero. The best reconstruction result is equivalent to
Gaussian sources with effectively independent cell of side length 2.0/h Mpc.
Using a source full map from z=10-20, this limiting sensitivity allows mapping
of dark matter at a Signal-to-Noise ratio (S/N) greater than 1 out to l < 6000,
which is better than any other proposed technique for large area weak lensing
mapping.


  Levenshtein distance is a commonly used edit distance metric, typically
applied in language processing, and to a lesser extent, in molecular biology
analysis. Biological nucleic acid sequences are often embedded in longer
sequences and are subject to insertion and deletion errors that introduce
frameshift during sequencing. These frameshift errors are due to string context
and should not be counted as true biological errors. Sequence-Levenshtein
distance is a modification to Levenshtein distance that is permissive of
frameshift error without additional penalty. However, in a biological context
Levenshtein distance needs to accommodate both frameshift and weighted errors,
which Sequence-Levenshtein distance cannot do. Errors are weighted when they
are associated with a numerical cost that corresponds to their frequency of
appearance. Here, we describe a modification that allows the use of Levenshtein
distance and Sequence-Levenshtein distance to appropriately accommodate
penalty-free frameshift between embedded sequences and correctly weight
specific error types.


  The question as to whether neutron acceleration can occur in uniform
electromagnetic fields is examined. Although such an effect has been predicted
using the canonical equations of motion some doubt has been raised recently as
to whether it is in principle observable for a spin 1/2 particle. To resolve
this issue a gedanken experiment is proposed and analyzed using a wave packet
construction for the neutron beam. By allowing arbitrary orientation for the
neutron spin as well as for the electric and magnetic fields a non vanishing
acceleration of the center of the neutron wave packet is found which confirms
the predictions of the canonical formalism.


  We solve the problem of discriminating with minimum error probability two
given Pauli channels. We show that, differently from the case of discrimination
between unitary transformations, the use of entanglement with an ancillary
system can strictly improve the discrimination, and any maximally entangled
state allows to achieve the optimal discrimination. We also provide a simple
necessary and sufficient condition in terms of the structure of the channels
for which the ultimate minimum error probability can be achieved without
entanglement assistance. When such a condition is satisfied, the optimal input
state is simply an eigenstate of one of the Pauli matrices.


  We isolate a new class of ultrafilters on N, called "quasi-selective" because
they are intermediate between selective ultrafilters and P-points. (Under the
Continuum Hypothesis these three classes are distinct.) The existence of
quasi-selective ultrafilters is equivalent to the existence of "asymptotic
numerosities" for all sets of tuples of natural numbers. Such numerosities are
hypernatural numbers that generalize finite cardinalities to countable point
sets. Most notably, they maintain the structure of ordered semiring, and, in a
precise sense, they allow for a natural extension of asymptotic density to all
sequences of tuples of natural numbers.


  This paper presents a fast algorithm for obtaining high-accuracy subpixel
translation of low PSNR images. Instead of locating the maximum point on the
upsampled images or fitting the peak of correlation surface, the proposed
algorithm is based on the measurement of centroid on the cross correlation
surface by Modified Moment method. Synthetic images, real solar images and
standard testing images with white Gaussian noise added were tested, and the
results show that the accuracies of our algorithm are comparable with other
subpixel registration techniques and the processing speed is higher. The
drawback is also discussed at the end of this paper.


  In Figure 6 we inadvertently labeled the proxy circular velocity as the
virial velocity of the dark matter halo instead of what is actually plotted,
the maximum circular velocity of the dark matter halo. The maximum halo
circular velocity is a much better estimate of the disk V_c than is V_vir. This
confusion influenced the discussion of the Tully-Fisher relation in our paper.
In fact, Figure 6 demonstrates that it is possible to simultaneously reproduce
both the local Tully-Fisher relation and luminosity function using
semi-analytic techniques applied to the standard LCDM cosmology, thus
contradicting previous studies of this issue and our own discussion in Section
3.6.


  A general form of quasi-de Sitter(dS) modes in a dynamical background is used
to study the creation of particle during the inflation. Actually, by
considering the general form of inflaton field equation as a function of the
Hankel function index and by using the Planck 2015 constraint on spectral
index, we obtain the possible new constraints for the values of coupling
constant in the era with quasi-dS space-time. Then, we explicitly calculate the
general form of expectation value of the created particles in terms of the
Hankel function index and the conformal time. As an important result, we see
that the number of created particles and the value of coupling constant can be
dependent to the selection of the background space-time and it's dynamics. Our
result is general and confirm the conventional special results for the
Minkowski and dS background.


  We extend the weighted ensemble (WE) path sampling method to perform rigorous
statistical sampling for systems at steady state. The straightforward
steady-state implementation of WE is directly practical for simple landscapes,
but not when significant metastable intermediates states are present. We
therefore develop an enhanced WE scheme, building on existing ideas, which
accelerates attainment of steady state in complex systems. We apply both WE
approaches to several model systems confirming their correctness and efficiency
by comparison with brute-force results. The enhanced version is significantly
faster than the brute force and straightforward WE for systems with WE bins
that accurately reflect the reaction coordinate(s). The new WE methods can also
be applied to equilibrium sampling, since equilibrium is a steady state.


  Let (A,\alpha) be a C*-dynamical system. We introduce the notion of pressure
P_\alpha(H) of the automorphism \alpha at a self-adjoint operator H\in A. Then
we consider the class of AF-systems satisfying the following condition: there
exists a dense \alpha-invariant *-subalgebra \A of A such that for all pairs
a,b\in\A the C*-algebra they generate is finite dimensional, and there is
p=p(a,b)\in\N such that [\alpha^j(a),b]=0 for |j|\ge p. For systems in this
class we prove the variational principle, i.e. show that P_\alpha(H) is the
supremum of the quantities h_\phi(\alpha)-\phi(H), where h_\phi(\alpha) is the
Connes-Narnhofer-Thirring dynamical entropy of \alpha with respect to the
\alpha-invariant state \phi. If H\in\A, and P_\alpha(H) is finite, we show that
any state on which the supremum is attained is a KMS-state with respect to a
one-parameter automorphism group naturally associated with H. In particular,
Voiculescu's topological entropy is equal to the supremum of h_\phi(\alpha),
and any state of finite maximal entropy is a trace.


  Graph contrastive learning (GCL), as an emerging self-supervised learning
technique on graphs, aims to learn representations via instance discrimination.
Its performance heavily relies on graph augmentation to reflect invariant
patterns that are robust to small perturbations; yet it still remains unclear
about what graph invariance GCL should capture. Recent studies mainly perform
topology augmentations in a uniformly random manner in the spatial domain,
ignoring its influence on the intrinsic structural properties embedded in the
spectral domain. In this work, we aim to find a principled way for topology
augmentations by exploring the invariance of graphs from the spectral
perspective. We develop spectral augmentation which guides topology
augmentations by maximizing the spectral change. Extensive experiments on both
graph and node classification tasks demonstrate the effectiveness of our method
in self-supervised representation learning. The proposed method also brings
promising generalization capability in transfer learning, and is equipped with
intriguing robustness property under adversarial attacks. Our study sheds light
on a general principle for graph topology augmentation.


  Classical inference methods notoriously fail when applied to data-driven test
hypotheses or inference targets. Instead, dedicated methodologies are required
to obtain statistical guarantees for these selective inference problems.
Selective inference is particularly relevant post-clustering, typically when
testing a difference in mean between two clusters. In this paper, we address
convex clustering with $\ell_1$ penalization, by leveraging related selective
inference tools for regression, based on Gaussian vectors conditioned to
polyhedral sets. In the one-dimensional case, we prove a polyhedral
characterization of obtaining given clusters, than enables us to suggest a test
procedure with statistical guarantees. This characterization also allows us to
provide a computationally efficient regularization path algorithm. Then, we
extend the above test procedure and guarantees to multi-dimensional clustering
with $\ell_1$ penalization, and also to more general multi-dimensional
clusterings that aggregate one-dimensional ones. With various numerical
experiments, we validate our statistical guarantees and we demonstrate the
power of our methods to detect differences in mean between clusters. Our
methods are implemented in the R package poclin.


  Using a sample with a split back-gate, a linear frequency dependence of the
ac quantum Hall resistance was observed. The frequency coefficient, which is
due to dielectric losses produced by leakage current between the 2DEG and the
back-gates, can be turned from a positive to a negative values by increasing
the back-gate voltage. More interestingly, by removing theses back-gates, the
losses can be considerably reduced leading to a residual frequency coefficient
on the order of (0.03+-0.03) ppm/kHz. Moreover, at 1 kHz, an extremely flat
plateau was observed over a magnetic field range of 1.4 T. These results
clearly indicate that the audio frequency dependence of the QHR is to a large
extend related to the measurement apparatus and does not originate from the
physical transport properties of the 2DEG.


