  We present the result of a survey of Monte Carlo simulations of globular
clusters hosting two generations of stars including a large (f_b=50%) fraction
of primordial binaries in both populations. The dynamical evolution of the two
stellar populations is followed for a Hubble time taking into account the
effect of the tidal field, two-body relaxation, stellar evolution and
three/four-bodies interactions. The fraction of surviving binaries, once
accounted for the observational bias and uncertainties, is compared with the
available radial velocity time-series performed in real globular clusters, and
it is used to constrain the initial spatial concentration of the second
generation. The fraction of second generation binaries appears to depend only
on the ratio between the total cluster mass and the initial size of the second
generation which determines the average velocity dispersion across the extent
of this stellar population. In spite of the various uncertainties, we find that
the observed fraction can be obtained only assuming a strong initial
concentration of the second generation (r_h,S~ 0.1 (M/10^6 M_s) pc). The
evolution of the first generation binary fraction is more sensitive to the
tidal field strength (with a non negligible effect of the cluster orbital
eccentricity) since the tidal field has a direct impact on the first generation
structural properties.


  The envelope theory is a simple technique to obtain approximate, but
reliable, solutions of many-body systems with identical particles. The accuracy
of this method is tested here for two systems in one dimension with pairwise
forces. The first one is the fermionic ground state of the analytical Calogero
model with linear forces supplemented by inverse-cube forces. The second one is
the ground state of up to 100 bosons interacting via a Gaussian potential. Good
bounds can be obtained depending on values of the model parameters.


  We devise the optimal form of Gaussian resource states enabling continuous
variable teleportation with maximal fidelity. We show that a nonclassical
optimal fidelity of $N$-user teleportation networks is {\it necessary and
sufficient} for $N$-party entangled Gaussian resources, yielding an estimator
of multipartite entanglement. This {\it entanglement of teleportation} is
equivalent to entanglement of formation in the two-user protocol, and to
localizable entanglement in the multi-user one. The continuous-variable tangle,
quantifying entanglement sharing in three-mode Gaussian states, is
operationally linked to the optimal fidelity of a tripartite teleportation
network.


  Limiting online data collection to the minimum required for specific purposes
is mandated by modern privacy legislation such as the General Data Protection
Regulation (GDPR) and the California Consumer Protection Act. This is
particularly true in online services where broad collection of personal
information represents an obvious concern for privacy. We challenge the view
that broad personal data collection is required to provide personalised
services. By first developing formal models of privacy and utility, we show how
users can obtain personalised content, while retaining an ability to plausibly
deny their interests in topics they regard as sensitive using a system of
proxy, group identities we call 3PS. Through extensive experiment on a
prototype implementation, using openly accessible data sources, we show that
3PS provides personalised content to individual users over 98% of the time in
our tests, while protecting plausible deniability effectively in the face of
worst-case threats from a variety of attack types.


  Adding right-handed neutrinos to the Standard Model is a natural and simple
extension and is well motivated on both the theoretical and the experimental
side. We extend the Standard Model by adding only one right-handed Majorana
neutrino and study the sensitivity of the Near Detector of the DUNE experiment
to the new physics parameters, namely the mixing parameters $|U_{e 4}|^2$ and
$|U_{\mu 4}|^2$ and the mass $m_N$. The study relies on searches of the
products of right-handed neutrino decays, which is possible thanks to an
extremely intense beam and a state-of-the-art detection technology. This type
of direct test is carried out with very few assumptions and in an
almost-completely model-independent way, providing thus a strong result. A
background analysis is also performed, simulating the detector performance to
particle identification. It is found that the existing bounds in the MeV-range
can be improved by one order of magnitude in different detection channels.


  Neural architecture search (NAS) has shown promising results discovering
models that are both accurate and fast. For NAS, training a one-shot model has
become a popular strategy to rank the relative quality of different
architectures (child models) using a single set of shared weights. However,
while one-shot model weights can effectively rank different network
architectures, the absolute accuracies from these shared weights are typically
far below those obtained from stand-alone training. To compensate, existing
methods assume that the weights must be retrained, finetuned, or otherwise
post-processed after the search is completed. These steps significantly
increase the compute requirements and complexity of the architecture search and
model deployment. In this work, we propose BigNAS, an approach that challenges
the conventional wisdom that post-processing of the weights is necessary to get
good prediction accuracies. Without extra retraining or post-processing steps,
we are able to train a single set of shared weights on ImageNet and use these
weights to obtain child models whose sizes range from 200 to 1000 MFLOPs. Our
discovered model family, BigNASModels, achieve top-1 accuracies ranging from
76.5% to 80.9%, surpassing state-of-the-art models in this range including
EfficientNets and Once-for-All networks without extra retraining or
post-processing. We present ablative study and analysis to further understand
the proposed BigNASModels.


  The absolute free energy -- or partition function, equivalently -- of a
molecule can be estimated computationally using a suitable reference system.
Here, we demonstrate a practical method for staging such calculations by
growing a molecule based on a series of fragments. Significant computer time is
saved by pre-calculating fragment configurations and interactions for re-use in
a variety of molecules. We employ such fragment libraries and interaction
tables for amino acids and capping groups to estimate free energies for small
peptides. Equilibrium ensembles for the molecules are generated at no
additional computational cost, and are used to check our results by comparison
to standard dynamics simulation.


  Using a first principles approach, we study the electron transport properties
of two molecules of length 2.5nm which are the building blocks for a new class
of molecular wires containing fluorenone units. We show that the presence of
side groups attached to these units leads to Fano resonances close to the Fermi
energy. As a consequence electron transport through the molecule can be
controlled either by chemically modifying the side group, or by changing the
conformation of the side group. This sensitivity, which is not present in
Breit-Wigner resonances, opens up new possibilities for novel single-molecule
sensors.


  In this talk I review recent advances on the structure of the meson and
baryon resonances which can be dynamically generated from the interaction of
mesons or mesons and baryons. Particular emphasis is put on results involving
vector mesons, which bring new light into the nature of some of the observed
higher mass mesons and baryons and make predictions for new states.


  An asymptotic solution of the thermodynamics of a BCS superconductor
containing spin 1/2 and 7/2 magnetic impurities, obtained recently in Ref. 1 is
exploited to derive the expressions for critical magnetic field
$H_{\mathrm{c}}(T)$ . The credibility of the resulting theoretical equations,
which depend on the magnetic coupling constant $g$ and impurity concentration
$c$, is verified on the experimental data for the following superconducting
alloys: LaCe, ThGd and SmRh$_{4}$B$_{4}$. Good quantitative agreement with
experimental data is found for sufficiently small values of $c$. The
discrepancies between theoretical and experimental values of
$H_{\mathrm{c}}(T)$ for larger values of $c$ in case of LaCe and ThGd are
reduced by introducing the concept of the effective temperature $\tilde{T}$,
which accounts for the Coulomb interactions between the electron gas and
impurity ions.
  At low temperatures, the critical magnetic field is found to increase with
decreasing temperature $T$. This enhancement of the critical magnetic field
provides evidence of the Jaccarino-Peter effect, which was experimentally
observed in the Kondo systems like LaCe, (La$_{1-x}$Ce$_{x}$)Al$_{2}$ and also
in the pseudoternary compounds, including Sn$_{1-x}$Eu$_{x}$Mo$_{6}$S$_{8}$,
Pb$_{1-x}$Eu$_{x}$Mo$_{6}$S$_{8}$ and La$_{1.2-x}$Eu$_{x}$Mo$_{6}$S$_{8}$.
  The effect of an external magnetic field ${\mathcal H}$ on a BCS
superconductor perturbed by magnetic impurities was also studied. On this
grounds, by analyzing the dependence of superconducting transition temperature
$T_{\mathrm{c}}$ on ${\mathcal H}$ of (La$_{1-x}$Ce$_{x}$)Al$_{2}$, we have
shown, that for certain parameter values, external magnetic field compensates
the destructive effect of magnetic impurities.


  Kubernetes is a container management system that has many automated
functionalities. Those functionalities are managed by configuring objects and
resources in the control plane. Since most objects change their state depending
on other objects' states, a change propagates to other objects in a chain. As
cluster availability is influenced by the time required for these cascading
changes, it is essential to make the propagations measurable and shed light on
the behavior of the Kubernetes control plane. However, it is not easy because
each object constantly monitors other objects' status and acts autonomously in
response to their changes to play its role. In this paper, we propose a
measurement system that outputs objects' change logs published from the API
server in the control plane and assists in analyzing the time of cascading
changes between objects by utilizing the relationships among resources. With a
practical change scenario, our system is confirmed that it can measure change
propagation times within a cascading change. Also, measurements on the system
itself showed it has a small CPU and memory footprint.


  Interface icons are prevalent in various digital applications. Due to limited
time and budgets, many designers rely on informal evaluation, which often
results in poor usability icons. In this paper, we propose a unique
human-in-the-loop framework that allows our target users, i.e., novice and
professional UI designers, to improve the usability of interface icons
efficiently. We formulate several usability criteria into a perceptual
usability function and enable users to iteratively revise an icon set with an
interactive design tool, EvIcon. We take a large-scale pre-trained joint
image-text embedding (CLIP) and fine-tune it to embed icon visuals with icon
tags in the same embedding space (IconCLIP). During the revision process, our
design tool provides two types of instant perceptual usability feedback. First,
we provide perceptual usability feedback modeled by deep learning models
trained on IconCLIP embeddings and crowdsourced perceptual ratings. Second, we
use the embedding space of IconCLIP to assist users in improving icons' visual
distinguishability among icons within the user-prepared icon set. To provide
the perceptual prediction, we compiled IconCEPT10K, the first large-scale
dataset of perceptual usability ratings over $10,000$ interface icons, by
conducting a crowdsourcing study. We demonstrated that our framework could
benefit UI designers' interface icon revision process with a wide range of
professional experience. Moreover, the interface icons designed using our
framework achieved better semantic distance and familiarity, verified by an
additional online user study.


