  The vast separation dividing the characteristic times of energy confinement
and turbulence in the core of toroidal plasmas makes first-principles
prediction on long timescales extremely challenging. Here we report the
demonstration of a multiple-timescale method that enables coupling global
gyrokinetic simulations with a transport solver to calculate the evolution of
the self-consistent temperature profile. This method, which exhibits resiliency
to the intrinsic fluctuations arising in turbulence simulations, holds
potential for integrating nonlocal gyrokinetic turbulence simulations into
predictive, whole-device models.


  A variation of Newton's method of mapping Kepler's orbits into orbits in the
simple harmonic oscillator is shown to give Henon's Isochrone. The statistical
mechanics of a micro-canonical ensemble of isochrone oscillators shows that the
temperature reaches a maximum as a function of the energy and then declines to
zero at the escape energy. In that declining region adding heat (energy)
decreases the temperature, as occurs in star clusters. We then define the
internal temperature of an ensemble of binary stars all at the same (negative)
energy and show that they too get cooler when heated and hotter when cooled.
When the internal temperature of a binary is less that the temperature of the
stars it interacts with, then on average heat will flow into it, making it less
bound and of still lower temperature. Conversely hard binaries have higher
internal temperatures than the local stars, so they lose energy and become
hotter and yet more strongly bound, a process invoked by Michel Henon in his
explanation of star-cluster evolution. Finally we give an isochronal variation
of Newton's exactly soluble N-body problem.


  Ge and Stefankovic have recently introduced a novel two-variable graph
polynomial. When specialised to a bipartite graphs G and evaluated at the point
(1/2,1) this polynomial gives the number of independent sets in the graph.
Inspired by this polynomial, they also introduced a Markov chain which, if
rapidly mixing, would provide an efficient sampling procedure for independent
sets in G. This sampling procedure in turn would imply the existence of
efficient approximation algorithms for a number of significant counting
problems whose complexity is so far unresolved. The proposed Markov chain is
promising, in the sense that it overcomes the most obvious barrier to mixing.
However, we show here, by exhibiting a sequence of counterexamples, that the
mixing time of their Markov chain is exponential in the size of the input when
the input is chosen from a particular infinite family of bipartite graphs.


  We present high signal-to-noise ratio, precise $YJH$ photometry and $Y$ band
(\gpiwave~$\mu$m) spectroscopy of HD 1160 B, a young substellar companion
discovered from the Gemini NICI Planet Finding Campaign, using the Subaru
Coronagraphic Extreme Adaptive Optics instrument and the Gemini Planet Imager.
HD 1160 B has typical mid-M dwarf-like infrared colors and a spectral type of
M5.5$^{+1.0}_{-0.5}$, where the blue edge of our $Y$ band spectrum rules out
earlier spectral types. Atmospheric modeling suggests HD 1160 B having an
effective temperature of 3000--3100 $K$, a surface gravity of log $g$ = 4--4.5,
a radius of~\bestfitradius~$R_{\rm J}$, and a luminosity of log $L$/$L_{\odot}
= -2.76 \pm 0.05$. Neither the primary's Hertzspring-Russell diagram position
nor atmospheric modeling of HD 1160 B show evidence for a sub-solar
metallicity. The interpretation of the HD 1160 B depends on which stellar
system components are used to estimate an age. Considering HD 1160 A, B and C
jointly, we derive an age of 80--125 Myr, implying that HD 1160 B straddles the
hydrogen-burning limit (70--90 $M_{\rm J}$). If we consider HD 1160 A alone,
younger ages (20--125 Myr) and a brown dwarf-like mass (35--90 $M_{\rm J}$) are
possible. Interferometric measurements of the primary, a precise GAIA parallax,
and moderate resolution spectroscopy can better constrain the system's age and
how HD 1160 B fits within the context of (sub)stellar evolution.


  We prove that any complete, uniformly elliptic Weingarten surface in
Euclidean $3$-space whose Gauss map image omits an open hemisphere is a
cylinder or a plane. This generalizes a classical theorem by Hoffman, Osserman
and Schoen for constant mean curvature surfaces. In particular, this proves
that planes are the only complete, uniformly elliptic Weingarten multigraphs.
We also show that this result holds for a large class of non-uniformly elliptic
Weingarten equations. In particular, this solves in the affirmative the
Bernstein problem for entire graphs for that class of elliptic equations. To
obtain these results, we prove that planes are the only complete multigraphs
with quasiconformal Gauss map and bounded second fundamental form.


  We present multi-wavelength monitoring results for the broad-line radio
galaxy 3C 120 in the MeV/GeV, sub-millimeter, and 43 GHz bands over six years.
Over the past two years, Fermi-LAT sporadically detected 3C 120 with high
significance and the 230 GHz data also suggest an enhanced activity of the
source. After the MeV/GeV detection from 3C 120 in MJD 56240-56300, 43 GHz VLBA
monitoring revealed a brightening of the radio core, followed by the ejection
of a superluminal knot. Since we observed the gamma-ray and VLBA phenomena in
temporal proximity to each other, it is naturally assumed that they are
physically connected. This assumption was further supported by the subsequent
observation that the 43 GHz core brightened again after a gamma-ray flare
occurred around MJD 56560. We can then infer that the MeV/GeV emission took
place inside an unresolved 43 GHz core of 3C 120 and that the jet dissipation
occurred at sub-parsec distances from the central black hole, if we take the
distance of the 43 GHz core from the central black hole as ~ 0.5 pc, as
previously estimated from the time lag between X-ray dips and knot ejections
(Marscher et al. 2002; Chatterjee et al. 2009). Based on our constraints on the
relative locations of the emission regions and energetic arguments, we conclude
that the gamma rays are more favorably produced via the synchrotron
self-Compton process, rather than inverse Compton scattering of external
photons coming from the broad line region or hot dusty torus. We also derived
the electron distribution and magnetic field by modeling the simultaneous
broadband spectrum.


  We present a quantum key distribution (QKD) system based on polarisation
entanglement for use in telecom fibers. A QKD exchange up to 50km was
demonstrated in the laboratory with a secure key rate of 550 bit/s. The system
is compact, portable with a fully automated start-up and stabilisation modules
for polarisation, synchronisation and photon coupling allow a hands-off
operation. Stable and reliable key exchange in a deployed optical fiber of 16km
length was demonstrated. In this fiber network we achieved over two weeks an
automatic key generation with an average key rate of 2000 bit/s without manual
intervention. During this period, the system had an average entanglement
visibility of 93%, highlighting the technical level and stability achieved for
entanglement-based quantum cryptography.


  We present our preliminary result for the charmed quark mass, which follows
from taking the D_s and K meson masses from experiment and r0=0.5 fm (or,
equivalently F_K=160 MeV) to set the scale. For the renormalization group
invariant quark mass we obtain M_c = 1684(64) MeV, which translates to
m_c(m_c)= 1314 (40)(20)(7) MeV for the running mass in the MSbar scheme.
Renormalization is treated non-perturbatively, and the continuum limit has been
taken, so that the only uncontrolled systematic error consists in the use of
the quenched approximation.


  This work reports on the magnetic reversal of sub-micrometer sized elements
consisting of an CoFeB/Ru/CoFeB artificial ferrimagnet (AFi). The elements were
patterned into ellipses having a width of approximately 250 to 270nm and a
varying aspect ratio between 1.3 and 8. The coercivity was found to decrease
with an increasing imbalance of the magnetic moment of the two
antiferromagnetically coupled layers and is therefore strongly affected by an
increase of effective anisotropy due to the antiferromagnetic coupling of the
two layers. With respect to a single layer of amorphous CoFeB, patterned in
comparable elements, the AFi has an increased coercivity. Switching asteroids
comparable to single layers were only observed for samples with a high net
moment.


  Semi-supervised classification, one of the most prominent fields in machine
learning, studies how to combine the statistical knowledge of the often
abundant unlabeled data with the often limited labeled data in order to
maximize overall classification accuracy. In this context, the process of
actively choosing the data to be labeled is referred to as active learning. In
this paper, we initiate the non-asymptotic analysis of the optimal policy for
semi-supervised classification with actively obtained labeled data. Considering
a general Bayesian classification model, we provide the first characterization
of the jointly optimal active learning and semi-supervised classification
policy, in terms of the cost-performance tradeoff driven by the label query
budget (number of data items to be labeled) and overall classification
accuracy. Leveraging recent results on the R\'enyi Entropy, we derive tight
information-theoretic bounds on such active learning cost-performance tradeoff.


  Without exceeding the limits of the conventional $\Lambda$CDM paradigm, we
argue for Yukawa law of interparticle interaction as the law of gravitation in
the real expanding inhomogeneous Universe. It covers the whole space and comes
up to take place of Newtonian gravity, which is restricted exclusively to
sub-horizon distances. The large-scale screening of gravitational interaction
between every two nonrelativistic massive particles is ensured by the
homogeneous cosmological background (specifically, by the nonzero average rest
mass density of nonrelativistic matter). We take advantage of the uniform
matter distribution case (i.e. the homogeneous Universe limit) to demonstrate
superiority of Yukawa gravity. Attention is also devoted to the concrete
particular case of inhomogeneity.


  Inverse problems of recovering heat transfer coefficient from integral
measurements are considered. The heat transfer coefficient occurs in the
transmission conditions of imperfect contact type or the Robin type boundary
conditions.
  It is representable as a finite part of the Fourier series with time
dependent coefficients. The additional measurements are integrals of a solution
multiplied by some weights.
  Existence and uniqueness of solutions in Sobolev classes are proven and the
conditions on the data are sharp. These conditions include smoothness and
consistency conditions on the data and additional conditions on the kernels of
the integral operators used in additional measurements. The proof relies on a
priori bounds and the contraction mapping principle. The existence and
uniqueness theorems are local in time.


  Molecule generation is a task made very difficult by the complex ways in
which we represent molecules computationally. A common technique used in
molecular generative modeling is to use SMILES strings with recurrent neural
networks built into variational autoencoders - but these suffer from a myriad
of issues: vanishing gradients, long-range forgetting, and invalid molecules.
In this work, we show that by combining recurrent neural networks with
convolutional networks in a hierarchical manner, we are able to both extract
autoregressive information from SMILES strings while maintaining signal and
long-range dependencies. This allows for generations with very high validity
rates on the order of 95% when reconstructing known molecules. We also observe
an average Tanimoto similarity of .6 between test set and reconstructed
molecules, which suggests our method is able to map between SMILES strings and
their learned representations in a more effective way than prior works using
similar methods.