  Context dependence is central to the description of complexity. Keying on the
pairwise definition of "set complexity" we use an information theory approach
to formulate general measures of systems complexity. We examine the properties
of multi-variable dependency starting with the concept of interaction
information. We then present a new measure for unbiased detection of
multi-variable dependency, "differential interaction information." This
quantity for two variables reduces to the pairwise "set complexity" previously
proposed as a context-dependent measure of information in biological systems.
We generalize it here to an arbitrary number of variables. Critical limiting
properties of the "differential interaction information" are key to the
generalization. This measure extends previous ideas about biological
information and provides a more sophisticated basis for study of complexity.
The properties of "differential interaction information" also suggest new
approaches to data analysis. Given a data set of system measurements
differential interaction information can provide a measure of collective
dependence, which can be represented in hypergraphs describing complex system
interaction patterns. We investigate this kind of analysis using simulated data
sets. The conjoining of a generalized set complexity measure, multi-variable
dependency analysis, and hypergraphs is our central result. While our focus is
on complex biological systems, our results are applicable to any complex
system.


  We present an extension of the multi-region relaxed magnetohydrodynamics
(MRxMHD) equilibrium model that includes pressure anisotropy and general plasma
flows. This anisotropic extension to our previous isotropic model is motivated
by Sun and Finn's model of relaxed anisotropic magnetohydrodynamic equilibria.
We prove that as the number of plasma regions becomes infinite, our anisotropic
extension of MRxMHD reduces to anisotropic ideal MHD with flow. The
continuously nested flux surface limit of our MRxMHD model is the first
variational principle for anisotropic plasma equilibria with general flow
fields.


  We introduce quasi-symplectic groupoids and explain their relation with
momentum map theories. This approach enables us to unify into a single
framework various momentum map theories, including the ordinary Hamiltonian
$G$-spaces, Lu's momentum maps of Poisson group actions, and group valued
momentum maps of Alekseev--Malkin--Meinrenken.
  More precisely, we carry out the following program:
  (1) Define and study properties of quasi-symplectic groupoids;
  (2) Study the momentum map theory defined by a quasi-symplectic groupoid. In
particular, we study the reduction theory and prove that the reduced space is
always a symplectic manifold. More generally, we prove that the classical
intertwiner space between two Hamiltonian $\Gamma$-spaces is always a
symplectic manifold whenever it is a smooth manifold;
  (3) Study the Morita equivalence of quasi-symplectic groupoids. In
particular, we prove that Morita equivalent quasi-symplectic groupoids give
rise to equivalent momentum map theories and that the intertwiner space depends
only on the Morita equivalence class. As a result, we recover various
well-known results concerning equivalence of momentum maps including Alekseev--
Ginzburg--Weinstein linearization theorem and Alekseev--Malkin--Meinrenken
equivalence theorem between quasi-Hamiltonian spaces and Hamiltonian loop group
sapces.


  The Lagrangian and Hamiltonian functions describing average motion of a
relativistic particle under the action of a slightly inhomogeneous intense
laser field are obtained. In weak low-frequency background fields, such a
particle on average drifts with an effective, relativistically invariant mass,
which depends on the laser intensity. The essence of the proposed ponderomotive
formulation is presented in a physically intuitive and mathematically simple
form, yet represents a powerful tool for studying various nonlinear phenomena
caused by interaction of currently available smooth ultra-intense laser pulses
with plasmas.


  We discuss how D=5 maximally supersymmetric Yang-Mills theory (MSYM) might be
used to study or even to define the (2,0) theory in six dimensions. It is known
that the compactification of (2,0) theory on a circle leads to D=5 MSYM. A
variety of arguments suggest that the relation can be reversed, and that all of
the degrees of freedom of (2,0) theory are already present in D=5 MSYM. If so,
this relation should have consequences for D=5 SYM perturbation theory. We
explore whether it might imply all orders finiteness, or else an unusual
relation between the cutoff and the gauge coupling. S-duality of the reduction
to D=4 may provide nonperturbative constraints or tests of these options.


  We have determined the fundamental properties and distance of a fourth
eclipsing binary system (EB) in the Large Magellanic Cloud, HV5936 (B0.5 V + B2
III). As in our previous studies, we combine "classical" EB light curve and
radial velocity curve analyses with modeling of the UV-through-optical spectral
energy distribution of HV5936 to produce a detailed characterization of the
system. In this paper, we also include an analysis of the high-resolution
optical absorption line spectra of the binary components. We find HV5936 to be
an Algol-class system, in which the masses of the primary and secondary stars
have evolved via mass transfer to their current values of 11.6 Mo and 4.7 Mo,
respectively. The properties of the primary star are indistinguishable from
those of a "normal" star of the same current mass. The secondary is found to be
overluminous for its current mass and exhibits a factor-of-2 enhancement in its
surface He abundance. These results are compatible with "Case A" mass exchange
occurring during the core hydrogen burning phase of the current secondary. The
distance derived to the system, 43.2 +/- 1.8 kpc, implies a distance of ~44.3
kpc to the optical center of the LMC. This is several kpc closer than found in
our analyses of other systems and we suggest that HV5936 lies "above" the LMC
disk. This is supported by the very low interstellar H I column density and low
E(B-V) found for the system - both of which are consistent with expected Milky
Way foreground material - and may be associated with HV5936's location near the
LMC supergiant shell LMC4.


  Generative AI (GAI) offers unprecedented opportunities for research and
innovation, but its commercialization has raised concerns about transparency,
reproducibility, and safety. Many open GAI models lack the necessary components
for full understanding and reproducibility, and some use restrictive licenses
whilst claiming to be ``open-source''. To address these concerns, we propose
the Model Openness Framework (MOF), a ranked classification system that rates
machine learning models based on their completeness and openness, following
principles of open science, open source, open data, and open access. The MOF
requires specific components of the model development lifecycle to be included
and released under appropriate open licenses. This framework aims to prevent
misrepresentation of models claiming to be open, guide researchers and
developers in providing all model components under permissive licenses, and
help individuals and organizations identify models that can be safely adopted
without restrictions. By promoting transparency and reproducibility, the MOF
combats ``openwashing'' practices and establishes completeness and openness as
primary criteria alongside the core tenets of responsible AI. Wide adoption of
the MOF will foster a more open AI ecosystem, benefiting research, innovation,
and adoption of state-of-the-art models.


  Building a natural language dataset requires caution since word semantics is
vulnerable to subtle text change or the definition of the annotated concept.
Such a tendency can be seen in generative tasks like question-answering and
dialogue generation and also in tasks that create a categorization-based
corpus, like topic classification or sentiment analysis. Open-domain
conversations involve two or more crowdworkers freely conversing about any
topic, and collecting such data is particularly difficult for two reasons: 1)
the dataset should be ``crafted" rather than ``obtained" due to privacy
concerns, and 2) paid creation of such dialogues may differ from how
crowdworkers behave in real-world settings. In this study, we tackle these
issues when creating a large-scale open-domain persona dialogue corpus, where
persona implies that the conversation is performed by several actors with a
fixed persona and user-side workers from an unspecified crowd.


  For a quantum measurement process described by a quantum instrument
$\mathcal{I}$ and a system observable corresponding to a positive-operator
valued measure (POVM) $E ,$ $\mathcal{I}$ is said to conserve the information
of $E$ if the joint successive measurement of $\mathcal{I}$ followed by $E$ is
equivalent to a single measurement of $E .$ We show that for any quantum
instrument $\mathcal{I}$ we can construct a POVM conserved by $\mathcal{I}$.
Intuitively the construction gives the infinite joint successive measurement of
$\mathcal{I}.$ We also show that the constructed POVM is the least informative
observable among POVMs conserved by $\mathcal{I}$, i.e. the constructed POVM
can be realized by a classical post-processing of any POVM conserved by
$\mathcal{I} .$ As typical examples of quantum instruments, we explicitly
evaluate POVMs of infinite successive measurements for photon counting and
quantum counter instruments.


  The SYZ Conjecture explains Mirror Symmetry between mirror Calabi-Yau 3-folds
M,M' in terms of special Lagrangian fibrations f : M --> B and f' : M' --> B
over the same base B, whose fibres are dual 3-tori, except for singular fibres.
  One of the main problems in proving the SYZ Conjecture (or even in finding
the right statement of it) is that the singularities of special Lagrangian
3-folds and fibrations are poorly understood. This paper studies the
singularities of special Lagrangian fibrations.
  Our main rigorous results are the construction of examples of special
Lagrangian fibrations on open subsets of C^3. The simplest are given
explicitly, and the rest are constructed using analytic existence results from
the author's three papers math.DG/0111324, math.DG/0111326, math.DG/0204343 on
U(1)-invariant special Lagrangian 3-folds in C^3.
  We then argue, without full proofs, that some features of our examples should
also hold for special Lagrangian fibrations f : M --> B of (almost) Calabi-Yau
3-folds, especially in the generic case. In particular, f will not be smooth
but only piecewise-smooth, and the discriminant (set of singular fibres) of f
will be of codimension 1 in B, and will typically be composed of 'ribbons'.
Finally we draw some conclusions on the SYZ Conjecture, which contradict some
stronger statements of it.