  This paper proposes a bidirectional multibeam hybrid transmitarray (HTA)
employing a transmission polarization-rotating metasurface (TPRM). A novel
configuration is introduced to facilitate bidirectional beam scanning by
combining the transmitarray (TA) and folded-transmitarray (FTA). To accomplish
the reconfiguration of both unidirectional and bidirectional radiation states
in the +z, -z, and +/-z directions, a polarization switchable multi-feed array
(MFA) is placed at the focal plane between the TA and FTA, radiating
x-polarization, y-polarization, and 45-degree oblique polarization waves,
respectively. Meanwhile, the proposed antenna can achieve multibeam radiation
in the three aforementioned states by switching the polarization of the MFA. To
demonstrate the operating principle, a prototype has been designed, simulated,
and fabricated. The measured results agree well with the simulated results. The
simulated and measured results indicate that the proposed design can generate
reconfigurable multibeam in both forward and backward directions, either
separately or simultaneously. In the unidirectional states, forward and
backward beam scanning is achieved within an angular range of +/-30{\deg} and
+/-22{\deg}, respectively, with peak gains of 23.6 dBi and 23.1 dBi. A
simultaneous forward and backward beam scanning of +/-40{\deg} and +/-22{\deg}
is achieved in the hybrid radiation state, with peak gains of 19.4 dBi and 19.3
dBi, respectively. The proposed antenna array design offers several advantages,
including bidirectional low-loss beam scanning, a simple structure, low power
consumption, and a low profile.


  Alfven waves are considered as potential transporters of energy heating the
solar corona. We seek spectroscopic signatures of the Alfven waves in the
chromosphere occupied by a bright network element, investigating temporal
variations of the spectral width, intensity, Dopplershift, and the asymmetry of
the core of the Halpha spectral line observed by the tunable Lyot filter
installed on the Dutch Open Telescope. The spectral characteristics are derived
through the fitting of five intensity samples, separated from each other by
0.35 A, by a 4th-order polynomial. The bright network element displays the most
pronounced variations of the Dopplershift varying from 0 to 4 km/s about the
average of 1.5 km/s. This fact implies a persistent redshift of the Halpha core
with a redward asymmetry of about 0.5 km/s, suggesting an inverse-C bisector.
The variations of the core intensity up to +-10% and the core width up to +-5%
about the respective averages are much less pronounced, but still detectable.
The core intensity variations lag behind the Dopplershift variations about 2.1
min. The Halpha core width tends to correlate with the Dopplershift and
anticorrelate with the asymmetry, suggesting that more redshifted Halpha
profiles are wider and the broadening of the Halpha core is accompanied with a
change of the core asymmetry from redward to blueward. We also found a striking
anticorrelation between the core asymmetry and the Dopplershift, suggesting a
change of the core asymmetry from redward to blueward with an increasing
redshift of the Halpha core. The data and the applied analysis do not show
meaningful tracks of Alfven waves in the selected network element.


  We show that the size-sensitive packing lemma follows from a simple
modification of the standard proof, due to Haussler and simplified by Chazelle,
of the packing lemma.


  In this paper we consider the problem of embedding almost-spanning, bounded
degree graphs in a random graph. In particular, let $\Delta\geq 5$,
$\varepsilon > 0$ and let $H$ be a graph on $(1-\varepsilon)n$ vertices and
with maximum degree $\Delta$. We show that a random graph $G_{n,p}$ with high
probability contains a copy of $H$, provided that $p\gg
(n^{-1}\log^{1/\Delta}n)^{2/(\Delta+1)}$. Our assumption on $p$ is optimal up
to the $polylog$ factor. We note that this $polylog$ term matches the
conjectured threshold for the spanning case.


  For a given stationary max-stable random field $X(t),t\in Z^d$ the
corresponding generalised Pickands constant coincides with the classical
extremal index $\theta$ which always exists. In this contribution we discuss
necessary and sufficient conditions for $\theta$ to be 0, positive or equal to
1 and also show that $\theta$ is equal to the so-called block extremal index.
Further, we consider some general functional indices of $X$ and prove that for
a large class of functionals they coincide with $\theta$. Our study of
max-stable and stationary random fields is important since the formulas are
valid with obvious modifications for the candidate extremal index of
multivariate regularly varying random fields.


  We investigate correlations between galaxy age and environment in the Abell
901/2 supercluster for separate morphologies. Using COMBO-17 data, we define a
sample of 530 galaxies, complete at $M_V -5\log h<-18$ on an area of $3.5\times
3.5$ (Mpc/$h$)$^2$. We explore several age indicators including an
extinction-corrected residual from the colour-magnitude relation (CMR). As a
result, we find a clear trend of age with density for galaxies of all
morphologies that include a spheroidal component, in the sense that galaxies in
denser environments are older. This trend is not seen among Scd/Irr galaxies
since they all have young ages. However, the trend among the other types is
stronger for fainter galaxies. While we also see an expected age-morphology
relation, we find no evidence for a morphology-density relation at fixed age.


  (To appear in Theory and Practice of Logic Programming (TPLP).)
  The seaport of Gioia Tauro is the largest transshipment terminal of the
Mediterranean coast. A crucial management task for the companies operating in
the seaport is team building: the problem of properly allocating the available
personnel for serving the incoming ships. Teams have to be carefully arranged
in order to meet several constraints, such as allocation of the employees with
the appropriate skills, fair distribution of the working load, and turnover of
the heavy/dangerous roles. This makes team building a hard and expensive task
requiring several hours per day of manual preparation.
  In this paper we present a system based on Answer Set Programming (ASP) for
the automatic generation of the teams of employees in the seaport of Gioia
Tauro. The system is currently exploited in the Gioia Tauro seaport by ICO BLG,
a company specialized in automobile logistics.


  Digital data is a gold mine for modern journalism. However, datasets which
interest journalists are extremely heterogeneous, ranging from highly
structured (relational databases), semi-structured (JSON, XML, HTML), graphs
(e.g., RDF), and text. Journalists (and other classes of users lacking advanced
IT expertise, such as most non-governmental-organizations, or small public
administrations) need to be able to make sense of such heterogeneous corpora,
even if they lack the ability to define and deploy custom
extract-transform-load workflows, especially for dynamically varying sets of
data sources.
  We describe a complete approach for integrating dynamic sets of heterogeneous
datasets along the lines described above: the challenges we faced to make such
graphs useful, allow their integration to scale, and the solutions we proposed
for these problems. Our approach is implemented within the ConnectionLens
system; we validate it through a set of experiments.


  We consider co--rotational wave maps from (3+1) Minkowski space into the
three--sphere. This is an energy supercritical model which is known to exhibit
finite time blow up via self-similar solutions. The ground state self--similar
solution $f_0$ is known in closed form and based on numerics, it is supposed to
describe the generic blow up behavior of the system. We prove that the blow up
via $f_0$ is stable under the assumption that $f_0$ does not have unstable
modes. This condition is equivalent to a spectral assumption for a linear
second order ordinary differential operator. In other words, we reduce the
problem of stable blow up to a linear ODE spectral problem. Although we are
unable, at the moment, to verify the mode stability of $f_0$ rigorously, it is
known that possible unstable eigenvalues are confined to a certain compact
region in the complex plane. As a consequence, highly reliable numerical
techniques can be applied and all available results strongly suggest the
nonexistence of unstable modes, i.e., the assumed mode stability of $f_0$.


  In the framework of the ordinary non-relativistic quantum mechanics, it is
known that a quantum particle in a rapidly-oscillating bound potential with
vanishing time average can be scattered off or even trapped owing to the
phenomenon of dynamical (Kapitza) stabilization. A similar phenomenon occurs
for scattering and trapping of optical waves. Such a remarkable result stems
from the fact that, even though the particle is not able to follow the rapid
external oscillations of the potential, these are still able to affect the
average dynamics by means of an effective -albeit small- nonvanishing potential
contribution. Here we consider the scattering and dynamical stabilization
problem for matter or classical waves by a bound potential with oscillating ac
amplitude $f(t)$ in the framework of a non-Hermitian extension of the
Schr\"odinger equation, and predict that for a wide class of imaginary
amplitude modulations $f(t)$ possessing a one-sided Fourier spectrum the
oscillating potential is effectively canceled, i.e. it does not have any effect
to the particle dynamics, contrary to what happens in the Hermitian case


  Assessing the technical efficiency of a set of observations requires that the
associated data composed of inputs and outputs are perfectly known. If this is
not the case, then biased estimates will likely be obtained. Data Envelopment
Analysis (DEA) is one of the most extensively used mathematical models to
estimate efficiency. It constructs a piecewise linear frontier against which
all observations are compared. Since the frontier is empirically defined, any
deviation resulting from low data quality (imperfect knowledge of data or IKD)
may lead to efficiency under/overestimation. In this study, we model IKD and,
then, apply the so-called Hit \& Run procedure to randomly generate admissible
observations, following some prespecified probability density functions. Sets
used to model IKD limit the domain of data associated with each observation.
Any point belonging to that domain is a candidate to figure out as the
observation for efficiency assessment. Hence, this sampling procedure must run
a sizable number of times (infinite, in theory) in such a way that it populates
the whole sets. The DEA technique is used during the execution of each
iteration to estimate bootstrapped efficiency scores for each observation. We
use some scenarios to show that the proposed routine can outperform some of the
available alternatives. We also explain how efficiency estimations can be used
for statistical inference. An empirical case study based on the Portuguese
public hospitals database (2013-2016) was addressed using the proposed method.


  In this version we have corrected some minor errors in the tables, corrected
typos, and added a reference. We have also updated our comparison with earlier
workers. Figures are now included as uuencoded compressed tar files.


  Quantifying the uncertainty of predictions is a core problem in modern
statistics. Methods for predictive inference have been developed under a
variety of assumptions, often -- for instance, in standard conformal prediction
-- relying on the invariance of the distribution of the data under special
groups of transformations such as permutation groups. Moreover, many existing
methods for predictive inference aim to predict unobserved outcomes in
sequences of feature-outcome observations. Meanwhile, there is interest in
predictive inference under more general observation models (e.g., for partially
observed features) and for data satisfying more general distributional
symmetries (e.g., rotationally invariant or coordinate-independent observations
in physics). Here we propose SymmPI, a methodology for predictive inference
when data distributions have general group symmetries in arbitrary observation
models. Our methods leverage the novel notion of distributional equivariant
transformations, which process the data while preserving their distributional
invariances. We show that SymmPI has valid coverage under distributional
invariance and characterize its performance under distribution shift,
recovering recent results as special cases. We apply SymmPI to predict
unobserved values associated to vertices in a network, where the distribution
is unchanged under relabelings that keep the network structure unchanged. In
several simulations in a two-layer hierarchical model, and in an empirical data
analysis example, SymmPI performs favorably compared to existing methods.


