  We present the first examples of smooth elliptic Calabi-Yau threefolds with
Mordell-Weil rank 10, the highest currently known value. They are given by the
Schoen threefolds introduced by Namikawa; there are six isolated fibers of
Kodaira Type IV. We explicitly compute the Shioda homomorphism for the
generators of the Mordell-Weil group and their induced height pairing.
Compactification of F-theory on these threefolds gives an effective theory in
six dimensions which contains ten abelian gauge group factors. We compute the
massless matter spectrum. In particular, we show that the charged singlet
matter need not reside at enhancement loci of Type $I_2$, as previously
believed. We relate the multiplicities of the massless spectrum to genus-zero
Gopakumar-Vafa invariants and other geometric quantities of the Calabi-Yau. We
show that the gravitational and abelian anomaly cancellation conditions are
satisfied. We prove a Geometric Anomaly Cancellation equation and we deduce
birational equivalence for the quantities in the spectrum. We explicitly
describe a Weierstrass model over $\mathbb P^2$ of the Calabi-Yau threefolds as
a log canonical model and compare it to a construction by Elkies and classical
results of Burkhardt.


  We extend the local newform theory of B. Roberts and R. Schmidt for generic,
irreducible, admissible representations of PGSp(4) to that for GSp(4). The
newform matches to the Langlands parameter.


  This chapter summarizes radio astrometry in relation to current very long
baseline interferometry (VLBI) projects and describes its perspectives with the
SKA. The scientific goals of the astrometry with the SKA have been discussed in
the international and Japanese communities of researchers, whose major issues
are shown here. We have demonstrated some of the issues, such as censuses of
possible targets and the technical feasibility of astrometry in the SKA
frequency bands. The preliminary results of our case studies on SKA astrometry
are also presented. In addition, possible synergy and commensality of the SKA
astrometric projects with those in the optical and infrared astrometric
missions, especially JASMINE (Japan Astrometry Satellite Mission for INfrared
Exploration) are discussed.


  We show that the braid group representations associated with the
$(3,6)$-quotients of the Hecke algebras factor over a finite group. This was
known to experts going back to the 1980s, but a proof has never appeared in
print. Our proof uses an unpublished quaternionic representation of the braid
group due to Goldschmidt and Jones. Possible topological and categorical
generalizations are discussed.


  Various methods to automate traffic data collection have recently been
developed by many researchers. A macroscopic data collection through image
processing has been proposed. For microscopic traffic flow data, such as
individual speed and time or distance headway, tracking of individual movement
is needed. The tracking algorithms for pedestrian or vehicle have been
developed to trace the movement of one or two pedestrians based on sign
pattern, and feature detection. No research has been done to track many
pedestrians or vehicles at once. This paper describes a new and fast algorithm
to track the movement of many individual vehicles or pedestrians


  We consider the Schr\"odinger operator ${\bf H}=(i\nabla+A)^2 $ in the space
$L_2({\mathbb R}^3)$ with a magnetic potential $A $ created by an infinite
straight current. We perform a spectral analysis of the operator ${\bf H}$
almost explicitly.
  In particular, we show that the operator ${\bf H}$ is absolutely continuous,
its spectrum has infinite multiplicity and coincides with the positive
half-axis. Then we find the large-time behavior of solutions $\exp(-i{\bf
H}t)f$ of the time dependent Schr\"odinger equation. Equations of classical
mechanics are also integrated. Our main observation is that both quantum and
classical particles have always a preferable (depending on its charge)
direction of propagation along the current and both of them are confined in the
plane orthogonal to the current.


  Among access control models, Role Based Access Control (RBAC) is very useful
and is used in many computer systems. Static Combination of Duty (SCD) and
Dynamic Combination of Duty (DCD) constraints have been introduced recently for
this model to handle dependent roles. These roles must be used together and can
be considered as a contrary point of conflicting roles. In this paper, we
propose several new types of SCD and DCD constraints. Also, we introduce strong
dependent roles and define new groups of SCD constraints for these types of
roles as SCD with common items and SCD with union items. In addition, we
present an extension for SCD constraints in the presence of hierarchy.


  Wei's celebrated Duality Theorem is generalized in several ways, expressed as
duality theorems for linear codes over division rings and, more generally,
duality theorems for matroids. These results are further generalized, resulting
in two Wei-type duality theorems for new combinatorial structures that are
introduced and named {\em demi-matroids}. These generalize matroids and are the
appropriate combinatorial objects for describing the duality in Wei's Duality
Theorem. A new proof of the Duality Theorem is thereby given that explains the
theorem in combinatorial terms. Special cases of the general duality theorems
are also given, including duality theorems for cycles and bonds in graphs and
for transversals.


  When people have the freedom to create and post content on the internet,
particularly anonymously, they do not always respect the rules and regulations
of the websites on which they post, leaving other unsuspecting users vulnerable
to sexism, racism, threats, and other unacceptable content in their daily
cyberspace diet. However, content moderators witness the worst of humanity on a
daily basis in place of the average netizen. This takes its toll on moderators,
causing stress, fatigue, and emotional distress akin to the symptomology of
post-traumatic stress disorder (PTSD). The goal of the present study was to
explore whether adding positive stimuli to breaktimes-images of baby animals or
beautiful, aweinspiring landscapes-could help reduce the negative side-effects
of being a content moderator. To test this, we had over 300 experienced content
moderators read and decide whether 200 fake text-based social media posts were
acceptable or not for public consumption. Although we set out to test positive
emotional stimulation, however, we actually found that it is the cumulative
nature of the negative emotions that likely negates most of the effects of the
intervention: the longer the person had practiced content moderation, the
stronger their negative experience. Connections to compassion fatigue and how
best to spend work breaks as a content moderator are discussed.


  We have investigated the dynamics of the electron-nuclei coupled system in
quantum dots. The bunching of results of the electron spin measurements and the
revival in the conditional probabilities are salient features of the nuclear
spin memory. The underlying mechanism is the squeezing of the nuclear spin
state and the correlations between the successive electron spin measurements.
Further we make a proposal for the preparation and detection of superposition
states of nuclear spins merely relying on electron spin measurements. For
unpolarized, completely random nuclear spin state one can still trace the
quantum interference effects. We discuss the realization of these schemes for
electron spins on both single and double QDs.