  In this work, our aim is to identify whether the choice of virtualization
strategy influences the performance of simulations in robotics. Performance is
quantified in the error between a reference trajectory and the actual
trajectory for the ball moving along the surface of a smooth plate. The
two-sample Kolmogorov-Smirnov test is used to assess significance of variations
in performance under the different experimental settings. Our results show that
the selection of virtualization technology does have a significant effect on
simulation, and moreover this effect can be amplified by the use of some
operating systems. While these results are a strong cause for caution, they
also provide reason for optimism for those considering 'repeatable robotics
research' using virtualization.


  Despite the impressive numerical performance of the quasi-Newton and
Anderson/nonlinear acceleration methods, their global convergence rates have
remained elusive for over 50 years. This study addresses this long-standing
issue by introducing a framework that derives novel, adaptive quasi-Newton and
nonlinear/Anderson acceleration schemes. Under mild assumptions, the proposed
iterative methods exhibit explicit, non-asymptotic convergence rates that blend
those of the gradient descent and Cubic Regularized Newton's methods. The
proposed approach also includes an accelerated version for convex functions.
Notably, these rates are achieved adaptively without prior knowledge of the
function's parameters. The framework presented in this study is generic, and
its special cases includes algorithms such as Newton's method with random
subspaces, finite-differences, or lazy Hessian. Numerical experiments
demonstrated the efficiency of the proposed framework, even compared to the
l-BFGS algorithm with Wolfe line-search.


  We report on the fabrication of hybrid molecular devices employing multilayer
graphene (MLG) flakes which are patterned with a constriction using a helium
ion microscope (HIM) or an oxygen plasma etch. The patterning step allows for
the localization of a few-nanometer gap, created by electroburning, that can
host single molecules or molecular ensembles. By controlling the width of the
sculpted constriction, we regulate the critical power at which the
electroburning process begins. We estimate the flake temperature given the
critical power and find that at low powers it is possible to electroburn MLG
with superconducting contacts in close proximity. Finally, we demonstrate the
fabrication of hybrid devices with superconducting contacts and
anthracene-functionalized copper curcuminoid molecules. This method is
extendable to spintronic devices with ferromagnetic contacts and a first step
towards molecular integrated circuits.


  Electric quadrupolar state in a frustrated quantum magnet $\rm Tb_{2+\it
\delta}Ti_{2-\it \delta}O_7$ has been studied by means of ultrasonic and
magnetostriction measurements. A single crystal showed elastic anomaly at about
0.4 K, manifesting a long-range quadrupole ordering. By investigating
anisotropy of the magnetoelastic responses, we found a crossover temperature
for the strongly correlated quadrupole state, below which the experimental data
of elastic constant and magnetostriction become qualitatively different from
their calculations based on a single-ion model. We suppose that relatively high
onset temperature of the quadrupole correlation compared with the transition
temperature is ascribed to the geometrical frustration effect, and this
correlated state seems to be responsible for the unusual properties in the
paramagentic state of $\rm Tb_2Ti_2O_7$.


  Recently, subgraph GNNs have emerged as an important direction for developing
expressive graph neural networks (GNNs). While numerous architectures have been
proposed, so far there is still a limited understanding of how various design
paradigms differ in terms of expressive power, nor is it clear what design
principle achieves maximal expressiveness with minimal architectural
complexity. To address these fundamental questions, this paper conducts a
systematic study of general node-based subgraph GNNs through the lens of
Subgraph Weisfeiler-Lehman Tests (SWL). Our central result is to build a
complete hierarchy of SWL with strictly growing expressivity. Concretely, we
prove that any node-based subgraph GNN falls into one of the six SWL
equivalence classes, among which $\mathsf{SSWL}$ achieves the maximal
expressive power. We also study how these equivalence classes differ in terms
of their practical expressiveness such as encoding graph distance and
biconnectivity. Furthermore, we give a tight expressivity upper bound of all
SWL algorithms by establishing a close relation with localized versions of WL
and Folklore WL (FWL) tests. Our results provide insights into the power of
existing subgraph GNNs, guide the design of new architectures, and point out
their limitations by revealing an inherent gap with the 2-FWL test. Finally,
experiments demonstrate that $\mathsf{SSWL}$-inspired subgraph GNNs can
significantly outperform prior architectures on multiple benchmarks despite
great simplicity.


  The high-$\mu_{\rm B}$ region of the QCD phase diagram has become the object
of several studies, focused on the investigation of the order of the phase
transition and the search for the critical point. Accessing rare probes is
experimentally challenging as it requires large integrated luminosities, and a
fixed-target environment represents an ideal solution for these studies. The
CERN SPS covers, with large beam intensity, the collision energy region
$5<\sqrt{s_{\rm NN}}<17$ GeV. A future experiment, NA60+, is being proposed to
access this region and perform accurate measurements of the dimuon spectrum
from threshold up to the charmonium mass region, and of hadronic decays of
charm and strange hadrons. The experiment, which is also part of the Physics
Beyond Colliders CERN initiative, aims at taking its first data with Pb and
proton beams around 2029.


  Existing domain adaptation methods on visual sentiment classification
typically are investigated under the single-source scenario, where the
knowledge learned from a source domain of sufficient labeled data is
transferred to the target domain of loosely labeled or unlabeled data. However,
in practice, data from a single source domain usually have a limited volume and
can hardly cover the characteristics of the target domain. In this paper, we
propose a novel multi-source domain adaptation (MDA) method, termed
Multi-source Sentiment Generative Adversarial Network (MSGAN), for visual
sentiment classification. To handle data from multiple source domains, it
learns to find a unified sentiment latent space where data from both the source
and target domains share a similar distribution. This is achieved via cycle
consistent adversarial learning in an end-to-end manner. Extensive experiments
conducted on four benchmark datasets demonstrate that MSGAN significantly
outperforms the state-of-the-art MDA approaches for visual sentiment
classification.


  The outer Galaxy is an environment with metallicity lower than the Solar one.
Because of this, the formation and survival of molecules in star-forming
regions located in the inner and outer Galaxy is expected to be different. To
gain understanding on how chemistry changes throughout the Milky Way, it is
crucial to observe outer Galaxy star-forming regions to constrain models
adapted for lower metallicity environments. In this paper we present a new
observational project: chemical complexity in star-forming regions of the outer
Galaxy (CHEMOUT). The goal is to unveil the chemical composition in 35 dense
molecular clouds associated with star-forming regions of the outer Galaxy
through observations obtained with the IRAM 30m telescope. In this first paper,
we present the sample, and report the detection at 3~mm of simple organic
species HCO+, H13CO+, HCN, c-C3H2, HCO, C4H, and HCS+, of the complex
hydrocarbon CH3CCH, and of SiO, CCS and SO. From c-C3H2, we estimate new
kinematic heliocentric and Galactocentric distances based on an updated
rotation curve of the Galaxy. The detection of the molecular tracers does not
seem to have a clear dependence on the Galactocentric distance. We also analyse
the HCO+ line profiles. We find high velocity wings in ~71% of the targets, and
their occurrence does not depend on the Galactocentric distance. Our results,
confirmed by a statistical analysis, show that the presence of organic
molecules and tracers of protostellar activity is ubiquitous in the
low-metallicity environment of the outer Galaxy. Based on this, and on the
additional evidence that small, terrestrial planets are omnipresent in the
Galaxy, we support previous claims that the definition of Galactic Habitable
Zone should be rediscussed in view of the ubiquitous capacity of the
interstellar medium to form organic molecules.


  In this paper local exact controllability to the trajectories for the
one-dimensional monodomain equations with the FitzHugh-Nagumo and
Rogers-McCulloch ionic models using distributed controls with a moving support
is investigated. In a first step a new Carleman inequality for the adjoint of
the linearized monodomain equations, under assumptions on the movement of the
control region, is presented. It leads to null controllability at any positive
time. Subsequently, a local result concerning the exact controllability to the
trajectories for the nonlinear monodomain equations is deduced.


  Full-field traffic state information (i.e., flow, speed, and density) is
critical for the successful operation of Intelligent Transportation Systems
(ITS) on freeways. However, incomplete traffic information tends to be directly
collected from traffic detectors that are insufficiently installed in most
areas, which is a major obstacle to the popularization of ITS. To tackle this
issue, this paper introduces an innovative traffic state estimation (TSE)
framework that hybrid regression machine learning techniques (e.g., artificial
neural network (ANN), random forest (RF), and support vector machine (SVM))
with a traffic physics model (e.g., second-order macroscopic traffic flow
model) using limited information from traffic sensors as inputs to construct
accurate and full-field estimated traffic state for freeway systems. To examine
the effectiveness of the proposed TSE framework, this paper conducted empirical
studies on a real-world data set collected from a stretch of I-15 freeway in
Salt Lake City, Utah. Experimental results show that the proposed method has
been proved to estimate full-field traffic information accurately. Hence, the
proposed method could provide accurate and full-field traffic information, thus
providing the basis for the popularization of ITS.


  We consider a class of difference-of-convex (DC) optimization problems whose
objective is level-bounded and is the sum of a smooth convex function with
Lipschitz gradient, a proper closed convex function and a continuous concave
function. While this kind of problems can be solved by the classical
difference-of-convex algorithm (DCA) [26], the difficulty of the subproblems of
this algorithm depends heavily on the choice of DC decomposition. Simpler
subproblems can be obtained by using a specific DC decomposition described in
[27]. This decomposition has been proposed in numerous work such as [18], and
we refer to the resulting DCA as the proximal DCA. Although the subproblems are
simpler, the proximal DCA is the same as the proximal gradient algorithm when
the concave part of the objective is void, and hence is potentially slow in
practice. In this paper, motivated by the extrapolation techniques for
accelerating the proximal gradient algorithm in the convex settings, we
consider a proximal difference-of-convex algorithm with extrapolation to
possibly accelerate the proximal DCA. We show that any cluster point of the
sequence generated by our algorithm is a stationary point of the DC
optimization problem for a fairly general choice of extrapolation parameters:
in particular, the parameters can be chosen as in FISTA with fixed restart
[15]. In addition, by assuming the Kurdyka-{\L}ojasiewicz property of the
objective and the differentiability of the concave part, we establish global
convergence of the sequence generated by our algorithm and analyze its
convergence rate. Our numerical experiments on two difference-of-convex
regularized least squares models show that our algorithm usually outperforms
the proximal DCA and the general iterative shrinkage and thresholding algorithm
proposed in [17].