  Motivated by previous observations that the usually applied $L_p$ norms
($p=1,2,\infty$) do not capture the perceptual quality of adversarial examples
in image classification, we propose to replace these norms with the structural
similarity index (SSIM) measure, which was developed originally to measure the
perceptual similarity of images. Through extensive experiments with
adversarially trained classifiers for MNIST and CIFAR-10, we demonstrate that
our SSIM-constrained adversarial attacks can break state-of-the-art
adversarially trained classifiers and achieve similar or larger success rate
than the elastic net attack, while consistently providing adversarial images of
better perceptual quality. Utilizing SSIM to automatically identify and
disallow adversarial images of low quality, we evaluate the performance of
several defense schemes in a perceptually much more meaningful way than was
done previously in the literature.


  We analyze a model proposed recently for the calculation of the energy of an
exciton in a quantum dot and show that the authors made a serious mistake in
the solution to the Schr\"{o}dinger equation.


  Any expanding homogeneous Ricci soliton (in particular any homogeneous
Einstein manifold of negative scalar curvature) can be obtained, up to
isometry, from a Lie subgroup of a nilpotent Iwasawa group $N$ whose induced
metric is a Ricci soliton. By nilpotent Iwasawa group we mean the nilpotent Lie
group $N$ of the Iwasawa decomposition associated with a symmetric space of
non-compact type. Motivated by this fact, in this paper we classify codimension
one Lie subgroups of any nilpotent Iwasawa group $N$ whose induced metric is a
Ricci soliton.


  By making use of a recently proposed framework for the inference of
thermodynamic irreversibility in bosonic quantum systems, we experimentally
measure and characterize the entropy production rates in the non-equilibrium
steady state of two different physical systems -- a micro-mechanical resonator
and a Bose-Einstein condensate -- each coupled to a high finesse cavity and
hence also subject to optical loss. Key features of our setups, such as cooling
of the mechanical resonator and signatures of a structural quantum phase
transition in the condensate are reflected in the entropy production rates. Our
work demonstrates the possibility to explore irreversibility in driven
mesoscopic quantum systems and paves the way to a systematic experimental
assessment of entropy production beyond the microscopic limit.


  We present a necessary and sufficient condition for a cubic polynomial to be
positive for all positive reals. We identify the set where the cubic polynomial
is nonnegative but not all positive for all positive reals, and explicitly give
the points where the cubic polynomial attains zero. We then reformulate a
necessary and sufficient condition for a quartic polynomial to be nonnegative
for all positive reals. From this, we derive a necessary and sufficient
condition for a quartic polynomial to be nonnegative and positive for all
reals. Our condition explicitly exhibits the scope and role of some
coefficients, and has strong geometrical meaning. In the interior of the
nonnegativity region for all reals, there is an appendix curve. The
discriminant is zero at the appendix, and positive in the other part of the
interior of the nonnegativity region. By using the Sturm sequences, we present
a necessary and sufficient condition for a quintic polynomial to be positive
and nonnegative for all positive reals. We show that for polynomials of a fixed
even degree higher than or equal to four, if they have no real roots, then
their discriminants take the same sign, which depends upon that degree only,
except on an appendix set of dimension lower by two, where the discriminants
attain zero.


  Our main objective is to compare the analytic properties of hydrodynamic
series with the stability and causality conditions applied to hydrodynamic
modes. Analyticity, in this context, implies that the hydrodynamic series
behaves as a univalent or single-valued function. Stability and causality
adhere to physical constraints where hydrodynamic modes neither exhibit
exponential growth nor travel faster than the speed of light. Through an
examination of various hydrodynamic models, such as the Muller-Israel-Stewart
(MIS) and the first-order hydro models like the BDNK
(Bemfica-Disconzi-Noronha-Kovtun) model, we observe no new restrictions
stemming from the analyticity limits in the shear channel of these models.
However, local univalence is maintained in the sound channel of these models
despite the global divergence of the hydrodynamic series. Notably, differences
in the sound equations between the MIS and BDNK models lead to distinct
analyticity limits. The MIS model's sound mode remains univalent at high
momenta within a specific transport range. Conversely, in the BDNK model, the
univalence of the sound mode extends to intermediate momenta across all stable
and causal regions. Generally, the convergence radius is independent of
univalence and the given dispersion relation predominantly influences their
correlation. For second-order frequency dispersions, the relationship is
precise, i.e. within the convergence radius, the hydro series demonstrates
univalence. However, with higher-order dispersions, the hydro series is locally
univalent within certain transport regions, which may fall within or outside
the stable and causal zones.


  We describe the idempotent Fourier multipliers that act contractively on
$H^p$ spaces of the $d$-dimensional torus $\mathbb{T}^d$ for $d\geq 1$ and
$1\leq p \leq \infty$. When $p$ is not an even integer, such multipliers are
just restrictions of contractive idempotent multipliers on $L^p$ spaces, which
in turn can be described by suitably combining results of Rudin and And\^{o}.
When $p=2(n+1)$, with $n$ a positive integer, contractivity depends in an
interesting geometric way on $n$, $d$, and the dimension of the set of
frequencies associated with the multiplier. Our results allow us to construct a
linear operator that is densely defined on $H^p(\mathbb{T}^\infty)$ for every
$1 \leq p \leq \infty$ and that extends to a bounded operator if and only if
$p=2,4,\ldots,2(n+1)$.


  A new type of charm pentaquark $P_{cs}$ with quark content $c\bar{c}uds$ in
light-flavor singlet state is studied in the quark model. This state is
analogous to the $P_{c}$ with $c\bar{c}uud$ in light-flavor octet, which was
observed in LHC in 2015. Considering various combinations of color, spin and
light flavor as internal quantum numbers in $P_{cs}$, we investigate the mass
ordering of the $P_{cs}$'s by adopting both the one-gluon exchange interaction
and the instanton-induced interaction in the quark model. The most stable
configuration of $P_{cs}$ is identified to be total spin $1/2$ in which the
$c\bar{c}$ is combined to be color octet and spin $1$, while the $uds$ cluster
is in a color octet state. The other color octet configurations, the total spin
$1/2$ state with the $c\bar{c}$ spin 0 and the state with total spin $3/2$ and
$c\bar{c}$ spin 1, are found as excited states. We also discuss possible decay
modes of these charm pentaquarks.


  This paper studies the complexity of classical modal logics and of their
extension with fixed-point operators, using translations to transfer results
across logics. In particular, we show several complexity results for
multi-agent logics via translations to and from the $\mu$-calculus and modal
logic, which allow us to transfer known upper and lower bounds. We also use
these translations to introduce terminating and non-terminating tableau systems
for the logics we study, based on Kozen's tableau for the $\mu$-calculus and
the one of Fitting and Massacci for modal logic. Finally, we describe these
tableaux with $\mu$-calculus formulas, thus reducing the satisfiability of each
of these logics to the satisfiability of the $\mu$-calculus, resulting in a
general 2EXP upper bound for satisfiability testing.


  Fluorescence microscopy allows for a detailed inspection of cells, cellular
networks, and anatomical landmarks by staining with a variety of
carefully-selected markers visualized as color channels. Quantitative
characterization of structures in acquired images often relies on automatic
image analysis methods. Despite the success of deep learning methods in other
vision applications, their potential for fluorescence image analysis remains
underexploited. One reason lies in the considerable workload required to train
accurate models, which are normally specific for a given combination of
markers, and therefore applicable to a very restricted number of experimental
settings. We herein propose Marker Sampling and Excite, a neural network
approach with a modality sampling strategy and a novel attention module that
together enable (i) flexible training with heterogeneous datasets with
combinations of markers and (ii) successful utility of learned models on
arbitrary subsets of markers prospectively. We show that our single neural
network solution performs comparably to an upper bound scenario where an
ensemble of many networks is na\"ively trained for each possible marker
combination separately. In addition, we demonstrate the feasibility of this
framework in high-throughput biological analysis by revising a recent
quantitative characterization of bone marrow vasculature in 3D confocal
microscopy datasets and further confirm the validity of our approach on an
additional, significantly different dataset of microvessels in fetal liver
tissues. Not only can our work substantially ameliorate the use of deep
learning in fluorescence microscopy analysis, but it can also be utilized in
other fields with incomplete data acquisitions and missing modalities.


  The aim of this note is to give a simpler proof of a result of Avsec, which
states that $q$-Gaussian algebras have the complete metric approximation
property.


  The nature of fast radio bursts (FRBs) is currently unknown. Repeating FRBs
offer better opportunity than non-repeating FRBs since their simultaneous
multi-wavelength counterparts might be identified. The magnetar flare model of
FRBs is one of the most promising models which predicts high energy emission in
addition to radio burst emission. To investigate such a possibility, we have
searched for simultaneous and quasi-simultaneous short-term hard X-ray bursts
in all the Swift/BAT event mode data which covered the periods when fast radio
bursts were reported detections in the repeating FRB 121102, by making use of
BAT's arcmin level spacial resolution and wide field-of-view. We did not find
any significant hard X-ray bursts which occurred simultaneously to those radio
bursts. We also investigated potential short X-ray bursts occurred
quasi-simultaneous with those radio bursts (occurrence time differs in the
range from hundreds of seconds to thousands of seconds) and concluded that even
the best candidates are consistent with background fluctuations. Therefore our
investigation concluded that there were no hard X-ray bursts detectable with
Swift/BAT which occurred simultaneously or quasi-simultaneously with those fast
radio bursts in the repeating FRB 121102.


  Let L denote the space of Lagrangians Hamiltonian isotopic to the standard
Lagrangian in the unit ball in Euclidean space. We prove that the Lagrangian
Hofer distance on L is unbounded.


  IllinoisSL is a Java library for learning structured prediction models. It
supports structured Support Vector Machines and structured Perceptron. The
library consists of a core learning module and several applications, which can
be executed from command-lines. Documentation is provided to guide users. In
Comparison to other structured learning libraries, IllinoisSL is efficient,
general, and easy to use.


