  We investigate the role of the pairing field dynamics in low-energy heavy ion
reactions within the nuclear time-dependent density functional theory extended
to superfluid systems. Recently, we have reported on unexpectedly large effects
associated with the relative phase of the pairing field of colliding nuclei on
the reaction outcomes, such as the total kinetic energy and the fusion cross
section [P. Magierski, K. Sekizawa, and G. Wlaz{\l}owski, arXiv:1611.10261
[nucl-th]]. We have elucidated that the effects are due to creation of a
"domain wall" or a "solitonic structure" of the pairing field in the neck
region, which hinders energy dissipation as well as the neck formation, leading
to significant changes of the reaction dynamics. The situation nicely mimics
the one extensively studied experimentally with ultracold atomic gases, where
two clouds of superfluid atoms possessing different phases of the pairing field
are forced to merge, creating various topological excitations, quantum vortices
and solitons, as well as Josephson currents. In this paper, we present
unpublished results for a lighter system, namely, $^{44}$Ca+$^{44}$Ca. It is
shown that the pairing effects on the fusion hindrance are rather small in
lighter systems, due to a strong tendency towards fusion, which is consistent
with an earlier study.


  Let G be a finite abelian group. A number field K is called a Hilbert-Speiser
field of type G if for every tame G-Galois extension L/K has a normal integral
basis, i.e., the ring of integers O_L is free as an O_K[G]-module. Let C_p
denote the cyclic group of prime order p. We show that if p >= 7 (or p=5 and
extra conditions are met) and K is totally real with K/Q ramified at p, then K
is not Hilbert-Speiser of type C_p.


  Knowledge graph (KG) alignment and completion are usually treated as two
independent tasks. While recent work has leveraged entity and relation
alignments from multiple KGs, such as alignments between multilingual KGs with
common entities and relations, a deeper understanding of the ways in which
multilingual KG completion (MKGC) can aid the creation of multilingual KG
alignments (MKGA) is still limited. Motivated by the observation that
structural inconsistencies -- the main challenge for MKGA models -- can be
mitigated through KG completion methods, we propose a novel model for jointly
completing and aligning knowledge graphs. The proposed model combines two
components that jointly accomplish KG completion and alignment. These two
components employ relation-aware graph neural networks that we propose to
encode multi-hop neighborhood structures into entity and relation
representations. Moreover, we also propose (i) a structural inconsistency
reduction mechanism to incorporate information from the completion into the
alignment component, and (ii) an alignment seed enlargement and triple
transferring mechanism to enlarge alignment seeds and transfer triples during
KGs alignment. Extensive experiments on a public multilingual benchmark show
that our proposed model outperforms existing competitive baselines, obtaining
new state-of-the-art results on both MKGC and MKGA tasks. We publicly release
the implementation of our model at https://github.com/vinhsuhi/JMAC


  In this paper, we introduce a novel approach to study reaction-diffusion
systems -- dynamic transition theory approach developed in Ma and Wang 2015.
This approach generalizes Turing's classical result (linear stability analysis)
on pattern formation and cast some new insights into Turing's systems.
Specifically, we studied the Turing's instability and dynamic transition
phenomenon for a Turing's system, and expressions of the critical parameters
$L(D_{u},D_{v})$, and $D_{v}^{*}$ are derived. These two simple parameters are
sufficient to provide us with enough information on the Turing's instability
result as well as the dynamic transition behavior of the system. As an
application, based on the method we establish in this paper, we found that the
Schnakenberg system has two different transition types: single real eigenvalue
transition and double real eigenvalues transition. These transition types are
interpreted using phase diagrams.


  Since first introduced by John von Neumann, the notion of cellular automaton
has grown into a key concept in computer science, physics and theoretical
biology. In its classical setting, a cellular automaton is a transformation of
the set of all configurations of a regular grid such that the image of any
particular cell of the grid is determined by a fixed local function that only
depends on a fixed finite neighbourhood. In recent years, with the introduction
of a generalised definition in terms of transformations of the form $\tau : A^G
\to A^G$ (where $G$ is any group and $A$ is any set), the theory of cellular
automata has been greatly enriched by its connections with group theory and
topology. In this paper, we begin the finite semigroup theoretic study of
cellular automata by investigating the rank (i.e. the cardinality of a smallest
generating set) of the semigroup $\text{CA}(\mathbb{Z}_n; A)$ consisting of all
cellular automata over the cyclic group $\mathbb{Z}_n$ and a finite set $A$. In
particular, we determine this rank when $n$ is equal to $p$, $2^k$ or $2^kp$,
for any odd prime $p$ and $k \geq 1$, and we give upper and lower bounds for
the general case.


  If C is a closed symmetric monoidal category, the Chu category Chu(C, g) over
C and an object g of it was defined by Chu, as a *-autonomous category
generated from C. Bishop introduced the category of complemented subsets of a
set, in order to overcome the problems generated by the use of negation in
constructive measure theory. Shulman mentions that Bishop's complemented
subsets correspond roughly to the Chu construction. In this paper we explain
this correspondence by showing that there is a Chu representation (a full
embedding) of the category of complemented subsets of a set X into Chu(Set, X x
X). A Chu representation of the category of Bishop spaces into Chu(Set, R) is
shown, as the constructive analogue to the standard Chu representation of the
category of topological spaces into Chu(Set, 2). In order to represent the
category of predicates (with objects pairs (X, A), where A is a subset of X,
and the category of complemented predicates (with objects pairs (X, A), where A
is a complemented subset of X, we generalise the Chu construction by defining
the Chu category over a cartesian closed category C and an endofunctor on C.
Finally, we introduce the antiparallel Grothendieck construction over a product
category and a contra-variant Set-valued functor on it of which the Chu
construction is a special case, in case C is a locally small, cartesian closed
category.


  This is the second in a series of three papers working towards constructing
fibrations of compact Spin(7) manifolds by Cayley submanifolds. In this paper
we show that a conically singular Cayley submanifold in an almost
Spin(7)-manifold can be desingularised by gluing in a rescaled asymptotically
conical submanifold of $\mathbb{R}^8$ with the same asymptotic cone. We assume
that both the conically singular and the asymptotically conical Cayley
submanifold are unobstructed in their respective moduli spaces.


  We use simple analytical models of the build up of the dust component and
compare these with radial dust distributions derived from observations of SINGS
galaxies. The observations show that dust gradients are indeed typically
steeper than the corresponding metallicity gradients and our models indicate
very little dust destruction, but significant dust growth in the ISM for most
of these galaxies. Hence, we conclude that there is evidence for significant
non-stellar dust production, and little evidence for dust destruction due to
SNe shock waves. We find that dust is reprocessed rather than destroyed by
shocks from SNe. Finally, we argue that dust abundances derived using standard
methods may be overestimated, since even very 'generous' estimates of the
metallicity results in dust-to-metals ratios above unity in several cases, if
the dust abundances given in the literature are taken at face value.


  Let X be a compact Hausdorff space. We study finite-to-one mappings r:X->X,
onto X, and measures on the corresponding projective limit space
X_\infinity(r). We show that the invariant measures on X_\infinity(r)
correspond in a one-to-one fashion to measures on X which satisfy two
identities. Moreover, we identify those special measures on X_\infinity(r)
which are associated via our correspondence with a function V on X, a Ruelle
transfer operator R_V, and an equilibrium measure \mu_V on X.


  Electronic Raman scattering studies on MgB2 single crystals as a function of
excitation and polarization have revealed three distinct superconducting
features: a clean gap below 37 cm-1 and two coherence peaks at 109 cm-1 and 78
cm-1 which we identify as the superconducting gaps in \pi- and \sigma-bands and
as the Leggett's collective mode arising from the fluctuation in the relative
phase between two superconducting condensates residing on corresponding bands.
The temperature and field dependencies of the superconducting features have
been established. A phononic Raman scattering study of the E2g boron stretching
mode anharmonicity and of superconductivity induced self-energy effects is
presented. We show that anharmonic two phonon decay is mainly responsible for
the unusually large linewidth of the E2g mode. We observe ~2.5% hardening of
the E2g phonon frequency upon cooling into the superconducting state and
estimate the electron-phonon coupling strength associated with this
renormalization.


  Recent experiments on similarly shaped polymer micro-cavity lasers show a
dramatic difference in the far-field emission patterns. We show for different
deformations of the ellipse, quadrupole and hexadecapole that the large
differences in the far-field emission patterns is explained by the differing
ray dynamics corresponding to each shape. Analyzing the differences in the
appropriate phase space for ray motion, it is shown that the differing
geometries of the unstable manifolds of periodic orbits are the decisive
factors in determining the far-field pattern. Surprisingly, we find that
strongly chaotic ray dynamics is compatible with highly directional emission in
the far-field.


  The binary Kob-Andersen (KA) Lennard-Jones mixture is the standard model for
computational studies of viscous liquids and the glass transition. For very
long simulations the viscous KA system crystallizes, however, by phase
separating into a pure A particle phase forming an FCC crystal. We present the
thermodynamic phase diagram for KA-type mixtures consisting of up to 50\% small
(B) particles showing, in particular, that the melting temperature of the
standard KA system at liquid density $1.2$ is $1.028(3)$ in A particle
Lennard-Jones units. At large B particle concentrations the system crystallizes
into the CsCl crystal structure. The eutectic corresponding to the FCC and CsCl
structures is cut-off in a narrow interval of B particle concentrations around
26\% at which the bipyramidal orthorhombic ${\rm PuBr_3}$ structure is the
thermodynamically stable phase. The melting temperature's variation with B
particle concentration at two other pressures, as well as at the constant
density $1.2$, is estimated from the simulations at pressure $10.19$ using
isomorph theory. Our data demonstrate approximate identity between the melting
temperature and the onset temperature below which viscous dynamics appears.
Finally, the nature of the solid-liquid interface is briefly discussed.