  Wrinkles in monolayer graphene (GN) affect the GN electronic and transport
properties. Defined network of wrinkles can be reached by placing the GN on the
substrate decorated with the nanoparticles (NPs). In order to explain mechanism
behind the topographically induced changes of the GN electronic structure and
to correlate it with the wrinkling, correct description of the GN morphology is
of high demand. We demonstrate here how to determine from the atomic force
microscopy (AFM) images whether the GN is in the contact with the substrate or
it is delaminated, how is the wrinkling of the layer connected with the density
of the NPs and if there is the preferential orientation of wrinkles. Also the
relevance of detection of the NPs hidden beneath the GN layer is discussed. The
study was done on nine samples of the GN on the top of Si-SiO2 substrate,
decorated with the metal-oxide NPs of nominal diameter 6 and 10 nm. NP density
varied in a range of 20 up to 470 NPs per um2. The projected area of wrinkles
was increasing linearly with the increasing NP density, independently on the NP
size.


  This paper proposes a method for automatic generation of textures for 3D city
meshes in immersive urban environments. Many recent pipelines capture or
synthesize large quantities of city geometry using scanners or procedural
modeling pipelines. Such geometry is intricate and realistic, however the
generation of photo-realistic textures for such large scenes remains a problem.
We propose to generate textures for input target 3D meshes driven by the
textural style present in readily available datasets of panoramic photos
capturing urban environments. Re-targeting such 2D datasets to 3D geometry is
challenging because the underlying shape, size, and layout of the urban
structures in the photos do not correspond to the ones in the target meshes.
Photos also often have objects (e.g., trees, vehicles) that may not even be
present in the target geometry. To address these issues we present a method,
called Projective Urban Texturing (PUT), which re-targets textural style from
real-world panoramic images to unseen urban meshes. PUT relies on contrastive
and adversarial training of a neural architecture designed for unpaired
image-to-texture translation. The generated textures are stored in a texture
atlas applied to the target 3D mesh geometry. To promote texture consistency,
PUT employs an iterative procedure in which texture synthesis is conditioned on
previously generated, adjacent textures. We demonstrate both quantitative and
qualitative evaluation of the generated textures.


  Feedback transmissions are used to acknowledge correct packet reception,
trigger erroneous packet re-transmissions, and adapt transmission parameters
(e.g., rate and power). Despite the paramount role of feedback in establishing
reliable communication links, the majority of the literature overlooks its
impact by assuming genie-aided systems relying on flawless and instantaneous
feedback. An idealistic feedback assumption is no longer valid for large-scale
Internet of Things (IoT), which has energy-constrained devices, susceptible to
interference, and serves delay-sensitive applications. Furthermore,
feedback-free operation is necessitated for IoT receivers with stringent energy
constraints. In this context, this paper explicitly accounts for the impact of
feedback in energy-constrained and delay-sensitive large-scale IoT networks. We
consider a time-slotted system with closed-loop and open-loop rate adaptation
schemes, where packets are fragmented to operate at a reliable transmission
rate satisfying packet delivery deadlines. In the closed-loop scheme, the
delivery of each fragment is acknowledged through an error-prone feedback
channel. The open-loop scheme has no feedback mechanism, and hence, a
predetermined fragment repetition strategy is employed to improve transmission
reliability. Using tools from stochastic geometry and queueing theory, we
develop a novel spatiotemporal framework to optimize the number of fragments
for both schemes and repetitions for the open-loop scheme. To this end, we
quantify the impact of feedback on the network performance in terms of
transmission reliability, latency, and energy consumption.


  Various metallic structures of complex shape, resembling natural objects such
as plants, mushrooms, and seashells, were produced when growing nanowires by
means of pulsed current electroplating in porous membranes. These structures
occur as the result of nanowires self-assembling (biomimetics) if the
electroplating is continued after the nanowires reach the membrane surface. By
varying the membrane geometry and the pulsed current parameters, and
alternating electroplating from two baths with different electrolytes, various
models were fabricated, including a hollow container with wall thickness of
10-30 nm. The possibility of shape regulation for models was demonstrated: in
certain conditions, mushroom- and shell-like convex-concave models of the same
kind were obtained. The hierarchical structure of models at the nano-, micro-
and mesoscopic levels is shown through fragmentation and chemical etching.


  Zaslavskii has suggested how to tighten Bekenstein's bound on entropy when
the object is electrically charged. Recently Hod has provided a second tighter
version of the bound applicable when the object is rotating. Here we derive
Zaslavskii's optimized bound by considering the accretion of an ordinary
charged object by a black hole. The force originating from the polarization of
the black hole by a nearby charge is central to the derivation of the bound
from the generalized second law. We also conjecture an entropy bound for
charged rotating objects, a synthesis of Zaslavskii's and Hod's. On the basis
of the no hair principle for black holes, we show that this last bound cannot
be tightened further in a generic way by knowledge of ``global'' conserved
charges, e.g., baryon number, which may be borne by the object.


  The phase transition of the one-dimensional, diffusive pair contact process
(PCPD) is investigated by N cluster mean-field approximations and high
precision simulations. The N=3,4 cluster approximations exhibit smooth
transition line to absorbing state by varying the diffusion rate D with
beta_2=2 mean-field order parameter exponent of the pair density. This
contradicts with former N=2 results, where two different mean-field behavior
was found along the transition line. Extensive dynamical simulations on L=10^5
lattices give estimates for the order parameter exponents of the particles for
0.05 <= D <= 0.7. These data can support former two distinct class findings.
However the gap between low and high D exponents is narrower than estimated
previously and the possibility for interpreting numerical data as a single
class behavior with exponents alpha=0.21(1), beta=0.41(1) assuming logarithmic
corrections is shown. Finite size scaling and cluster simulation results are
also presented.


  Using astrometric techniques developed by Anderson et al., we determine
proper motions (PMs) in 14.60 arcmin X 16.53 arcmin area of the kinematically
"thick-disk" globular cluster M12. The cluster's proximity and sparse nature
makes it a suitable target for ground-based telescopes. Archive images with
time gap of 11.1 years were observed with wide-field imager (WFI) mosaic camera
mounted on ESO 2.2 m telescope. The median value of PM error in both components
is 0.7 mas/yr for the stars having V less than or equal to 20 mag. PMs are used
to determine membership probabilities and to separate field stars from the
cluster sample. In electronic form, a membership catalog of 3725 stars with
precise coordinates, PMs, BVRI photometry is being provided. One of the
possible applications of the catalog was shown by gathering the membership
information of the variable stars, blue stragglers and X-ray sources reported
earlier in the cluster's region.


  We present studies of strong coupling in single-photon photoassociation of
cesium dimers using an optical dipole trap. A thermodynamic model of the trap
depletion dynamics is employed to extract absolute rate coefficents. From the
dependence of the rate coefficient on the photoassociation laser intensity, we
observe saturation of the photoassociation scattering probability at the
unitarity limit in quantitative agreement with the theoretical model by Bohn
and Julienne [Phys. Rev. A, 60, 414 (1999)]. Also the corresponding power
broadening of the resonance width is measured. We could not observe an
intensity dependent light shift in contrast to findings for lithium and
rubidium, which is attributed to the absence of a p or d-wave shape resonance
in cesium.


  Recent vision transformer based video models mostly follow the ``image
pre-training then finetuning" paradigm and have achieved great success on
multiple video benchmarks. However, full finetuning such a video model could be
computationally expensive and unnecessary, given the pre-trained image
transformer models have demonstrated exceptional transferability. In this work,
we propose a novel method to Adapt pre-trained Image Models (AIM) for efficient
video understanding. By freezing the pre-trained image model and adding a few
lightweight Adapters, we introduce spatial adaptation, temporal adaptation and
joint adaptation to gradually equip an image model with spatiotemporal
reasoning capability. We show that our proposed AIM can achieve competitive or
even better performance than prior arts with substantially fewer tunable
parameters on four video action recognition benchmarks. Thanks to its
simplicity, our method is also generally applicable to different image
pre-trained models, which has the potential to leverage more powerful image
foundation models in the future. The project webpage is
\url{https://adapt-image-models.github.io/}.


  Matrix elements of Wilson-line dressed operators play a central role in the
factorization of soft and collinear modes in gauge theories. When expressed
using spinor helicity variables, these so-called form factors admit a
classification starting from a Maximally Helicity Violating configuration, in
close analogy with gauge theory amplitudes. We show that a single-line complex
momentum shift can be used to derive recursion relations that efficiently
compute these helicity form factors at tree-level: a combination of lower point
form factors and on-shell amplitudes serve as the input building blocks. We
obtain novel compact expressions for the $1\to 2$ and $1\to 3$ splitting
functions in QCD, which also serves to validate our methods.