  The class of totally balanced games is a class of transferable-utility
coalitional games providing important models of cooperative behavior used in
mathematical economics. They coincide with market games of Shapley and Shubik
and every totally balanced game is also representable as the minimum of a
finite set of additive games. In this paper we characterize the polyhedral cone
of totally balanced games by describing its facets. Our main result is that
there is a correspondence between facet-defining inequalities for the cone and
the class of special balanced systems of coalitions, the so-called irreducible
min-balanced systems. Our method is based on refining the notion of
balancedness introduced by Shapley. We also formulate a conjecture about what
are the facets of the cone of exact games, which addresses an open problem
appearing in the literature.


  We investigate the dynamics of quantum correlations (QC) under the effects of
reservoir memory, as a resource for quantum information and computation tasks.
Quantum correlations of two-qubit systems are used for implementing quantum
teleportation successfully, and for investigating how teleportation fidelity,
violation of Bell-CHSH inequality, quantum steering and entanglement are
connected with each other under the influence of noisy environments. Both
Markovian and non-Markovian channels are considered, and it is shown that the
decay and revival of correlations follow the hierarchy of quantum correlations
in the state space. Noise tolerance of quantum correlations are checked for
different types of unital and non-unital quantum channels, with and without
memory. The quantum speed limit time $(\tau_{QSL})$ is investigated from the
perspective of memory of quantum noise, and the corresponding dynamics is used
to analyze the evolution of quantum correlations. We establish the connection
between information backflow, quantum speed limit time and dynamics of quantum
correlations for non-Markovian quantum channels.


  The temperature dependence of BGO coupled with photomultiplier tube R5610A-01
was studied in the range of -30{\deg}C~30{\deg}C. The temperature coefficient
of the BGO and R5610A in whole was tested to be -1.82%. And the temperature
coefficient of the gain of the R5610A is -0.44% which was tested in the same
situation using a blue LED. Thus the temperature coefficient of BGO's light
yield can be evaluated as -1.38%.


  We show that every transformation is disjoint from almost every interval
exchange transformation (IET), answering a question of Bufetov. In particular,
we prove that almost every pair of IETs is disjoint. It follows that the
product of almost every pair is uniquely ergodic. A key step in the proof is
showing that any sequence of density 1 contains a rigidity sequence for almost
every IET, strengthening a result of Veech.


  The "dyadosphere" (from the Greek word "duas-duados" for pairs) is here
defined as the region outside the horizon of a black hole endowed with an
electromagnetic field (abbreviated to EMBH for "electromagnetic black hole")
where the electromagnetic field exceeds the critical value, predicted by
Heisenberg and Euler for electron-positron pair production. In a very short
time, a very large number of pairs is created there. I give limits on the EMBH
parameters leading to a Dyadosphere for 10 solar mass and 100000 solar mass
EMBH's, and give as well the pair densities as functions of the radial
coordinate. These data give the initial conditions for the analysis of an
enormous pair-electromagnetic-pulse or "PEM-pulse" which naturally leads to
relativistic expansion. Basic energy requirements for gamma ray bursts (GRB),
including GRB971214 recently observed at z=3.4, can be accounted for by
processes occurring in the dyadosphere.


  This paper comments on the published work dealing with robustness and
regularization of support vector machines (Journal of Machine Learning
Research, vol. 10, pp. 1485-1510, 2009) [arXiv:0803.3490] by H. Xu, etc. They
proposed a theorem to show that it is possible to relate robustness in the
feature space and robustness in the sample space directly. In this paper, we
propose a counter example that rejects their theorem.


  Timely status updates are crucial to enabling applications in massive
Internet of Things (IoT). This paper measures the data-freshness performance of
a status update system with an energy harvesting transmitter, considering the
randomness in information generation, transmission and energy harvesting. The
performance is evaluated by a non-linear function of age of information (AoI)
that is defined as the time elapsed since the generation of the most up-to-date
status information at the receiver. The system is formulated as two queues with
status packet generation and energy arrivals both assumed to be Poisson
processes. With negligible service time, both First-Come-First-Served (FCFS)
and Last-Come-First-Served (LCFS) disciplines for arbitrary buffer and battery
capacities are considered, and a method for calculating the average penalty
with non-linear penalty functions is proposed. The average AoI, the average
penalty under exponential penalty function, and AoI's threshold violation
probability are obtained in closed form. When the service time is assumed to
follow exponential distribution, matrix geometric method is used to obtain the
average peak AoI. The results illustrate that under the FCFS discipline, the
status update frequency needs to be carefully chosen according to the service
rate and energy arrival rate in order to minimize the average penalty.


  In this paper, we are interested in memoryless computation, a modern paradigm
to compute functions which generalises the famous XOR swap algorithm to
exchange the contents of two variables without using a buffer. This uses a
combinatorial framework for procedural programming languages, where programs
are only allowed to update one variable at a time. We first consider programs
which do not have any memory. We prove that any function of $n$ variables can
be computed this way in only $4n-3$ variable updates. We then derive the exact
number of instructions required to compute any manipulation of variables. This
shows that combining variables, instead of simply moving them around, not only
allows for memoryless programs, but also yields shorter programs. Second, we
show that allowing programs to use memory is also incorporated in the
memoryless computation framework. We then quantify the gains obtained by using
memory: this leads to shorter programs and allows us to use only binary
instructions, which is not sufficient in general when no memory is used.


  Factor graphs have recently gained increasing attention as a unified
framework for representing and constructing algorithms for signal processing,
estimation, and control. One capability that does not seem to be well explored
within the factor graph tool kit is the ability to handle deterministic
nonlinear transformations, such as those occurring in nonlinear filtering and
smoothing problems, using tabulated message passing rules. In this
contribution, we provide general forward (filtering) and backward (smoothing)
approximate Gaussian message passing rules for deterministic nonlinear
transformation nodes in arbitrary factor graphs fulfilling a Markov property,
based on numerical quadrature procedures for the forward pass and a
Rauch-Tung-Striebel-type approximation of the backward pass. These message
passing rules can be employed for deriving many algorithms for solving
nonlinear problems using factor graphs, as is illustrated by the proposition of
a nonlinear modified Bryson-Frazier (MBF) smoother based on the presented
message passing rules.


  Gapless Luttinger liquid is conventionally viewed as topologically trivial,
unless it hosts degenerate ground states and or entanglement spectrum, which
necessitates partial bulk degree of freedom to be gapped out. Here we predict
an emergent gapless topological Luttinger liquid which is beyond the
conventional scenarios and is characterized by the nontrivial many-body bulk
spin texture, and propose feasible scheme for experimental observation. We
consider a one-dimensional spin-orbit coupled Fermi-Hubbard model with
fractional filling, whose low-energy physics is effectively described by a
spinless Luttinger liquid and is trivial in the conventional characterization.
We show that, as being tuned by the filling factor and interaction strength,
the many-body ground state may exhibit nontrivial winding in its bulk spin
texture in the projected momentum space, manifesting an emergent topological
phase. A topological transition occurs when the projected spin-state at a high
symmetry momentum becomes fully mixed one, resulting from competing processes
of particle scattering to the lower and higher subbands, for which the spin
texture at such momentum point is ill-defined, but the Luttinger liquid keeps
gapless through the transition. Surprisingly, at relatively small filling the
Luttinger liquid remains topologically nontrivial even at infinitely strong
interaction. The results can be generalized to finite temperature which
facilitates the real experimental detection. This work shows a novel gapless
topological Luttinger liquid whose characterization is beyond the low-energy
effective theory, and can be verified based on current experiments.


  Cardiac indices estimation is of great importance during identification and
diagnosis of cardiac disease in clinical routine. However, estimation of
multitype cardiac indices with consistently reliable and high accuracy is still
a great challenge due to the high variability of cardiac structures and
complexity of temporal dynamics in cardiac MR sequences. While efforts have
been devoted into cardiac volumes estimation through feature engineering
followed by a independent regression model, these methods suffer from the
vulnerable feature representation and incompatible regression model. In this
paper, we propose a semi-automated method for multitype cardiac indices
estimation. After manual labelling of two landmarks for ROI cropping, an
integrated deep neural network Indices-Net is designed to jointly learn the
representation and regression models. It comprises two tightly-coupled
networks: a deep convolution autoencoder (DCAE) for cardiac image
representation, and a multiple output convolution neural network (CNN) for
indices regression. Joint learning of the two networks effectively enhances the
expressiveness of image representation with respect to cardiac indices, and the
compatibility between image representation and indices regression, thus leading
to accurate and reliable estimations for all the cardiac indices.
  When applied with five-fold cross validation on MR images of 145 subjects,
Indices-Net achieves consistently low estimation error for LV wall thicknesses
(1.44$\pm$0.71mm) and areas of cavity and myocardium (204$\pm$133mm$^2$). It
outperforms, with significant error reductions, segmentation method (55.1% and
17.4%) and two-phase direct volume-only methods (12.7% and 14.6%) for wall
thicknesses and areas, respectively. These advantages endow the proposed method
a great potential in clinical cardiac function assessment.


  Here we update the predictions for lepton flavour violating tau and muon
decays, $l_j \to l_i \gamma$, $l_j \to 3 l_i$, and $\mu-e$ conversion in
nuclei. We work within a SUSY-seesaw context where the particle content of the
Minimal Supersymmetric Standard Model is extended by three right handed
neutrinos plus their corresponding SUSY partners, and where a seesaw mechanism
for neutrino mass generation is implemented. Two different scenarios with
either universal or non-universal soft supersymmetry breaking Higgs masses at
the gauge coupling unification scale are considered. After comparing the
predictions with present experimental bounds and future sensitivities, the most
promising processes are particularly emphasised.


  The photon blockade (PB) effect in emitter-cavity systems depends on the
anharmonicity of the ladder of dressed energy eigenstates. The recent
developments in color center photonics are leading toward experimental
demonstrations of multi-emitter-cavity solid-state systems with an expanded set
of energy levels compared to the traditionally studied single-emitter systems.
We focus on the case of N = 2 nonidentical quasi-atoms strongly coupled to a
nanocavity in the bad cavity regime (with parameters within reach of the color
center systems), and discover three PB mechanisms: polaritonic, subradiant and
unconventional. The polaritonic PB, which is the conventional mechanism studied
in single-emitter-cavity systems, also occurs at the polariton frequencies in
multi-emitter systems. The subradiant PB is a new interference effect owing to
the inhomogeneous broadening of the emitters which results in a purer and a
more robust single photon emission than the polaritonic PB. The unconventional
PB in the modeled system corresponds to the suppression of the single- and
two-photon correlation statistics and the enhancement of the three-photon
correlation statistic. Using the effective Hamiltonian approach, we unravel the
origin and the time-domain evolution of these phenomena.