  We investigate p-wave pion production in nucleon-nucleon collisions up to
next-to-next-to-leading order in chiral effective field theory. In particular,
we show that it is possible to describe simultaneously the p-wave amplitudes in
the $pn\to pp\pi^-$, $pp\to pn\pi^+$, $pp\to d\pi^+$ channels by adjusting a
single low-energy constant accompanying the short-range operator which is
available at this order. This study provides a non-trivial test of the
applicability of chiral effective field theory to reactions of the type $NN\to
NN\pi$.


  In this paper we describe our efforts to make a bidirectional Congolese
Swahili (SWC) to French (FRA) neural machine translation system with the
motivation of improving humanitarian translation workflows. For training, we
created a 25,302-sentence general domain parallel corpus and combined it with
publicly available data. Experimenting with low-resource methodologies like
cross-dialect transfer and semi-supervised learning, we recorded improvements
of up to 2.4 and 3.5 BLEU points in the SWC-FRA and FRA-SWC directions,
respectively. We performed human evaluations to assess the usability of our
models in a COVID-domain chatbot that operates in the Democratic Republic of
Congo (DRC). Direct assessment in the SWC-FRA direction demonstrated an average
quality ranking of 6.3 out of 10 with 75% of the target strings conveying the
main message of the source text. For the FRA-SWC direction, our preliminary
tests on post-editing assessment showed its potential usefulness for
machine-assisted translation. We make our models, datasets containing up to 1
million sentences, our development pipeline, and a translator web-app available
for public use.


  We present a simple yet efficient approach capable of training deep neural
networks on large-scale weakly-supervised web images, which are crawled raw
from the Internet by using text queries, without any human annotation. We
develop a principled learning strategy by leveraging curriculum learning, with
the goal of handling a massive amount of noisy labels and data imbalance
effectively. We design a new learning curriculum by measuring the complexity of
data using its distribution density in a feature space, and rank the complexity
in an unsupervised manner. This allows for an efficient implementation of
curriculum learning on large-scale web images, resulting in a high-performance
CNN model, where the negative impact of noisy labels is reduced substantially.
Importantly, we show by experiments that those images with highly noisy labels
can surprisingly improve the generalization capability of the model, by serving
as a manner of regularization. Our approaches obtain state-of-the-art
performance on four benchmarks: WebVision, ImageNet, Clothing-1M and Food-101.
With an ensemble of multiple models, we achieved a top-5 error rate of 5.2% on
the WebVision challenge for 1000-category classification. This result was the
top performance by a wide margin, outperforming second place by a nearly 50%
relative error rate. Code and models are available at:
https://github.com/MalongTech/CurriculumNet .


  We report on a new study aimed at understanding the diversity and
evolutionary properties of distant galactic bulges in the context of
well-established trends for pure spheroidal galaxies. Bulges have been isolated
for a sample of 137 spiral galaxies in the GOODS fields within the redshift
range 0.1 < z < 1.2. Using proven photometric techniques we determine for each
galaxy the characteristic parameters (size, surface brightness, profile shape)
in the 4 GOODS-ACS imaging bands of both the disk and bulge components. Using
the DEIMOS spectrograph on Keck, precision stellar velocity dispersions were
secured for a sizeable fraction of the bulges. This has enabled us to compare
the Fundamental Plane of our distant bulges with that of field spheroidal
galaxies in a similar redshift range. Bulges in spiral galaxies with a
bulge-to-total luminosity ratio (B/T) > 0.2 show very similar patterns of
evolution to those seen for low luminosity spheroidals. To first order, their
recent mass assembly histories are equivalent.


  A new detector concept (R2D) is needed to harvest the unique physics
opportunities at RHIC-II during the LHC era. This concept is based on a high
granularity hermetic array of detectors featuring high momentum particle
identification and superior resolution for photon and onium measurements. Most
components of R2D can also be applied to future electron-ion interactions.
Thus, R2D allows us to perform precision QCD-type measurements at RHIC-II and
eRHIC.


  We classify symplectic 4-dimensional semifields over $\mathbb{F}_q$, for
$q\leq 9$, thereby extending (and confirming) the previously obtained
classifications for $q\leq 7$. The classification is obtained by classifying
all symplectic semifield subspaces in $\mathrm{PG}(9,q)$ for $q\leq 9$ up to
$K$-equivalence, where $K\leq \mathrm{PGL}(10,q)$ is the lift of
$\mathrm{PGL}(4,q)$ under the Veronese embedding of $\mathrm{PG}(3,q)$ in
$\mathrm{PG}(9,q)$ of degree two. Our results imply the non-existence of
non-associative symplectic 4-dimensional semifields for $q$ even, $q\leq 8$.
For $q$ odd, and $q\leq 9$, our results imply that the isotopism class of a
symplectic non-associative 4-dimensional semifield over $\mathbb{F}_q$ is
contained in the Knuth orbit of a Dickson commutative semifield.


  We propose a complete R-parity violating supersymmetric model with baryon
triality that contains a Dine-Fischler-Srednicki-Zhitnitsky axion chiral
superfield. We parametrize supersymmetry breaking with soft terms, and
determine under which conditions the model is cosmologically viable. As
expected we always find a region of parameter space in which the axion is a
cold dark matter candidate. The mass of the axino, the fermionic partner of the
axion, is controlled by a Yukawa coupling. When heavy [${\mathcal O}$(TeV)],
the axino decays early and poses no cosmological problems. When light
[$\mathcal{O}$(keV)] it can be long lived and a warm dark matter candidate. We
concentrate on the latter case and study in detail the decay modes of the
axino. We find that constraints from astrophysical X- and gamma rays on the
decay into photon and neutrino can set new bounds on some trilinear
supersymmetric R-parity violating Yukawa couplings. In some corners of the
parameter space the decays of a relic axino can also explain a putative 3.5 keV
line.


  We show how an algorithm for the problem of inverting a permutation may be
used to design one for the problem of unordered search (with a unique
solution). Since there is a straightforward reduction in the reverse direction,
the problems are essentially equivalent.
  The reduction we present helps us bypass the hybrid argument due to Bennett,
Bernstein, Brassard, and Vazirani (1997) and the quantum adversary method due
to Ambainis (2002) that were earlier used to derive lower bounds on the quantum
query complexity of the problem of inverting permutations. It directly implies
that the quantum query complexity of the problem is asymptotically the same as
that for unordered search, namely in Theta(sqrt(n)).


  Clinically, automated polyp segmentation techniques have the potential to
significantly improve the efficiency and accuracy of medical diagnosis, thereby
reducing the risk of colorectal cancer in patients. Unfortunately, existing
methods suffer from two significant weaknesses that can impact the accuracy of
segmentation. Firstly, features extracted by encoders are not adequately
filtered and utilized. Secondly, semantic conflicts and information redundancy
caused by feature fusion are not attended to. To overcome these limitations, we
propose a novel approach for polyp segmentation, named MLFF-Net, which
leverages multi-level feature fusion and attention mechanisms. Specifically,
MLFF-Net comprises three modules: Multi-scale Attention Module (MAM),
High-level Feature Enhancement Module (HFEM), and Global Attention Module
(GAM). Among these, MAM is used to extract multi-scale information and polyp
details from the shallow output of the encoder. In HFEM, the deep features of
the encoders complement each other by aggregation. Meanwhile, the attention
mechanism redistributes the weight of the aggregated features, weakening the
conflicting redundant parts and highlighting the information useful to the
task. GAM combines features from the encoder and decoder features, as well as
computes global dependencies to prevent receptive field locality. Experimental
results on five public datasets show that the proposed method not only can
segment multiple types of polyps but also has advantages over current
state-of-the-art methods in both accuracy and generalization ability.


  We introduce a novel parameterization of complex unitary matrices, which
allows for the efficient photonic implementation of arbitrary linear discrete
unitary operators. The proposed architecture is built on factorizing an $N
\times N$ unitary matrix into interlaced discrete fractional Fourier transforms
and $N$-parameter diagonal phase shifts. We show that such a configuration can
represent arbitrary unitary operators with $N+1$ phase layers. We discuss a
gradient-based algorithm for finding the optimal phase parameters for
implementing a given unitary matrix. By increasing the number of phase layers
beyond the critical value of $N+1$, the optimization consistently converges
faster as the system becomes over-determined. We propose an integrated photonic
circuit realization of this architecture with coupled waveguide arrays and
reconfigurable phase modulators. The proposed architecture can pave the way for
developing novel families of programmable photonic circuits for optical
classical and quantum information processing.


  A ubiquitous task in processing electronic medical data is the assignment of
standardized codes representing diagnoses and/or procedures to free-text
documents such as medical reports. This is a difficult natural language
processing task that requires parsing long, heterogeneous documents and
selecting a set of appropriate codes from tens of thousands of
possibilities---many of which have very few positive training samples. We
present a deep learning system that advances the state of the art for the
MIMIC-III dataset, achieving a new best micro F1-measure of 55.85\%,
significantly outperforming the previous best result (Mullenbach et al. 2018).
We achieve this through a number of enhancements, including two major novel
contributions: multi-view convolutional channels, which effectively learn to
adjust kernel sizes throughout the input; and attention regularization,
mediated by natural-language code descriptions, which helps overcome sparsity
for thousands of uncommon codes. These and other modifications are selected to
address difficulties inherent to both automated coding specifically and deep
learning generally. Finally, we investigate our accuracy results in detail to
individually measure the impact of these contributions and point the way
towards future algorithmic improvements.


  The Hopf-Galois structures on normal extensions $K/k$ with $G=Gal(K/k)$ are
in one-to-one correspondence with the set of regular subgroups $N\leq
B=Perm(G)$ that are normalized by the left regular representation
$\lambda(G)\leq B$. Each such $N$ corresponds to a Hopf algebra $H_N=(K[N])^G$
that acts on $K/k$. Such regular subgroups $N$ need not be isomorphic to $G$
but must have the same order. One can subdivide the totality of all such $N$
into collections $R(G,[M])$ which is the set of those regular $N$ normalized by
$\lambda(G)$ and isomorphic to a given abstract group $M$ where $|M|=|G|$.
There arises an injective correspondence between the characteristic subgroups
of a given $N$ an d the set of subgroups of $G$ stemming from the Galois
correspondence between sub-Hopf algebras of $H_N$ and intermediate fields
$k\subseteq F\subseteq K$. We utilize this correspondence to show that for
certain pairings $(G,[M])$, the collection $R(G,[M])$ must be empty.