  We use Monte Carlo simulations to investigate the theory of galaxy-galaxy
lensing by non-spherical dark matter haloes. The simulations include a careful
accounting of the effects of multiple deflections. In a typical data set where
the mean tangential shear of sources with redshifts zs ~ 0.6 is measured with
respect to the observed symmetry axes of foreground galaxies with redshifts zl
~ 0.3, the signature of anisotropic galaxy-galaxy lensing differs substantially
from the expectation that one would have in the absence of multiple
deflections. The observed ratio of the mean tangential shears, g+/g-, is
strongly suppressed compared to the function that one would measure if the
intrinsic symmetry axes of the foreground galaxies were known. Depending upon
the characteristic masses of the lenses, the observed ratio of the mean
tangential shears may be consistent with an isotropic signal (despite the fact
that the lenses are non-spherical), or it may even be reversed from the
expected signal (i.e., the mean tangential shear for sources close to the
observed minor axes of the lenses may exceed the mean tangential shear for
sources close to the observed major axes of the lenses). These effects are
caused primarily by the fact that the lens galaxies have, themselves, been
lensed and therefore the observed symmetry axes of the lenses differ from their
intrinsic symmetry axes. The effects of lensing of the foreground galaxies on
the observed function g+/g- cannot be eliminated by the rejection of foreground
galaxies with small image ellipticities, nor by focusing the analysis on
sources that are located very close to the observed symmetry axes of the
foreground galaxies. We conclude that any attempt to use a measurement of g+/g-
to constrain the shapes of dark matter galaxy haloes must include Monte Carlo
simulations that take multiple deflections properly into account.


  Updates on results for the electric, magnetic and axial vector form factors
are presented. The data analyzed cover high statistics measurements on 11
ensembles generated with 2+1+1 flavors of HISQ fermions by the MILC
collaboration. The data cover the range $0.057\;\mathrm{fm} < a <
0.15\;\mathrm{fm}$ in lattice spacing, $135\;\mathrm{MeV} < M_\pi <
320\;\mathrm{MeV}$ in the pion mass and $3.3 < M_\pi L < 5.5 $ in the lattice
size. Fits to control excited-state contamination use up to 3-states in the
spectral decomposition of the 3-point functions. The simultaneous
chiral-continuum-finite-volume fits include leading order corrections in each
of the three variables.


  A sequence of graphs with diverging number of nodes is a dense graph sequence
if the number of edges grows approximately as for complete graphs. To each such
sequence a function, called graphon, can be associated, which contains
information about the asymptotic behavior of the sequence. Here we show that
the problem of subdividing a large graph in communities with a minimal amount
of cuts can be approached in terms of graphons and the $\Gamma$-limit of the
cut functional, and discuss the resulting variational principles on some
examples. Since the limit cut functional is naturally defined on Young
measures, in many instances the partition problem can be expressed in terms of
the probability that a node belongs to one of the communities. Our approach can
be used to obtain insights into the bisection problem for large graphs, which
is known to be NP-complete.


  The mechanical properties of cells, which influence the properties of the
tissue they belong to, are controlled by various mechanisms. Bi et al.
theoretically demonstrated that density-independent rigidity transition occurs
in two-dimensional confluent tissues that consist of mechanically uniform
cells. They also analyzed the dynamical behavior of tissues near the critical
point, which is geometrically controlled by `shape parameter'. To investigate
whether the behavior of three-dimensional tissues is similar to that of
two-dimensional ones, we extend the model proposed by Bi et al. to a
three-dimensional one both dynamically and statically. The model reveals that
the two mechanical states exist with a phase transition and has some
similarities with those of glassy materials. Scaling analysis is applied to the
static model focused in the rearrangement viewpoint. The results suggest that
the upper critical dimension is also the same as the jamming transition.


  Although the disease-relevant microtubule-associated protein tau is known to
severely inhibit kinesin-based transport in vitro, the potential mechanisms for
reversing this detrimental effect to maintain healthy transport in cells remain
unknown. Here we report the unambiguous upregulation of multiple-kinesin travel
distance despite the presence of tau, via decreased single-kinesin velocity.
Interestingly, the presence of tau also modestly reduced cargo velocity in
multiple-kinesin transport, and our stochastic simulations indicate that the
tau-mediated reduction in single-kinesin travel underlies this observation.
Taken together, our observations highlight a nontrivial interplay between
velocity and travel distance for kinesin transport, and suggest that
single-kinesin velocity is a promising experimental handle for tuning the
effect of tau on multiple-kinesin travel distance.


  We discuss the status of the Gribov-Pontecorvo (GP) solution to the solar
neutrino problem. This solution naturally appears in bimaximal neutrino mixing
and reduces the solar and atmospheric neutrino problems to vacuum oscillations
of three active neutrinos. The GP solution predicts an energy-independent
suppression of the solar neutrino flux. It is disfavoured by the rate of the
Homestake detector, but its statistical significance greatly improves, when the
chlorine rate and the boron neutrino flux are slightly rescaled, and when the
Super-Kamiokande neutrino spectrum is included in the analysis. Our results
show that rescaling of the chlorine signal by only 10% is sufficient for the GP
solution to exist, if the boron-neutrino flux is taken 10 -- 20% lower than the
SSM prediction. The regions allowed for the GP solution in the parameter space
are found and observational signatures of this solution are discussed.


  The goal of this study is to establish a general framework for predicting the
so-called critical Turning Period in an infectious disease epidemic such as the
COVID-19 outbreak in China early this year. This framework enabled a timely
prediction of the turning period when applied to Wuhan COVID-19 epidemic and
informed the relevant authority for taking appropriate and timely actions to
control the epidemic. It is expected to provide insightful information on
turning period for the world's current battle against the COVID-19 pandemic.
The underlying mathematical model in our framework is the individual
Susceptible-Exposed- Infective-Removed (iSEIR) model, which is a set of
differential equations extending the classic SEIR model. We used the observed
daily cases of COVID-19 in Wuhan from February 6 to 10, 2020 as the input to
the iSEIR model and were able to generate the trajectory of COVID-19 cases
dynamics for the following days at midnight of February 10 based on the updated
model, from which we predicted that the turning period of CIVID-19 outbreak in
Wuhan would arrive within one week after February 14. This prediction turned to
be timely and accurate, providing adequate time for the government, hospitals,
essential industry sectors and services to meet peak demands and to prepare
aftermath planning. Our study also supports the observed effectiveness on
flatting the epidemic curve by decisively imposing the Lockdown and Isolation
Control Program in Wuhan since January 23, 2020. The Wuhan experience provides
an exemplary lesson for the whole world to learn in combating COVID-19.


  Most work in the area of statistical relational learning (SRL) is focussed on
discrete data, even though a few approaches for hybrid SRL models have been
proposed that combine numerical and discrete variables. In this paper we
distinguish numerical random variables for which a probability distribution is
defined by the model from numerical input variables that are only used for
conditioning the distribution of discrete response variables. We show how
numerical input relations can very easily be used in the Relational Bayesian
Network framework, and that existing inference and learning methods need only
minor adjustments to be applied in this generalized setting. The resulting
framework provides natural relational extensions of classical probabilistic
models for categorical data. We demonstrate the usefulness of RBN models with
numeric input relations by several examples.
  In particular, we use the augmented RBN framework to define probabilistic
models for multi-relational (social) networks in which the probability of a
link between two nodes depends on numeric latent feature vectors associated
with the nodes. A generic learning procedure can be used to obtain a
maximum-likelihood fit of model parameters and latent feature values for a
variety of models that can be expressed in the high-level RBN representation.
Specifically, we propose a model that allows us to interpret learned latent
feature values as community centrality degrees by which we can identify nodes
that are central for one community, that are hubs between communities, or that
are isolated nodes. In a multi-relational setting, the model also provides a
characterization of how different relations are associated with each community.


  We prove in constructive logic that the statement of the Cantor-Bernstein
theorem implies excluded middle. This establishes that the Cantor-Bernstein
theorem can only be proven assuming the full power of classical logic. The key
ingredient is a theorem of Mart\'in Escard\'o stating that quantification over
a particular subset of the Cantor space $2^{\mathbb{N}}$, the so-called
one-point compactification of $\mathbb{N}$, preserves decidable predicates.


  We discuss the origin of the anti-helium-3 and -4 events possibly detected by
AMS-02. Using up-to-date semi-analytical tools, we show that spallation from
primary hydrogen and helium nuclei onto the ISM predicts a $\overline{{}^3{\rm
He}}$ flux typically one to two orders of magnitude below the sensitivity of
AMS-02 after 5 years, and a $\overline{{}^4{\rm He}}$ flux roughly 5 orders of
magnitude below the AMS-02 sensitivity. We argue that dark matter annihilations
face similar difficulties in explaining this event. We then entertain the
possibility that these events originate from anti-matter-dominated regions in
the form of anti-clouds or anti-stars. In the case of anti-clouds, we show how
the isotopic ratio of anti-helium nuclei might suggest that BBN has happened in
an inhomogeneous manner, resulting in anti-regions with a anti-baryon-to-photon
ratio $\bar{\eta}\simeq10^{-3}\eta$. We discuss properties of these regions, as
well as relevant constraints on the presence of anti-clouds in our Galaxy. We
present constraints from the survival of anti-clouds in the Milky-Way and in
the early Universe, as well as from CMB, gamma-ray and cosmic-ray observations.
In particular, these require the anti-clouds to be almost free of normal
matter. We also discuss an alternative where anti-domains are dominated by
surviving anti-stars. We suggest that part of the unindentified sources in the
3FGL catalog can originate from anti-clouds or anti-stars. AMS-02 and GAPS data
could further probe this scenario.