  This note is a synthesis of my reflexions on some questions that have emerged
during the MATRIX event "Recent Trends on Nonlinear PDEs of Elliptic and
Parabolic Type" concerning the qualitative properties of solutions to some non
local reaction-diffusion equations of the form L[u](x) + f (u(x)) = 0, for x
$\in$ R n \ K, where K $\subset$ R N is a bounded smooth compact "obstacle", L
is non local operator and f is a bistable nonlinearity. When K is convex and
the nonlocal operator L is a continuous operator of convolution type then some
Liouville-type results for solutions satisfying some asymptotic limiting
conditions at infinity have been recently established by Brasseur, Coville,
Hamel and Valdinoci [4]. Here, we show that for a bounded smooth convex
obstacle K, similar Liouville type results hold true when the operator L is the
regional s-fractional Laplacian.


  In this paper, we propose a definition of Neron models of arbitrary Deligne
1-motives over Dedekind schemes, extending Neron models of semi-abelian
varieties. The key property of our Neron models is that they satisfy a
generalization of Grothendieck's duality conjecture in SGA 7 when the residue
fields of the base scheme at closed points are perfect. The assumption on the
residue fields is unnecessary for the class of 1-motives with semistable
reduction everywhere. In general, this duality holds after inverting the
residual characteristics. The definition of Neron models involves careful
treatment of ramification of lattice parts and its interaction with
semi-abelian parts. This work is a complement to Grothendieck's philosophy on
Neron models of motives of arbitrary weights.


  Let $X$ be a K3 surface and $L$ be an ample line bundle on it. In this
article we will give an alternative and elementary proof of Lelli Chiesa's
Theorem in the case of $r= 2$. More precisely we will prove that that under
certain condition the second co-ordinate of the gonality sequence is constant
along the smooth curves in the linear system $|L|$. Using Lelli Chiesa's
theorem for $r \ge 3$ we also extend Lelli Chiesa's Theorem in the case of $r=
2$ in weaker condition.


  We propose a self-contained description of Vasiliev higher-spin theories with
the emphasis on nonlinear equations. The main sections are supplemented with
some additional material, including introduction to gravity as a gauge theory;
the review of the Fronsdal formulation of free higher-spin fields; Young
diagrams and tensors as well as sections with advanced topics. The shortest
route to Vasiliev equations covers 40 pages.
  The general discussion is dimension independent, while the essence of the
Vasiliev formulation is discussed on the base of the four-dimensional
higher-spin theory. Three-dimensional and $d$-dimensional higher-spin theories
follow the same logic.


  This paper presents an approach to model features and function nets of
automotive systems comprehensively. In order to bridge the gap between feature
requirements and function nets, we describe an approach to describe both using
a SysML-based notation. If requirements on the automotive system are changed by
several developers responsible for different features, it is important for
developers to have a good overview and understanding of the functions affected.
We show that this can be comprehensively modeled using so called "feature
views". In order to validate these views against the complete function nets,
consistency checks are provided.


  We conduct a study of the aliased spectral densities of Mat\'ern covariance
functions on a regular grid of points, providing clarity on the properties of a
popular approximation based on stochastic partial differential equations; while
others have shown that it can approximate the covariance function well, we find
that it assigns too much power at high frequencies and does not provide
increasingly accurate approximations to the inverse as the grid spacing goes to
zero, except in the one-dimensional exponential covariance case. We provide
numerical results to support our theory, and in a simulation study, we
investigate the implications for parameter estimation, finding that the SPDE
approximation tends to overestimate spatial range parameters.


  The three-dimensional nonlinear dynamics of an electron gas in a
semiconductor quantum well is analyzed in terms of a self-consistent fluid
formulation and a variational approach. Assuming a time-dependent localized
profile for the fluid density and appropriated spatial dependences of the
scalar potential and fluid velocity, a set of ordinary differential equations
is derived. In the radially symmetric case, the prominent features of the
associated breathing mode are characterized.


  We investigate the spatial distribution of the baryonic and non-baryonic mass
components in a sample of 66 virialized systems. We have used X-ray
measurements to determine the deprojected temperature and density structure of
the intergalactic medium and have employed these to map the underlying
gravitational potential. In addition, we have measured the deprojected spatial
distribution of galaxy luminosity for a subset of this sample, spanning over 2
decades in mass. With this combined X-ray/optical study we examine the scaling
properties of the baryons and address the issue of mass-to-light (M/L) ratio in
groups and clusters of galaxies. We measure a median mass-to-light ratio of 224
h70 M/L (solar) in the rest frame B_j band, in good agreement with other
measurements based on X-ray determined masses. There is no trend in M/L with
X-ray temperature and no significant trend for mass to increase faster than
luminosity: M \propto \L_{B,j}^{1.08 +/- 0.12}. This implied lack of
significant variation in star formation efficiency suggests that gas cooling
cannot be greatly enhanced in groups, unless it drops out to form baryonic dark
matter. Correspondingly, our results indicate that non-gravitational heating
must have played a significant role in establishing the observed departure from
self-similarity in low mass systems. The median baryon fraction for our sample
is 0.162 h70^{-3/2}, which allows us to place an upper limit on the
cosmological matter density, Omega_m <= 0.27 h70^{-1}, in good agreement with
the latest results from WMAP. We find evidence of a systematic trend towards
higher central density concentration in the coolest haloes, indicative of an
early formation epoch and consistent with hierarchical formation models.


  A type-II superconductor survives in an external magnetic field by admitting
an Abrikosov lattice of quantized vortices. This is an imprint of the
Aharonov-Bohm effect created by the Abelian U(1) gauge field. The simplest
non-Abelian analogue of such a gauge field, which belongs to the SU(2) symmetry
group, can be found in topological insulators. Here we discover a
superconducting ground state with a lattice of SU(2) vortices in a simple
two-dimensional model that presents an SU(2) "magnetic" field (invariant under
time-reversal) to attractively interacting fermions. The model directly
captures the correlated topological insulator quantum well, and approximates
one channel for instabilities on the Kondo topological insulator surface. Due
to its simplicity, the model might become amenable to cold atom simulations in
the foreseeable future. The vitality of low-energy vortex states born out of
SU(2) "magnetic" fields is promising for the creation of incompressible vortex
liquids with non-Abelian fractional excitations.


  A new class of solutions for Einstein's field equations representing a static
spherically symmetric anisotropic distribution of matter is obtained on the
background of pseudo-spheroidal spacetime. We have prescribed the bounds of the
model parameters $ k $ and $ p_0 $ on the basis of the elementary criteria for
physical acceptability, viz., regularity, stability and energy conditions. By
taking the values of model parameters from the prescribed bounds, we have shown
that our model is compatible with the observational data of a wide variety of
compact stars like 4U 1820-30, PSR J1903+327, 4U 1608-52, Vela X-1, PSR
J1614-2230, SMC X-4 and Cen X-3.


  Saliency Map, the gradient of the score function with respect to the input,
is the most basic technique for interpreting deep neural network decisions.
However, saliency maps are often visually noisy. Although several hypotheses
were proposed to account for this phenomenon, there are few works that provide
rigorous analyses of noisy saliency maps. In this paper, we firstly propose a
new hypothesis that noise may occur in saliency maps when irrelevant features
pass through ReLU activation functions. Then, we propose Rectified Gradient, a
method that alleviates this problem through layer-wise thresholding during
backpropagation. Experiments with neural networks trained on CIFAR-10 and
ImageNet showed effectiveness of our method and its superiority to other
attribution methods.


  A b-coloring of a graph is a proper coloring such that every color class
contains a vertex that is adjacent to all other color classes. The b-chromatic
number of a graph G, denoted by \chi_b(G), is the maximum number t such that G
admits a b-coloring with t colors. A graph G is called b-continuous if it
admits a b-coloring with t colors, for every t = \chi(G),\ldots,\chi_b(G), and
b-monotonic if \chi_b(H_1) \geq \chi_b(H_2) for every induced subgraph H_1 of
G, and every induced subgraph H_2 of H_1.
  We investigate the b-chromatic number of graphs with stability number two.
These are exactly the complements of triangle-free graphs, thus including all
complements of bipartite graphs. The main results of this work are the
following:
  - We characterize the b-colorings of a graph with stability number two in
terms of matchings with no augmenting paths of length one or three. We derive
that graphs with stability number two are b-continuous and b-monotonic.
  - We prove that it is NP-complete to decide whether the b-chromatic number of
co-bipartite graph is at most a given threshold.
  - We describe a polynomial time dynamic programming algorithm to compute the
b-chromatic number of co-trees.
  - Extending several previous results, we show that there is a polynomial time
dynamic programming algorithm for computing the b-chromatic number of
tree-cographs. Moreover, we show that tree-cographs are b-continuous and
b-monotonic.


  We derive an expression for the superfluid density of a uniform two-component
Fermi gas through the BCS-BEC crossover in terms of the thermodynamic potential
in the presence of an imposed superfluid flow. Treating the pairing
fluctuations in a Gaussian approximation following the approach of Nozi\`eres
and Schmitt-Rink, we use this definition of $\rho_s$ to obtain an explicit
result which is valid at finite temperatures and over the full BCS-BEC
crossover. It is crucial that the BCS gap $\Delta$, the chemical potential
$\mu$, and $\rho_s$ all include the effect of fluctuations at the same level in
a self-consistent manner. We show that the normal fluid density $\rho_n \equiv
n - \rho_s$ naturally separates into a sum of contributions from Fermi BCS
quasiparticles ($\rho^F_{n}$) and Bose collective modes ($\rho^B_{n}$). The
expression for $\rho^F_{n}$ is just Landau's formula for a BCS Fermi superfluid
but now calculated over the BCS-BEC crossover. The expression for the Bose
contribution $\rho^B_{n}$ is more complicated and only reduces to Landau's
formula for a Bose superfluid in the extreme BEC limit, where all the fermions
have formed stable Bose pairs and the Bogoliubov excitations of the associated
molecular Bose condensate are undamped. In a companion paper, we present
numerical calculations of $\rho_s$ using an expression equivalent to the one
derived in this paper, over the BCS-BEC crossover, including unitarity, and at
finite temperatures.