  We present the results of a study of the spectral properties of galaxies in
the central part of the Shapley Concentration, covering an extremely wide range
of densities, from the rich cluster cores to the underlying supercluster
environment. Our sample is homogeneous, in a well defined magnitude range
(17=<b_J=<18.8) and contains ~1300 spectra of galaxies at the same distance,
covering an area of ~26 sq.deg. These characteristics allowed an accurate
spectral classification, that we performed using a Principal Components
Analysis technique.
  This spectral classification, together with the [OII] equivalent widths and
the star formation rates, has been used to study the properties of galaxies at
different densities: cluster, intercluster (i.e. galaxies in the supercluster
but outside clusters) and field environment.
  No significant differences are present between samples at low density regimes
(i.e. intercluster and field galaxies). Cluster galaxies, instead, not only
have values significantly different from the field ones, but also show a
dependence on the local density. Moreover, a well defined morphology-density
relation is present in the cluster complexes, although these structures are
known to be involved in major merging events. Also the mean equivalent width of
[OII] shows a trend with the local environment, decreasing at increasing
densities, even if it is probably induced by the morphology-density relation.
  Finally we analyzed the mean star formation rate as a function of the
density, finding again a decreasing trend (at ~ 3sigma significance level). Our
analysis is consistent with the claim of Balogh et al. (1998) that the star
formation in clusters is depressed.


  To what degree should we ascribe cognitive capacities to Large Language
Models (LLMs), such as the ability to reason about intentions and beliefs known
as Theory of Mind (ToM)? Here we add to this emerging debate by (i) testing 11
base- and instruction-tuned LLMs on capabilities relevant to ToM beyond the
dominant false-belief paradigm, including non-literal language usage and
recursive intentionality; (ii) using newly rewritten versions of standardized
tests to gauge LLMs' robustness; (iii) prompting and scoring for open besides
closed questions; and (iv) benchmarking LLM performance against that of
children aged 7-10 on the same tasks. We find that instruction-tuned LLMs from
the GPT family outperform other models, and often also children. Base-LLMs are
mostly unable to solve ToM tasks, even with specialized prompting. We suggest
that the interlinked evolution and development of language and ToM may help
explain what instruction-tuning adds: rewarding cooperative communication that
takes into account interlocutor and context. We conclude by arguing for a
nuanced perspective on ToM in LLMs.


  Biological agents do not have infinite resources to learn new things. For
this reason, a central aspect of human learning is the ability to recycle
previously acquired knowledge in a way that allows for faster, less
resource-intensive acquisition of new skills. In spite of that, how neural
networks in the brain leverage existing knowledge to learn new computations is
not well understood. In this work, we study this question in artificial
recurrent neural networks (RNNs) trained on a corpus of commonly used
neuroscience tasks. Combining brain-inspired inductive biases we call
functional and structural, we propose a system that learns new tasks by
building on top of pre-trained latent dynamics organised into separate
recurrent modules. These modules, acting as prior knowledge acquired previously
through evolution or development, are pre-trained on the statistics of the full
corpus of tasks so as to be independent and maximally informative. The
resulting model, we call a Modular Latent Primitives (MoLaP) network, allows
for learning multiple tasks while keeping parameter counts, and updates, low.
We also show that the skills acquired with our approach are more robust to a
broad range of perturbations compared to those acquired with other multi-task
learning strategies, and that generalisation to new tasks is facilitated. This
work offers a new perspective on achieving efficient multi-task learning in the
brain, illustrating the benefits of leveraging pre-trained latent dynamical
primitives.


  Let G be a polyhedral group, namely a finite subgroup of SO(3). Nakamura's
G-Hilbert scheme provides a preferred Calabi-Yau resolution Y of the polyhedral
singularity C^3/G. The classical McKay correspondence describes the classical
geometry of Y in terms of the representation theory of G. In this paper we
describe the quantum geometry of Y in terms of R, an ADE root system associated
to G. Namely, we give an explicit formula for the Gromov-Witten partition
function of Y as a product over the positive roots of R. In terms of counts of
BPS states (Gopakumar-Vafa invariants), our result can be stated as a
correspondence: each positive root of R corresponds to one half of a genus zero
BPS state. As an application, we use the crepant resolution conjecture to
provide a full prediction for the orbifold Gromov-Witten invariants of [C^3/G].


  We study the Type 0A string theory in the (2,4k) superconformal minimal model
backgrounds, focusing on the fully non-perturbative string equations which
define the partition function of the model. The equations admit a parameter,
Gamma, which in the spacetime interpretation controls the number of background
D-branes, or R-R flux units, depending upon which weak coupling regime is
taken. We study the properties of the string equations (often focusing on the
(2,4) model in particular) and their physical solutions. The solutions are the
potential for an associated Schrodinger problem whose wavefunction is that of
an extended D-brane probe. We perform a numerical study of the spectrum of this
system for varying Gamma and establish that when Gamma is a positive integer
the equations' solutions have special properties consistent with the spacetime
interpretation. We also show that a natural solution-generating transformation
(that changes Gamma by an integer) is the Backlund transformation of the KdV
hierarchy specialized to (scale invariant) solitons at zero velocity. Our
results suggest that the localized D-branes of the minimal string theories are
directly related to the solitons of the KdV hierarchy. Further, we observe an
interesting transition when Gamma=-1.


  A Fabry-Perot-type interferometer is experimentally realized for electrons in
a semiconductor device. A special experimental geometry creates interference
conditions for co-propagating electrons in quantum Hall edge states, which
results in oscillations of the current through the device. The visibility of
these oscillations is found to increase at the high-field edge of the quantum
Hall plateau.


  Using the methods from topological dynamics, H. Furstenberg introduced the
notions of Central sets and proved the famous Central Sets Theorem which is the
simultaneous extension of the van der Waerden and Hindman Theorem. Later N.
Hindman and V. Bergelson found an equivalent formulation of Central sets in the
set of natural numbers in terms of the algebra of the Stone-\v{C}ech
compactification of discrete semigroups. The general case was proved by H. Shi
and H. Yang. Using the notions of ultrafilters, J. McLeod introduced the
notions of Central sets for commutative adequate partial semigroups, however
for noncommutative cases, Central sets can be defined similarly. In this
article, introducing the notions of topological dynamics for partial semigroup
actions, we find an equivalent dynamical characterization of central sets in
partial semigroups\footnote{Recently in \cite{GTG}, authors attempted to do the
same but in a different approach.}. Throughout our article, we follow the
approach of N. Hindman and D. Strauss [N. Hindman, and D. Strauss: Algebra in
the Stone-\v Cech compactification: theory and applications, second edition, de
Gruyter, Berlin, 2012.].


  Using new observations for a sample of 931 early-type galaxies we investigate
whether the \mg2--\so relation shows any dependence on the local environment.
The galaxies have been assigned to three different environments depending on
the local overdensity: clusters, groups, and field, having used our
completeredshift database to guide the assignment of galaxies. It is found that
cluster, group and field early-type galaxies follow almost identical \mg2--\so\
relations, with the largest \mg2 zero-point difference (clusters minus field)
being only $0.007\pm 0.002$ mag. No correlation of the residuals is found with
the morphological type or the bulge to disk ratio. Using stellar population
models in a differential fashion, this small zero-point difference implies a
luminosity-weighted age difference of only $\sim 1$ Gyr between the
corresponding stellar populations, with field galaxies being younger. The
mass-weighted age difference could be significantly smaller, if minor events of
late star formation took place preferentially in field galaxies. We combine
these results with the existing evidence for the bulk of stars in cluster
early-type galaxies having formed at very high redshift, and conclude that the
bulk of stars in galactic spheroids had to form at high redshifts ($z\gsim 3$),
no matter whether such spheroids now reside in low or high density regions. The
cosmological implications of these findings are briefly discussed.


  If Lorentz invariance is only an approximate property of equations describing
a sector of matter above some critical distance scale, the speed of light c
will not necessarily be the only critical speed in vacuum. Superluminal sectors
of matter may exist related to new degrees of freedom not yet discovered
experimentally. The new particles would not be tachyons: they may feel
different minkowskian space-times with critical speeds much higher than c and
behave kinematically like ordinary particles apart from the difference in
critical speed. We present a discussion of possible physical (theoretical and
experimental) and cosmological implications of such a scenario, assuming that
the superluminal sectors couple weakly to ordinary matter.


  Computational models of managerial search often build on backward-looking
search based on hill-climbing algorithms. Regardless of its prevalence, there
is some evidence that this family of algorithms does not universally represent
managers' search behavior. Against this background, the paper proposes an
alternative algorithm that captures key elements of Simon's concept of
satisficing which received considerable support in behavioral experiments. The
paper contrasts the satisficing-based algorithm to two variants of
hill-climbing search in an agent-based model of a simple decision-making
organization. The model builds on the framework of NK fitness landscapes which
allows controlling for the complexity of the decision problem to be solved. The
results suggest that the model's behavior may remarkably differ depending on
whether satisficing or hill-climbing serves as an algorithmic representation
for decision-makers' search. Moreover, with the satisficing algorithm, results
indicate oscillating aspiration levels, even to the negative, and intense - and
potentially destabilizing - search activities when intra-organizational
complexity increases. Findings may shed some new light on prior computational
models of decision-making in organizations and point to avenues for future
research.


  We study the entanglement production for Dirac and Klein-Gordon fields in an
expanding spacetime characterized by the presence of torsion. Torsion is here
considered according to the Einstein-Cartan theory with a conformally flat
Friedmann-Robertson-Walker spacetime. In this framework, torsion is seen as an
external field, fulfilling precise constraints directly got from the
cosmological constant principle. For Dirac field, we find that torsion
increases the amount of entanglement. This turns out to be particularly evident
for small values of particle momentum. We discuss the roles of Pauli exclusion
principle in view of our results, and, in particular, we propose an
interpretation of the two maxima that occur for the entanglement entropy in
presence of torsion. For Klein-Gordon field, and differently from the Dirac
case, the model can be exactly solved by adopting the same scale factor as in
the Dirac case. Again, we show how torsion affects the amount of entanglement,
providing a robust physical motivation behind the increase or decrease of
entanglement entropy. A direct comparison of our findings is also discussed in
view of previous results derived in absence of torsion. To this end, we give
prominence on how our expectations would change in terms of the coupling
between torsion and the scale factor for both Dirac and Klein-Gordon fields.