  The Mellin transform is usually applied in probability theory to the product
of independent random variables. In recent times the machinery of the Mellin
transform has been adopted to describe the L\'evy stable distributions, and
more generally the probability distributions governed by generalized diffusion
equations of fractional order in space and/or in time. In these cases the
related stochastic processes are self-similar and are simply referred to as
fractional diffusion processes. We provide some integral formulas involving the
distributions of these processes that can be interpreted in terms of
subordination laws.


  To evidence multimode spatial entanglement of spontaneous down-conversion,
detector arrays allow a full field measurement, without any a priori selection
of the paired photons. We show by comparing results of the recent literature
that electron-multiplying CCD (EMCCD) cameras allow, in the present state of
technology, the detection of quantum correlations with the best signal-to-noise
ratio (SNR), while intensified CCD (ICCD) cameras allow at best to identify
pairs. The SNR appears to be proportional to the square root of the number of
coherence cells in each image, or Schmidt number. Then, corrected estimates are
derived for extended coherence cells and not very low and not space-stationary
photon fluxes. Finally, experimental measurements of the SNR confirm our model.


  Quantum algebras U_q(su_n) used as the algebras of flavour symmetry (usually
described by SU(n)) to study static properties of hadrons lead to intriguing
results. In this contribution we focus on the peculiar properties manifested by
different q-deformed structures (e.g., the braided line, the quantum algebras
U_q(su_2) and U_q(su_n), n >= 3) in the special limit of q = -1. Similarities
(complete or partial) with supersymmetry that emerge in this special limit are
discussed.


  We consider the equilibrium statistical properties of interfaces submitted to
competing interactions; a long-range repulsive Coulomb interaction inherent to
the charged interface and a short-range, anisotropic, attractive one due to
either elasticity or confinement. We focus on one-dimensional interfaces such
as strings. Model systems considered for applications are mainly aggregates of
solitons in polyacetylene and other charge density wave systems, domain lines
in uniaxial ferroelectrics and the stripe phase of oxides. At zero temperature,
we find a shape instability which lead, via phase transitions, to tilted
phases. Depending on the regime, elastic or confinement, the order of the
zero-temperature transition changes. Thermal fluctuations lead to a pure
Coulomb roughening of the string, in addition to the usual one, and to the
presence of angular kinks. We suggest that such instabilities might explain the
tilting of stripes in cuprate oxides. The 3D problem of the charged wall is
also analyzed. The latter experiences instabilities towards various tilted
phases separated by a tricritical point in the elastic regime. In the
confinement regime, the increase of dimensionality favors either the melting of
the wall into a Wigner crystal of its constituent charges or a strongly
inclined wall which might have been observed in nickelate oxides.


  Recent experimental developments in the loading of ultracold KRb molecules
into quasi-two-dimensional traps, combined with the ability to tune the ratio
between elastic and loss (inelastic/reactive) collisions through application of
an external electric field, are opening the door to achieving efficient
evaporative cooling of reactive polar molecules. In this paper, we use Monte
Carlo simulations and semianalytic models to study theoretically the
experimental parameter regimes in which evaporative cooling is feasible under
current trapping conditions. We investigate the effect of the anisotropic
character of dipole-dipole collisions and reduced dimensionality on evaporative
cooling. We also present an analysis of the experimentally relevant
anti-evaporation effects that are induced by chemical reactions that take place
when more than one axial vibrational state is populated.


  Excitons, or bound electron-hole pairs, play a crucial role in the optical
response of monolayer, 2H-phase transition-metal dichalcogenides (TMDs). They
hold significant promise for the development of novel quantum opto-electronic
devices due to their large binding energies and strong spin-orbit coupling.
Among the monolayer TMDs, MoTe2 stands out because of its bandgap in the
near-infrared (NIR) regime. Here, we report the experimental observation of NIR
Rydberg excitons and conduction band-split charged excitons, in high-quality,
boron nitride (BN)-encapsulated monolayer MoTe2 devices, probed by
photoluminescence and electroluminescence spectroscopy. By employing a graphite
bottom gate, we successfully modulate the emission intensity of various
excitonic species. Additionally, our device fabrication process within an
argon-filled glove box ensures clean TMD/metal electrode interfaces, enabling
the construction of p-n junctions near the electrodes. Our work significantly
advances our understanding of excitons in monolayer TMDs and contributes to the
application of MoTe2 in NIR quantum opto-electronic devices.


  This article concerns the antisymmetry, uniqueness, and monotonicity
properties of solutions to some elliptic functionals involving weights and a
double well potential. In the one-dimensional case, we introduce the continuous
odd rearrangement of an increasing function and we show that it decreases the
energy functional when the weights satisfy a certain convexity-type hypothesis.
This leads to the antisymmetry or oddness of increasing solutions (and not only
of minimizers). We also prove a uniqueness result (which leads to antisymmetry)
where a convexity-type condition by Berestycki and Nirenberg on the weights is
improved to a monotonicity condition. In addition, we provide with a large
class of problems where antisymmetry does not hold. Finally, some rather
partial extensions in higher dimensions are also given.


  We study numerically the dispersion and dissipation properties of the plane
wave virtual element method and the nonconforming Trefftz virtual element
method for the Helmholtz problem. Whereas the former method is based on a
conforming virtual partition of unity approach in the sense that the local
(implicitly defined) basis functions are given as modulations of lowest order
harmonic virtual element functions with plane waves, the latter one represents
a pure Trefftz method with local edge-related basis functions that are
eventually glued together in a nonconforming fashion. We will see that the
qualitative and quantitative behavior of dissipation and dispersion of the
method hinges upon the level of conformity and the use of Trefftz basis
functions. To this purpose, we also compare the results to those obtained in
[15] for the plane wave discontinuous Galerkin method, and to those for the
standard polynomial based finite element method.


  A direct numerical algorithm for solving the time-nonlocal non-Markovian
master equation in the second Born approximation is introduced and the range of
utility of this approximation, and of the Markov approximation, is analyzed for
the traditional dimer system that models excitation energy transfer in
photosynthesis. Specifically, the coupled integro-differential equations for
the reduced density matrix are solved by an efficient auxiliary function method
in both the energy and site representations. In addition to giving exact
results to this order, the approach allows us to computationally assess the
range of the reorganization energy and decay rates of the phonon
auto-correlation function for which the Markovian Redfield theory and the
second order approximation is valid. For example, the use of Redfield theory
for $\lambda> 10 \textrm{cm}^{-1}$ in systems like Fenna-Mathews-Olson (FMO)
type systems is shown to be in error. In addition, analytic inequalities are
obtained for the regime of validity of the Markov approximation in cases of
weak and strong resonance coupling, allowing for a quick determination of the
utility of the Markovian dynamics in parameter regions. Finally, results for
the evolution of states in a dimer system, with and without initial coherence,
are compared in order to assess the role of initial coherences.


  The cross sections for the binary fission of 197Au, 181Ta and 209Bi targets
induced by 11B ions were measured at intermediate energies. The fission
products cross sections were studied by means of activation analysis in
off-line regime observed gamma-ray spectra. The fission cross section is
reconstructed on the basis of charge and mass distribution of the fission
products.


  In many consumer virtual reality (VR) applications, users embody predefined
characters that offer minimal customization options, frequently emphasizing
storytelling over user choice. We explore whether matching a user's physical
characteristics, specifically ethnicity and gender, with their virtual
self-avatar affects their sense of embodiment in VR. We conducted a 2 x 2
within-subjects experiment (n=32) with a diverse user population to explore the
impact of matching or not matching a user's self-avatar to their ethnicity and
gender on their sense of embodiment. Our results indicate that matching the
ethnicity of the user and their self-avatar significantly enhances sense of
embodiment regardless of gender, extending across various aspects, including
appearance, response, and ownership. We also found that matching gender
significantly enhanced ownership, suggesting that this aspect is influenced by
matching both ethnicity and gender. Interestingly, we found that matching
ethnicity specifically affects self-location while matching gender specifically
affects one's body ownership.


  This paper defines fractional Heston-type (fHt) model as an arbitrage-free
financial market model with the infinitesimal return volatility described by
the square of a single stochastic equation with respect to fractional Brownian
motion with Hurst parameter H in (0, 1). We extend the idea of Alos and [Alos,
E., & Ewald, C. O. (2008). Malliavin differentiability of the Heston volatility
and applications to option pricing. Advances in Applied Probability, 40(1),
144-162.] to prove that fHt model is Malliavin differentiable and deduce an
expression of expected payoff function having discontinuity of any kind. Some
simulations of stock price process and option prices are performed.