  The water snowline in circumstellar disks is a crucial component in planet
formation, but direct observational constraints on its location remain sparse
due to the difficulty of observing water in both young embedded and mature
protoplanetary disks. Chemical imaging provides an alternative route to locate
the snowline, and HCO$^+$ isotopologues have been shown to be good tracers in
protostellar envelopes and Herbig disks. Here we present
$\sim$0.5$^{\prime\prime}$ resolution ($\sim$35 au radius) Atacama Large
Millimeter/submillimeter Array (ALMA) observations of HCO$^+$ $J=4-3$ and
H$^{13}$CO$^+$ $J=3-2$ toward the young (Class 0/I) disk L1527 IRS. Using a
source-specific physical model with the midplane snowline at 3.4 au and a small
chemical network, we are able to reproduce the HCO$^+$ and H$^{13}$CO$^+$
emission, but for HCO$^+$ only when the cosmic ray ionization rate is lowered
to $10^{-18}$ s$^{-1}$. Even though the observations are not sensitive to the
expected HCO$^+$ abundance drop across the snowline, the reduction in HCO$^+$
above the snow surface and the global temperature structure allow us to
constrain a snowline location between 1.8 and 4.1 au. Deep observations are
required to eliminate the envelope contribution to the emission and to derive
more stringent constraints on the snowline location. Locating the snowline in
young disks directly with observations of H$_2$O isotopologues may therefore
still be an alternative option. With a direct snowline measurement, HCO$^+$
will be able to provide constraints on the ionization rate.


  The article discusses distributed gradient-descent algorithms for computing
local and global minima in nonconvex optimization. For local optimization, we
focus on distributed stochastic gradient descent (D-SGD)--a simple
network-based variant of classical SGD. We discuss local minima convergence
guarantees and explore the simple but critical role of the stable-manifold
theorem in analyzing saddle-point avoidance. For global optimization, we
discuss annealing-based methods in which slowly decaying noise is added to
D-SGD. Conditions are discussed under which convergence to global minima is
guaranteed. Numerical examples illustrate the key concepts in the paper.


  The Planet Formation Imager (PFI) Project is dedicated to defining a
next-generation facility that can answer fundamental questions about how
planets form, including detection of young giant exoplanets and their
circumplanetary disks. The proposed expansive design for a 12-element array of
8m class telescopes with >1.2 km baselines would indeed revolutionize our
understanding of planet formation and is technically achievable, albeit at a
high cost. It has been 10 years since this conceptual design process began and
we give an overview of the status of the PFI project. We also review how a
scaled back PFI with fewer large telescopes could answer a range of compelling
science questions, including in planet formation and as well as totally
different astrophysics areas. New opportunities make a space-based PFI more
feasible now and we give a brief overview of new efforts that could also pave
the way for the Large Interferometer For Exoplanets (LIFE) space mission.


  The quite low Higgs particle mass makes it natural for the next high energy
facility to be a circular e+e- Higgs factory and, after that, a next-generation
p,p collider in the same tunnel. Surveying the luminosity-limiting phenomena of
synchrotron radiation power loss, beam-beam interaction limitations, and
beamstrahlung, scaling laws are established that fix all parameters of the
Higgs factory, as functions of assumed radius $r$, and RF power $P$. at least
to a first approximation. Historically the accelerator formalisms of electron
and hadron rings have been distinguished largely by the importance of
synchrotron radiation for electrons, and its unimportance for protons. While
electron beams equilibrate within seconds, proton beam distributions have
survived largely intact for extended periods. For future hadron colliders, this
distinction will no longer be valid. This will have a large impact on the
design of the future FCC-pp proton collider whose parameters can be
extrapolated using formulas previously applicable only to electron rings. The
most important scaling law has the luminosity depending on $r$ and $P_{\rm rf}$
only as a function of their product $rP$. This relation simplifies choosing a
tunnel radius that is optimal for both Higgs factory and p,p collider while
(almost) minimizing the initial cost---by increasing $r$ and decreasing $P$
proportionally, the tunnel circumference can be increased (as required for p,p)
without significant increase in Higgs factory cost.


  Nitrate is an important pollutant in drinking water worldwide, and a number
of methods exist for the removal of nitrate from water including ion exchange
and reverse osmosis. However, these approaches suffer from a variety of
disadvantages including requirements for supply and disposal of brine used for
regeneration in ion exchange and low water recovery ratio for reverse osmosis.
Here, we demonstrate the use of high surface area activated carbon electrodes
functionalized with moieties having high affinity for adsorption of nitrate
from aqueous solution, such as those used in ion exchange. Adsorption of
surfactant molecules having a quaternary amine ionic group to the activated
carbon surfaces provides functionalization of the surfaces without complex
chemistries. The functionalized electrodes have adsorption capacities of about
80 mg NaNO$_3$ per gram of activated carbon material. Unlike a traditional ion
exchanger, the functionalized surfaces can be repeatedly regenerated by the
application of an electrostatic potential which displaces the bound NO$_3^-$
while leaving an excess of electronic charge on the electrode. The cell is
completed by an inert counter electrode where Faradaic reactions occur during
regeneration. Up to approximately 40% of the initial capacity of the electrode
is accessible following electrical regeneration.


  A phenomenological theory of rigid and saturated ferromagnetic conductors is
constructed from a four-continuum model consisting of a rigid lattice
continuum, a bound charge continuum for polarization, a circulating current
continuum for magnetization, and a free charge continuum for electrical
conduction. The basic laws of physics are applied to the four continua. Thermal
couplings and the related dissipative effects are also included. The theory
includes the Landau-Lifshitz-Gilbert equation as one of a system of
simultaneous equations.


  Using two-dimensional simulations, we numerically explore the dependences of
Kelvin-Helmholtz instability upon various physical parameters, including
viscosity, width of sheared layer, flow speed, and magnetic field strength. In
most cases, a multi-vortex phase exists between the initial growth phase and
final single-vortex phase. The parametric study shows that the evolutionary
properties, such as phase duration and vortex dynamics, are generally sensitive
to these parameters except in certain regimes. An interesting result is that
for supersonic flows, the phase durations and saturation of velocity growth
approach constant values asymptotically as the sonic Mach number increases. We
confirm that the linear coupling between magnetic field and Kelvin-Helmholtz
modes is negligible if the magnetic field is weak enough. The morphological
behaviour suggests that the multi-vortex coalescence might be driven by the
underlying wave-wave interaction. Based on these results, we make a preliminary
discussion about several events observed in the solar corona. The numerical
models need to be further improved to make a practical diagnostic of the
coronal plasma properties.


  Our aim is to describe the theory of Cartesian decompositions preserved by
some member of a large family of finite transitive permutation groups called
innatelytransitive groups.


  This paper describes our submission to the MEDIQA-CORR 2024 shared task for
automatically detecting and correcting medical errors in clinical notes. We
report results for three methods of few-shot In-Context Learning (ICL)
augmented with Chain-of-Thought (CoT) and reason prompts using a large language
model (LLM). In the first method, we manually analyse a subset of train and
validation dataset to infer three CoT prompts by examining error types in the
clinical notes. In the second method, we utilise the training dataset to prompt
the LLM to deduce reasons about their correctness or incorrectness. The
constructed CoTs and reasons are then augmented with ICL examples to solve the
tasks of error detection, span identification, and error correction. Finally,
we combine the two methods using a rule-based ensemble method. Across the three
sub-tasks, our ensemble method achieves a ranking of 3rd for both sub-task 1
and 2, while securing 7th place in sub-task 3 among all submissions.


  We present an experimental realization of a 16 element, temporal-array,
photon-number-resolving (PNR) detector, which is a multiplexed single-photon
detector that splits an input signal over multiple time-bins, and the time-bins
are detected using two superconducting nanowire single-photon detectors
(SNSPD). A theoretical investigation of the PNR capabilities of the detector is
performed and it is concluded that compared to a single-photon detector, our
array detector can resolve one order of magnitude higher mean photon numbers,
given the same number of input pulses to measure. This claim is experimentally
verified and we show that the detector can accurately predict photon numbers
between $10^{-3}$ to $10^{2}$. Our present detector is incapable of single-shot
photon-number measurements with high precision since its effective quantum
efficiency is $49\,\%$. Using SNSPDs with a higher quantum efficiency the PNR
performance will improve, but the photon-number resolution will still be
limited by the array size.


  Safe deployment of graph neural networks (GNNs) under distribution shift
requires models to provide accurate confidence indicators (CI). However, while
it is well-known in computer vision that CI quality diminishes under
distribution shift, this behavior remains understudied for GNNs. Hence, we
begin with a case study on CI calibration under controlled structural and
feature distribution shifts and demonstrate that increased expressivity or
model size do not always lead to improved CI performance. Consequently, we
instead advocate for the use of epistemic uncertainty quantification (UQ)
methods to modulate CIs. To this end, we propose G-$\Delta$UQ, a new single
model UQ method that extends the recently proposed stochastic centering
framework to support structured data and partial stochasticity. Evaluated
across covariate, concept, and graph size shifts, G-$\Delta$UQ not only
outperforms several popular UQ methods in obtaining calibrated CIs, but also
outperforms alternatives when CIs are used for generalization gap prediction or
OOD detection. Overall, our work not only introduces a new, flexible GNN UQ
method, but also provides novel insights into GNN CIs on safety-critical tasks.


  The outflow efficiency (eta) from black hole (BH) accretion disc systems is
known to depend upon both the BH spin (a) and the amount of large-scale
magnetic flux threading the BH and disc. Semi-analytical flux-trapping models
suggest retrograde BHs should trap much more large-scale magnetic flux near the
BH leading to much higher eta than for prograde BHs. We self-consistently
determine the amount of large-scale magnetic flux trapped by rapidly spinning
(a = -0.9 and 0.9) BHs using global 3D time-dependent non-radiative general
relativistic magnetohydrodynamic simulations of thick (h/r ~ 0.3-0.6) discs. We
find that BH-trapped flux builds up until it is strong enough to disrupt the
inner accretion disc. Contrary to prior flux-trapping models, which do not
include the back-reaction of magnetic flux on the disc, our simulations show
prograde BHs trap more magnetic flux, leading to about 3 times higher eta than
retrograde BHs for |a| = 0.9. Both spin orientations can produce highly
efficient jets, eta ~ 100%, with increasing eta for increasing disc thickness.
The similarity of eta for prograde and retrograde BHs makes it challenging to
infer the sign of BH spin based on jet energetics alone.