  We investigate the thermal evolution of comet 67P/Churyumov-Gerasimenko's
subsurface in the Seth_01 region, where active pits have been observed by the
ESA/Rosetta mission. Our simulations show that clathrate destabilization and
amorphous ice crystallization can occur at depths corresponding to those of the
observed pits in a timescale shorter than 67P/Churyumov-Gerasimenko's lifetime
in the comet's activity zone in the inner solar system. Sublimation of
crystalline ice down to such depths is possible only in the absence of a dust
mantle, which requires the presence of dust grains in the matrix small enough
to be dragged out by gas from the pores. Our results are consistent with both
pits formation via sinkholes or subsequent to outbursts, the dominant process
depending on the status of the subsurface porosity. A sealed dust mantle would
favor episodic and disruptive outgassing as a result of an increasing gas
pressure in the pores, while a high porosity should allow the formation of
large voids in the subsurface due to the continuous escape of volatiles. We
finally conclude that the subsurface of 67P/Churyumov-Gerasimenko is not
uniform at a spatial scale of 100-200~m.


  In a recent publication (Telhat Ozdogan, Int. J. Quantum Chem., 92 (2003)
419), we presented a unified algorithm for the evaluation of multicenter
multielectron integrals over Slater type orbitals with noninteger principal
quantum numbers, using the one center expansion formula for Slater type
orbitals with integer principal quantum numbers (E. Oztekin et. all., J. Mol.
Struct. Theochem, 544 (2001) 69; I.I. Guseinov et all., Z. Struct. Khim., 23
(1987) 148 (in Russian)). Guseinov in his comment (physics/0510235) on our
publication claims that the presented formulae in our paper could be derived
from formulae in his papers by simple algebra. We give a brief response to some
of his claims wherever scientifically appropriate. We also assert that the
comments are not scientifically justified and rhetoric is highly inappropriate.
It should be noted also that it is not easy to understand that what Guseinov
intends to do by transforming our procedure into his procedure, which we don't
evaluate as a development but can be regarded as a nice sound of science.


  If the QCD axion solves the strong CP problem then light axion-like-particles
(ALPs) are expected to be ubiquitous in string theory - the string axiverse.
Such ALPs can be the QCD axion and constitute dark matter (DM) or radiation,
quintessence, and lead to new forces. String ALPs are also expected to give
rise to a multiplicity of cosmologically important global axion strings. We
study the properties of these axiverse cosmic strings including the vital
effects of moduli stabilization, and find that the string cores provide
`portals' to different decompactifications - to be precise, the cores explore
the large K\"ahler or complex structure boundary of moduli space. As usual for
global strings the tension $T_1\sim \Lambda^2 \log(L\Lambda)$ with inter-string
separation, $L$, while $\Lambda$ can be small $\ll M_{\rm pl}$. At long
distances from the string there are potential new signatures involving
variations in Standard Model (SM) parameters (Yukawa couplings, gauge
couplings, masses) and equivalence principle violations.


  Ultra-low latency supported by the fifth generation (5G) give impetus to the
prosperity of many wireless network applications, such as autonomous driving,
robotics, telepresence, virtual reality and so on. Ultra-low latency is not
achieved in a moment, but requires long-term evolution of network structure and
key enabling communication technologies. In this paper, we provide an
evolutionary overview of low latency in mobile communication systems, including
two different evolutionary perspectives: 1) network architecture; 2) physical
layer air interface technologies. We firstly describe in detail the evolution
of communication network architecture from the second generation (2G) to 5G,
highlighting the key points reducing latency. Moreover, we review the evolution
of key enabling technologies in the physical layer from 2G to 5G, which is also
aimed at reducing latency. We also discussed the challenges and future research
directions for low latency in network architecture and physical layer.


  The goal of local citation recommendation is to recommend a missing reference
from the local citation context and optionally also from the global context. To
balance the tradeoff between speed and accuracy of citation recommendation in
the context of a large-scale paper database, a viable approach is to first
prefetch a limited number of relevant documents using efficient ranking methods
and then to perform a fine-grained reranking using more sophisticated models.
In that vein, BM25 has been found to be a tough-to-beat approach to
prefetching, which is why recent work has focused mainly on the reranking step.
Even so, we explore prefetching with nearest neighbor search among text
embeddings constructed by a hierarchical attention network. When coupled with a
SciBERT reranker fine-tuned on local citation recommendation tasks, our
hierarchical Attention encoder (HAtten) achieves high prefetch recall for a
given number of candidates to be reranked. Consequently, our reranker requires
fewer prefetch candidates to rerank, yet still achieves state-of-the-art
performance on various local citation recommendation datasets such as ACL-200,
FullTextPeerRead, RefSeer, and arXiv.


  With its growing number of deployed devices and applications, the Internet of
Things (IoT) raises significant challenges for network maintenance procedures.
In this work we address a problem of active fault detection in an IoT scenario,
whereby a monitor can probe a remote device in order to acquire fresh
information and facilitate fault detection. However, probing could have a
significant impact on the system's energy and communication resources. To this
end, we utilize Age of Information as a measure of the freshness of information
at the monitor and adopt a semantics-aware communication approach between the
monitor and the remote device. In semantics-aware communications, the processes
of generating and transmitting information are treated jointly to consider the
importance of information and the purpose of communication. We formulate the
problem as a Partially Observable Markov Decision Process and show analytically
that the optimal policy is of a threshold type. Finally, we use a
computationally efficient stochastic approximation algorithm to approximate the
optimal policy and present numerical results that exhibit the advantage of our
approach compared to a conventional delay-based probing policy.


  Quantum sensing, built upon fundamental quantum phenomena like entanglement
and squeezing, is revolutionizing precision and sensitivity across diverse
domains, including quantum metrology and imaging. Its impact is now stretching
into radar and LiDAR applications, giving rise to the concept of quantum radar.
Unlike traditional radar systems relying on classical electromagnetic, quantum
radar harnesses the potential of the quantum properties of photon states like
entanglement and quantum superposition to transcend established boundaries in
sensitivity and accuracy. This comprehensive review embarks on an exploration
of quantum radar and quantum LiDAR, guided by two primary objectives: enhancing
sensitivity through quantum resources and refining accuracy in target detection
and range estimation through quantum techniques. We initiate our exploration
with a thorough analysis of the fundamental principles of quantum radar, which
includes an evaluation of quantum illumination protocols, receiver designs, and
their associated methodologies. This investigation spans across both microwave
and optical domains, providing us with insights into various experimental
demonstrations and the existing technological limitations. Additionally, we
review the applications of quantum radar protocols for enhanced accuracy in
target range determination and estimation. This section of our review involves
a comprehensive analysis of quantum illumination, quantum interferometry radar,
and other quantum radar protocols, providing insights into their contributions
to the field. This review offers valuable insights into the current state of
quantum radar, providing a deep understanding of key concepts, experiments, and
the evolving landscape of this dynamic and promising field.


  This article may be seen as a summary and a final discussion of the work that
the author has done in recent years on the foundation of quantum theory. It is
shown that quantum mechanics as a model follows under certain specific
conditions from a quite different, much simpler model. This model is connected
to the mind of an observer, or to the joint minds of a group of communicating
observers. The model is based upon conceptual variables, and an important
aspect is that an observer (a group of observers) must decide on which variable
to measure. The model is then linked more generally to a theory of decisions.
The results are discussed from several angles. In particular, macroscopic
consequences are treated briefly.


  By numerically simulating an implementation of the quantum baker's map on a
3-qubit NMR quantum computer based on the molecule trichloroethylene, we
demonstrate the feasibility of quantum chaos experiments on present-day quantum
computers. We give detailed descriptions of proposed experiments that
investigate (a) the rate of entropy increase due to decoherence and (b) the
phenomenon of hypersensitivity to perturbation.


  Radiative generation of the solar scale $\Delta_{\odot}$ is discussed in the
presence of leptonic CP violation. We assume that both the solar scale and
$U_{e3}$ are zero at a high scale and the weak radiative corrections generate
them. It is shown that all leptonic mass matrices satisfying these requirements
lead to a unique prediction $\Delta_{\odot} \cos 2\theta_{\odot}\approx 4
\delta_\tau \sin^2 \theta_A |m_{ee}|^2$ for the solar scale in terms of the
radiative correction parameter $\delta_\tau$, the physical solar (atmospheric)
mixing angles $\theta_{odot} (\theta_A)$ and the Majorana neutrino mass
$m_{ee}$ probed in neutrinoless double beta decay. This relation is independent
of the mixing matrix and CP-violating phases at the high scale. The presence of
CP-violating phases leads to dilution in the solar mixing angle defined at the
high scale. Because of this, bi-maximal mixing pattern at the high energy leads
to large but non-maximal solar mixing in the low-energy theory. An illustrative
model with this feature is discussed.


  Constraints from surveys of post common envelope binaries (PCEBs) consisting
of a white dwarf plus an M-dwarf companion have led to significant progress in
our understanding of the formation of close white dwarf binary stars with
low-mass companions. The white dwarf binary pathways project aims at extending
these previous surveys to larger secondary masses, i.e. secondary stars of
spectral type AFGK. Here we present the discovery and observational
characterization of three PCEBs with G-type secondary stars and orbital periods
between 1.2 and 2.5 days. Using our own tools as well as MESA we estimate the
evolutionary history of the binary stars and predict their future. We find a
large range of possible evolutionary histories for all three systems and
identify no indications for differences in common envelope evolution compared
to PCEBs with lower mass secondary stars. Despite their similarities in orbital
period and secondary spectral type, we estimate that the future of the three
systems are very different: TYC 4962-1205-1 is a progenitor of a cataclysmic
variable system with an evolved donor star, TYC 4700-815-1 will run into
dynamically unstable mass transfer that will cause the two stars to merge, and
TYC 1380-957-1 may appear as super soft source before becoming a rather typical
cataclysmic variable star.


  We use the specialization homomorphism for the birational automorphism group
to study finite order birational automorphisms. For a family of varieties over
a DVR, we prove that a birational automorphism of order coprime to the residue
characteristic cannot specialize to the identity. As an application, we show
that very general $n$-dimensional hypersurfaces of degree $d \geq 5 \lceil
(n+3)/6 \rceil$ have no finite order birational automorphisms.