  We present a novel concept for pulse compression scheme applicable at RF,
microwave and possibly to optical frequencies based on structured energy
distribution in cavities supporting degenerate band-edge (DBE) modes. For such
modes a significant fraction of energy resides in a small fraction of the
cavity length. Such energy concentration provides a basis for superior
performance for applications in microwave pulse compression devices (MPC) when
compared to conventional cavities. The novel design features: larger loaded
quality factor of the cavity and stored energy compared to conventional
designs, robustness to variations of cavity loading, energy feeding and
extraction at the cavity center, substantial reduction of the cavity size by
use of equivalent lumped circuits for low energy sections of the cavity,
controlled pulse shaping via engineered extraction techniques. The presented
concepts are general, in terms of equivalent transmission lines, and can be
applied to a variety of realistic guiding structures.


  We consider uniformly random set partitions of size $n$ with exactly $k$
blocks, and uniformly random permutations of size $n$ with exactly $k$ cycles,
under the regime where $n-k \sim t\sqrt{n}$, $t>0$. In this regime, there is a
simple approximation for the entire process of component counts; in particular,
the number of components of size 3 converges in distribution to Poisson with
mean $\frac{2}{3}t^2$ for set partitions and mean $\frac{4}{3}t^2$ for
permutations, and with high probability all other components have size one or
two. These approximations are proved, with preasymptotic error bounds, using
combinatorial bijections for placements of $r$ rooks on a triangular half of an
$n\times n$ chess board, together with the Chen--Stein method for processes of
indicator random variables.


  NASA's Kepler Mission has revealed two transiting planets orbiting Kepler-68.
Follow-up Doppler measurements have established the mass of the innermost
planet and revealed a third jovian-mass planet orbiting beyond the two
transiting planets. Kepler-68b, in a 5.4 day orbit has mass 8.3 +/- 2.3 Earth,
radius 2.31 +/- 0.07 Earth radii, and a density of 3.32 +/- 0.92 (cgs), giving
Kepler-68b a density intermediate between that of the ice giants and Earth.
Kepler-68c is Earth-sized with a radius of 0.953 Earth and transits on a 9.6
day orbit; validation of Kepler-68c posed unique challenges. Kepler-68d has an
orbital period of 580 +/- 15 days and minimum mass of Msin(i) = 0.947 Jupiter.
Power spectra of the Kepler photometry at 1-minute cadence exhibit a rich and
strong set of asteroseismic pulsation modes enabling detailed analysis of the
stellar interior. Spectroscopy of the star coupled with asteroseismic modeling
of the multiple pulsation modes yield precise measurements of stellar
properties, notably Teff = 5793 +/- 74 K, M = 1.079 +/- 0.051 Msun, R = 1.243
+/- 0.019 Rsun, and density 0.7903 +/- 0.0054 (cgs), all measured with
fractional uncertainties of only a few percent. Models of Kepler-68b suggest it
is likely composed of rock and water, or has a H and He envelope to yield its
density of about 3 (cgs).


  In this paper, we intend to address the high-order gas-kinetic scheme (HGKS)
in the direct numerical simulation (DNS) of compressible isotropic turbulence
up to the supersonic regime. With the consideration of robustness and accuracy,
the WENO-Z scheme is adopted for spatial reconstruction in the current
higher-order scheme. Statistical quantities are compared with the high-order
compact finite difference scheme to determine the spatial and temporal
criterion for DNS. According to the grid and time convergence study, it can be
concluded that the minimum spatial resolution parameter $\kappa_{max} \eta_0
\ge 2.71$ and the maximum temporal resolution parameter $\Delta
t_{ini}/\tau_{t_0} \leq 5.58/1000$ are adequate for HGKS to resolve the
compressible isotropic turbulence, where $\kappa_{max}$ is the maximum resolved
wave number, $\Delta t_{ini}$ is the initial time step, $\eta_0$ and
$\tau_{t_0}$ are the initial Kolmogorov length scale and the
large-eddy-turnover time. Guided by such criterion, the compressible isotropic
turbulence from subsonic regime $Ma_t=0.8$ to supersonic one $Ma_t=1.2$, and
the Taylor microscale Reynolds number $Re_{\lambda}$ ranging from $10$ to $72$
are simulated. With the high initial turbulent Mach number, the strong random
shocklets and high expansion regions are identified, as well as the wide range
of probability density function over local turbulence Mach number. All those
impose great challenge for high-order schemes. In order to construct
compressible large eddy simulation models at high turbulent Mach number, the
ensemble budget of turbulent kinetic energy is fully analyzed. The solenoidal
dissipation rate decreases with the increasing of $Ma_t$ and $Re_{\lambda}$.
Meanwhile, the dilational dissipation rate increases with the increasing of
$Ma_t$, which cannot be neglected for constructing supersonic turbulence model.


  People involved in mass emergencies increasingly publish information-rich
contents in online social networks (OSNs), thus acting as a distributed and
resilient network of human sensors. In this work, we present HERMES, a system
designed to enrich the information spontaneously disclosed by OSN users in the
aftermath of disasters. HERMES leverages a mixed data collection strategy,
called hybrid crowdsensing, and state-of-the-art AI techniques. Evaluated in
real-world emergencies, HERMES proved to increase: (i) the amount of the
available damage information; (ii) the density (up to 7x) and the variety (up
to 18x) of the retrieved geographic information; (iii) the geographic coverage
(up to 30%) and granularity.


  In this paper we apply the KKT conditions to find the minimal sum of powered
distances from the sides of an arbitrary triangle.


  The angular momentum of the physical electron, modelled as a Dirac fermion
coupled to the electromagnetic field, is found to be hbar/2, the same as that
of a bare Dirac fermion and independent of the size of the electric charge.


  We compare Steane's and Shor's syndrome extraction methods on the Bacon-Shor
code. We propose a straightforward strategy based on post-selection to prepare
the logical $|0\rangle_L$ and $|+\rangle_L$ states of the Bacon-Shor code by
using flag-like qubits to verify their constituent Greenberger-Horne-Zeilinger
states. We perform stabilizer simulations with a depolarizing Pauli error model
and find that Steane's method significantly outperforms Shor's. Not only does
Steane's method result in pseudo-thresholds that are about 1 order of magnitude
higher than Shor's, but also its advantage increases monotonically as we go
from a distance-3 to a distance-9 Bacon-Shor code. The advantage of Steane's
method is the greatest in the regime where gate errors dominate over
measurement errors. Some of the circuit constructions we propose for Steane's
method are not formally fault-tolerant, yet outperform the formally
fault-tolerant Shor's protocols for experimentally relevant physical error
rates. This suggest that constructing formally fault-tolerant circuits that
maintain the full code distance is not strictly necessary to guarantee the
usefulness of a quantum error-correcting protocol. Despite relying on
post-selection, we find that our methods can be efficient. These protocols
would be naturally implementable on a platform with long-range qubit
interactions like trapped ions or neutral atoms.


  The paper describes methods used for the detection of cosmic rays with
energies above 10^18 eV (UHECR, UltraHigh Energy Cosmic Rays). It had been
anticipated there would be a cutoff in the energy spectrum of primary cosmic
rays around 3 10^19 eV induced by their interaction with the 2.7 K primordial
photons. This has become known as the GZK cutoff. However, several showers have
been detected with estimated primary energy exceeding this limit.


  Dark radiation (DR) is generally predicted in new physics scenarios that
address fundamental puzzles of the Standard Model or tensions in the
cosmological data. Cosmological data has the sensitivity to constrain not only
the energy density of DR, but also whether it is interacting. In this paper, we
present a systematic study of five types of interacting DR (free-streaming,
fluid, decoupling, instantaneous decoupling, and recoupling DR) and their
impact on cosmological observables. We modify the Boltzmann hierarchy to
describe all these types of interacting DR under the relaxation time
approximation. We, for the first time, robustly calculate the collision terms
for recoupling scalar DR and provide a better estimation of the recoupling
transition redshift. We demonstrate the distinct features of each type of DR on
the CMB and matter power spectra. We perform MCMC scans using the Planck 2018
data and BAO data. Assuming no new physics in the SM neutrino sector, we find
no statistically significant constraints on the couplings of DR, although there
is a slight preference for the fluid-like limit of all the cases. In the case
of instantaneous decoupling DR, this limit corresponds to a late transition
redshift around recombination. The $\Delta N_{\rm eff}$ constraint varies
marginally depending on the type of DR.


  We present the kinematical properties, distribution of spectroscopic
subtypes, stellar population subcomponents of the white dwarfs within 20 pc of
the sun. We find no convincing evidence of halo white dwarfs in the total 20 pc
sample of 129 white dwarfs nor is there convincing evidence of genuine thick
disk subcomponent members within 20 parsecs. Virtually the entire 20 pc sample
likely belongs to the thin disk. The total DA to non-DA ratio of the 20 pc
sample is 1.6, a manifestation of deepening envelope convection which
transforms DA stars with sufficiently thin H surface layers into non-DAs. The
addition of 5 new stars to the 20 pc sample yields a revised local space
density of white dwarfs of $4.9\pm0.5 \times 10^{-3}$ M$_{\sun}$/yr and a
corresponding mass density of $3.3\pm0.3 \times 10^{-3}$ M$_{\sun}$/pc$^{3}$.
We find that at least 15% of the white dwarfs within 20 parsecs of the sun (the
DAZ and DZ stars) have photospheric metals that possibly originate from
accretion of circumstellar material (debris disks) around them. If this
interpretation is correct, this suggests the possibility that the same
percentage have planets or asteroid-like bodies orbiting them.