  In this paper we initiate the study of birational Kleinian groups, i.e.\
groups of birational transformations of complex projective varieties acting in
a free, properly discontinuous and cocompact way on an open set of the variety
with respect to the usual topology. We obtain a classification in dimension
two.


  We study dust and associated molecular gas in 352 nearby early-type galaxies
(ETGs) with prominent dust lanes. 65% of these `dusty ETGs' (D-ETGs) are
morphologically disturbed, suggesting a merger origin. This is consistent with
the D-ETGs residing in lower density environments compared to the controls
drawn from the general ETG population. 80% of D-ETGs inhabit the field
(compared to 60% of the controls) and <2% inhabit clusters (compared to 10% of
the controls). Compared to the controls, D-ETGs exhibit bluer UV-optical
colours (indicating enhanced star formation) and an AGN fraction that is more
than an order of magnitude greater (indicating higher incidence of nuclear
activity). The clumpy dust mass residing in large-scale features is estimated,
using the SDSS r-band images, to be 10^{4.5}-10^{6.5} MSun. A comparison to the
total (clumpy + diffuse) dust masses- calculated using the far-IR fluxes of 15%
of the D-ETGs that are detected by the IRAS- indicates that only ~20% of the
dust resides in these large-scale features. The dust masses are several times
larger than the maximum value expected from stellar mass loss, ruling out an
internal origin. The dust content shows no correlation with the blue
luminosity, indicating that it is not related to a galactic scale cooling flow.
No correlation is found with the age of the recent starburst, suggesting that
the dust is accreted directly in the merger rather than being produced in situ
by the triggered star formation. Using molecular gas-to-dust ratios of ETGs in
the literature we estimate that the median current and initial molecular gas
fraction are ~1.3% and ~4%, respectively. Recent work suggests that the merger
activity in nearby ETGs largely involves minor mergers (mass ratios between
1:10 and 1:4). If the IRAS-detected D-ETGs form via this channel, then the
original gas fractions of the accreted satellites are 20%-44%. [Abridged]


  Based on experimental observations in \textit{Daphnia}, we introduce an
agent-based model for the motion of single and swarms of animals. Each agent is
described by a stochastic equation that also considers the conditions for
active biological motion. An environmental potential further reflects local
conditions for \textit{Daphnia}, such as attraction to light sources. This
model is sufficient to describe the observed cycling behavior of single
\textit{Daphnia}. To simulate vortex swarming of many \textit{Daphnia}, i.e.
the collective rotation of the swarm in one direction, we extend the model by
considering avoidance of collisions. Two different ansatzes to model such a
behavior are developed and compared. By means of computer simulations of a
multi-agent system we show that local avoidance - as a special form of
asymmetric repulsion between animals - leads to the emergence of a vortex
swarm. The transition from uncorrelated rotation of single agents to the vortex
swarming as a function of the swarm size is investigated. Eventually, some
evidence of avoidance behavior in \textit{Daphnia} is provided by comparing
experimental and simulation results for two animals.


  Constructing ontologies from relational databases is an active research topic
in the Semantic Web domain. While conceptual mapping rules/principles of
relational databases and ontology structures are being proposed, several
software modules or plug-ins are being developed to enable the automatic
conversion of relational databases into ontologies. However, the correlation
between the resulting ontologies built automatically with plug-ins from
relational databases and the database-to-ontology mapping principles has been
given little attention. This study reviews and applies two Prot\'eg\'e
plug-ins, namely, DataMaster and OntoBase to automatically construct ontologies
from a relational database. The resulting ontologies are further analysed to
match their structures against the database-to-ontology mapping principles. A
comparative analysis of the matching results reveals that OntoBase outperforms
DataMaster in applying the database-to-ontology mapping principles for
automatically converting relational databases into ontologies.


  In these notes we generalize the Ohsawa's results on the Hartogs extension
phenomenon in the complement of effective divisors in K\"ahler manifolds with
semipositive non-flat normal bundle. Namely, we prove that the Hartogs
extension phenomenon occurs in the complement of effective and nef divisors
with connected supports in K\"ahler manifolds. We use homological algebra
methods instead of a construction of the $(n-1)$-convex exhaustion function.
Also, the Demailly-Peternell vanishing theorem is a crucial argument for us.
Moreover, we obtain geometric characterizations of the Hartogs phenomenon for
the complement of basepoint-free divisors.


  We give a formula for the duality structure of the 3-manifold obtained by
doing zero-framed surgery along a knot in the 3-sphere, starting from a diagram
of the knot. We then use this to give a combinatorial algorithm for computing
the twisted Blanchfield pairing of such 3-manifolds. With the twisting defined
by Casson-Gordon style representations, we use our computation of the twisted
Blanchfield pairing to show that some subtle satellites of genus two ribbon
knots yield non-slice knots. The construction is subtle in the sense that, once
based, the infection curve lies in the second derived subgroup of the knot
group, and that we identify these infection curves explicitly.


  Numerous particle physics experiments utilize gadolinium (Gd), a rare earth
element with the most significant neutron capture cross-section among all
elements, to detect anti-neutrinos via inverse beta-decays or to remove
neutron-induced background events. For example, to load Gd into water Cherenkov
detectors, $\mathrm{{Gd_{2}(SO_{4})_{3}\cdot 8H_{2}O}}$ is dissolved and rare
event search experiments are required to screen for radioactive impurities in
$\mathrm{{Gd_{2}(SO_{4})_{3}\cdot 8H_{2}O}}$ before dissolution. This study
developed a new method to rapidly measure the radium-226($\mathrm{^{226}Ra}$)
concentration in $\mathrm{{Gd_{2}(SO_{4})_{3}\cdot 8H_{2}O}}$. This method
requires only three days to measure a batch of samples, as opposed to the usual
method using high-purity germanium detectors, which takes approximately 20 days
after arrival. The detection limit for the measurement of $\mathrm{^{226}Ra}$
is 0.32 mBq/kg. This method has been already used for
$\mathrm{{Gd_{2}(SO_{4})_{3}\cdot 8H_{2}O}}$ screening at the Super-Kamiokande
Gd(SK-Gd) project, and it can be applied to future experiments.


  A class of above-barrier quantum-scattering problems is shown to provide an
experimentally-accessible platform for studying $\mathcal{PT}$-symmetric
Schr\"odinger equations that exhibit spontaneous $\mathcal{PT}$ symmetry
breaking despite having purely real potentials. These potentials are
one-dimensional, inverted, and unstable and have the form $V(x) = - \lvert
x\rvert^p$ ($p>0$), terminated at a finite length or energy to a constant value
as $x\to \pm\infty$. The signature of unbroken $\mathcal{PT}$ symmetry is the
existence of reflectionless propagating states at discrete real energies up to
arbitrarily high energy. In the $\mathcal{PT}$-broken phase, there are no such
solutions. In addition, there exists an intermediate mixed phase, where
reflectionless states exist at low energy but disappear at a fixed finite
energy, independent of termination length. In the mixed phase exceptional
points (EPs) occur at specific $p$ and energy values, with a quartic dip in the
reflectivity in contrast to the quadratic behavior away from EPs.
$\mathcal{PT}$-symmetry-breaking phenomena have not been previously predicted
in a quantum system with a real potential and no reservoir coupling. The
effects predicted here are measurable in standard cold-atom experiments with
programmable optical traps. The physical origin of the symmetry-breaking
transition is elucidated using a WKB force analysis that identifies the spatial
location of the above-barrier scattering.


  Phylogenetic networks provide a way to describe and visualize evolutionary
histories that have undergone so-called reticulate evolutionary events such as
recombination, hybridization or horizontal gene transfer. The level k of a
network determines how non-treelike the evolution can be, with level-0 networks
being trees. We study the problem of constructing level-k phylogenetic networks
from triplets, i.e. phylogenetic trees for three leaves (taxa). We give, for
each k, a level-k network that is uniquely defined by its triplets. We
demonstrate the applicability of this result by using it to prove that (1) for
all k of at least one it is NP-hard to construct a level-k network consistent
with all input triplets, and (2) for all k it is NP-hard to construct a level-k
network consistent with a maximum number of input triplets, even when the input
is dense. As a response to this intractability we give an exact algorithm for
constructing level-1 networks consistent with a maximum number of input
triplets.


  We characterize the groupoids for which an operator is Fredholm if, and only
if, its principal symbol and all its boundary restrictions are invertible. A
groupoid with this property is called {\em Fredholm}. Using results on the
Effros-Hahn conjecture, we show that an almost amenable, Hausdorff, second
countable groupoid is Fredholm. Many groupoids, and hence many
pseudodifferential operators appearing in practice, fit into this framework. In
particular, one can use these results to characterize the Fredholm operators on
manifolds with cylindrical and poly-cylindrical ends, on manifolds that are
asymptotically Euclidean or asymptotically hyperbolic, on products of such
manifolds, and on many others. Moreover, we show that the desingularization of
Lie groupoids preserves the class of Fredholm groupoids.


  In this paper, we study a maximization and a minimization problem associated
with a Poisson boundary value problem. Optimal solutions in a set of
rearrangements of a given function define stationary and stable flows of an
ideal fluid in two dimensions. The main contribution of this paper is to
determine the optimal solutions. At first, we derive the solutions analytically
when the problems are in low contrast regime. Moreover, it is established that
the solutions of both problems are unique. Secondly, for the high contrast
regime, two optimization algorithms are developed. For the minimization
problem, we prove that our algorithm converges to the global minimizer
regardless of the initializer. The maximization algorithm is capable of
deriving all local maximizers including the global one. Numerical experiments
leads us to a conjecture about the location of the maximizers in the set of
rearrangements of a function.


  Repeated games have provided an explanation how mutual cooperation can be
achieved even if defection is more favorable in a one-shot game in prisoner's
dilemma situation. Recently found zero-determinant strategies have
substantially been investigated in evolutionary game theory. The original
memory-one zero-determinant strategies unilaterally enforce linear relations
between average payoffs of players. Here, we extend the concept of
zero-determinant strategies to memory-two strategies in repeated games.
Memory-two zero-determinant strategies unilaterally enforce linear relations
between correlation functions of payoffs and payoffs at the previous round.
Examples of memory-two zero-determinant strategy in the repeated prisoner's
dilemma game are provided, some of which generalize the Tit-for-Tat strategy to
memory-two case. Extension of zero-determinant strategies to memory-$n$ case
with $n\geq 2$ is also straightforward.