  We study results related to a conjecture formulated by Strohmer and Beaver
about optimal Gaussian Gabor frame set-ups. Our attention will be restricted to
the case of Gabor systems with standard Gaussian window and rectangular
lattices of density 2. Although this case has been fully treated by Faulhuber
and Steinerberger, the results in this work are new and quite curious. Indeed,
the optimality of the square lattice for the Tolimieri and Orr bound already
implies the optimality of the square lattice for the sharp lower frame bound.
Our main tools include determinants of Laplace--Beltrami operators on tori as
well as special functions from analytic number theory, in particular Eisenstein
series, zeta functions, theta functions and Kronecker's limit formula. We note
that our results also carry over to energy minimization problems over lattices
and a heat distribution problem over flat tori.


  Skill chaining is a promising approach for synthesizing complex behaviors by
sequentially combining previously learned skills. Yet, a naive composition of
skills fails when a policy encounters a starting state never seen during its
training. For successful skill chaining, prior approaches attempt to widen the
policy's starting state distribution. However, these approaches require larger
state distributions to be covered as more policies are sequenced, and thus are
limited to short skill sequences. In this paper, we propose to chain multiple
policies without excessively large initial state distributions by regularizing
the terminal state distributions in an adversarial learning framework. We
evaluate our approach on two complex long-horizon manipulation tasks of
furniture assembly. Our results have shown that our method establishes the
first model-free reinforcement learning algorithm to solve these tasks; whereas
prior skill chaining approaches fail. The code and videos are available at
https://clvrai.com/skill-chaining


  Learning the underlying distribution of molecular graphs and generating
high-fidelity samples is a fundamental research problem in drug discovery and
material science. However, accurately modeling distribution and rapidly
generating novel molecular graphs remain crucial and challenging goals. To
accomplish these goals, we propose a novel Conditional Diffusion model based on
discrete Graph Structures (CDGS) for molecular graph generation. Specifically,
we construct a forward graph diffusion process on both graph structures and
inherent features through stochastic differential equations (SDE) and derive
discrete graph structures as the condition for reverse generative processes. We
present a specialized hybrid graph noise prediction model that extracts the
global context and the local node-edge dependency from intermediate graph
states. We further utilize ordinary differential equation (ODE) solvers for
efficient graph sampling, based on the semi-linear structure of the probability
flow ODE. Experiments on diverse datasets validate the effectiveness of our
framework. Particularly, the proposed method still generates high-quality
molecular graphs in a limited number of steps. Our code is provided in
https://github.com/GRAPH-0/CDGS.


  In this paper, an alternative count distribution suitable for modeling over
dispersed, zero vertex unimodality and monotonically decreasing data sets.
Though the proposed probability model includes Gauss Hypergeometric special
function, it possesses simple and closed expressions for various distributional
characteristics. An application to count regression modeling using a well-known
data set from the National Medical Expenditure Survey is discussed by
considering the length of stay in hospitalization as a dependent variable and
following the proposed count model. We compare our result with the classical
Negative Binomial regression model and recently proposed Uniform Poisson
regression model.


  Phonemic segmentation of speech is a critical step of speech recognition
systems. We propose a novel unsupervised algorithm based on sequence prediction
models such as Markov chains and recurrent neural network. Our approach
consists in analyzing the error profile of a model trained to predict speech
features frame-by-frame. Specifically, we try to learn the dynamics of speech
in the MFCC space and hypothesize boundaries from local maxima in the
prediction error. We evaluate our system on the TIMIT dataset, with
improvements over similar methods.


  In the field of low-light image enhancement, both traditional Retinex methods
and advanced deep learning techniques such as Retinexformer have shown distinct
advantages and limitations. Traditional Retinex methods, designed to mimic the
human eye's perception of brightness and color, decompose images into
illumination and reflection components but struggle with noise management and
detail preservation under low light conditions. Retinexformer enhances
illumination estimation through traditional self-attention mechanisms, but
faces challenges with insufficient interpretability and suboptimal enhancement
effects. To overcome these limitations, this paper introduces the RetinexMamba
architecture. RetinexMamba not only captures the physical intuitiveness of
traditional Retinex methods but also integrates the deep learning framework of
Retinexformer, leveraging the computational efficiency of State Space Models
(SSMs) to enhance processing speed. This architecture features innovative
illumination estimators and damage restorer mechanisms that maintain image
quality during enhancement. Moreover, RetinexMamba replaces the IG-MSA
(Illumination-Guided Multi-Head Attention) in Retinexformer with a
Fused-Attention mechanism, improving the model's interpretability. Experimental
evaluations on the LOL dataset show that RetinexMamba outperforms existing deep
learning approaches based on Retinex theory in both quantitative and
qualitative metrics, confirming its effectiveness and superiority in enhancing
low-light images.


  Recently, the saturation problem of $0$-$1$ matrices gained a lot of
attention. This problem can be regarded as a saturation problem of ordered
bipartite graphs. Motivated by this, we initiate the study of the saturation
problem of ordered and cyclically ordered graphs.
  We prove that dichotomy holds also in these two cases, i.e., for a
(cyclically) ordered graph its saturation function is either bounded or linear.
We also determine the order of magnitude for large classes of (cyclically)
ordered graphs, giving infinite many examples exhibiting both possible
behaviours, answering a problem of P\'alv\"olgyi. In particular, in the ordered
case we define a natural subclass of ordered matchings, the class of linked
matchings, and we start their systematic study, concentrating on linked
matchings with at most three links and prove that many of them have bounded
saturation function.
  In both the ordered and cyclically ordered case we also consider the
semisaturation problem, where dichotomy holds as well and we can even fully
characterize the graphs that have bounded semisaturation function.


  We investigate the Sunyaev-Zel'dovich (SZ) effect caused by primordial black
holes (PBHs) on the cosmic microwave background (CMB) temperature fluctuations.
The gas accreting on a PBH heats up by the release of the gravitational energy.
As a result, the heated gas in the vicinity of the PBH emits the UV and X-ray
photons. These photons can ionize and heat the intergalactic medium (IGM)
around the PBH. Assuming the simple model of these emitting photons, we compute
the profiles of the IGM ionization fraction and temperature around a PBH. Using
these profiles, we evaluate the Compton $y$-parameter created by the IGM gas
around a PBH. Finally, we estimate the CMB temperature angular power spectrum
due to the PBH SZ effect in our model. We show that the SZ temperature
anisotropy due to the PBHs has the flat angular power spectrum on small scale,
$l\leq2000$ and could dominate the primordial temperature spectrum on smaller
scales than the Silk scale. This flat spectrum extends to the scale of the
ionized region by the PBH emission. We also discuss the impact of the
small-scale CMB measurement on the PBH abundance based on our results.


  The compactification of the heterotic string on six-dimensional orbifolds is
reviewed. Some important technical aspects of their construction are clarified
and new parameters, called generalized discrete torsion, are introduced and
related to the torsionless construction. Furthermore, a systematic search for
MSSM-like models is performed in the context of Z6-II orbifolds, addressing
questions like the identification of a supersymmetric vacuum with a naturally
small mu-term and proton decay. Finally, the blow-up of Z3 singularities is
discussed in the local and in the global case - also in the presence of Wilson
lines. This procedure is exemplified with the resolution of a Z3 MSSM
candidate.


  This is an introduction to the volume of Lecture Notes in Physics on
"Strongly interacting matter in magnetic fields". The volume combines
contributions written by a number of experts on different aspects of the
problem. The response of QCD matter to intense magnetic fields has attracted a
lot of interest recently. On the theoretical side, this interest stems from the
possibility to explore the plethora of novel phenomena arising from the
interplay of magnetic field with QCD dynamics. On the experimental side, the
interest is motivated by the recent results on the behavior of quark-gluon
plasma in a strong magnetic field created in relativistic heavy ion collisions
at RHIC and LHC. The purpose of this introduction is to provide a brief
overview and a guide to the individual contributions where these topics are
covered in detail.


  For future quantum technologies the combination of a long quantum state
lifetime and an efficient interface with external optical excitation are
required. In solids, the former is for example achieved by individual spins,
while the latter is found in semiconducting artificial atoms combined with
modern photonic structures. One possible combination of the two aspects is
reached by doping a single quantum dot, providing a strong excitonic dipole,
with a magnetic ion, that incorporates a characteristic spin texture. Here, we
perform four-wave mixing spectroscopy to study the system's quantum coherence
properties. We characterize the optical properties of the undoped CdTe quantum
dot and find a strong photon echo formation which demonstrates a significant
inhomogeneous spectral broadening. Incorporating the Mn$^{2+}$ ion introduces
its spin-5/2 texture to the optical spectra via the exchange interaction,
manifesting as six individual spectral lines in the coherent response. The
random flips of the Mn-spin result in a special type of spectral wandering
between the six transition energies, which is fundamentally different from the
quasi-continuous spectral wandering that results in the Gaussian inhomogeneous
broadening. Here, the discrete spin-ensemble manifests in additional dephasing
and oscillation dynamics.


  We study the problem of mean estimation for high-dimensional distributions,
assuming access to a statistical query oracle for the distribution. For a
normed space $X = (\mathbb{R}^d, \|\cdot\|_X)$ and a distribution supported on
vectors $x \in \mathbb{R}^d$ with $\|x\|_{X} \leq 1$, the task is to output an
estimate $\hat{\mu} \in \mathbb{R}^d$ which is $\epsilon$-close in the distance
induced by $\|\cdot\|_X$ to the true mean of the distribution. We obtain sharp
upper and lower bounds for the statistical query complexity of this problem
when the the underlying norm is symmetric as well as for Schatten-$p$ norms,
answering two questions raised by Feldman, Guzm\'{a}n, and Vempala (SODA 2017).


  The Hermitian Yang-Mills equations on certain vector bundles over Calabi-Yau
cones can be reduced to a set of matrix equations; in fact, these are Nahm-type
equations. The latter can be analysed further by generalising arguments of
Donaldson and Kronheimer used in the study of the original Nahm equations.
Starting from certain equivariant connections, we show that the full set of
instanton equations reduce, with a unique gauge transformation, to the
holomorphicity condition alone.