  A self-dual and anti-self-dual decomposition of the teleparallel gravity is
carried out and the self-dual Lagrangian of the teleparallel gravity which is
equivalent to the Ashtekar Lagrangian in vacuum is obtained. Its Hamiltonian
formulation and the constraint analysis are developed. Starting from Witten's
equation Nester's gauge condition is derived directly and a new expression of
the boundary term is obtained. Using this expression and Witten's identity the
proof of the positive energy theorem by Nester et al is extended to a case
including momentum.


  The origin of the most energetic cosmic ray events, with $E \gsim 10^{20}$
eV, remains mysterious. One possibility is that they are produced in the decay
of very massive, long--lived particles. It has been suggested that these
so--called ``top--down scenarios'' can be tested by searching for
ultrarelativistic neutralinos, which would be produced copiously if
superparticles exist at or near the TeV scale. In this paper we present a
detailed analysis of the interactions of such neutralinos with ordinary matter.
To this end we compute several new contributions to the total interaction cross
section; in particular, the case of higgsino--like neutralinos is treated for
the first time. We also carefully solve the transport equations. We show that a
semi--analytical solution that has been used in the literature to treat the
somewhat analogous propagation of $\tau$ neutrinos leads to large errors; we
therefore use a straightforward numerical method to solve these
integro--differential equations.


  We consider higher dimensional operators due to quantum gravity or
spontaneous compactification of extra dimensions in Kaluza-Klein type theory
and their effect in the $SO(10)$ Lagrangian. These operators change the
boundary conditions at the unification scale. As a result one can allow
left-right symmetry to survive till very low energy (as low as $\sim$ TeV) for
a wide range of values for the coupling of these higher dimensional operators
and still make the theory compatible with the latest values of $\sin^2
\theta_W$ and $\alpha_s$ derived from LEP. We consider both non-supersymmetric
and supersymmetric cases with standard higgses. Proton lifetime is very large
in these theories.


  We elucidate a mechanism for obtaining polar behavior in magnetic perovskites
based on A-site disorder and demonstrate this mechanism by density functional
calculations for the double perovskite (La,Lu)MnNiO$_6$ with Lu concentrations
at and below 50%. We show that this material combines polar behavior and
ferromagnetism. The mechanism is quite general and may be applicable to a wide
range of magnetic perovskites.


  We report on high-resolution dc-magnetization (M) measurements on a
high-quality single crystal of YbCo2Si2. M was measured down to 0.05K and in
fields up to 4T, with the magnetic field oriented along the crystallographic
directions [100], [110] and [001] of the tetragonal structure.


  Two colour photometry of the cluster A1689 reveals a `relative
magnification-bias' between lensed blue and red background galaxies, arising
from a dependence of the faint galaxy count-slope on colour. The colour
distribution is skewed blueward of the far field, allowing us to measure the
cluster magnification and to understand the notorious blueness of large arcs.
We show that the magnification information can be combined with the usual image
distortion measurements to isolate the local `convergence' component of lensing
and hence derive the projected mass. This is achieved through a simple local
relation between the convergence and the observables, which can be applied
generally over the surface a cluster. In the weak lensing limit, the
convergence reduces to a dependence on the magnification alone, so that in the
outskirts of clusters the surface-density of matter is obtained directly from
the surface-density of background galaxies. Hence, useful lensing work requires
colour information but not necessarily good seeing. Interestingly, convergence
varies slowly at high redshift, saturating at a level depending on the Horizon
distance, allowing a useful model-independent measurement of the Global
Geometry.


  Sparse Network Coding (SNC) has been a promising network coding scheme as an
improvement for Random Linear Network Coding (RLNC) in terms of the
computational complexity. However, in this literature, there has been no
analytical expressions for the probability of decoding a fraction of source
messages after transmission of some coded packets. In this work, we looked into
the problem of the probability of decoding a fraction of source messages, i.e.,
partial decoding, in the decoder for a system which uses SNC. We exploited the
Principle of Inclusion and Exclusion to derive expressions of partial decoding
probability. The presented model predicts the probability of partial decoding
with an average deviation of 6%. Our results show that SNC has a great
potential for recovering a fraction of the source message, especially in higher
sparsity and lower Galois Field size. Moreover, to achieve a better probability
of partial decoding throughout transmissions, we define a sparsity tuning
scheme that significantly increases the probability of partial decoding. Our
results show that this tuning scheme achieves a 16% improvement in terms of
probability of decoding a fraction of source packets with respect to
traditional SNC.


  Observations of surface magnetic fields of cool stars reveal a large
diversity of configurations. Although there is now a consensus that these
fields are generated through dynamo processes occurring within the convective
zone, the physical mechanism driving such a variety of field topologies is
still debated. This paper discusses the possible origins of dipole and
multipole-dominated morphologies using three-dimensional numerical simulations
of stratified systems where the magnetic feedback on the fluid motion is
significant. Our main result is that dipolar solutions are found at Rossby
numbers up to 0.4 in strongly stratified simulations, where previous works
suggested that only multipolar fields should exist. We argue that these
simulations are reminiscent of the outlier stars observed at Rossby numbers
larger than 0.1, whose large-scale magnetic field is dominated by their
axisymmetric poloidal component. As suggested in previous Boussinesq
calculations, the relative importance of inertial over Lorentz forces is again
controlling the dipolar to multipolar transition. Alternatively, we find that
the ratio of kinetic to magnetic energies can equally well capture the
transition in the field morphology. We test the ability of this new proxy to
predict the magnetic morphology of a few M-dwarf stars whose internal structure
matches that of our simulations and for which homogeneous magnetic field
characterization is available. Finally, the magnitude of the differential
rotation obtained in our simulations is compared to actual measurements
reported in the literature for M-dwarfs. In our simulations, we find a clear
relationship between anti-solar differential rotation and the emergence of
dipolar fields.


  It has been shown that word embeddings derived from large corpora tend to
incorporate biases present in their training data. Various methods for
mitigating these biases have been proposed, but recent work has demonstrated
that these methods hide but fail to truly remove the biases, which can still be
observed in word nearest-neighbor statistics. In this work we propose a
probabilistic view of word embedding bias. We leverage this framework to
present a novel method for mitigating bias which relies on probabilistic
observations to yield a more robust bias mitigation algorithm. We demonstrate
that this method effectively reduces bias according to three separate measures
of bias while maintaining embedding quality across various popular benchmark
semantic tasks


  An extension of Quantum Group is described. We propose to unite the quantum
groups with parameter q and with parameter modularly dual to q.


  Federated learning refers to the task of machine learning based on
decentralized data from multiple clients with secured data privacy. Recent
studies show that quantum algorithms can be exploited to boost its performance.
However, when the clients' data are not independent and identically distributed
(IID), the performance of conventional federated algorithms is known to
deteriorate. In this work, we explore the non-IID issue in quantum federated
learning with both theoretical and numerical analysis. We further prove that a
global quantum channel can be exactly decomposed into local channels trained by
each client with the help of local density estimators. This observation leads
to a general framework for quantum federated learning on non-IID data with
one-shot communication complexity. Numerical simulations show that the proposed
algorithm outperforms the conventional ones significantly under non-IID
settings.


  Maintenance optimization has been extensively studied in the past decades.
However, most of the existing maintenance models focus on single-component
systems and are not applicable for complex systems consisting of multiple
components, due to various interactions between the components. Multi-component
maintenance optimization problem, which joins the stochastic processes
regarding the failures of the components with the combinatorial problems
regarding the grouping of maintenance activities, is challenging in both
modeling and solution techniques, and has remained as an open issue in the
literature. In this paper, we study the multi-component maintenance problem
over a finite planning horizon and formulate the problem as a multi-stage
stochastic integer program with decision-dependent uncertainty. There is a lack
of general efficient methods to solve this type of problem. To address this
challenge, we use an alternative approach to model the underlying failure
process and develop a novel two-stage model without decision-dependent
uncertainty. Structural properties of the two-stage problem are investigated,
and a progressive-hedging-based heuristic is developed based on the structural
properties. Our heuristic algorithm demonstrates a significantly improved
capacity in handling practically large-size two-stage problems comparing to
three conventional methods for stochastic integer programming, and solving the
two-stage model by our heuristic in a rolling horizon provides a good
approximation of the multi-stage problem. The heuristic is further benchmarked
with a dynamic programming approach commonly adopted in the literature.
Numerical results show that our heuristic can lead to significant cost savings
compared with the benchmark approach.