  In this paper we study the problem of identifying active subcarriers in an
OFDM signal from compressive measurements sampled at sub-Nyquist rate. The
problem is of importance in Cognitive Radio systems when secondary users (SUs)
are looking for available spectrum opportunities to communicate over them while
sensing at Nyquist rate sampling can be costly or even impractical in case of
very wide bandwidth. We first study the effect of timing offset and derive the
necessary and sufficient conditions for signal recovery in the oracle-assisted
case when the true active sub-carriers are assumed known. Then we propose an
Orthogonal Matching Pursuit (OMP)-based joint sparse recovery method for
identifying active subcarriers when the timing offset is known. Finally we
extend the problem to the case of unknown timing offset and develop a joint
dictionary learning and sparse approximation algorithm, where in the dictionary
learning phase the timing offset is estimated and in the sparse approximation
phase active subcarriers are identified. The obtained results demonstrate that
active subcarrier identification can be carried out reliably, by using the
developed framework.


  This paper reports on an effort of reproducing the organizers' baseline as
well as the top performing participant submission at the 2021 edition of the
TREC Conversational Assistance track. TREC systems are commonly regarded as
reference points for effectiveness comparison. Yet, the papers accompanying
them have less strict requirements than peer-reviewed publications, which can
make reproducibility challenging. Our results indicate that key practical
information is indeed missing. While the results can be reproduced within a 19%
relative margin with respect to the main evaluation measure, the relative
difference between the baseline and the top performing approach shrinks from
the reported 18% to 5%. Additionally, we report on a new set of experiments
aimed at understanding the impact of various pipeline components. We show that
end-to-end system performance can indeed benefit from advanced retrieval
techniques in either stage of a two-stage retrieval pipeline. We also measure
the impact of the dataset used for fine-tuning the query rewriter and find that
employing different query rewriting methods in different stages of the
retrieval pipeline might be beneficial. Moreover, these results are shown to
generalize across the 2020 and 2021 editions of the track. We conclude our
study with a list of lessons learned and practical suggestions.


  The aim of this paper is to make sample computations with the Salvetti
complex of the "center of mass" arrangement introduced in [arXiv:math/0611732]
by Cohen and Kamiyama. We compute the homology of the Salvetti complex of these
arrangements with coefficients in the sign representation of symmetric groups
on F_p in the case of four particles. We show, when p is an odd prime, the
homology is isomorphic to the homology of the configuration space F(C,4) of
distinct four points in the complex plane with the same coefficients. When p=2,
we show the homology is different from that of F(C,4), hence obtain an
alternative and more direct proof of a theorem of Cohen and Kamiyama in
[arXiv:math/0611732].


  Aims: We wish to establish whether sequential star formation is taking place
at the periphery of the Galactic HII region Sh2-212.
  Methods: We present CO millimetre observations of this region obtained at the
IRAM 30-m telescope to investigate the distribution of associated molecular
material. We also use deep JHK observations obtained at the CFHT to study the
stellar content of the region, and radio observations obtained at the VLA to
look for the presence of an ultra-compact (UC) HII region and for maser
emission.
  Results: In the optical, Sh2-212 is spherically symmetric around its central
exciting cluster. This HII region is located along a molecular filament. A
thin, well-defined half ring of molecular material surrounds the brightest part
of the HII region at the rear and is fragmented. The most massive fragment
(~200 solar masses) contains a massive young stellar object displaying a
near-IR excess; its spectral energy distribution indicates a high-mass
(~14solar masses), high-temperature (~30000K), and high-luminosity (~17000
solar luminosities) source. This object ionizes a UC HII region.
  Conclusions: Sh2-212 is a good example of massive-star formation triggered
via the collect and collapse process. The massive YSO observed at its periphery
is a good candidate for a massive star formed in isolation.


  We show that the system of equations \begin{align*} \sum_{i=1}^s
(x_i^j-y_i^j) = a_j \qquad (1 \le j \le k) \end{align*} has appreciably fewer
solutions in the subcritical range $s < k(k+1)/2$ than its homogeneous
counterpart, provided that $a_\ell \neq 0$ for some $\ell \le k-1$. Our methods
use Vinogradov's mean value theorem in combination with a shifting argument.


  In this paper, we investigate the behavior of the heavy quark potential in
the backgrounds with hyperscaling violation. The metrics are covariant under a
generalized Lifshitz scaling symmetry with the dynamical Lifshitz parameter $z$
and hyperscaling violation exponent $\theta$. We calculate the potential for a
certain range of $z$ and $\theta$ and discuss how it changes in the presence of
the two parameters. Moreover, we add a constant electric field to the
backgrounds and study its effects on the potential. It is shown that the heavy
quark potential depends on the non-relativistic parameters. Also, the presence
of the constant electric field tends to increase the potential.


  In this paper, we investigate complexity of anisotropic cylindrical object
under the influence of electromagnetic field in $f(G,T)$ theory, where $G$ and
$T$ indicate the Gauss-Bonnet term and trace of the stress-energy tensor,
respectively. For this purpose, we calculate the modified field equations,
non-conservation equation and mass distributions that assist in comprehending
the structure of astrophysical objects. The Riemann tensor is divided into
different structure scalars, among which one is called the complexity factor.
This factor is used to measure complexity of the system due to the involvement
of inhomogeneous energy density, anisotropic pressure and charge. The vanishing
of the complexity factor is employed as a constraint to formulate charged
static solutions for the Gokhroo-Mehra model and polytropic equation of state.
We conclude that the presence of charge reduces the complexity of the
anisotropic system.


  We study the plasma-vacuum interface problem in relativistic
magnetohydrodynamics for the case when the plasma density does not go to zero
continuously, but jumps. In the vacuum region we consider the Maxwell equations
for electric and magnetic fields. We show that a sufficiently large vacuum
electric field can make the planar interface violently unstable. By using a
suitable secondary symmetrization of the vacuum Maxwell equations, we find a
sufficient condition that precludes violent instabilities. Under this condition
we derive an energy a priori estimate in the anisotropic weighted Sobolev space
$H^1_*$ for the variable coefficients linearized problem for nonplanar
plasma-vacuum interfaces.


  In this paper, we construct a dumbbell domain for which the associated
principle $\infty$-eigenvalue is not simple. This gives a negative answer to
the outstanding problem posed by Juutinen-Lindquivst-Manfredi ("The
$\infty$-eigenvalue problem", Arch. Ration. Mech. Anal. 148, 1999, no.2,
89-105). It remains a challenge to determine whether simplicity holds for
convex domains.


  The number of publications considering Narrow-Line Seyfert 1 galaxies has
increased dramatically in recent years. Especially after the launch of the
X-ray missions ROSAT and ASCA, Narrow-Line Seyfert 1s have become very popular.
In these proceedings I will give an overview of how they are distributed over
the electromagnetic spectrum. I will describe what we know about them at radio,
infrared, optical, and X-ray bands, and how they differ and how they are
similar to Broad-Line Seyfert 1s. Finally I will introduce a method to find
them with high probability.


  This paper presents a comparative analysis of the performances of three
portfolio optimization approaches. Three approaches of portfolio optimization
that are considered in this work are the mean-variance portfolio (MVP),
hierarchical risk parity (HRP) portfolio, and reinforcement learning-based
portfolio. The portfolios are trained and tested over several stock data and
their performances are compared on their annual returns, annual risks, and
Sharpe ratios. In the reinforcement learning-based portfolio design approach,
the deep Q learning technique has been utilized. Due to the large number of
possible states, the construction of the Q-table is done using a deep neural
network. The historical prices of the 50 premier stocks from the Indian stock
market, known as the NIFTY50 stocks, and several stocks from 10 important
sectors of the Indian stock market are used to create the environment for
training the agent.


  We consider the minimum of a super-critical branching random walk.
Addario-Berry and Reed [Ann. Probab. 37 (2009) 1044-1079] proved the tightness
of the minimum centered around its mean value. We show that a convergence in
law holds, giving the analog of a well-known result of Bramson [Mem. Amer.
Math. Soc. 44 (1983) iv+190] in the case of the branching Brownian motion.


  Mechanotransduction, the biological response to mechanical stress, is often
initiated by the activation of mechanosensitive (MS) proteins upon mechanically
induced deformations of the cell membrane. A current challenge to fully
understand this process is to predict how lipid bilayers deform upon
application of mechanical stress. In this context, it is now well established
that anionic lipids influence the function of many proteins. Here, we test the
hypothesize that anionic lipids could indirectly modulate MS proteins by
alteration of the lipid bilayer mechanical properties. Using all-atom molecular
dynamics simulations, we computed the bilayer bending rigidity (K_C), the area
compressibility (K_A), and the surface shear viscosity ({\eta}_m) of
phosphocholine (PC) lipid bilayers containing or not phosphatidylserine (PS) or
phosphatidylinositol bisphosphate (PIP2) at physiological concentrations in the
lower leaflet. Tensionless leaflets were first checked for each asymmetric
bilayer model, and a formula for embedding an asymmetric channel in an
asymmetric bilayer is proposed. Results from two different sized bilayers show
consistently that the addition of 20% surface charge in the lower leaflet of PC
bilayer by PIP2 has minimal impact on its mechanical properties, while PS
reduced the bilayer bending rigidity by 22%. As a comparison, supplementing the
PIP2-enriched PC membrane with 30% cholesterol, a known rigidifying steroid
lipid, produces a significant increase in all three mechanical constants.
Analysis of pairwise splay moduli suggests that the effect of anionic lipids on
bilayer bending rigidity largely depends on the number of anionic lipid pairs
formed during simulations. The potential implication of bilayer bending
rigidity is discussed in the framework of mechanosensitive Piezo channels.


  We present the numerical simulations for an electron-beam-driven and
loss-cone-driven electron-cyclotron maser (ECM) with different plasma
parameters and different magnetic field strengths for a relatively small region
and short time-scale in an attempt to interpret the recent discovered intense
radio emission from ultracool dwarfs. We find that a large amount of
electromagnetic field energy can be effectively released from the beam-driven
ECM, which rapidly heats the surrounding plasma. A rapidly developed
high-energy tail of electrons in velocity space (resulting from the heating
process of the ECM) may produce the radio continuum depending on the initial
strength of the external magnetic field and the electron beam current. Both
significant linear polarization and circular polarization of electromagnetic
waves can be obtained from the simulations. The spectral energy distributions
of the simulated radio waves show that harmonics may appear from 10 to
70$\nu_{\rm pe}$ ($\nu_{\rm pe}$ is the electron plasma frequency) in the
non-relativistic case and from 10 to 600$\nu_{\rm pe}$ in the relativistic
case, which makes it difficult to find the fundamental cyclotron frequency in
the observed radio frequencies. A wide frequency band should therefore be
covered by future radio observations.