  We present Hubble Space Telescope WFPC2 images of a portion of the bright
northeast rim of NGC 6888, the nebular shell physically associated with the
Wolf-Rayet star HD 192163. The exposures are taken in the light of Halpha 6563,
[O III] 5007, and [S II] 6717,6731. The images are used to constrain models of
the ionization structure of nebular features. From these models we infer
physical conditions within features, and estimate elemental abundances within
the nebula. The results of our analysis, together with the degree of small
scale inhomogeneity apparent in the images, call into question the assumptions
underlying traditional methodologies for interpretation of nebular
spectroscopy.
  The thermal pressure of photoionized clumps is higher than the inferred
internal pressure of the shocked stellar wind, implying that the current
physical conditions have changed significantly over less than a few thousand
years. These results are discussed within the context of published three-wind
evolutionary scenarios for the formation of the nebula. We also discuss the
nature of a back-illuminated radiative shock driven into the cavity surrounding
NGC 6888.


  Theoretical and computational studies of the quantum phase diagram of the
one-dimensional half-filled extended Hubbard model (EHM) indicate a narrow bond
order wave (BOW) phase with finite magnetic gap $E_m$ for on-site repulsion $U
< U^*$, the critical point, and nearest neighbor interaction $V_c \approx U/2$
near the boundary of the charge density wave (CDW) phase. Potentials with more
extended interactions that retain the EHM symmetry are shown to have a less
cooperative CDW transition with higher $U^*$ and wider BOW phase. Density
matrix renormalization group (DMRG) is used to obtain $E_m$ directly as the
singlet-triplet gap, with finite $E_m$ marking the BOW boundary $V_s(U)$. The
BOW/CDW boundary $V_c(U)$ is obtained from exact finite-size calculations that
are consistent with previous EHM determinations. The kinetic energy or bond
order provides a convenient new estimate of $U^*$ based on a metallic point at
$V_c(U)$ for $U < U^*$. Tuning the BOW phase of half-filled Hubbard models with
different intersite potentials indicates a ground state with large charge
fluctuations and magnetic frustration. The possibility of physical realizations
of a BOW phase is raised for Coulomb interactions.


  The shortage of highly qualified high school physics teachers is a national
problem. The Mitchell Institute Physics Enhancement Program (MIPEP) is a
two-week professional development program for in-service high school physics
teachers with a limited background in the subject area. MIPEP, which started in
2012, includes intense training in both subject matter and research-based
instructional strategies. Content and materials used in the program fulfill
state curriculum requirements. The MIPEP curriculum is taught by Texas A&M
University faculty from the Department of Physics & Astronomy along with two
master high school physics teachers. In this paper we present the design and
implementation of MIPEP. We report on assessment of knowledge and confidence of
2014-2018 MIPEP cohorts. We also present the results of the 2020 program that
was delivered remotely due to the pandemic. Analysis of these assessments
showed that the majority of MIPEP participants increased their physics
knowledge and their confidence in that knowledge during both traditional and
virtual program deliveries.


  The production and dynamics of strange and antistrange hadrons in heavy-ion
reactions from $\sqrt{s_{NN}} \approx$ 3 GeV to 200 GeV is analyzed within the
Parton-Hadron-String-Dynamics (PHSD) transport model. The PHSD results for
strange baryon and antibaryon production are roughly consistent with the
experimental data starting from upper SPS energies. Nevertheless, hadronic
final state flavor-exchange reactions are important for the actual abundances,
in particular at large rapidities where hadronic dynamics, parton fragmentation
and string decay dominate. A striking disagreement between the PHSD results and
the available data persists, however, for bombarding energies below
$\sqrt{s_{NN}} \approx$ 8 GeV where the strangeness production is significantly
underestimated as in earlier HSD studies. This finding implies that the
strangeness enhancement seen experimentally at FAIR/NICA energies cannot be
attributed to a deconfinement phase transition or crossover but probably
involves the approximate restoration of chiral symmetry in the hadronic phase.


  With the supervision from source domain only in class-level, existing
unsupervised domain adaptation (UDA) methods mainly learn the domain-invariant
representations from a shared feature extractor, which causes the source-bias
problem. This paper proposes an unsupervised domain adaptation approach with
Teacher-Student Competition (TSC). In particular, a student network is
introduced to learn the target-specific feature space, and we design a novel
competition mechanism to select more credible pseudo-labels for the training of
student network. We introduce a teacher network with the structure of existing
conventional UDA method, and both teacher and student networks compete to
provide target pseudo-labels to constrain every target sample's training in
student network. Extensive experiments demonstrate that our proposed TSC
framework significantly outperforms the state-of-the-art domain adaptation
methods on Office-31 and ImageCLEF-DA benchmarks.


  We propose a new reinforcement learning algorithm for partially observable
Markov decision processes (POMDP) based on spectral decomposition methods.
While spectral methods have been previously employed for consistent learning of
(passive) latent variable models such as hidden Markov models, POMDPs are more
challenging since the learner interacts with the environment and possibly
changes the future observations in the process. We devise a learning algorithm
running through episodes, in each episode we employ spectral techniques to
learn the POMDP parameters from a trajectory generated by a fixed policy. At
the end of the episode, an optimization oracle returns the optimal memoryless
planning policy which maximizes the expected reward based on the estimated
POMDP model. We prove an order-optimal regret bound with respect to the optimal
memoryless policy and efficient scaling with respect to the dimensionality of
observation and action spaces.


  After the first treatments of quantum finite state automata by Moore and
Crutchfield and by Kondacs and Watrous, a number of papers study the power of
quantum finite state automata and their variants. This paper introduces a model
of two-way quantum one-counter automata (2Q1CAs), combining the model of
two-way quantum finite state automata (2QFAs) by Kondacs and Watrous and the
model of one-way quantum one-counter automata (1Q1CAs) by Kravtsev. We give the
definition of 2Q1CAs with well-formedness conditions. It is proved that 2Q1CAs
are at least as powerful as classical two-way deterministic one-counter
automata (2D1CAs), that is, every language L recognizable by 2D1CAs is
recognized by 2Q1CAs with no error. It is also shown that several
non-context-free languages including {a^n b^{n^2}} and {a^n b^{2^n}} are
recognizable by 2Q1CAs with bounded error.


  We investigate the feasibility of using ultracold neutral atoms trapped near
a thin superconductor to study vortex noise close to the
Kosterlitz-Thouless-Berezinskii transition temperature. Alkali atoms such as
rubidium probe the magnetic field produced by the vortices. We show that the
relaxation time $T_1$ of the Zeeman sublevel populations can be conveniently
adjusted to provide long observation times. We also show that the transverse
relaxation times $T_2$ for Zeeman coherences are ideal for studying the vortex
noise. We briefly consider the motion of atom clouds held close to the surface
as a method for monitoring the vortex motion.


  Isotope variations of nucleosynthetic origin among Solar System's solid
samples are well documented, yet the origin of these variations is still
uncertain. The observed variability of \iso{54}Cr among materials formed in
different regions of the proto-planetary disk has been attributed to variable
amounts of presolar chromium-rich oxide (chromite) grains, which exist within
the meteoritic stardust inventory and most likely originated from some type of
supernova explosions. To investigate if core-collapse supernovae (CCSNe) could
be the site of origin of these grains, we analyse yields of CCSN models of
stars with initial mass 15, 20 and 25 M$_{\odot}$, and solar metallicity. We
present an extensive abundance data set of the Cr, Mg, and Al isotopes as a
function of enclosed mass. We find cases in which the explosive C-ashes produce
a composition in good agreement with the observed \iso{54}Cr/\iso{52}Cr and
\iso{53}Cr/\iso{52}Cr ratios as well as the \iso{50}Cr/\iso{52}Cr ratios.
Taking into account that the signal at atomic mass 50 could also originate from
\iso{50}Ti, the ashes of explosive He-burning also match the observed ratios.
Addition of material from the He ashes (enriched in Al and Cr relative to Mg to
simulate the make-up of chromite grains) to the Solar System composition may
reproduce the observed correlation between Mg and Cr anomalies, while material
from the C-ashes does not present significant Mg anomalies together with Cr
isotopic variations. In all cases, non-radiogenic, stable Mg isotope variations
dominate over the variations expected from \iso{26}Al.


  In recent years, the discovery of complex dynamic systems in various fields
through data-driven methods has attracted widespread attention. This method has
played the role of data and has become an advantageous tool for us to study
complex phenomena. In this work, we propose a framework for detecting the
dynamic behavior, such as the maximum likelihood transition path, of stochastic
dynamic systems from data. For the stochastic dynamic system, we need to use
the Kramers-Moyal formula to convert it into a deterministic form for
processing, then use the extended SINDy method to obtain the parameters of
stochastic dynamic systems, and finally calculate the maximum likelihood
transition path. We give two examples of stochastic dynamical systems driven by
additive and multiplicative Gaussian noise, and demonstrate the validity of the
method by reproducing the known dynamical system behavior.


  Entanglement-assisted quantum error correcting codes (EAQECCs) are a simple
and fundamental class of codes. They allow for the construction of quantum
codes from classical codes by relaxing the duality condition and using
pre-shared entanglement between the sender and receiver. However, in general it
is not easy to determine the number of shared pairs required to construct an
EAQECC. In this paper, we show that this number is related to the hull of the
classical code. Using this fact, we give methods to construct EAQECCs requiring
desirable amount of entanglement. This leads to design families of EAQECCs with
good error performance. Moreover, we construct maximal entanglement EAQECCs
from LCD codes. Finally, we prove the existence of asymptotically good EAQECCs
in the odd characteristic case.


  A common approach to medical image analysis on volumetric data uses deep 2D
convolutional neural networks (CNNs). This is largely attributed to the
challenges imposed by the nature of the 3D data: variable volume size, GPU
exhaustion during optimization. However, dealing with the individual slices
independently in 2D CNNs deliberately discards the depth information which
results in poor performance for the intended task. Therefore, it is important
to develop methods that not only overcome the heavy memory and computation
requirements but also leverage the 3D information. To this end, we evaluate a
set of volume uniformizing methods to address the aforementioned issues. The
first method involves sampling information evenly from a subset of the volume.
Another method exploits the full geometry of the 3D volume by interpolating
over the z-axis. We demonstrate performance improvements using controlled
ablation studies as well as put this approach to the test on the ImageCLEF
Tuberculosis Severity Assessment 2019 benchmark. We report 73% area under curve
(AUC) and binary classification accuracy (ACC) of 67.5% on the test set beating
all methods which leveraged only image information (without using clinical
meta-data) achieving 5-th position overall. All codes and models are made
available at https://github.com/hasibzunair/uniformizing-3D.