  We propose a new method that employs transfer learning techniques to
effectively correct sampling selection errors introduced by sparse annotations
during supervised learning for automated tumor segmentation. The practicality
of current learning-based automated tissue classification approaches is
severely impeded by their dependency on manually segmented training databases
that need to be recreated for each scenario of application, site, or
acquisition setup. The comprehensive annotation of reference datasets can be
highly labor-intensive, complex, and error-prone. The proposed method derives
high-quality classifiers for the different tissue classes from sparse and
unambiguous annotations and employs domain adaptation techniques for
effectively correcting sampling selection errors introduced by the sparse
sampling. The new approach is validated on labeled, multi-modal MR images of 19
patients with malignant gliomas and by comparative analysis on the BraTS 2013
challenge data sets. Compared to training on fully labeled data, we reduced the
time for labeling and training by a factor greater than 70 and 180 respectively
without sacrificing accuracy. This dramatically eases the establishment and
constant extension of large annotated databases in various scenarios and
imaging setups and thus represents an important step towards practical
applicability of learning-based approaches in tissue classification.


  Recently, deep convolutional neural networks have achieved great success for
medical image segmentation. However, unlike segmentation of natural images,
most medical images such as MRI and CT are volumetric data. In order to make
full use of volumetric information, 3D CNNs are widely used. However, 3D CNNs
suffer from higher inference time and computation cost, which hinders their
further clinical applications. Additionally, with the increased number of
parameters, the risk of overfitting is higher, especially for medical images
where data and annotations are expensive to acquire. To issue this problem,
many 2.5D segmentation methods have been proposed to make use of volumetric
spatial information with less computation cost. Despite these works lead to
improvements on a variety of segmentation tasks, to the best of our knowledge,
there has not previously been a large-scale empirical comparison of these
methods. In this paper, we aim to present a review of the latest developments
of 2.5D methods for volumetric medical image segmentation. Additionally, to
compare the performance and effectiveness of these methods, we provide an
empirical study of these methods on three representative segmentation tasks
involving different modalities and targets. Our experimental results highlight
that 3D CNNs may not always be the best choice. Despite all these 2.5D methods
can bring performance gains to 2D baseline, not all the methods hold the
benefits on different datasets. We hope the results and conclusions of our
study will prove useful for the community on exploring and developing efficient
volumetric medical image segmentation methods.


  This is a pedagogical article cited in the foregoing research note,
quant-ph/9911050


  UAVs are capable of improving the performance of next generation wireless
systems. Specifically, UAVs can be exploited as aerial base-stations (UAV-BS)
for supporting legitimate ground users in remote uncovered areas or in
environments temporarily requiring high capacity. However, their communication
performance is prone to both channel estimation errors and potential
eavesdropping. Hence, we investigate the effective secrecy throughput of the
UAV-aided uplink, in which rate-splitting multiple access (RSMA) is employed by
each legitimate user for secure transmission under the scenario of massive
access. To maximize the effective network secrecy throughput in the uplink, the
transmission rate vs. power allocation relationship is formulated as a max-min
optimization problem, relying on realistic imperfect CSI of both the legitimate
users and of the potential eavesdroppers (Eves). We then propose a novel
transformation of the associated probabilistic constraints for decoupling the
variables, so that our design problem can be solved by alternatively activating
the related block coordinate decent programming. In the model considered, each
user transmits a superposition of two messages to a UAV-BS, each having
different transmit power and the UAV-BS uses a SIC technique to decode the
received messages. Given the non-convexity of the problem, it is decoupled into
a pair of sub-problems. In particular, we derive a closed form expression for
the optimal rate-splitting fraction of each user. Then, given the optimal
rate-splitting fraction of each user, the \epsilon-constrainted transmit power
of each user is calculated by harnessing SPCA programming.


  We outline the evaluation of $n$-dimensional fermion traces
($n\in\mathbb{N}$) built by products of Dirac-$\gamma$ matrices suitable for a
uniform dimensional continuation. Such a continuation is needed for
calculations employing a dimensional regulator whenever intrinsically integer
dimensional tensors yield non-vanishing contributions. A prime example for such
a tensor is given by $\gamma_5$ for $n=4$. The main difference between
Dimensional Regularization (DREG) and a Dimensionally Continued Regularization
(DCREG) is that DCREG does not attempt to lift the algebra to continuous $d$
dimensions ($d\in\mathbb{R}$). As a consequence one has to properly deal with
evanescent structures in order to ensure the uniform application of the
regulator. In basic steps we identify evanescent structures in fermion traces
and show that their proper treatment is crucial for example when calculating
the $VVA$ anomaly in four dimensions. We checked that the performed
considerations enable the evaluation of Standard Model (SM) $Z$-factors within
DCREG up to including three loops.


  We describe a flasher system designed for use in monitoring the gains of the
photomultiplier tubes used in the VERITAS gamma-ray telescopes. This system
uses blue light-emitting diodes (LEDs) so it can be operated at much higher
rates than a traditional laser-based system. Calibration information can be
obtained with better statistical precision with reduced loss of observing time.
The LEDs are also much less expensive than a laser. The design features of the
new system are presented, along with measurements made with a prototype mounted
on one of the VERITAS telescopes.


  We present a CNN-BiLSTM system for the problem of offline English handwriting
recognition, with extensive evaluations on the public IAM dataset, including
the effects of model size, data augmentation and the lexicon. Our best model
achieves 3.59\% CER and 9.44\% WER using CNN-BiLSTM network with CTC layer.
Test time augmentation with rotation and shear transformations applied to the
input image, is proposed to increase recognition of difficult cases and found
to reduce the word error rate by 2.5\% points. We also conduct an error
analysis of our proposed method on IAM dataset, show hard cases of handwriting
images and explore samples with erroneous labels. We provide our source code as
public-domain, to foster further research to encourage scientific
reproducibility.