  Influence maximization aims to select k most-influential vertices or seeds in
a network, where influence is defined by a given diffusion process. Although
computing optimal seed set is NP-Hard, efficient approximation algorithms
exist. However, even state-of-the-art parallel implementations are limited by a
sampling step that incurs large memory footprints. This in turn limits the
problem size reach and approximation quality. In this work, we study the memory
footprint of the sampling process collecting reverse reachability information
in the IMM (Influence Maximization via Martingales) algorithm over large
real-world social networks. We present a memory-efficient optimization approach
(called HBMax) based on Ripples, a state-of-the-art multi-threaded parallel
influence maximization solution. Our approach, HBMax, uses a portion of the
reverse reachable (RR) sets collected by the algorithm to learn the
characteristics of the graph. Then, it compresses the intermediate reverse
reachability information with Huffman coding or bitmap coding, and queries on
the partially decoded data, or directly on the compressed data to preserve the
memory savings obtained through compression. Considering a NUMA architecture,
we scale up our solution on 64 CPU cores and reduce the memory footprint by up
to 82.1% with average 6.3% speedup (encoding overhead is offset by performance
gain from memory reduction) without loss of accuracy. For the largest tested
graph Twitter7 (with 1.4 billion edges), HBMax achieves 5.9X compression ratio
and 2.2X speedup.


  We demonstrate the guiding of neutral atoms by the magnetic fields due to
microfabricated current-carrying wires on a chip. Atoms are guided along a
magnetic field minimum parallel to and above the current-carrying wires. Two
waveguide configurations are demonstrated: one using two wires with an external
magnetic field, and a second using four wires without an external field. These
waveguide geometries can be extended to integrated atom optics circuits,
including beamsplitters.


  Evidently, the linear superposition principle can not be exactly established
as a general principle in the presence of nonlinearity, and, at the first
glance, there is no expectation for it to hold even approximately. In this
letter, it is shown that the balance of different nonlinear effects describes
what linear superpositions may occur in nonlinear systems. The heavenly
equations are of significance in several scientific fields, especially in
relativity, gravity, field theory, and fluid dynamics. A special type of
implicit shock wave solution with three two-dimensional arbitrary functions of
the general heavenly equation is revealed. Restrict the two-dimensional
arbitrary functions to some types of one-dimensional arbitrary functions, it is
found that the nonlinear effects can be balanced such that the "impossible"
linear superposition solutions can be nontrivially constituted to new solutions
of the general heavenly equation.


  To investigate the role of information flow in group formation, we introduce
a model of communication and social navigation. We let agents gather
information in an idealized network society, and demonstrate that heterogeneous
groups can evolve without presuming that individuals have different interests.
In our scenario, individuals' access to global information is constrained by
local communication with the nearest neighbors on a dynamic network. The result
is reinforced interests among like-minded agents in modular networks; the flow
of information works as a glue that keeps individuals together. The model
explains group formation in terms of limited information access and highlights
global broadcasting of information as a way to counterbalance this
fragmentation. To illustrate how the information constraints imposed by the
communication structure affects future development of real-world systems, we
extrapolate dynamics from the topology of four social networks.


  Hardware generation languages (HGLs) increase hardware design productivity by
creating parameterized modules and test benches. Unfortunately, existing tools
are not widely adopted due to several demerits, including limited support for
asynchronous circuits and unknown states, lack of concise and efficient
language features, and low integration of simulation and verification
functions. This paper introduces PyHGL, an open-source Python framework that
aims to provide a simple and unified environment for hardware generation,
simulation, and verification. PyHGL language is a syntactical superset of
Python, which greatly reduces the lines of code (LOC) and improves productivity
by providing unique features such as dynamic typing, vectorized operations, and
automatic port deduction. In addition, PyHGL integrates an event-driven
simulator that simulates the asynchronous behaviors of digital circuits using
three-state logic. We also propose an algorithm that eliminates the calculation
and transmission overhead of unknown state propagation for binary stimuli. The
results suggest that PyHGL code is up to 6.1x denser than traditional RTL and
generates high-quality synthesizable RTL code. Moreover, the optimized
simulator achieves 2.9x speed up and matches the performance of a commonly used
open-source logic simulator.


  We compute the {\Omega}^1(G) invariant when 1 {\to} H {\to} G {\to} K {\to} 1
is a split short exact sequence. We use this result to compute the invariant
for pure and full braid groups on compact surfaces. Applications to twisted
conjugacy classes and to finite generation of commutator subgroups are also
discussed.


  We compute the rational points on the Atkin-Lehner quotient $X^+_0(125)$
using the quadratic Chabauty method. Our work completes the study of
exceptional rational points on the curves $X^+_0(N)$ of genus between 2 and 6.
Together with the work of several authors, this completes the proof of a
conjecture of Galbraith.


  The ${\bm E}\times{\bm B}$ drift motion of charged test particle dynamics in
the Scrape Off Layer (SOL)is analyzed to investigate a transport control
strategy based on Hamiltonian dynamics. We model SOL turbulence using a 2D
non-linear fluid code based on interchange instability which was found to
exhibit intermittent dynamics of the particle flux. The effect of a small and
appropriate modification of the turbulent electric potential is studied with
respect to the chaotic diffusion of test particle dynamics. Over a significant
range in the magnitude of the turbulent electrostatic field, a three-fold
reduction of the test particle diffusion coefficient is achieved.


  Context. Remote sensing of weak and small-scale solar magnetic fields is of
utmost relevance for a number of important open questions in solar physics.
This requires the acquisition of spectropolarimetric data with high spatial
resolution (0.1 arcsec) and low noise (1e-3 to 1e-5 of the continuum
intensity). The main limitations to obtain these measurements from the ground,
are the degradation of the image resolution produced by atmospheric seeing and
the seeing-induced crosstalk (SIC). Aims. We introduce the prototype of the
Fast Solar Polarimeter (FSP), a new ground-based, high-cadence polarimeter that
tackles the above-mentioned limitations by producing data that are optimally
suited for the application of post-facto image restoration, and by operating at
a modulation frequency of 100 Hz to reduce SIC. Results. The pnCCD camera
reaches 400 fps while keeping a high duty cycle (98.6 %) and very low noise
(4.94 erms). The modulator is optimized to have high (> 80%) total polarimetric
efficiency in the visible spectral range. This allows FSP to acquire 100
photon-noise-limited, full-Stokes measurements per second. We found that the
seeing induced signals present in narrow-band, non-modulated, quiet-sun
measurements are (a) lower than the noise (7e-5) after integrating 7.66 min,
(b) lower than the noise (2.3e-4) after integrating 1.16 min and (c) slightly
above the noise (4e-3) after restoring case (b) by means of a multi-object
multi-frame blind deconvolution. In addition, we demonstrate that by using only
narrow-band images (with low SNR of 13.9) of an active region, we can obtain
one complete set of high-quality restored measurements about every 2 s.


  The discovery of unusual heat conduction properties of graphene has led to a
surge of theoretical and experimental studies of phonon transport in
two-dimensional material systems. The rapidly developing graphene thermal field
spans from theoretical physics to practical engineering applications. In this
invited review we outline different theoretical approaches developed for
describing phonon transport in graphene and provide comparison with available
experimental thermal conductivity data. A special attention is given to
analysis of the recent theoretical results for the phonon thermal conductivity
of graphene and few-layer graphene, the effects of the strain, defects,
isotopes and edge scattering on the acoustic phonon transport in these material
systems.


  We present a derivation of the Gribov equation for the gluon/photon Green's
function D(q). Our derivation is based on the second derivative of the
gauge-invariant quantity Tr ln D(q), which we interpret as the gauge-boson
`self-loop'. By considering the higher-order corrections to this quantity, we
are able to obtain a Gribov equation which sums the logarithmically enhanced
corrections. By solving this equation, we obtain the non-perturbative running
coupling in both QCD and QED. In the case of QCD, alpha_S has a singularity in
the space-like region corresponding to super-criticality, which is argued to be
resolved in Gribov's light-quark confinement scenario. For the QED coupling in
the UV limit, we obtain a \propto Q^2 behaviour for space-like Q^2=-q^2. This
implies the decoupling of the photon and an NJLVL-type effective theory in the
UV limit.


  Traditionally, the Bayesian optimal auction design problem has been
considered either when the bidder values are i.i.d., or when each bidder is
individually identifiable via her value distribution. The latter is a
reasonable approach when the bidders can be classified into a few categories,
but there are many instances where the classification of bidders is a
continuum. For example, the classification of the bidders may be based on their
annual income, their propensity to buy an item based on past behavior, or in
the case of ad auctions, the click through rate of their ads. We introduce an
alternate model that captures this aspect, where bidders are \emph{a priori}
identical, but can be distinguished based (only) on some side information the
auctioneer obtains at the time of the auction.
  We extend the sample complexity approach of Dhangwatnotai, Roughgarden, and
Yan (2014) and Cole and Roughgarden (2014) to this model and obtain almost
matching upper and lower bounds. As an aside, we obtain a revenue monotonicity
lemma which may be of independent interest. We also show how to use Empirical
Risk Minimization techniques to improve the sample complexity bound of Cole and
Roughgarden (2014) for the non-identical but independent value distribution
case.


  MagAO-X system is a new adaptive optics for the Magellan Clay 6.5m telescope.
MagAO-X has been designed to provide extreme adaptive optics (ExAO) performance
in the visible. VIS-X is an integral-field spectrograph specifically designed
for MagAO-X, and it will cover the optical spectral range (450 - 900 nm) at
high-spectral (R=15.000) and high-spatial resolution (7 mas spaxels) over a
0.525 arsecond field of view. VIS-X will be used to observe accreting
protoplanets such as PDS70 b and c. End-to-end simulations show that the
combination of MagAO-X with VIS-X is 100 times more sensitive to accreting
protoplanets than any other instrument to date. VIS-X can resolve the planetary
accretion lines, and therefore constrain the accretion process. The instrument
is scheduled to have its first light in Fall 2021. We will show the lab
measurements to characterize the spectrograph and its post-processing
performance.