  The essential postulates of classical thermodynamics are formulated, from
which the second law is deduced as the principle of increase of entropy in
irreversible adiabatic processes that take one equilibrium state to another.
The entropy constructed here is defined only for equilibrium states and no
attempt is made to define it otherwise. Statistical mechanics does not enter
these considerations. One of the main concepts that makes everything work is
the comparison principle (which, in essence, states that given any two states
of the same chemical composition at least one is adiabatically accessible from
the other) and we show that it can be derived from some assumptions about the
pressure and thermal equilibrium. Temperature is derived from entropy, but at
the start not even the concept of `hotness' is assumed. Our formulation offers
a certain clarity and rigor that goes beyond most textbook discussions of the
second law.


  A memoryless state-dependent multiple-access channel (MAC) is considered,
where two transmitters wish to convey their messages to a single receiver while
simultaneously sensing (estimating) the respective states via generalized
feedbacks. For this channel, an improved inner bound is provided on the
fundamental rate-distortions tradeoff which characterizes the communication
rates the transmitters can achieve while simultaneously ensuring that their
state-estimates satisfy desired distortion criteria. The new inner bound is
based on a scheme where each transmitter codes over the generalized feedback so
as to improve the state estimation at the other transmitter. This is in
contrast to the schemes proposed for point-to-point and broadcast channels
where coding is used only for the transmission of messages and the optimal
estimators operate on a symbol-by-symbol basis on the sequences of channel
inputs and feedback outputs.


  Hepatocellular carcinoma (HCC) is the most common type of primary liver
cancer in adults, and the most common cause of death of people suffering from
cirrhosis. The segmentation of liver lesions in CT images allows assessment of
tumor load, treatment planning, prognosis and monitoring of treatment response.
Manual segmentation is a very time-consuming task and in many cases, prone to
inaccuracies and automatic tools for tumor detection and segmentation are
desirable. In this paper, we compare two network architectures, one that is
composed of one neural network and manages the segmentation task in one step
and one that consists of two consecutive fully convolutional neural networks.
The first network segments the liver whereas the second network segments the
actual tumor inside the liver. Our networks are trained on a subset of the LiTS
(Liver Tumor Segmentation) Challenge and evaluated on data.


  An attempt is made to present the contribution of the scalar unparticle on
some scattering processes in the Randall - Sundum (RS) model. We have evaluated
the contribution of the scalar unparticle on the W - pair production
cross-sections at International Linear Colliders (ILC). The results indicate
that at the low values of the scaling dimension and the bounds on scale
$\Lambda_{U}$ are around few TeV, the cross-sections are much enhanced, which
is quite comparable with the W-production in the standard model and hence it is
worthwhile to explore in future colliders.


  Results on \jpsi production in $e p$ interactionsin the H1 experiment at HERA
are presented. The \jpsi mesons are produced by almost real photons
($Q^2\approx 0$) and detected via their leptonic decays. The data have been
taken in 1994 and correspond to an integrated luminosity of $2.7 {pb}^{-1}$.
The $\gamma p$ cross section for elastic \jpsi production is observed to
increase strongly with the \cm energy. The cross section for diffractive
$J/\psi$ production with proton dissociation is found to be of similar
magnitude as the elastic cross section. Distributions of transverse momentum
and decay angle are studied and found to be in accord with a diffractive
production mechanism. For inelastic \jpsi production the total $\gamma p$ cross
section, the distribution of transverse momenta, and the elasticity of the
\jpsi are compared to NLO QCD calculations in a colour singlet model and
agreement is found. Diffractive \psiprime production has been observed and a
first estimate of the ratio to \jpsi production in the HERA energy regime is
given.


  We discuss the problems of consensus and unity in science. The natural
sciences seem to contrast with many other areas of endeavor in that a high
level of consensus seems to exist in them. However, a careful analysis of the
structure of particular physical theories,such as those concerned with
electrons, shows that there is great heterogeneity of both theory and
methodology. We argue that the natural science community tends to be tolerant
of diversity. We contrast this tolerance among natural scientists with the more
overt disagreement occurring in the social sciences and humanities. Our central
theme is that many intellectual problems arise from straining too hard to make
a successful perspective into a total worldview.


  The study of new BPS objects in AdS_5 has led to a deeper understanding of
AdS/CFT. To help complete this picture, and to fully explore the consequences
of the supersymmetry algebra, it is also important to obtain new solutions with
bulk fermions turned on. In this paper we construct superpartners of the 1/2
BPS black hole in AdS_5 using a natural set of fermion zero modes. We
demonstrate that these superpartners, carrying fermionic hair, have conserved
charges differing from the original bosonic counterpart. To do so, we find the
R-charge and dipole moment of the new system, as well as the mass and angular
momentum, defined through the boundary stress tensor. The complete set of
superpartners fits nicely into a chiral representation of AdS_5 supersymmetry,
and the spinning solutions have the expected gyromagnetic ratio, g=1.


  Objective Electronic health records (EHRs) are a promising source of data for
health outcomes research in oncology. A challenge in using EHR data is that
selecting cohorts of patients often requires information in unstructured parts
of the record. Machine learning has been used to address this, but even
high-performing algorithms may select patients in a non-random manner and bias
the resulting cohort. To improve the efficiency of cohort selection while
measuring potential bias, we introduce a technique called Model-Assisted Cohort
Selection (MACS) with Bias Analysis and apply it to the selection of metastatic
breast cancer (mBC) patients. Materials and Methods We trained a model on
17,263 patients using term-frequency inverse-document-frequency (TF-IDF) and
logistic regression. We used a test set of 17,292 patients to measure algorithm
performance and perform Bias Analysis. We compared the cohort generated by MACS
to the cohort that would have been generated without MACS as reference
standard, first by comparing distributions of an extensive set of clinical and
demographic variables and then by comparing the results of two analyses
addressing existing example research questions. Results Our algorithm had an
area under the curve (AUC) of 0.976, a sensitivity of 96.0%, and an abstraction
efficiency gain of 77.9%. During Bias Analysis, we found no large differences
in baseline characteristics and no differences in the example analyses.
Conclusion MACS with bias analysis can significantly improve the efficiency of
cohort selection on EHR data while instilling confidence that outcomes research
performed on the resulting cohort will not be biased.


  Experiments with trapped atomic gases have opened novel possibilities for
studying the evolution of nonequilibrium finite quantum systems, which revived
the necessity of reconsidering and developing the theory of such processes.
This review analyzes the basic approaches to describing the phenomena of
equilibration, thermalization, and decoherence in finite quantum systems.
Isolated, nonisolated, and quasi-isolated quantum systems are considered. The
relations between equilibration, decoherence, and the existence of time arrow
are emphasized. The possibility for the occurrence of rare events, preventing
complete equilibration, are mentioned.


  We present a catalogue of point-like H{\alpha}-excess sources in the Northern
Galactic Plane. Our catalogue is created using a new technique that leverages
astrometric and photomeric information from Gaia to select H{\alpha}-bright
outliers in the INT Photometric H{\alpha} Survey of the Northern Galactic Plane
(IPHAS), across the colour-absolute magnitude diagram. To mitigate the
selection biases due to stellar population mixing and to extinction, the
investigated objects are first partitioned with respect to their positions in
the Gaia colour-absolute magnitude space, and in the Galactic coordinates
space, respectively. The selection is then performed on both partition types
independently. Two significance parameters are assigned to each target, one for
each partition type. These represent a quantitative degree of confidence that
the given source is a reliable H{\alpha}-excess candidate, with reference to
the other objects in the corresponding partition. Our catalogue provides two
flags for each source, both indicating the significance level of the
H{\alpha}-excess. By analysing their intensity in the H{\alpha} narrow band,
28,496 objects out of 7,474,835 are identified as H{\alpha}-excess candidates
with a significance higher than 3. The completeness fraction of the H{\alpha}
outliers selection is between 3% and 5%. The suggested 5{\sigma} conservative
cut yields a purity fraction of 81.9%.


  This article aims to provide insights into the qualitative analysis of some
nonlinear Reaction-Diffusion (RD) systems arising in Neuroscience. We first
introduce a non-homogeneous FitzHugh-Nagumo (nhFHN) featuring excitability and
oscillatory properties. Then, we discuss the qualitative analysis of a toy
model related to nhFHN. In particular, we focus on the convergence of solutions
of the toy model toward different solutions (fixed point, periodic) and show
the existence of a cascade of Hopf bifurcations. Finally, we connect this
analysis to the nhFHN system.


  We make stacks of intrinsic Josephson junctions (IJJs) imbedded in the bulk
of very thin ($d\leq 100$~nm) $\mathrm{Bi_2Sr_2CaCu_2O_{8+x}}$ single crystals.
By precisely controlling the etching depth during the double-sided fabrication
process, the stacks can be reproducibly tailor-made to be of any microscopic
height ($0-9 \mathrm{nm} <d$), i.e. enclosing a specified number of IJJ (0-6),
including the important case of a single junction. We discuss reproducible
gap-like features in the current-voltage characteristics of the samples at high
bias.


  A method for computing lower bounds on capacities of 2-dimensional
constraints having a symmetric presentation in either the horizontal or the
vertical direction is presented. The method is a generalization of the method
of Calkin and Wilf (SIAM J. Discrete Math., 1998). Previous best lower bounds
on capacities of certain constraints are improved using the method. It is also
shown how this method, as well as their method for computing upper bounds on
the capacity, can be applied to constraints which are not of finite-type.
Additionally, capacities of 2 families of multi-dimensional constraints are
given exactly.


  The Strassen algorithm and Winograd's variant accelerate matrix
multiplication by using fewer arithmetic operations than standard matrix
multiplication. Although many papers have been published to accelerate single-
as well as double-precision matrix multiplication by using these algorithms, no
research to date has been undertaken to accelerate multiple precision matrix
multiplication. In this paper, we propose a multiple precision matrix
multiplication program for matrices of any size and test its performance. We
also reveal special properties of our program through its application to LU
decomposition.