  Light field imaging involves capturing both angular and spatial distribution
of light; it enables new capabilities, such as post-capture digital refocusing,
camera aperture adjustment, perspective shift, and depth estimation. Micro-lens
array (MLA) based light field cameras provide a cost-effective approach to
light field imaging. There are two main limitations of MLA-based light field
cameras: low spatial resolution and narrow baseline. While low spatial
resolution limits the general purpose use and applicability of light field
cameras, narrow baseline limits the depth estimation range and accuracy. In
this paper, we present a hybrid stereo imaging system that includes a light
field camera and a regular camera. The hybrid system addresses both spatial
resolution and narrow baseline issues of the MLA-based light field cameras
while preserving light field imaging capabilities.


  A common property of many large networks, including the Internet, is that the
connectivity of the various nodes follows a scale-free power-law distribution,
P(k)=ck^-a. We study the stability of such networks with respect to crashes,
such as random removal of sites. Our approach, based on percolation theory,
leads to a general condition for the critical fraction of nodes, p_c, that need
to be removed before the network disintegrates. We show that for a<=3 the
transition never takes place, unless the network is finite. In the special case
of the Internet (a=2.5), we find that it is impressively robust, where p_c is
approximately 0.99.


  A stable approach for integrating the impedance matrix in cylindrical, radial
inhomogeneous structures is developed and studied. A Stroh-like system using
the time-harmonic displacement-traction state vector is used to derive the
Riccati matrix differential equation involving the impedance matrix. It is
found that the resulting equation is stiff and leads to exponential
instabilities. A stable scheme for integration is found in which a local
expansion is performed by combining the matricant and impedance matrices. This
method offers a stable solution for fully anisotropic materials, which was
previously unavailable in the literature. Several approximation schemes for
integrating the Riccati equation in cylindrical coordinates are considered:
exponential, Magnus, Taylor series, Lagrange polynomials, with numerical
examples indicating that the exponential scheme performs best. The impedance
matrix is compared with solutions involving Buchwald potentials in which the
material is limited to piecewise constant transverse isotropy. Lastly a
scattering example is considered and compared with the literature.


  Geo-tagged photo based tourist attraction recommendation can discover users'
travel preferences from their taken photos, so as to recommend suitable tourist
attractions to them. However, existing visual content based methods cannot
fully exploit the user and tourist attraction information of photos to extract
visual features, and do not differentiate the significances of different
photos. In this paper, we propose multi-level visual similarity based
personalized tourist attraction recommendation using geo-tagged photos (MEAL).
MEAL utilizes the visual contents of photos and interaction behavior data to
obtain the final embeddings of users and tourist attractions, which are then
used to predict the visit probabilities. Specifically, by crossing the user and
tourist attraction information of photos, we define four visual similarity
levels and introduce a corresponding quintuplet loss to embed the visual
contents of photos. In addition, to capture the significances of different
photos, we exploit the self-attention mechanism to obtain the visual
representations of users and tourist attractions. We conducted experiments on a
dataset crawled from Flickr, and the experimental results proved the advantage
of this method.


  We present a 1.1 mm wavelength imaging survey covering 0.3 sq. deg. in the
COSMOS field. These data, obtained with the AzTEC continuum camera on the James
Clerk Maxwell Telescope (JCMT), were centred on a prominent large-scale
structure over-density which includes a rich X-ray cluster at z = 0.73. A total
of 50 millimetre galaxy candidates, with a significance ranging from 3.5-8.5
sigma, are extracted from the central 0.15 sq. deg. area which has a uniform
sensitivity of 1.3 mJy/beam. Sixteen sources are detected with S/N > 4.5, where
the expected false-detection rate is zero, of which a surprisingly large number
(9) have intrinsic (de-boosted) fluxes > 5 mJy at 1.1 mm. Assuming the emission
is dominated by radiation from dust, heated by a massive population of young,
optically-obscured stars, then these bright AzTEC sources have FIR luminosities
> 6 x 10^12 L(sun) and star formation-rates > 1100 M(sun)/yr. Two of these nine
bright AzTEC sources are found towards the extreme peripheral region of the
X-ray cluster, whilst the remainder are distributed across the larger-scale
over-density. We describe the AzTEC data reduction pipeline, the
source-extraction algorithm, and the characterisation of the source catalogue,
including the completeness, flux de-boosting correction, false-detection rate
and the source positional uncertainty, through an extensive set of Monte-Carlo
simulations. We conclude with a preliminary comparison, via a stacked analysis,
of the overlapping MIPS 24 micron data and radio data with this AzTEC map of
the COSMOS field.


  We present the performance of a 33 g Li2MoO4 crystal working as a
scintillating bolometer. The crystal was tested for more than 400 h in a
dilution refrigerator installed in the underground laboratory of Laboratori
Nazionali del Gran Sasso (Italy). This compound shows promising features in the
frame of neutron detection, dark matter search (solar axions) and neutrinoless
double-beta decay physics. Low temperature scintillating properties were
investigated by means of different alpha, beta/gamma and neutron sources, and
for the first time the Light Yield for different types of interacting particle
is estimated. The detector shows great ability of tagging fast neutron
interactions and high intrinsic radiopurity levels (< 90 \muBq/kg for 238-U and
< 110 \muBq/kg for 232-Th).


  To tackle the issues of catastrophic forgetting and overfitting in few-shot
class-incremental learning (FSCIL), previous work has primarily concentrated on
preserving the memory of old knowledge during the incremental phase. The role
of pre-trained model in shaping the effectiveness of incremental learning is
frequently underestimated in these studies. Therefore, to enhance the
generalization ability of the pre-trained model, we propose Learning with Prior
Knowledge (LwPK) by introducing nearly free prior knowledge from a few
unlabeled data of subsequent incremental classes. We cluster unlabeled
incremental class samples to produce pseudo-labels, then jointly train these
with labeled base class samples, effectively allocating embedding space for
both old and new class data. Experimental results indicate that LwPK
effectively enhances the model resilience against catastrophic forgetting, with
theoretical analysis based on empirical risk minimization and class distance
measurement corroborating its operational principles. The source code of LwPK
is publicly available at: \url{https://github.com/StevenJ308/LwPK}.


  We now know that a large number of stars are born in multiple systems.
Additionally, more than 70% of massive stars are found in close binary systems,
meaning that they will interact over the course of their lifetime. This has
strong implications for their evolution as well as the transients (e.g
supernovae) and the potential gravitational wave progenitors they produce.
Therefore, in order to understand and correctly interpret astronomical
observations of stellar populations, we must use theoretical models able to
account for the effects of binary stars. This is the case of the Binary
Population and Spectral Synthesis code (BPASS), which has been a staple of the
field for over 10 years. As is the case for most other theoretical models, the
data products of BPASS are large, varied and complex. As a result, their use
requires a level of expertise that is not immediately accessible to a wider
community that may hold key observational data. The goal of hoki is to bridge
the gap between observation and theory, by providing a set of tools to make
BPASS data easily accessible and facilitate analysis. The use of Python is
deliberate as it is a ubiquitous language within Astronomy. This allows BPASS
results to be used naturally within the pre-existing workflow of most
astronomers.


  The performance of multiprocessor synchronization and locking protocols is a
key factor to utilize the computation power of multiprocessor systems under
real-time constraints. While multiple protocols have been developed in the past
decades, their performance highly depends on the task partition and
prioritization. The recently proposed Dependency Graph Approach showed its
advantages and attracted a lot of interest. It is, however, restricted to task
sets where each task has at most one critical section. In this paper, we remove
this restriction and demonstrate how to utilize algorithms for the classical
job shop scheduling problem to construct a dependency graph for tasks with
multiple critical sections. To show the applicability, we discuss the
implementation in Litmus^{RT} and report the overheads. Moreover, we provide
extensive numerical evaluations under different configurations, which in many
situations show significant improvement compared to the state-of-the-art.


  We discuss the rigidity problem for Mori fibrations on del Pezzo surfaces of
degree 1, 2 and 3 over ${\mathbb P}^1$ and formulate the following conjecture:
such a del Pezzo fibration $V/{\mathbb P}^1$ is birationally rigid if and only
if its quasi-effective and adjunction thresholds coincide. We prove the "only
if" part of this conjecture.


  We investigate the photoproduction of K*0Sigma+ and K*+Sigma0 off the proton
target, employing the effective Lagrangian approach at the tree-level Born
approximation. In addition to the (s, t, u)-channel Born diagrams, we take into
account various baryon-resonance contributions such as F15(2000), D13(2080),
G17(2190), D15(2200), F35(2000), G37(2200), F37(2390), and Sigma*(1385, 3/2+)
in a fully covariant manner. We present the numerical results for the energy
and angular dependences for the cross sections in comparison to available
experimental data. The single-polarization observables, i.e. the photon-beam,
recoil and target baryon polarization asymmetries are computed as well for
future experiments. We observe from the numerical results that the resonance
contributions play a minor role in producing the strength of the cross
sections, being different from the K*Lambda photoproduction. In contrast, it
turns out that the Delta(1232)-pole contribution and strange-meson exchanges in
the t-channel dominate the scattering process. On the other hand, the higher
resonances influence the polarization observables such as the recoil and target
asymmetries.