  We use a coalescence model to generate $f_{0}$(980) particles for four
configurations: ${s\bar{s}}$ meson, ${u\bar{u}s\bar{s}}$ tetraquark,
${K^{+}K^{-}}$ molecule and $u\bar{u}$ p-wave state. The phase-space
information of the coalescing constituents is taken from a multi-phase
transport (AMPT) simulation of proton-proton and proton-lead collisions at the
LHC. It is shown that the transverse momentum spectra and production yields of
$f_0(980)$ differ significantly among the configurations. It is suggested that
the $p_T$ spectra of the $f_0(980)$ compared to those of other hadrons (such as
pion) and the ratio of the $f_0(980)$ $p_T$ spectra in pPb over pp can be
exploited to tell the configuration of the $f_0(980)$.


  We introduce Automorphism-based graph neural networks (Autobahn), a new
family of graph neural networks. In an Autobahn, we decompose the graph into a
collection of subgraphs and apply local convolutions that are equivariant to
each subgraph's automorphism group. Specific choices of local neighborhoods and
subgraphs recover existing architectures such as message passing neural
networks. Our formalism also encompasses novel architectures: as an example, we
introduce a graph neural network that decomposes the graph into paths and
cycles. The resulting convolutions reflect the natural way that parts of the
graph can transform, preserving the intuitive meaning of convolution without
sacrificing global permutation equivariance. We validate our approach by
applying Autobahn to molecular graphs, where it achieves results competitive
with state-of-the-art message passing algorithms.


  The discovery of genomic polymorphisms influencing gene expression (also
known as expression quantitative trait loci or eQTLs) can be formulated as a
sparse Bayesian multivariate/multiple regression problem. An important aspect
in the development of such models is the implementation of bespoke inference
methodologies, a process which can become quite laborious, when multiple
candidate models are being considered. We describe automatic, black-box
inference in such models using Stan, a popular probabilistic programming
language. The utilisation of systems like Stan can facilitate model prototyping
and testing, thus accelerating the data modelling process. The code described
in this chapter can be found at https://github.com/dvav/eQTLBookChapter.


  In object detection, bounding box regression (BBR) is a crucial step that
determines the object localization performance. However, we find that most
previous loss functions for BBR have two main drawbacks: (i) Both $\ell_n$-norm
and IOU-based loss functions are inefficient to depict the objective of BBR,
which leads to slow convergence and inaccurate regression results. (ii) Most of
the loss functions ignore the imbalance problem in BBR that the large number of
anchor boxes which have small overlaps with the target boxes contribute most to
the optimization of BBR. To mitigate the adverse effects caused thereby, we
perform thorough studies to exploit the potential of BBR losses in this paper.
Firstly, an Efficient Intersection over Union (EIOU) loss is proposed, which
explicitly measures the discrepancies of three geometric factors in BBR, i.e.,
the overlap area, the central point and the side length. After that, we state
the Effective Example Mining (EEM) problem and propose a regression version of
focal loss to make the regression process focus on high-quality anchor boxes.
Finally, the above two parts are combined to obtain a new loss function, namely
Focal-EIOU loss. Extensive experiments on both synthetic and real datasets are
performed. Notable superiorities on both the convergence speed and the
localization accuracy can be achieved over other BBR losses.


  A path integral formalism for multispecies anyons is introduced, whereby
partition functions are expressed in terms of generating functions of winding
number probability distributions. In a certain approximation, the equation of
state for exclusion statistics follows. By Monte Carlo simulation, third-order
cluster and virial coefficients are found numerically.


  For a fixed integer a>1, we suggest that the probability of nullity of the
p-Fermat quotient q(p,a) is much lower than 1/p for any arbitrary large prime
number p. For this we use various heuristics, justified by means of numerical
computations and analytical results, which may imply the finiteness of the
q(p,a) equal to 0 and the existence of integers a such that q(p,a) is different
from 0 for all p. However no proofs are obtained concerning these heuristics.


  Human activity recognition has grown in popularity with its increase of
applications within daily lifestyles and medical environments. The goal of
having efficient and reliable human activity recognition brings benefits such
as accessible use and better allocation of resources; especially in the medical
industry. Activity recognition and classification can be obtained using many
sophisticated data recording setups, but there is also a need in observing how
performance varies among models that are strictly limited to using sensor data
from easily accessible devices: smartphones and smartwatches. This paper
presents the findings of different models that are limited to train using such
sensors. The models are trained using either the k-Nearest Neighbor, Support
Vector Machine, or Random Forest classifier algorithms. Performance and
evaluations are done by comparing various model performances using different
combinations of mobile sensors and how they affect recognitive performances of
models. Results show promise for models trained strictly using limited sensor
data collected from only smartphones and smartwatches coupled with traditional
machine learning concepts and algorithms.


  We demonstrate single-atom resolved imaging with a survival probability of
$0.99932(8)$ and a fidelity of $0.99991(1)$, enabling us to perform repeated
high-fidelity imaging of single atoms in tweezers for thousands of times. We
further observe lifetimes under laser cooling of more than seven minutes, an
order of magnitude longer than in previous tweezer studies. Experiments are
performed with strontium atoms in $813.4~\text{nm}$ tweezer arrays, which is at
a magic wavelength for the clock transition. Tuning to this wavelength is
enabled by off-magic Sisyphus cooling on the intercombination line, which lets
us choose the tweezer wavelength almost arbitrarily. We find that a single not
retro-reflected cooling beam in the radial direction is sufficient for
mitigating recoil heating during imaging. Moreover, this cooling technique
yields temperatures below $5~\mu$K, as measured by release and recapture.
Finally, we demonstrate clock-state resolved detection with average survival
probability of $0.996(1)$ and average state detection fidelity of $0.981(1)$.
Our work paves the way for atom-by-atom assembly of large defect-free arrays of
alkaline-earth atoms, in which repeated interrogation of the clock transition
is an imminent possibility.


  We study the two-species symbiotic contact process (2SCP), recently proposed
in [de Oliveira, Santos and Dickman, Phys. Rev. E {\bf 86}, 011121 (2012)] . In
this model, each site of a lattice may be vacant or host single individuals of
species A and/or B. Individuals at sites with both species present interact in
a symbiotic manner, having a reduced death rate, $\mu < 1$. Otherwise, the
dynamics follows the rules of the basic CP, with individuals reproducing to
vacant neighbor sites at rate $\lambda$ and dying at a rate of unity. We
determine the full phase diagram in the $\lambda-\mu$ plane in one and two
dimensions by means of exact numerical quasistationary distributions, cluster
approximations, and Monte Carlo simulations. We also study the effects of
asymmetric creation rates and diffusion of individuals. In two dimensions, for
sufficiently strong symbiosis (i.e., small $\mu$), the absorbing-state phase
transition becomes discontinuous for diffusion rates $D$ within a certain
range. We report preliminary results on the critical surface and tricritical
line in the $\lambda-\mu-D$ space. Our results raise the possibility that
strongly symbiotic associations of mobile species may be vulnerable to sudden
extinction under increasingly adverse conditions.


  For Boolean satisfiability problems, the structure of the solution space is
characterized by the solution graph, where the vertices are the solutions, and
two solutions are connected iff they differ in exactly one variable. In 2006,
Gopalan et al. studied connectivity properties of the solution graph and
related complexity issues for CSPs, motivated mainly by research on
satisfiability algorithms and the satisfiability threshold. They proved
dichotomies for the diameter of connected components and for the complexity of
the st-connectivity question, and conjectured a trichotomy for the connectivity
question. Recently, we were able to establish the trichotomy [arXiv:1312.4524].
  Here, we consider connectivity issues of satisfiability problems defined by
Boolean circuits and propositional formulas that use gates, resp. connectives,
from a fixed set of Boolean functions. We obtain dichotomies for the diameter
and the two connectivity problems: on one side, the diameter is linear in the
number of variables, and both problems are in P, while on the other side, the
diameter can be exponential, and the problems are PSPACE-complete. For
partially quantified formulas, we show an analogous dichotomy.


  From analysis of the DIRBE weekly averaged sky maps, we have detected
substantial flux in the 60 and 100 micron channels in excess of expected
zodiacal and Galactic emission. Two methods are used to separate zodiacal light
from more distant emission. Method I makes use of the time-dependence of the
North-South annual variation observed at the ecliptic poles. This method is
robust against errors in the inter-planetary dust (IPD) model, but does not
demonstrate isotropy of the background. Method II measures the ecliptic
latitude dependence of the dust over a range of ecliptic latitudes at solar
elongation e=90 degrees. This allows the excess to be determined in each week
of the DIRBE mission for high redundancy, but the results depend weakly on the
IPD model. Both methods give consistent results at 60 and 100 microns. The
observed signal is consistent with an isotropic background at the level \nu
I_\nu = 28.1 +- 1.8 +- 7(syst) nW/m^2/sr at 60 microns and 24.6 +- 2.5 +- 8
nW/m^2/sr at 100 microns.
  The IR excess detected at 140 and 240 microns by these methods agrees with
previous measurements, which are thought to be the cosmic infra-red background
(CIB). The detections at 60 and 100 microns are new. While this new excess is
not necessarily the CIB, we have ruled out all known sources of emission in the
solar system and Galaxy. We therefore tentatively interpret this signal as the
CIB and consider the implications of such energy production from the viewpoint
of star formation efficiency and black hole accretion efficiency. However, the
IR excess exceeds limits on the CIB derived from the inferred opacity of the
IGM to observed TeV photons, thus casting doubt on this interpretation. There
is currently no satisfactory explanation for the 60-100 micron excess.


  We characterize the operational task of environment-assisted distillation of
quantum coherence under different sets of free operations when only a finite
supply of copies of a given state is available. We first evaluate the one-shot
assisted distillable coherence exactly, and introduce a semidefinite
programming bound on it in terms of a smooth entropic quantity. We prove the
bound to be tight for all systems in dimensions 2 and 3, which allows us to
obtain computable expressions for the one-shot rate of distillation, establish
an analytical expression for the best achievable fidelity of assisted
distillation for any finite number of copies, and fully solve the problem of
asymptotic zero-error assisted distillation for qubit and qutrit systems. Our
characterization shows that all relevant sets of free operations in the
resource theory of coherence have exactly the same power in the task of
one-shot assisted coherence distillation, and furthermore resolves a conjecture
regarding the additivity of coherence of assistance in dimension 3.