  The dissipative dynamics of strongly interacting systems are often
characterised by the timescale set by the inverse temperature
$\tau_P\sim\hbar/(k_BT)$. We show that near a class of strongly interacting
quantum critical points that arise in the infra-red limit of translationally
invariant holographic theories, there is a collective excitation (a quasinormal
mode of the dual black hole spacetime) whose lifetime $\tau_{eq}$ is
parametrically longer than $\tau_P$: $\tau_{eq}\gg T^{-1}$. The lifetime is
enhanced due to its dependence on a dangerously irrelevant coupling that breaks
the particle-hole symmetry and the invariance under Lorentz boosts of the
quantum critical point. The thermal diffusivity (in units of the butterfly
velocity) is anomalously large near the quantum critical point and is governed
by $\tau_{eq}$ rather than $\tau_P$. We conjecture that there exists a
long-lived, propagating collective mode with velocity $v_s$, and in this case
the relation $D=v_s^2\tau_{eq}$ holds exactly in the limit $T\tau_{eq}\gg1$.
While scale invariance is broken, a generalised scaling theory still holds
provided that the dependence of observables on the dangerously irrelevant
coupling is incorporated. Our work further underlines the connection between
dangerously irrelevant deformations and slow equilibration.


  The state-of-the-art in text-to-speech synthesis has recently improved
considerably due to novel neural waveform generation methods, such as WaveNet.
However, these methods suffer from their slow sequential inference process,
while their parallel versions are difficult to train and even more expensive
computationally. Meanwhile, generative adversarial networks (GANs) have
achieved impressive results in image generation and are making their way into
audio applications; parallel inference is among their lucrative properties. By
adopting recent advances in GAN training techniques, this investigation studies
waveform generation for TTS in two domains (speech signal and glottal
excitation). Listening test results show that while direct waveform generation
with GAN is still far behind WaveNet, a GAN-based glottal excitation model can
achieve quality and voice similarity on par with a WaveNet vocoder.


  There is growing evidence that the small weak scale may be related to
self-organized criticality. In this regard, we note that if the strange quark
were lighter, the QCD phase transition could have been first order, possibly
exhibiting quantum critical points at zero temperature as a function of the
Higgs vacuum expectation value $v_h$ smaller than (but near) the weak scale. We
show that these quantum critical points allow a dynamical selection of the
observed weak scale, via quantum-dominated stochastic evolutions of the value
of $v_h$ during eternal inflation. Although the values of $v_h$ in different
Hubble patches are described by a probability distribution in the multiverse,
inflationary quantum dynamics ensures that the peak of the distribution evolves
toward critical points (self-organized criticality), driven mainly by the
largest Hubble expansion rate there -- the Hubble selection of the universe. To
this end, we first explore the quantum critical points of the three-flavor QCD
linear sigma model, parametrized by $v_h$ at zero temperature, and we present a
relaxion model for the weak scale. Among the patches that have reached
reheating, it results in a sharp probability distribution of $v_h$ near the
observed weak scale, which is critical not to the crossover at $v_h=0$ but to
the sharp transition at ${\sim}\Lambda_{\rm QCD}$.


  Although the overall time-scale for nuclear fission is long, suggesting a
slow process, rapid shape evolution occurs in its later stages near scission.
Theoretical prediction of the fission fragments and their characteristics are
often based on the assumption that the internal degrees of freedom are
equilibrated along the fission path. However, this adiabatic approximation may
break down near scission. This is studied for the symmetric fission of
$^{258,264}$Fm. The non-adiabatic evolution is computed using the
time-dependent Hartree-Fock method, starting from an adiabatic configuration
where the fragments have acquired their identity. It is shown that dynamics has
an important effect on the kinetic and excitation energies of the fragments.
The vibrational modes of the fragments in the post-scission evolution are also
analyzed.


  We propose a low noise, triply-resonant, electro-optic (EO) scheme for
quantum microwave-to-optical conversion based on coupled nanophotonics
resonators integrated with a superconducting qubit. Our optical system features
a split resonance - a doublet - with a tunable frequency splitting that matches
the microwave resonance frequency of the superconducting qubit. This is in
contrast to conventional approaches where large optical resonators with
free-spectral range comparable to the qubit microwave frequency are used. In
our system, EO mixing between the optical pump coupled into the low frequency
doublet mode and a resonance microwave photon results in an up-converted
optical photon on resonance with high frequency doublet mode. Importantly, the
down-conversion process, which is the source of noise, is suppressed in our
scheme as the coupled-resonator system does not support modes at that
frequency. Our device has at least an order of magnitude smaller footprint than
the conventional devices, resulting in large overlap between optical and
microwave fields and large photon conversion rate ($g/2\pi$) in the range of
$\sim$5-15 kHz. Owing to large $g$ factor and doubly-resonant nature of our
device, microwave-to-optical frequency conversion can be achieved with optical
pump powers in the range of tens of microwatts, even with moderate values for
optical $\it{Q}$ ($\sim 10^6$) and microwave $Q$ ($ \sim10^4$). The performance
metrics of our device, with substantial improvement over the previous EO-based
approaches, promise a scalable quantum microwave-to-optical conversion and
networking of superconducting processors via optical fiber communication.


  In the last six years, Indium selenide (InSe) has appeared as a new van der
Waals heterostructure platform which has been extensively studied due to its
unique electronic and optical properties. Such as transition metal
dichalcogenides (TMDCs), the considerable bandgap and high electron mobility
can provide a potential optoelectronic application. Here we present
low-temperature transport measurements on a few-layer InSe van der Waals
heterostructure with graphene-gated contacts. For high magnetic fields, we
observe magnetoresistance minima at even filling factors related to two-fold
spin degeneracy. By electrostatic gating with negatively biased split gates, a
one-dimensional channel is realized. Close to pinch-off, transport through the
constriction is dominated by localized states with charging energies ranging
from 2 to 5 meV. This work opens new possibility to explore the low-dimensional
physics including quantum point contact and quantum dot.


  We obtain a bijection between certain lattice paths and partitions. This
implies a proof of polynomial identities conjectured by Melzer. In a limit,
these identities reduce to Rogers--Ramanujan-type identities for the
$\chi_{1,1}^{(p,p+1)}(q)$ Virasoro characters, conjectured by the Stony Brook
group.


  In this paper, we focus on the personalized response generation for
conversational systems. Based on the sequence to sequence learning, especially
the encoder-decoder framework, we propose a two-phase approach, namely
initialization then adaptation, to model the responding style of human and then
generate personalized responses. For evaluation, we propose a novel human aided
method to evaluate the performance of the personalized response generation
models by online real-time conversation and offline human judgement. Moreover,
the lexical divergence of the responses generated by the 5 personalized models
indicates that the proposed two-phase approach achieves good results on
modeling the responding style of human and generating personalized responses
for the conversational systems.


  In recent years, analog quantum simulators have reached unprecedented
quality, both in qubit numbers and coherence times. Most of these simulators
natively implement Ising-type Hamiltonians, which limits the class of models
that can be simulated efficiently. We propose a method to overcome this
limitation and simulate the time-evolution of a large class of spinless
fermionic systems in 1D using simple Ising-type Hamiltonians with local
transverse fields. The time complexity of the simulation scales with the square
root of the inverse error, and thus favorably compared to the worst-case error
of first-order product formulas. Our method is based on domain wall encoding,
which is implemented via strong (anti-)ferromagnetic couplings $|J|$. We show
that in the limit of strong $|J|$, the domain walls behave like spinless
fermions in 1D. The Ising Hamiltonians are one-dimensional chains with
nearest-neighbor and, optionally, next-nearest-neighbor interactions. As a
proof-of-concept, we perform numerical simulations of various 1D-fermionic
systems using domain wall evolution and accurately reproduce the systems'
properties, such as topological edge states, Anderson localization, quantum
chaotic time evolution and time-reversal symmetry breaking via
Floquet-engineering. Our approach makes the simulation of a large class of
fermionic many-body systems feasible on analogue quantum hardware that natively
implements Ising-type Hamiltonians with transverse fields.


  A Calabi-Yau orbifold is locally modeled on C^n/G where G is a finite
subgroup of SL(n, C). In dimension n=3 a crepant resolution is given by
Nakamura's G-Hilbert scheme. This crepant resolution has a description as a
GIT/symplectic quotient. We use tools from global analysis to give a
geometrical generalization of the McKay Correspondence to this case.


  A spider is an axiomatization of the representation theory of a group,
quantum group, Lie algebra, or other group or group-like object. We define
certain combinatorial spiders by generators and relations that are isomorphic
to the representation theories of the three rank two simple Lie algebras,
namely A2, B2, and G2. They generalize the widely-used Temperley-Lieb spider
for A1. Among other things, they yield bases for invariant spaces which are
probably related to Lusztig's canonical bases, and they are useful for
computing quantities such as generalized 6j-symbols and quantum link
invariants.


  The nuclear Skyrme model is considered in the extreme limit where the nucleon
radius tends to infinity. In this limit only the Skyrme term in the action is
significant. The model is then conformally invariant in dimension 4, and
supports an instanton solution which can be constructed explicitly. The
construction uses the conformal invariance and a certain symmetry reduction to
reduce the model to the static phi^4 model in one dimension. The phi^4 kink
solution gives the radial profile of the instanton, the kink position zero-mode
corresponding to the instanton width.


  The mass of the lowest scalar glueball is discussed by using QCD sum rules.
We find that the glueball mass is sensitive to the choice of moments and
slightly depends on the radiative corrections. With the help of suitable
moments and stability criteria, we get the scalar glueball mass: $1710\pm110$
MeV without radiative corrections and $1580\pm150$ MeV with radiative
corrections.


  Analysis of comprehensive monitoring of 34 gamma-ray bright quasars, BL Lac
objects, and radio galaxies reveals a close connection between events in the
millimeter-wave emission imaged with the VLBA at 43 GHz and flares at gamma-ray
and lower frequencies. Roughly 2/3 of the flares are coincident with the
appearance of a new superluminal knot and/or a flare in the millimeter-wave
"core'" located parsecs from the central engine. This presents a theoretical
challenge to explain how the gamma-ray flux can often be variable on intra-day
time-scales. Possible answers to this include very narrow opening angles of the
jet, small volume filling factors of the highest energy electrons, chaotic
magnetic fields, and turbulent velocity fields relative to the mean jet flow.


  We review recent developments in special geometry, emphasizing the role of
real coordinates. In the first part we discuss the para-complex geometry of
vector and hypermultiplets in rigid Euclidean N=2 supersymmetry. In the second
part we study the variational principle governing the near horizon limit of BPS
black holes in matter-coupled N=2 supergravity and observe that the black hole
entropy is the Legendre transform of the Hesse potential encoding the geometry
of the scalar fields.