  We derive a long distance effective action for space-time coordinates from a
IIB matrix model. It provides us an effective tool to study the structures of
space-time. We prove the finiteness of the theory for finite $N$ to all orders
of the perturbation theory. Space-time is shown to be inseparable and its
dimensionality is dynamically determined. The IIB matrix model contains a
mechanism to ensure the vanishing cosmological constant which does not rely on
the manifest supersymmetry. We discuss possible mechanisms to obtain realistic
dimensionality and gauge groups from the IIB matrix model.


  We investigate the young stellar populations associated with DR 18 and ECX
6-21, which are two isolated globules irradiated by the O-type stars of the
Cygnus OB2 association. Both are HII regions containing obvious tracers of
recent and ongoing star formation. We also study smaller isolated molecular
structures in their surroundings. Both globules contain their own embedded
populations, with a higher fraction of the less-evolved classes. Masses and
temperatures are estimated under the assumption of a common age of 1 Myr, which
has been found to appropriately represent the general Cygnus OB2 YSO population
but is most probably an overestimate for both globules, especially ECX 6-21.
The early-B star responsible for the erosion of DR 18 is found to be part of a
small aggregate of intermediate-mass stars still embedded in the cloud, which
probably contains a second site of recent star formation, also with
intermediate-mass stars. We confirm the two main star forming sites embedded in
ECX 6-21 described in previous works, with the southern site being more evolved
than the northern site. We also discuss the small globule ECX 6-21-W ($=
G79.8+1.2$), and propose that its non thermal radio spectrum is due to
synchrotron emission from an embedded jet, whose existence is suggested by our
observations. The extreme youth of some of the YSOs suggests that star
formation in both globules started after they became externally irradiated. The
populations of both globules are not found to be particularly rich, but they
contain stars with estimated masses similar or above that of the Sun in numbers
that hint at some differences with respect to the star formation process taking
place in more quiescent regions where low-mass stars dominate, which deeper
observations may confirm.


  We consider two-player games with imperfect information and the synthesis of
a randomized strategy for one player that ensures the objective is satisfied
almost-surely (i.e., with probability 1), regardless of the strategy of the
other player. Imperfect information is modeled by an indistinguishability
relation describing the pairs of histories that the first player cannot
distinguish, a generalization of the traditional model with partial
observations. The game is regular if it admits a regular function whose kernel
commutes with the indistinguishability relation.
  The synthesis of pure strategies that ensure all possible outcomes satisfy
the objective is possible in regular games, by a generic reduction that holds
for all objectives. While the solution for pure strategies extends to
randomized strategies in the traditional model with partial observations (which
is always regular), we show that a similar reduction does not exist in the more
general model. Despite that, we show that in regular games with Buechi
objectives the synthesis problem is decidable for randomized strategies that
ensure the outcome satisfies the objective almost-surely.


  Full chemical equilibrium calculations of the sequence of condensation of the
elements from cosmic gases made by total vaporization of dust-enriched systems
were performed to investigate the oxidation state of the resulting condensates.
Computations included 23 elements and 374 gas species over a range of
-3=log10(total P) to -6 bar and for enrichments to 1000x in dust of C1
chondritic composition relative to a system of solar composition. Because
liquids are stable condensates in these systems, the MELTS non-ideal solution
model for silicate liquids was used. Condensation at logP=-3 bar and dust
enrichments of 100x, 500x and 1000x occurs at oxygen fugacities of IW-3.1,
IW-1.7 and IW-1.2, respectively, and, at the temperature of cessation of direct
condensation of olivine from the vapor, yields X(fayalite) of 0.019, 0.088 and
0.164, respectively. Silicate liquid is a stable condensate at dust enrichments
>~12.5x at logP=-3. At 1000x, the Na and K oxide contents of the last liquid
reach 10.1 and 1.3 wt%, respectively, at logP=-3 bar. At logP=-3 bar, iron
sulfide liquids are stable condensates at dust enrichments at least as low as
500x, and the predicted distribution of Fe between metal, silicate and sulfide
at 1310K and a dust enrichment of 560x matches that found in H chondrites, and
at 1330K and 675x matches that of L chondrites prior to metal loss. With some
exceptions, many chondrule glass compositions fall along bulk composition
trajectories for liquids in equilibrium with cosmic gases at logP=-3 bar and
dust enrichments between 600x and 1000x. If these chondrules formed by
secondary melting of mixtures of condensates that formed at different T,
nebular regions with characteristics such as these would have been necessary to
prevent loss of Na by evaporation and FeO by reduction from the liquid
precursors, assuming that liquids and gas were hot for enough time to have
equilibrated.


  We analyze a classically scale invariant extension of the Standard Model with
dark gauge $U(1)_X$ broken by doubly charge scalar $\Phi$ leaving a remnant
$Z_2$ symmetry. Dark fermions are introduced as dark matter candidates and for
anomaly reasons we introduce two chiral fermions. Due to classical scale
invariance, bare mass term that would mix these two states is absent and they
end up as stable Majorana fermions $N_1$ and $N_2$. We calculate cross sections
for $N_aN_a \to \phi\phi$, $N_aN_a \to X^\mu \phi$ and $N_2N_2 \to N_1N_1$
annihilation channels. We put constraints to the model from the Higgs searches
at the LHC, dark matter relic abundance and dark matter direct detection limits
by LUX. The dark gauge boson plays a crucial role in the Coleman-Weinberg
mechanism and has to be heavier then 680 GeV. The viable mass region for dark
matter is from 470 GeV up to a few TeV. In the case when two Majorana fermions
have different masses, two dark matter signals at direct detection experiments
could provide a distinctive signature of this model.


  The usual procedure for estimating the significance of a peak in a power
spectrum is to calculate the probability of obtaining that value or a larger
value by chance (known as the "p-value"), on the assumption that the time
series contains only noise - typically that the measurements are derived from
random samplings of a Gaussian distribution. We really need to know the
probability that the time series is - or is not - compatible with the null
hypothesis that the measurements are derived from noise. This probability can
be calculated by Bayesian analysis, but this requires one to specify and
evaluate a second hypothesis, that the time series does contain a contribution
other than noise. We approach the problem of identifying this function in two
ways. We first propose three simple conditions that it seems reasonable to
impose on this function, and show that these conditions may be satisfied by a
simple function with one free parameter. We then define two different ways of
combining information derived from two independent power estimates. We find
that this consistency condition may be satisfied, to good approximation, by a
special case of the previously proposed likelihood function. We find that the
resulting significance estimates are considerably more conservative than those
usually associated with the p-values. As two examples, we apply the new
procedure to two recent analyses of solar neutrino data: (a) power spectrum
analysis of Super-Kamiokande data, and (b) the combined analysis of
radiochemical neutrino data and irradiance data.


  With the aim of unraveling the complexity of the morpho-kinematics of the
circumstellar envelope (CSE) of Mira Ceti, we review, extend and in some cases
revisit ALMA millimeter observations of the emission of the SiO(5-4) and
CO(3-2) molecular lines. In addition, we present a detailed analysis of the
optically thin $^{13}$CO(3-2) emission, which provides several important new
results. In agreement with observations at infrared and visible wavelengths, we
give evidence for confinement and probably rotation of a dense gas volume
within $\sim$50 au from the star and for a large SiO line-width within $\sim$15
au. We show that the mass loss process is episodic and takes the form of clumps
having a very low SiO/CO abundance ratio compared with similar oxygen-rich long
period variables, probably a result of depletion on dust grains and
photo-dissociation. We evaluate the mass loss rate associated with the main
clumps and compare it with values obtained from single dish observations. We
argue that the SiO emission observed in the south-western quadrant is not
related to the mechanism of generation of the nascent wind but to a mass
ejection that occurred eleven years before the observations. We remark that
Mira Ceti is not a good archetype in terms of its wind: models aiming at
describing the very complex gas-dust chemistry in action in the CSE of
oxygen-rich AGB stars may find it difficult to account for its peculiar
features, small variations in the parameters deciding when and where mass loss
can proceed significantly.


  Temporal Bell inequalities, or Leggett-Garg Inequalities (LGI), are studied
for continuous-variable systems placed in a squeezed state. The importance of
those systems lies in their broad applicability which allows the description of
many different physical settings in various branches of physics, ranging from
cosmology to condensed matter physics and from optics to quantum information
theory. LGI violations are explored and systematically mapped in squeezing
parameter space. Configurations for which LGI violation occurs are found but it
is shown that no violation can be obtained if all squeezing angles vanish,
contrary to what happens for the spatial Bell inequalities. We also assess the
effect of decoherence on the detectability of such violations. Our study opens
up the possibility of new experimental designs for the observation of LGI
violation.


  The availability of a number of new interferometric measurements of Main
Sequence and subgiant stars makes it possible to calibrate the surface
brightness relations of these stars using exclusively direct angular diameter
measurements. These empirical laws allow to predict the limb darkened angular
diameters theta_LD of dwarfs and subgiants using their dereddened Johnson
magnitudes, or their effective temperature. The smallest intrinsic dispersions
of sigma < 1% on theta_LD are obtained for the relations based on the K and L
magnitudes, for instance log theta_LD = 0.0502 (B-L) + 0.5133 - 0.2 L or log
theta_LD = 0.0755 (V-K) + 0.5170 - 0.2 K. Our calibrations are valid between
the spectral types A0 and M2 for dwarf stars (with a possible extension to
later types when using the effective temperature), and between A0 and K0 for
subgiants. Such relations are particularly useful to estimate the angular size
of calibrators for long baseline interferometry from readily available
broadband photometry.


  We have recently completed a comprehensive photometric survey of 27 Abell
clusters with the 8k mosaic camera on the KPNO 0.9m telescope. Preliminary
luminosity functions and dwarf-to-giant galaxy ratios have been calculated for
five galaxy clusters (A1185, A1656, A2151, A2152, and A2197). A significant
increase in the faint end slope between the inner (0.0-0.75 Mpc) and outer
(0.75-1.50 Mpc) luminosity function is measured for A2151 (H_o = 50 km/s/Mpc).
All five clusters show a significant dip in the luminosity function at M_R =
-19.5.