  We focus on the descriptive approach to linear discriminant analysis for
matrix-variate data in the binary case. Under a separability assumption on row
and column variability, the most discriminant linear combinations of rows and
columns are determined by the singular value decomposition of the difference of
the class-averages with the Mahalanobis metric in the row and column spaces.
This approach provides data representations of data in two-dimensional or
three-dimensional plots and singles out discriminant components. An application
to electroencephalographic multi-sensor signals illustrates the relevance of
the method.


  As neural networks (NNs) are increasingly introduced into safety-critical
domains, there is a growing need to formally verify NNs before deployment. In
this work we focus on the formal verification problem of NN equivalence which
aims to prove that two NNs (e.g. an original and a compressed version) show
equivalent behavior. Two approaches have been proposed for this problem: Mixed
integer linear programming and interval propagation. While the first approach
lacks scalability, the latter is only suitable for structurally similar NNs
with small weight changes.
  The contribution of our paper has four parts. First, we show a theoretical
result by proving that the epsilon-equivalence problem is coNP-complete.
Secondly, we extend Tran et al.'s single NN geometric path enumeration
algorithm to a setting with multiple NNs. In a third step, we implement the
extended algorithm for equivalence verification and evaluate optimizations
necessary for its practical use. Finally, we perform a comparative evaluation
showing use-cases where our approach outperforms the previous state of the art,
both, for equivalence verification as well as for counter-example finding.


  We study the pion-nucleon P_33 and P_11 scattering, where the Delta and the
Roper resonances are seen, respectively. We use the Lippmann-Schwinger equation
extended to couple to a one-body state, and investigate nature of these
resonances by taking and omitting a one-baryon state into account. We see
validity and puzzle of the standard quark model interpretation, for the Delta
and the Roper resonances, respectively.


  Solar active region jets are small-scale collimated plasma eruptions that are
triggered from magnetic sites embedded in sunspot penumbral regions. Multiple
trigger mechanisms for recurrent jets are under debate. Vector magnetic field
data from SDO-HMI observations are used to analyze a prolific photospheric
configuration, identified in extreme ultraviolet observations as a `Coronal
Geyser', that triggered a set of at least 10 recurrent solar active region
jets. We focus on interpreting the magnetic fields of small-scale flaring sites
aiming to understand the processes that govern recurrent jet eruptions. We
perform a custom reprocessing of the SDO-HMI products, including disambiguation
and uncertainty estimation. We scrutinized the configuration and dynamics of
the photospheric magnetic structures. The magnetic configuration is described
via the analysis of the photospheric magnetic vertical fields, to identify the
process is responsible for driving the jet eruptions. We report that the two
widely debated magnetic trigger processes, namely magnetic flux cancellation
and magnetic flux emergence, appear to be responsible on a case by case basis
for generating each eruption in our set. We find that 4 of 10 jets were due to
flux cancellation while the rest were clearly not, and were more likely due to
flux emergence.


  Through a combination of X-ray diffraction, electrical transport, magnetic
susceptibility, and heat capacity measurements, we report the effect of La
doping on Sr in the newly discovered SrFBiS2 system. Superconducting transition
with critical temperature Tc of 2.8 K, developed from a semiconducting-like
normal state, was found in Sr0.5La0.5FBiS2. A strong diamagnetic signal and a
clear specific heat anomaly associated with this transition were observed,
confirming bulk superconductivity. The upper critical field Hc2(0) was
estimated to be 1 Tesla by using the Ginzburg-Landau approach. Our experiments
therefore demonstrate that bulk superconductivity can be achieved by electron
doping in the SrFBiS2 system.


  ePSproc provides codes for post-processing results from ePolyScat (ePS), a
suite of codes for the calculation of quantum scattering problems, developed
and released by Luchesse \& co-workers (Gianturco et al. 1994)(Natalense and
Lucchese 1999)(R. R. Lucchese and Gianturco 2016). ePS is a powerful
computational engine for solving scattering problems, but its inherent
complexity, combined with additional post-processing requirements, ranging from
simple visualizations to more complex processing involving further calculations
based on ePS outputs, present a significant barrier to use for most
researchers. ePSproc aims to lower this barrier by providing a range of
functions for reading, processing and plotting outputs from ePS. Since ePS
calculations are currently finding multiple applications in AMO physics (see
below), ePSproc is expected to have significant reuse potential in the
community, both as a basic tool-set for researchers beginning to use ePS, and
as a more advanced post-processing suite for those already using ePS. ePSproc
is currently written for Matlab/Octave, and distributed via Github:
https://github.com/phockett/ePSproc.


  Let $(M,F)$ be a connected Finsler space. An isometry of $(M,F)$ is called a
Clifford-Wolf translation (or simply CW-translation) if it moves all points the
same distance. The compact Finsler space $(M,F)$ is called restrictively
Clifford-Wolf homogeneous (restrictively CW-homogeneous) if for any two
sufficiently close points $x_1,x_2\in M$, there exists a CW-translation
$\sigma$ such that $\sigma(x_1)=x_2$. In this paper, we define the good
normalized datum for a homogeneous non-Riemannian $(\alpha,\beta)$-space, and
use it to study the restrictive CW-homogeneity of left invariant
$(\alpha,\beta)$-metrics on a compact connected semisimple Lie group. We prove
that a left invariant restrictively CW-homogeneous $(\alpha,\beta)$-metric on a
compact semisimple Lie group must be of the Randers type. This gives a complete
classification of left invariant $(\alpha,\beta)$-metrics on compact
semi-simple Lie groups which are restrictively Clifford-Wolf homogeneous.


  The bivariate normal density with unit variance and correlation $\rho$ is
well-known. We show that by integrating out $\rho$, the result is a function of
the maximum norm. The Bayesian interpretation of this result is that if we put
a uniform prior over $\rho$, then the marginal bivariate density depends only
on the maximal magnitude of the variables. The square-shaped isodensity contour
of this resulting marginal bivariate density can also be regarded as the
equally-weighted mixture of bivariate normal distributions over all possible
correlation coefficients. This density links to the Khintchine mixture method
of generating random variables. We use this method to construct the higher
dimensional generalizations of this distribution. We further show that for each
dimension, there is a unique multivariate density that is a differentiable
function of the maximum norm and is marginally normal, and the bivariate
density from the integral over $\rho$ is its special case in two dimensions.


  This paper summarizes Kormendy et al. (2009, ApJS, in press,
arXiv:0810.1681). We confirm that spheroidal galaxies have fundamental plane
correlations that are almost perpendicular to those for bulges and ellipticals.
Spheroidals are not dwarf ellipticals. They are structurally similar to
late-type galaxies. We suggest that they are defunct ("red and dead") late-type
galaxies transformed by a variety of gas removal processes. Minus spheroidals,
ellipticals come in two varieties: giant, non-rotating, boxy galaxies with
cuspy cores and smaller, rotating, disky galaxies that lack cores. We find a
new feature of this "E-E dichotomy": Coreless ellipticals have extra light at
the center with respect to an inward extrapolation of the outer Sersic profile.
We suggest that extra light is made in starbursts that swamp core scouring in
wet mergers. In general, only giant, core ellipticals contain X-ray gas halos.
We suggest that they formed in mergers that were kept dry by X-ray gas heated
by active galactic nuclei.


  The essential feature of a root-graded Lie algebra L is the existence of a
split semisimple subalgebra g with respect to which L is an integrable module
with weights in a possibly non-reduced root system S of the same rank as the
root system R of g. Examples include map algebras (maps from an affine scheme
to g, S = R), matrix algebras like sl_n(A) for a unital associative algebra A
(S = R = A_{n-1}), finite-dimensional isotropic central-simple Lie algebras (S
properly contains R in general), and some equivariant map algebras.
  In this paper we study the category of representations of a root-graded Lie
algebra L which are integrable as representations of g and whose weights are
bounded by some dominant weight of g. We link this category to the module
category of an associative algebra, whose structure we determine for map
algebras and sl_n(A). Our results unify previous work of Chari and her
collaborators on map algebras and of Seligman on isotropic Lie algebras.


  We describe a unitary scattering process, as observed from spatial infinity,
of massless scalar particles on an asymptotically flat Schwarzschild black hole
background. In order to do so, we split the problem in two different regimes
governing the dynamics of the scattering process. The first describes the
evolution of the modes in the region away from the horizon and can be analysed
in terms of the effective Regge-Wheeler potential. In the near horizon region,
where the Regge-Wheeler potential becomes insignificant, the WKB geometric
optics approximation of Hawking's is replaced by the near-horizon gravitational
scattering matrix that captures non-perturbative soft graviton exchanges near
the horizon. We perform an appropriate matching for the scattering solutions of
these two dynamical problems and compute the resulting Bogoliubov relations,
that combines both dynamics. This allows us to formulate an S-matrix for the
scattering process that is manifestly unitary. We discuss the analogue of the
(quasi)-normal modes in this setup and the emergence of gravitational echoes
that follow an original burst of radiation as the excited black hole relaxes to
equilibrium.


  We present a general method for accelerating by more than an order of
magnitude the convolution of pixelated function on the sphere with a
radially-symmetric kernel. Our method splits the kernel into a compact
real-space, and a compact spherical harmonic space component that can then be
convolved in parallel using an inexpensive commodity GPU and a CPU,
respectively. We provide models for the computational cost of both real-space
and Fourier space convolutions and an estimate for the approximation error.
Using these models we can determine the optimum split that minimizes the wall
clock time for the convolution while satisfying the desired error bounds. We
apply this technique to the problem of simulating a cosmic microwave background
sky map at the resolution typical of the high resolution maps of the cosmic
microwave background anisotropies produced by the Planck space craft. For the
main Planck CMB science channels we achieve a speedup of over a factor of ten,
assuming an acceptable fractional rms error of order 10^-5 in the (power
spectrum of the) output map.


  The previously discussed anomalous behavior (i.e. negative) of the thermal
expansion coefficient obtained from the pair correlation function is examined
in the context of the nearest-neighbor distance (bond length) distribution. The
bond length distribution is obtained from a Voronoi tessellation analysis of
the atomic structures obtained from both reverse Monte Carlo simulations of
x-ray scattering data and molecular dynamics simulations. When a robust measure
of central tendency (mean or median) is used a positive thermal expansion is
obtained from the temperature-dependent bond length that has the same magnitude
as that obtained from direct measurements of the volume as a function of
temperature. The same is true when larger neighbor distances, as obtained in
higher order peaks in the pair distribution function are tracked. This calls
into question the recent claim that fragility of metallic liquids is embedded
in these higher order peaks. It also shows that the previously reported
anomalous contraction of the bond length arise from tracking the mode, which
does not account for the skewness of the distribution.