  We analyze longslit spectral observations of fourteen Wolf-Rayet galaxies
from the sample of Schaerer, Contini & Pindao (1999). All 14 galaxies show
broad Wolf-Rayet emission in the blue region of the spectrum, consisting of a
blend of NIII4640, CIII4650, CIV4658, and HeII4686 emission lines, which is a
spectral characteristic of WN stars. Broad CIV5808 emission, termed the red
bump, is detected in 9 galaxies and CIII5996 is detected in 6 galaxies. These
emission features are due to WC stars. We derive the numbers of late WN and
early WC stars from the luminosity of the blue and red bumps, respectively. The
number of O stars is estimated from the luminosity of the Hbeta emission line,
after subtracting the contribution of WR stars. The Schaerer & Vacca 1998
(hereafter SV98) models predict that the number of WR stars relative to O
stars, N_WR/N_O, increases with metallicity. For low metallicity galaxies, the
results agree with predictions of evolutionary synthesis models for galaxies
with a burst of star formation, and indicates an IMF slope -2 < Gamma < -2.35
in the low metallicity regime. For high metallicity galaxies our observations
suggest a Salpeter IMF (Gamma = -2.35) and an extended short burst. The main
possible sources of error are the adopted luminosities for single WCE and WNL
stars. We also report, for the first time, NGC 450 as a galaxy with WR
characteristics.


  Deep-learning-based pipelines have shown the potential to revolutionalize
microscopy image diagnostics by providing visual augmentations to a trained
pathology expert. However, to match human performance, the methods rely on the
availability of vast amounts of high-quality labeled data, which poses a
significant challenge. To circumvent this, augmented labeling methods, also
known as expert-algorithm-collaboration, have recently become popular. However,
potential biases introduced by this operation mode and their effects for
training neuronal networks are not entirely understood. This work aims to shed
light on some of the effects by providing a case study for three pathologically
relevant diagnostic settings. Ten trained pathology experts performed a
labeling tasks first without and later with computer-generated augmentation. To
investigate different biasing effects, we intentionally introduced errors to
the augmentation. Furthermore, we developed a novel loss function which
incorporates the experts' annotation consensus in the training of a deep
learning classifier. In total, the pathology experts annotated 26,015 cells on
1,200 images in this novel annotation study. Backed by this extensive data set,
we found that the consensus of multiple experts and the deep learning
classifier accuracy, was significantly increased in the computer-aided setting,
versus the unaided annotation. However, a significant percentage of the
deliberately introduced false labels was not identified by the experts.
Additionally, we showed that our loss function profited from multiple experts
and outperformed conventional loss functions. At the same time, systematic
errors did not lead to a deterioration of the trained classifier accuracy.
Furthermore, a classifier trained with annotations from a single expert with
computer-aided support can outperform the combined annotations from up to nine
experts.


  We introduce a non-increasing tree growth process $((T_n,\sigma_n),\, n\ge
1)$, where $T_n$ is a rooted labeled tree on $n$ vertices and ${\sigma}_n$ is a
permutation of the vertex labels. The construction of $(T_{n},{\sigma}_n)$ from
$(T_{n-1},{\sigma}_{n-1})$ involves rewiring a random (possibly empty) subset
of edges in $T_{n-1}$ towards the newly added vertex; as a consequence $T_{n-1}
\not\subset T_n$ with positive probability. The key feature of the process is
that the shape of $T_n$ has the same law as that of a random recursive tree,
while the degree distribution of any given vertex is not monotonous in the
process.
  We present two applications. First, while couplings between Kingman's
coalescent and random recursive trees where known for any fixed $n$, this new
process provides a non-standard coupling of all finite Kingman's coalescents.
Second, we use the new process and the Chen-Stein method to extend the
well-understood properties of degree distribution of random recursive trees to
extremal-range cases. Namely, we obtain convergence rates on the number of
vertices with degree at least $c\ln n$, $c\in (1,2)$, in trees with $n$
vertices. Further avenues of research are discussed.


  Analyses of thermal diffusivity data on complex insulators and on strongly
correlated electron systems hosted in similar complex crystal structures
suggest that quantum chaos is a good description for thermalization processes
in these systems, particularly in the high temperature regime where the many
phonon bands and their interactions dominate the thermal transport. Here we
observe that for these systems diffusive thermal transport is controlled by a
universal Planckian time scale $\tau\sim \hbar/k_BT$, and a unique velocity
$v_E$. Specifically, $v_E \approx v_{ph} $ for complex insulators, and $v_{ph}
\lesssim v_E \ll v_{F}$ in the presence of strongly correlated itinerant
electrons ($v_{ph}$ and $v_F$ are the phonons and electrons velocities
respectively). For the complex correlated electron systems we further show that
charge diffusivity, while also reaching the Planckian relaxation bound, is
largely dominated by the Fermi velocity of the electrons, hence suggesting that
it is only the thermal (energy) diffusivity that describes chaos diffusivity.


  Variants of the black hole information paradox are studied in Type IIB string
theory setups that realize four-dimensional gravity coupled to a bath. The
setups are string theory versions of doubly-holographic Karch/Randall brane
worlds, with black holes coupled to non-gravitating and gravitating baths. The
10d versions are based on fully backreacted solutions for configurations of D3,
D5 and NS5 branes, and admit dual descriptions as $\mathcal N=4$ SYM on a half
space and 3d $T_\rho^\sigma[SU(N)]$ SCFTs. Island contributions to the
entanglement entropy of black hole radiation systems are identified through
Ryu/Takayanagi surfaces and lead to Page curves. Analogs of the critical angles
found in the Karch/Randall models are identified in 10d, as critical parameters
in the brane configurations and dual field theories.


  We investigate the stability of a new class of BPS cosmic strings in N=1
supergravity with D-terms recently proposed by Blanco-Pillado, Dvali and Redi.
These have been conjectured to be the low energy manifestation of D-strings
that might form from tachyon condensation after D- anti-D-brane annihilation in
type IIB superstring theory. There are three one-parameter families of
cylindrically symmetric one-vortex solutions to the BPS equations (tachyonic,
axionic and hybrid). We find evidence that the zero mode in the axionic case,
or s-strings, can be excited. Its evolution leads to the decompactification of
four-dimensional spacetime at late times, with a rate that decreases with
decreasing brane tension.