  The nascent field of Rate-Distortion-Perception (RDP) theory is seeing a
surge of research interest due to the application of machine learning
techniques in the area of lossy compression. The information RDP function
characterizes the three-way trade-off between description rate, average
distortion, and perceptual quality measured by discrepancy between probability
distributions. However, computing RDP functions has been a challenge due to the
introduction of the perceptual constraint, and existing research often resorts
to data-driven methods. In this paper, we show that the information RDP
function can be transformed into a Wasserstein Barycenter problem. The
nonstrictly convexity brought by the perceptual constraint can be regularized
by an entropy regularization term. We prove that the entropy regularized model
converges to the original problem. Furthermore, we propose an alternating
iteration method based on the Sinkhorn algorithm to numerically solve the
regularized optimization problem. Experimental results demonstrate the
efficiency and accuracy of the proposed algorithm.


  For decades ever since the early detection in the 1990s of the emission
spectral features of crystalline silicates in oxygen-rich evolved stars, there
is a long-standing debate on whether the crystallinity of the silicate dust
correlates with the stellar mass loss rate. To investigate the relation between
the silicate crystallinities and the mass loss rates of evolved stars, we carry
out a detailed analysis of 28 nearby oxygen-rich stars. We derive the mass loss
rates of these sources by modeling their spectral energy distributions from the
optical to the far infrared. Unlike previous studies in which the silicate
crystallinity was often measured in terms of the crystalline-to-amorphous
silicate mass ratio, we characterize the silicate crystallinities of these
sources with the flux ratios of the emission features of crystalline silicates
to that of amorphous silicates. This does not require the knowledge of the
silicate dust temperatures which are the major source of uncertainties in
estimating the crystalline-to-amorphous silicate mass ratio. With a Pearson
correlation coefficient of ~0.24, we find that the silicate crystallinities and
the mass loss rates of these sources are not correlated. This supports the
earlier findings that the dust shells of low mass-loss rate stars can contain a
significant fraction of crystalline silicates without showing the
characteristic features in their emission spectra.


  Massive MIMO has been the subject of intense interest in both academia and
industry for the past few years. 3GPP standardization for cellular systems have
adopted the principles of massive MIMO and categorized the use of large
rectangular planar arrays at the base station as full-dimension MIMO (FD-MIMO)
to operate in both TDD and FDD. Operating a large antenna array base station
requires the system to overcome several implementation challenges caused by
hardware impairments making practical solutions non-ideal and expensive to
deploy at scale. It is important to learn from existing challenges and
solutions in order to prepare for larger scale deployment for example with cell
free massive MIMO. Hence in this paper, we specifically study the phase and
amplitude instability due to RF impairments using measurements carried out in
the lab and in the field in a commercial LTE network. We investigate the effect
of phase and magnitude errors on the performance of FD-MIMO systems. We discuss
and characterize various sources creating these errors including time varying
phase drift from low cost local oscillator (LO) and internal temperature
variations affecting frequency response of RF chains. The minimum requirements
and tradeoffs of different LO architectures and calibration mechanisms for
practical cellular deployment are discussed. We then provide details of a novel
coherent LO distribution mechanism and related novel array calibration
mechanism that can be applied to both TDD and FDD systems. Measurement results
are provided to validate the performance of these methods used in a 2D
full-connected hybrid beamforming array architecture called High Definition
Active Antenna System (HDAAS). These results showcase the efficacy of the
proposed methods which can easily be extended to other array architectures
including sub-array hybrid beamforming and element-level digitization.


  Energy demand has increased considerably with the growth of world population,
increasing the interest in the hydrocarbon reservoir management problem.
Companies are concerned with maximizing oil recovery while minimizing capital
investment and operational costs. A first step in solving this problem is to
consider optimal well placement. In this work, we investigate the Differential
Evolution (DE) optimization method, using distinct configurations with respect
to population size, mutation factor, crossover probability, and mutation
strategy, to solve the well placement problem. By assuming a bare control
procedure, one optimizes the parameters representing positions of injection and
production wells. The Tenth SPE Comparative Solution Project and MATLAB
Reservoir Simulation Toolbox (MRST) are the benchmark dataset and simulator
used, respectively. The goal is to evaluate the performance of DE in solving
this important real-world problem. We show that DE can find high-quality
solutions, when compared with a reference from the literature, and a
preliminary analysis on the results of multiple experiments gives useful
information on how DE configuration impacts its performance.


  The use of deep learning techniques for automatic facial expression
recognition has recently attracted great interest but developed models are
still unable to generalize well due to the lack of large emotion datasets for
deep learning. To overcome this problem, in this paper, we propose utilizing a
novel transfer learning approach relying on PathNet and investigate how
knowledge can be accumulated within a given dataset and how the knowledge
captured from one emotion dataset can be transferred into another in order to
improve the overall performance. To evaluate the robustness of our system, we
have conducted various sets of experiments on two emotion datasets: SAVEE and
eNTERFACE. The experimental results demonstrate that our proposed system leads
to improvement in performance of emotion recognition and performs significantly
better than the recent state-of-the-art schemes adopting fine-\
tuning/pre-trained approaches.


  Doped Hubbard model is a simple model for the high-Tc cuprate
superconductors, while its ground state remains a challenge. Here, by
performing state-of-the-art variational Monte Carlo calculations for the
strong-coupling Hubbard model, we find evidences that the d-wave
superconducting phase emerges always near the phase separation region and the
superconducting order has one-to-one correspondence with the enhancement of
charge compressibility. The order as well as the phase separation are
vulnerable to realistic intersite Coulomb interaction while the superexchange
interaction enhances both. An appropriate combination of these two widens the
stable superconducting phase.


  Moduli spaces of complete skew-forms are compactifications of spaces of
skew-symmetric linear maps of maximal rank on a fixed vector space, where the
added boundary divisor is simple normal crossing. In this paper we compute
their effective, nef and movable cones, the generators of their Cox rings, and
for those spaces having Picard rank two we give an explicit presentation of the
Cox ring. Furthermore, we give a complete description of both the Mori chamber
and stable base locus decompositions of the effective cone of some spaces of
complete skew-forms having Picard rank at most four.


  We investigate the aspherization of an active mirror for correcting third and
fifth-order aberrations. We use a stainless steel AISI 420 mirror with a
controlled pressure load, two series of 12-punctual radial positions of force
application distributed symmetrically in two concentric rings around the
mirror. We obtain the wavefronts for Cv1, Sph3, Coma3, Astm3, Comatri, Astm5
aswell as those of the added wavefronts. Although this active prototype mirror
has general uses, our goal is to compensate the aberrations of a liquid mirror
observing at large angles from the zenith.


  Similar to most of the real world data, the ubiquitous presence of
non-stationarities in the EEG signals significantly perturb the feature
distribution thus deteriorating the performance of Brain Computer Interface. In
this letter, a novel method is proposed based on Joint Approximate
Diagonalization (JAD) to optimize stationarity for multiclass motor imagery
Brain Computer Interface (BCI) in an information theoretic framework.
Specifically, in the proposed method, we estimate the subspace which optimizes
the discriminability between the classes and simultaneously preserve
stationarity within the motor imagery classes. We determine the subspace for
the proposed approach through optimization using gradient descent on an
orthogonal manifold. The performance of the proposed stationarity enforcing
algorithm is compared to that of baseline One-Versus-Rest (OVR)-CSP and JAD on
publicly available BCI competition IV dataset IIa. Results show that an
improvement in average classification accuracies across the subjects over the
baseline algorithms and thus essence of alleviating within session
non-stationarities.


  We present Fast-Downsampling MobileNet (FD-MobileNet), an efficient and
accurate network for very limited computational budgets (e.g., 10-140 MFLOPs).
Our key idea is applying an aggressive downsampling strategy to MobileNet
framework. In FD-MobileNet, we perform 32$\times$ downsampling within 12
layers, only half the layers in the original MobileNet. This design brings
three advantages: (i) It remarkably reduces the computational cost. (ii) It
increases the information capacity and achieves significant performance
improvements. (iii) It is engineering-friendly and provides fast actual
inference speed. Experiments on ILSVRC 2012 and PASCAL VOC 2007 datasets
demonstrate that FD-MobileNet consistently outperforms MobileNet and achieves
comparable results with ShuffleNet under different computational budgets, for
instance, surpassing MobileNet by 5.5% on the ILSVRC 2012 top-1 accuracy and
3.6% on the VOC 2007 mAP under a complexity of 12 MFLOPs. On an ARM-based
device, FD-MobileNet achieves 1.11$\times$ inference speedup over MobileNet and
1.82$\times$ over ShuffleNet under the same complexity.


  This dissertation is to study the interplay between large-scale electric
vehicle (EV) charging and the power system. We address three important issues
pertaining to EV charging and integration into the power system: (1) charging
station placement, (2) pricing policy and energy management strategy, and (3)
electricity trading market and distribution network design to facilitate
integrating EV and renewable energy source (RES) into the power system.
  For charging station placement problem, we propose a multi-stage consumer
behavior based placement strategy with incremental EV penetration rates and
model the EV charging industry as an oligopoly where the entire market is
dominated by a few charging service providers (oligopolists). The optimal
placement policy for each service provider is obtained by solving a Bayesian
game.
  For pricing and energy management of EV charging stations, we provide
guidelines for charging service providers to determine charging price and
manage electricity reserve to balance the competing objectives of improving
profitability, enhancing customer satisfaction, and reducing impact on the
power system. Two algorithms --- stochastic dynamic programming (SDP) algorithm
and greedy algorithm (benchmark algorithm) are applied to derive the pricing
and electricity procurement strategy.
  We design a novel electricity trading market and distribution network, which
supports seamless RES integration, grid to vehicle (G2V), vehicle to grid
(V2G), vehicle to vehicle (V2V), and distributed generation (DG) and storage.
We apply a sharing economy model to the electricity sector to stimulate
different entities to exchange and monetize their underutilized electricity. A
fitness-score (FS)-based supply-demand matching algorithm is developed by
considering consumer surplus, electricity network congestion, and economic
dispatch.


  We prove a magnetic version of the Maz'ya-Shaposhnikova singular limit of
nonlocal norms with vanishing fractional parameter. This complements a general
convergence result recently obtained by authors when the parameter approaches
one.