  We present a Markov chain on the $n$-dimensional hypercube $\{0,1\}^n$ which
satisfies $t_{{\rm mix}}(\epsilon) = n[1 + o(1)]$. This Markov chain alternates
between random and deterministic moves and we prove that the chain has cut-off
with a window of size at most $O(n^{0.5+\delta})$ where $\delta>0$. The
deterministic moves correspond to a linear shift register.


  Macroscopic plasma polarization, which is created by gravitation and other
mass-acting (inertial) forces in massive astrophysical objects (MAO) is under
discussion. Non-ideality effect due to strong Coulomb interaction of charged
particles is introduced into consideration as a new source of such
polarization. Simplified situation of totally equilibrium isothermal star
without relativistic effects and influence of magnetic field is considered. The
study is based on conditions of constancy for generalized (electro)chemical
potentials and/or conditions of equilibrium for the forces acting on each
charged specie. New "non-ideality force" appears in this consideration.
Hypothetical sequences of gravitational, inertial and non-ideality polarization
on thermo- and hydrodynamics of MAO are under discussion.


  Let $X$ be a cubic threefold, quartic double solid or Gushel--Mukai
threefold, and $\mathcal{K}u(X)\subset \mathrm{D}^b(X)$ be its Kuznetsov
component. We show that a stability condition $\sigma$ on $\mathcal{K}u(X)$ is
Serre-invariant if and only if its homological dimension is at most $2$. As a
corollary, we prove that all Serre-invariant stability conditions on
$\mathcal{K}u(X)$ form a contractible connected component of the stability
manifold.


  Action advising is a peer-to-peer knowledge exchange technique built on the
teacher-student paradigm to alleviate the sample inefficiency problem in deep
reinforcement learning. Recently proposed student-initiated approaches have
obtained promising results. However, due to being in the early stages of
development, these also have some substantial shortcomings. One of the
abilities that are absent in the current methods is further utilising advice by
reusing, which is especially crucial in the practical settings considering the
budget and cost constraints in peer-to-peer. In this study, we present an
approach to enable the student agent to imitate previously acquired advice to
reuse them directly in its exploration policy, without any interventions in the
learning mechanism itself. In particular, we employ a behavioural cloning
module to imitate the teacher policy and use dropout regularisation to have a
notion of epistemic uncertainty to keep track of which state-advice pairs are
actually collected. As the results of experiments we conducted in three Atari
games show, advice reusing via generalisation is indeed a feasible option in
deep RL and our approach can successfully achieve this while significantly
improving the learning performance, even when paired with a simple early
advising heuristic.


  We describe our theoretical formalism and computational scheme for making
ab-initio calculations of the dynamic paramagnetic spin susceptibilities of
metals and alloys at finite temperatures. Its basis is Time-Dependent Density
Functional Theory within an electronic multiple scattering, imaginary time
Green function formalism. Results receive a natural interpretation in terms of
overdamped oscillator systems making them suitable for incorporation into spin
fluctuation theories. For illustration we apply our method to the nearly
ferromagnetic metal Pd and the nearly antiferromagnetic chromium alloy Cr95V5.
We compare and contrast the spin dynamics of these two metals and in each case
identify those fluctuations with relaxation times much longer than typical
electronic `hopping times'


  We analyze a simple textbook approach to nonlinear oscillators proposed
recently, disclose its errors, limitations and misconceptions and complete the
calculations that the authors failed to perform.


  On shopping websites, product images of low quality negatively affect
customer experience. Although there are plenty of work in detecting images with
different defects, few efforts have been dedicated to correct those defects at
scale. A major challenge is that there are thousands of product types and each
has specific defects, therefore building defect specific models is unscalable.
In this paper, we propose a unified Image-to-Image (I2I) translation model to
correct multiple defects across different product types. Our model leverages an
attention mechanism to hierarchically incorporate high-level defect groups and
specific defect types to guide the network to focus on defect-related image
regions. Evaluated on eight public datasets, our model reduces the Frechet
Inception Distance (FID) by 24.6% in average compared with MoNCE, the
state-of-the-art I2I method. Unlike public data, another practical challenge on
shopping websites is that some paired images are of low quality. Therefore we
design our model to be semi-paired by combining the L1 loss of paired data with
the cycle loss of unpaired data. Tested on a shopping website dataset to
correct three image defects, our model reduces (FID) by 63.2% in average
compared with WS-I2I, the state-of-the art semi-paired I2I method.


  In recent years, there has been considerable interest in estimating
conditional independence graphs in the high-dimensional setting. Most prior
work has assumed that the variables are multivariate Gaussian, or that the
conditional means of the variables are linear. Unfortunately, if these
assumptions are violated, then the resulting conditional independence estimates
can be inaccurate. We present a semi-parametric method, SpaCE JAM, which allows
the conditional means of the features to take on an arbitrary additive form. We
present an efficient algorithm for its computation, and prove that our
estimator is consistent. We also extend our method to estimation of directed
graphs with known causal ordering. Using simulated data, we show that SpaCE JAM
enjoys superior performance to existing methods when there are non-linear
relationships among the features, and is comparable to methods that assume
multivariate normality when the conditional means are linear. We illustrate our
method on a cell-signaling data set.


  A simplified model of periodic chiral beam-lattices containing local
resonators has been formulated to obtain a better understanding of the
influence of the chirality and of the dynamic characteristics of the local
resonators on the acoustic behavior. The simplified beam-lattices is made up of
a periodic array of rigid heavy rings, each one connected to the others through
elastic slender massless ligaments and containing an internal resonator made of
a rigid disk in a soft elastic annulus. The band structure and the occurrence
of low frequency band-gaps are analysed through a discrete Lagrangian model.
For both the hexa- and the tetrachiral lattice, two acoustic modes and four
optical modes are identified and the influence of the dynamic characteristics
of the resonator on those branches is analyzed together with some properties of
the band structure. By approximating the generalized displacements of the rings
of the discrete Lagrangian model as a continuum field and through an
application of the generalized macro-homogeneity condition, a generalized
micropolar equivalent continuum has been derived, together with the overall
equation of motion and the constitutive equation given in closed form. The
validity limits of the micropolar model with respect to the dispersion
functions are assessed by comparing the dispersion curves of this model in the
irreducible Brillouin domain with those obtained by the discrete model, which
are exact within the assumptions of the proposed simplified model.


  A Weyl semimetal with broken time-reversal symmetry has a minimum of two
species of Weyl fermions, distinguished by their opposite chirality, in a pair
of Weyl cones at opposite momenta $\pm K$ that are displaced in the direction
of the magnetization. Andreev reflection at the interface between a Weyl
semimetal in the normal state (N) and a superconductor (S) that pairs $\pm K$
must involve a switch of chirality, otherwise it is blocked. We show that this
"chirality blockade" suppresses the superconducting proximity effect when the
magnetization lies in the plane of the NS interface. A Zeeman field at the
interface can provide the necessary chirality switch and activate Andreev
reflection.


  We present the results of a study of the morphology of the dwarf galaxy
population in Abell 868, a rich, intermediate redshift (z=0.154) cluster which
has a galaxy luminosity function with a steep faint-end slope (alpha=-1.26 +/-
0.05). A statistical background subtraction method is employed to study the B-R
colour distribution of the cluster galaxies. This distribution suggests that
the galaxies contributing to the faint-end of the measured cluster LF can be
split into three populations: dIrrs with B-R<1.4; dEs with 1.4<B-R<2.5; and
contaminating background giant ellipticals (gEs) with B-R>2.5. The remvoal of
the contribution of the background gEs from the counts only marginally lessens
the faint-end slope (alpha=-1.22 +/- 0.16). However, the removal of the
contribution of the dIrrs from the counts produces a flat LF (alpha=-0.91 +/-
0.16). The dEs and the dIrrs have similar spatial distributions within the
cluster except that the dIrrs appear to be totally absent within a central
projected radius of about 0.2 Mpc (Ho=75 km/s /Mpc). The number density of both
dEs and dIrrs appear to fall off beyond a projected radius of about 0.35 Mpc.
We suggest that the dE and dIrr populations of A868 have been associated with
the cluster for similar timescales but that evolutionary processes such as
`galaxy harassment' tend to fade the dIrr galaxies while having much less
effect on the dE galaxies. The harassement would be expected to have the
greatest effect on dwarfs residing in the central parts of the cluster.


  In this paper, we study the homogenization of the third boundary value
problem for semilinear parabolic PDEs with rapidly oscillating periodic
coefficients in the weak sense. Our method is entirely probabilistic, and
builds upon the work of [28] and [3]. Backward stochastic differential
equations with singular coefficients play an important role in our approach.


  Mach's principle is surely one of those tantalizingly beautiful concepts in
physics which remain elusive. Though General Relativity (GR) was conceived in
the spirit of realizing it, the theory failed to fulfill this expectation.
  Here a study on the implications of imposing Mach's principle on GR with an
insight that spacetime has no independent existence without a material
background, is presented. This inclusion of the principle in GR turns out to be
unexpectedly rewarding. The resulting theory solves many mysteries and averts
lingering problems of the conventional forms of GR and cosmology.


  We study the production of the heavy W' and Z' bosons in the three site
higgsless model at the LHC. We focus on the s-channel production mode to
estimate the prospects for measuring their suppressed couplings to standard
model fermions.


  When sample data are governed by an unknown sequence of independent but
possibly non-identical distributions, the data-generating process (DGP) in
general cannot be perfectly identified from the data. For making decisions
facing such uncertainty, this paper presents a novel approach by studying how
the data can best be used to robustly improve decisions. That is, no matter
which DGP governs the uncertainty, one can make a better decision than without
using the data. I show that common inference methods, e.g., maximum likelihood
and Bayesian updating cannot achieve this goal. To address, I develop new
updating rules that lead to robustly better decisions either asymptotically
almost surely or in finite sample with a pre-specified probability. Especially,
they are easy to implement as are given by simple extensions of the standard
statistical procedures in the case where the possible DGPs are all independent
and identically distributed. Finally, I show that the new updating rules also
lead to more intuitive conclusions in existing economic models such as asset
pricing under ambiguity.