  With the interactivity and multiple representation features, computer
simulations lend itself to the guided inquiry learning. However, these
simulations are usually designed for post-elementary students. Thus, the aim of
this study is to investigate how the use of guided inquiry approach with
customized energy simulation can improve students' understanding of this topic.
In this ongoing research, the case study is adopted. In the first phase of the
study, we have modified open source energy simulation based on principles for
reducing extraneous processing, existing energy simulation and guided inquiry
approach. The modified simulation is sent to teachers for evaluation and the
feedback is encouraging. In the next phase of the study, the guided inquiry
lesson package involving the energy simulation would be designed and deployed
in an elementary classroom. Multiple data sources would be collected to seek a
deeper understanding on how this learning package can possibly impact students'
understanding of the physics concepts.


  Create an articulated and realistic human 3D model is a complicated task, not
only get a model with the right body proportions but also to the whole process
of rigging the model with correct articulation points and vertices weights.
Having a tool that can create such a model with just a few clicks will be very
advantageous for amateurs developers to use in their projects, researchers to
easily generate datasets to train neural networks and industry for game
development. We present a software that is integrated in Blender in form of
add-on that allows us to design and animate a dressed 3D human models based on
Makehuman with just a few clicks. Moreover, as it is already integrated in
Blender, python scripts can be created to animate, render and further customize
the current available options.


  Many data-rich industries are interested in the efficient discovery and
modelling of structures underlying large data sets, as it allows for the fast
triage and dimension reduction of large volumes of data embedded in high
dimensional spaces. The modelling of these underlying structures is also
beneficial for the creation of simulated data that better represents real data.
In particular, for systems testing in cases where the use of real data streams
might prove impractical or otherwise undesirable. We seek to discover and model
the structure by combining methods from topological data analysis with
numerical modelling. As a first step in combining these two areas, we examine
the recovery of the abstract graph $G$ structure, and model a linear embedding
$|G|$ given only a noisy point cloud sample $X$ of $|G|$.


  The intra-cluster correlation coefficient (ICC) plays an important role while
designing the cluster randomized trials (CRTs). Often optimal CRTs are designed
assuming that the magnitude of the ICC is constant across the clusters.
However, this assumption is hardly satisfied. In some applications, the precise
information about the cluster specific correlation is known in advance. In this
article, we propose an optimal design with non-constant ICC across the
clusters. Also in many situations, the cost of sampling of an observation from
a particular cluster may differ from that of some other cluster. An optimal
design in those scenarios is also obtained assuming unequal costs of sampling
from different clusters. The theoretical findings are supplemented by thorough
numerical examples.


  It is shown that brane world gravity produces an attractive force between
cosmic strings, in contrast to conventional Einstein gravity. This force is
sufficient for stable bound states of Type II strings (which normally repel
each other) to form. There is a small separation between the strings, giving
them a rope-like structure. At astronomical scales these `cosmic ropes'
resemble higher winding number strings, and so all brane world cosmic strings
are effectively Type I.


  We discuss the metallicity effect on the theoretical visual and near-infrared
PL and PLC relations of classical Cepheids, as based on nonlinear, nonlocal and
time--dependent convective pulsating models at varying chemical composition. In
view of the two usual methods of averaging (magnitude-weighted and
intensity-weighted) observed magnitudes and colors over the full pulsation
cycle, we briefly discuss the differences between static and mean quantities.
We show that the behavior of the synthetic mean magnitudes and colors fully
reproduces the observed trend of Galactic Cepheids, supporting the validity of
the model predictions. In the second part of the paper we show how the estimate
of the mean reddening and true distance modulus of a galaxy from Cepheid VK
photometry depend on the adopted metal content, in the sense that larger
metallicities drive the host galaxy to lower extinctions and distances.
Conversely, self-consistent estimates of the Cepheid mean reddening, distance
and metallicity may be derived if three-filter data are taken into account. By
applying the theoretical PL and PLC relations to available BVK data of Cepheids
in the Magellanic Clouds we eventually obtain Z \sim 0.008, E(B-V) \sim 0.02
mag, DM \sim 18.63 mag for LMC and Z \sim 0.004, E(B-V) \sim 0.01 mag., DM \sim
19.16 mag. for SMC. The discrepancy between such reddenings and the current
values based on BVI data is briefly discussed.


  We construct the non-linear realisation of the E8 motion group and compare
this with the bosonic sector of eleven dimensional supergravity. The
construction naturally leads to the introduction of a new potential field. We
identify this new field with the dual gravity field by considering the
reduction of the eleven-dimensional theory to three dimensions.


  Gaia is a cornerstone mission in the science programme of the European Space
Agency (ESA). The spacecraft construction was approved in 2006, following a
study in which the original interferometric concept was changed to a
direct-imaging approach. Both the spacecraft and the payload were built by
European industry. The involvement of the scientific community focusses on data
processing for which the international Gaia Data Processing and Analysis
Consortium (DPAC) was selected in 2007. Gaia was launched on 19 December 2013
and arrived at its operating point, the second Lagrange point of the
Sun-Earth-Moon system, a few weeks later. The commissioning of the spacecraft
and payload was completed on 19 July 2014. The nominal five-year mission
started with four weeks of special, ecliptic-pole scanning and subsequently
transferred into full-sky scanning mode. We recall the scientific goals of Gaia
and give a description of the as-built spacecraft that is currently (mid-2016)
being operated to achieve these goals. We pay special attention to the payload
module, the performance of which is closely related to the scientific
performance of the mission. We provide a summary of the commissioning
activities and findings, followed by a description of the routine operational
mode. We summarise scientific performance estimates on the basis of in-orbit
operations. Several intermediate Gaia data releases are planned and the data
can be retrieved from the Gaia Archive, which is available through the Gaia
home page at http://www.cosmos.esa.int/gaia.


  Novel String Banana Template Method (SBTM) for track reconstruction in high
multiplicity events in non-uniform magnetic field spectrometer with emphasis on
the lowest momenta tracks with significant Multiple Scattering (MS) is
described. Two steps model of track with additional parameter/s which takes
into account MS for this particular track is introduced. SBTM is time efficient
and demonstrates better resolutions than another method equivalent to the Least
Squares method (LSM).


  Reversible jump Markov chain Monte Carlo (RJMCMC) proposals that achieve
reasonable acceptance rates and mixing are notoriously difficult to design in
most applications. Inspired by recent advances in deep neural network-based
normalizing flows and density estimation, we demonstrate an approach to enhance
the efficiency of RJMCMC sampling by performing transdimensional jumps
involving reference distributions. In contrast to other RJMCMC proposals, the
proposed method is the first to apply a non-linear transport-based approach to
construct efficient proposals between models with complicated dependency
structures. It is shown that, in the setting where exact transports are used,
our RJMCMC proposals have the desirable property that the acceptance
probability depends only on the model probabilities. Numerical experiments
demonstrate the efficacy of the approach.


  Facial alignment involves finding a set of landmark points on an image with a
known semantic meaning. However, this semantic meaning of landmark points is
often lost in 2D approaches where landmarks are either moved to visible
boundaries or ignored as the pose of the face changes. In order to extract
consistent alignment points across large poses, the 3D structure of the face
must be considered in the alignment step. However, extracting a 3D structure
from a single 2D image usually requires alignment in the first place. We
present our novel approach to simultaneously extract the 3D shape of the face
and the semantically consistent 2D alignment through a 3D Spatial Transformer
Network (3DSTN) to model both the camera projection matrix and the warping
parameters of a 3D model. By utilizing a generic 3D model and a Thin Plate
Spline (TPS) warping function, we are able to generate subject specific 3D
shapes without the need for a large 3D shape basis. In addition, our proposed
network can be trained in an end-to-end framework on entirely synthetic data
from the 300W-LP dataset. Unlike other 3D methods, our approach only requires
one pass through the network resulting in a faster than real-time alignment.
Evaluations of our model on the Annotated Facial Landmarks in the Wild (AFLW)
and AFLW2000-3D datasets show our method achieves state-of-the-art performance
over other 3D approaches to alignment.


  This paper presents a novel ultrasound imaging point-of-care (PoC) COVID-19
diagnostic system. The adaptive visual diagnostics utilize few-shot learning
(FSL) to generate encoded disease state models that are stored and classified
using a dictionary of knowns. The novel vocabulary based feature processing of
the pipeline adapts the knowledge of a pretrained deep neural network to
compress the ultrasound images into discrimative descriptions. The
computational efficiency of the FSL approach enables high diagnostic deep
learning performance in PoC settings, where training data is limited and the
annotation process is not strictly controlled. The algorithm performance is
evaluated on the open source COVID-19 POCUS Dataset to validate the system's
ability to distinguish COVID-19, pneumonia, and healthy disease states. The
results of the empirical analyses demonstrate the appropriate efficiency and
accuracy for scalable PoC use. The code for this work will be made publicly
available on GitHub upon acceptance.


  We present IFS-RedEx, a spectrum and redshift extraction pipeline for
integral-field spectrographs. A key feature of the tool is a wavelet-based
spectrum cleaner. It identifies reliable spectral features, reconstructs their
shapes, and suppresses the spectrum noise. This gives the technique an
advantage over conventional methods like Gaussian filtering, which only smears
out the signal. As a result, the wavelet-based cleaning allows the quick
identification of true spectral features. We test the cleaning technique with
degraded MUSE spectra and find that it can detect spectrum peaks down to S/N =
8 while reporting no fake detections. We apply IFS-RedEx to MUSE data of the
strong lensing cluster MACSJ1931.8-2635 and extract 54 spectroscopic redshifts.
We identify 29 cluster members and 22 background galaxies with z >= 0.4.
IFS-RedEx is open source and publicly available.


  Investigating the optimal nature of social interactions among generic actors
(e.g., people or firms), aiming to achieve specifically-agreed objectives, has
been the subject of extensive academic research. Using the relational models
theory - comprehensively describing all social interactions among actors as
combinations of only four forms of sociality: communal sharing, authority
ranking, equality matching, and market pricing - the common approach within the
literature revolves around qualitative assessments of the sociality models'
configurations most effective in realizing predefined purposes, at times
supplemented by empirical data. In this treatment, we formulate this question
as a mathematical optimization problem, in order to quantitatively determine
the best possible configurations of sociality forms between dyadic actors which
would optimize their mutually-agreed objectives. For this purpose, we develop
an analytical framework for quantifying the (meta)relational models theory, and
mathematically demonstrate that combining the four sociality forms within a
specific meaningful social interaction inevitably prompts an inherent tension
among them, through a single elementary and universal metarelation. In analogy
with financial portfolio management, we subsequently introduce the concept of
Social Relations Portfolio (SRP) management, and propose a generalizable
procedural methodology capable of quantitatively identifying the efficient SRP
for any objective involving meaningful social relations. As an important
illustration, the methodology is applied to the Triple Bottom Line paradigm to
derive its efficient SRP, guiding practitioners in precisely measuring,
monitoring, reporting and (proactively) steering stakeholder management efforts
regarding Corporate Social Responsibility (CSR) and Environmental, Social and
Governance (ESG) within and / or across organizations.


  We present an unbiased orbit solution and mass determination of the
components of the eclipsing binary NY Vir as a critical test for the formation
scenarios of subdwarf B stars. We obtained high-resolution time series VLT/UVES
spectra and high-speed multicolour VLT/ULTRACAM photometric observations of NY
Vir, a rapidly pulsating subdwarf B star in a short period eclipsing binary.
Combining the radial velocity curve obtained from the VLT/UVES spectra with the
VLT/ULTRACAM multicolour lightcurves, we determined numerical orbital solutions
for this eclipsing binary. Due to the large number of free parameters and their
strong correlations, no unique solution could be found, only families of
solutions. We present three solutions of equal statistical significance, two of
which are compatible with the primary having gone through a core He-flash and a
common-envelope phase described by the $\alpha$-formalism. These two models
have an sdB primary of 0.466 \msol and 0.389 \msol, respectively. Finally, we
report the detection of the Rossiter-McLaughlin effect for NY Vir.


  We present (bi-)symmetric generating functions for the joint distributions of
Euler-Stirling statistics on permutations, including the number of descents
($\mathsf{des}$), inverse descents ($\mathsf{ides}$), the number of
left-to-right maxima ($\mathsf{lmax}$), the number of right-to-left maxima
($\mathsf{rmax}$) and the number of left-to-right minima ($\mathsf{lmin}$). We
also show how they recover the classical symmetric generating function of
permutations due to Carlitz, Roselle and Scoville (1966).
  Our proofs exploit three different recursive constructions of inversion
sequences, bijections on the multiple equidistributions of Euler-Stirling
statistics over permutations and transformation formulas of basic
hypergeometric series. Furthermore, we establish a new quadruple
equidistribution of Euler-Stirling statistics over inversion sequences, as
progress towards a conjecture proposed by Schlosser and the author (2020).


  The transition from reversible microdynamics to irreversible transport can be
studied very efficiently with the help of the so-called projection method. We
give a concise introduction to that method, illustrate its power by using it to
analyze the well-known rate and quantum Boltzmann equations, and present, as a
new application, the derivation of a source term accounting for the spontaneous
creation of electron-positron pairs in strong fields. Thereby we emphasize the
fundamental importance of time scales: only if the various time scales
exhibited by the dynamics are widely disparate, can the evolution of the slower
degrees of freedom be described by a conventional Markovian transport equation;
otherwise, one must account for finite memory effects. We show how the
projection method can be employed to determine these time scales, and how --if
necessary-- it allows one to include memory effects in a straightforward
manner. Finally, there is an appendix in which we discuss the concepts of
entropy and macroscopic irreversibility.


  Assuming General Relativity is correct on large-scales, Redshift-Space
Distortions (RSDs) and the Integrated Sachs-Wolfe effect (ISW) are both
sensitive to the time derivative of the linear growth function. We investigate
the extent to which these probes provide complementary or redundant information
when they are combined to constrain the evolution of the linear velocity power
spectrum, often quantified by the function $f(z)\sigma_8(z)$, where $f$ is the
logarithmic derivative of $\sigma_8$ with respect to $(1+z)$. Using a spherical
Fourier-Bessel (SFB) expansion for galaxy number counts and a spherical
harmonic expansion for the CMB anisotropy, we compute the covariance matrices
of the signals for a large galaxy redshift survey combined with a CMB survey
like Planck. The SFB basis allows accurate ISW estimates by avoiding the
plane-parallel approximation, and it retains RSD information that is otherwise
lost when projecting angular clustering onto redshift shells. It also allows
straightforward calculations of covariance with the CMB. We find that the
correlation between the ISW and RSD signals are low since the probes are
sensitive to different modes. For our default surveys, on large scales ($k<0.05
\Mpc/h$), the ISW can improve constraints on $f\sigma_8$ by more than 10%
compared to using RSDs alone. In the future, when precision RSD measurements
are available on smaller scales, the cosmological constraints from ISW
measurements will not be competitive; however, they will remain a useful
consistency test for possible systematic contamination and alternative models
of gravity.


  The PAANDA experiment was conceived to characterize the acceleration ambient
of a rocket launched microgravity platform, specially the microgravity phase.
The recorded data was transmitted to ground stations, leading to loss of
telemetry information sent during the reentry period. Traditionally, an
error-correcting code for this channel consists of a block code with very large
block size to protect against long periods of data loss. Instead, we propose
the use of digital fountain codes along with conventional Reed-Solomon block
codes to protect against long and short burst error periods, respectively.
Aiming to use this approach for a second version of PAANDA to prevent data
corruption, we propose a model for the communication channel based on
information extracted from Cum\~a II's telemetry data, and simulate the
performance of our proposed error-correcting code under this channel model.
Simulation results show that nearly all telemetry data can be recovered,
including data from the reentry period.


  We present a simple, empirically motivated model that simultaneously predicts
the evolution of the mean size and the comoving mass density of massive
early-type galaxies from z=2 to the present. First we demonstrate that some
size evolution of the population can be expected simply due to the continuous
emergence of early-type galaxies. SDSS data reveal that in the present-day
universe more compact early-type galaxies with a given dynamical mass have
older stellar populations. In contrast, at a given stellar velocity dispersion,
SDSS data show that there is no relation between size and age, which implies
that the velocity dispersion can be used to estimate the epoch at which
galaxies stopped forming stars, turning into early-type galaxies. Applying such
a 'formation' criterion to a large sample of nearby early-type galaxies, we
predict the redshift evolution in the size distribution and the comoving mass
density. The resulting evolution in the mean size is roughly half of the
observed evolution. Then we include a prescription for the merger histories of
galaxies between the 'formation' redshift and the present, based on
cosmological simulations of the assembly of dark matter halos. Such mergers
after the transformation into an early-type galaxy are presumably
dissipationless ('dry'), where the increase in size is expected to be
approximately proportional to the increase in mass. This model successfully
reproduces the observed evolution since z~2 in the mean size and in the
comoving mass density of massive early-type galaxies. We conclude that the
recently measured, substantial size evolution of early-type galaxies can be
explained by the combined effect of the continuous emergence of galaxies as
early types and their subsequent growth through dry merging.


  We seek to develop simultaneous segmentation and classification of notes from
audio recordings in presence of outliers. The selected architecture for
modeling time series is hierarchical linear dynamical system (HLDS). We propose
a novel method for its parameter setting. HLDS can potentially be employed in
two ways: 1) simultaneous segmentation and clustering for exploring data, i.e.
finding unknown notes, 2) simultaneous segmentation and classification of audio
recording for finding the notes of interest in the presence of outliers. We
adapted HLDS for the second purpose since it is an easier task and still a
challenging problem, e.g. in the field of bioacoustics. Each test clip has the
same notes (but different instances) as of the training clip and also contain
outlier notes. At test, it is automatically decided to which class of interest
a note belongs to if any. Two applications of this work are to the fields of
bioacoustics for detection of animal sounds in audio field recordings and also
to musicology. Experiments have been conducted for segmentation and
classification of both avian and musical notes from recorded audio.


  Within the incompressible three-dimensional Euler equations, we study the
pancake-like high vorticity regions, which arise during the onset of developed
hydrodynamic turbulence. We show that these regions have an internal fine
structure consisting of three vortex layers. Such a layered structure, together
with the power law of self-similar evolution of the pancake, prevents
development of the Kelvin-Helmholtz instability.


  Multi-label image classification (MLIC) is a fundamental and practical task,
which aims to assign multiple possible labels to an image. In recent years,
many deep convolutional neural network (CNN) based approaches have been
proposed which model label correlations to discover semantics of labels and
learn semantic representations of images. This paper advances this research
direction by improving both the modeling of label correlations and the learning
of semantic representations. On the one hand, besides the local semantics of
each label, we propose to further explore global semantics shared by multiple
labels. On the other hand, existing approaches mainly learn the semantic
representations at the last convolutional layer of a CNN. But it has been noted
that the image representations of different layers of CNN capture different
levels or scales of features and have different discriminative abilities. We
thus propose to learn semantic representations at multiple convolutional
layers. To this end, this paper designs a Multi-layered Semantic Representation
Network (MSRN) which discovers both local and global semantics of labels
through modeling label correlations and utilizes the label semantics to guide
the semantic representations learning at multiple layers through an attention
mechanism. Extensive experiments on four benchmark datasets including VOC 2007,
COCO, NUS-WIDE, and Apparel show a competitive performance of the proposed MSRN
against state-of-the-art models.


  We describe a presentation for the augmented fundamental rack of a link in
the lens space $L(p,1)$. Using this presentation, the (enhanced) counting rack
invariants that have been defined for the classical links are applied to the
links in $L(p,1)$. In this case, the counting rack invariants also include the
information about the action of $\pi_{1}(L(p,1))$ on the augmented fundamental
rack of a link.


  A superfluid spontaneously breaks the usual $U(1)$ symmetry because of
condensation. In this article, we illustrate six classes of emergent $U(1)$
symmetries naturally appear in infrared limits in a broad class of gapless
topological superfluids (that either belong to a stable phase or are quantum
critical). In gapless states we have considered, emergent $U(1)$ symmetry
groups are embedded in an $Spin(4)=SU(2) \otimes SU(2)$ group that are
algebraically isomorphic to an $SO(4)$ group. All $U(1)$ charges associated
with symmetries are further invariant under an $SU(2)$ spin group or an
equivalent of it but always break pre-existing higher space-time Lorentz
symmetry of $SO(3,1)$ group. Emergent $U(1)$ symmetries can be further
spontaneously broken only if interactions are strong enough and resultant
strong coupling states become fully gapped. However if states remain gapless,
emergent $U(1)$ symmetries are always present, despite that these states may
exhibit much lower space-time symmetries compared to their weakly interacting
gapless Lorentz symmetric counter parts. In the limit of our interests, we have
identified all possible gapless real fermions with or without Lorentz
symmetries and find that they all display emergent $U(1)$ symmetries in the
infrared limit.We argue emergent $U(1)$ symmetries in infrared are intrinsic in
a broad class of interacting gapless superfluid or superconducting states and
are typically well defined in high dimensions where there are infrared stable
fixed points dictating emergent properties.


  Using supersymmetric localization, we consider four-dimensional
$\mathcal{N}=2$ superconformal quiver gauge theories obtained from
$\mathbb{Z}_n$ orbifolds of $\mathcal{N}=4$ Super Yang-Mills theory in the
large $N$ limit at weak coupling. In particular, we show that: 1) The partition
function for arbitrary couplings can be constructed in terms of universal
building blocks. 2) It can be computed in perturbation series, which converges
uniformly for $|\lambda_I|<\pi^2$, where $\lambda_I$ are the 't Hooft coupling
of the gauge groups. 3) The perturbation series for two-point functions can be
explicitly computed to arbitrary orders. There is no universal effective
coupling by which one can express them in terms of correlators of the
$\mathcal{N}=4$ theory. 4) One can define twisted and untwisted sector
operators. At the perturbative orbifold point, when all the couplings are the
same, the correlators of untwisted sector operators coincide with those of
$\mathcal{N}=4$ Super Yang-Mills theory. In the twisted sector, we find
remarkable cancellations of a certain number of planar loops, determined by the
conformal dimension of the operator.


  We propose 5-brane webs for 5d $\mathcal{N}=1$ $G_2$ gauge theories. From a
Higgsing of the $SO(7)$ gauge theory with a hypermultiplet in the spinor
representation, we construct two types of 5-brane web configurations for the
pure $G_2$ gauge theory using an O5-plane or an $\widetilde{\text{O5}}$-plane.
Adding flavors to the 5-brane web for the pure $G_2$ gauge theory is also
discussed. Based on the obtained 5-brane webs, we compute the partition
functions for the 5d $G_2$ gauge theories using the recently suggested
topological vertex formulation with an O5-plane, and we find agreement with
known results.


  We answer the questions raised by Donev, Torquato, Stillinger, and Connelly
in their "Comment on "Jamming at zero temperature and zero applied stress: The
epitome of disorder.' " We emphasize that we follow a fundamentally different
approach than they have done to reinterpret random close packing in terms of
the "maximally random jammed" framework. We define the "maximally random jammed
packing fraction" to be where the largest number of initial states, chosen
completely randomly, have relaxed final states at the jamming threshold in the
thermodynamic limit. Thus, we focus on an ensemble of states at the jamming
threshold, while DTSC are interested in determining the amount of order and
degree of jamming for a particular configuration. We also argue that
soft-particle systems are as "clean" as those using hard spheres for studying
jammed packings and point out the benefits of using soft potentials.


  The study of highly cited documents on Google Scholar (GS) has never been
addressed to date in a comprehensive manner. The objective of this work is to
identify the set of highly cited documents in Google Scholar and define their
core characteristics: their languages, their file format, or how many of them
can be accessed free of charge. We will also try to answer some additional
questions that hopefully shed some light about the use of GS as a tool for
assessing scientific impact through citations. The decalogue of research
questions is shown below:
  1. Which are the most cited documents in GS?
  2. Which are the most cited document types in GS?
  3. What languages are the most cited documents written in GS?
  4. How many highly cited documents are freely accessible?
  4.1 What file types are the most commonly used to store these highly cited
documents?
  4.2 Which are the main providers of these documents?
  5. How many of the highly cited documents indexed by GS are also indexed by
WoS?
  6. Is there a correlation between the number of citations that these highly
cited documents have received in GS and the number of citations they have
received in WoS?
  7. How many versions of these highly cited documents has GS detected?
  8. Is there a correlation between the number of versions GS has detected for
these documents, and the number citations they have received?
  9. Is there a correlation between the number of versions GS has detected for
these documents, and their position in the search engine result pages?
  10. Is there some relation between the positions these documents occupy in
the search engine result pages, and the number of citations they have received?


  In this paper we deal with a new class of Clifford algebra valued automorphic
forms on arithmetic subgroups of the Ahlfors-Vahlen group. The forms that we
consider are in the kernel of the operator $D \Delta^{k/2}$ for some even $k
\in {\mathbb{Z}}$. They will be called $k$-holomorphic Cliffordian automorphic
forms. $k$-holomorphic Cliffordian functions are well equipped with many
function theoretical tools. Furthermore, the real component functions have also
the property that they are solutions to the homogeneous and inhomogeneous
Weinstein equation. This function class includes the set of $k$-hypermonogenic
functions as a special subset. While we have not been able so far to propose a
construction for non-vanishing $k$-hypermonogenic cusp forms for $k \neq 0$, we
are able to do so within this larger set of functions. After having explained
their general relation to hyperbolic harmonic automorphic forms we turn to the
construction of Poincar\'e series. These provide us with non-trivial examples
of cusp forms within this function class. Then we establish a decomposition
theorem of the spaces of $k$-holomorphic Cliffordian automorphic forms in terms
of a direct orthogonal sum of the spaces of $k$-hypermonogenic Eisenstein
series and of $k$-holomorphic Cliffordian cusp forms.


  Under fairly general assumptions, we prove that every compact invariant set
$\mathcal I$ of the semiflow generated by the semilinear damped wave equation
u_{tt}+\alpha u_t+\beta(x)u-\Deltau = f(x,u), (t,x)\in[0,+\infty[\times\Omega,
u = 0, (t,x)\in[0,+\infty[\times\partial\Omega in $H^1_0(\Omega)\times
L^2(\Omega) has finite Hausdorff and fractal dimension. Here $\Omega$ is a
regular, possibly unbounded, domain in $\R^3$ and $f(x,u)$ is a nonlinearity of
critical growth. The nonlinearity $f(x,u)$ needs not to satisfy any
dissipativeness assumption and the invariant subset $\mathcal I$ needs not to
be an attractor. If $f(x,u)$ is dissipative and $\mathcal I$ is the global
attractor, we give an explicit bound on the Hausdorff and fractal dimension of
$\mathcal I$ in terms of the structure parameters of the equation.


  We study Lusztig's theory of cells for quantum affine $\mathfrak{sl}_n$.
Using the geometric construction of the quantum group due to Lusztig and
Ginzburg--Vasserot, we describe explicitly the two-sided cells, the number of
left cells in a two--sided cell, and the asymptotic algebra, verifying
conjectures of Lusztig.


  Extra dimensions with boundaries are often used in the literature, to provide
phenomenological models that mimic the standard model. In this context, we
explore possible modifications to Newton's law due to the existence of an
extra-dimensional space, at the boundary of which the gravitational field obeys
Dirichlet, Neumann or mixed boundary conditions. We focus on two types of extra
space, namely, the disk and the interval. As we prove, in order to have a
consistent Newton's law modification (i.e., of the Yukawa-type), some of the
extra-dimensional spaces that have been used in the literature, must be ruled
out.


  We study the convergence rate of Sinkhorn's algorithm for solving
entropy-regularized optimal transport problems when at least one of the
probability measures, $\mu$, admits a density over $\mathbb{R}^d$. For a
semi-concave cost function bounded by $c_{\infty}$ and a regularization
parameter $\lambda > 0$, we obtain exponential convergence guarantees on the
dual sub-optimality gap with contraction rate polynomial in
$\lambda/c_{\infty}$. This represents an exponential improvement over the known
contraction rate $1 - \Theta(\exp(-c_{\infty}/\lambda))$ achievable via
Hilbert's projective metric. Specifically, we prove a contraction rate value of
$1-\Theta(\lambda^2/c_\infty^2)$ when $\mu$ has a bounded log-density. In some
cases, such as when $\mu$ is log-concave and the cost function is
$c(x,y)=-\langle x, y \rangle$, this rate improves to
$1-\Theta(\lambda/c_\infty)$. The latter rate matches the one that we derive
for the transport between isotropic Gaussian measures, indicating tightness in
the dependency in $\lambda/c_\infty$. Our results are fully non-asymptotic and
explicit in all the parameters of the problem.


  This paper discusses the critical decision process of extracting or selecting
the features in a supervised learning context. It is often confusing to find a
suitable method to reduce dimensionality. There are pros and cons to deciding
between a feature selection and feature extraction according to the data's
nature and the user's preferences. Indeed, the user may want to emphasize the
results toward integrity or interpretability and a specific data resolution.
This paper proposes a new method to choose the best dimensionality reduction
method in a supervised learning context. It also helps to drop or reconstruct
the features until a target resolution is reached. This target resolution can
be user-defined, or it can be automatically defined by the method. The method
applies a regression or a classification, evaluates the results, and gives a
diagnosis about the best dimensionality reduction process in this specific
supervised learning context. The main algorithms used are the Random Forest
algorithms (RF), the Principal Component Analysis (PCA) algorithm, and the
multilayer perceptron (MLP) neural network algorithm. Six use cases are
presented, and every one is based on some well-known technique to generate
synthetic data. This research discusses each choice that can be made in the
process, aiming to clarify the issues about the entire decision process of
selecting or extracting the features.


  We study a model of moral hazard with heterogeneous beliefs where each of
agent's actions gives rise to a pair of probability distributions over output
levels, one representing the beliefs of the agent and the other those of the
principal. The agent's relative optimism or pessimism dictates whether the
contract is high-powered (i.e. with high variability between wage levels) or
low-powered. When the agent is sufficiently more optimistic than the principal,
the trade-off between risk-sharing and incentive provision may be eliminated.
Using Monotone Likelihood Ratio ranking to model disagreement in the parties'
beliefs, we show that incentives move in the direction of increasing
disagreement. In general, the shape of the wage scheme is sensitive to the
differences in beliefs. Thereby, key features of optimal incentive contracts
under common beliefs do not readily generalize to the case of belief
heterogeneity.


  We introduce the basic elements of the theory of parametrized
$\infty$-categories and functors between them. These notions are defined as
suitable fibrations of $\infty$-categories and functors between them. We give
as many examples as we are able at this stage. Simple operations, such as the
formation of opposites and the formation of functor $\infty$-categories, become
slightly more involved in the parametrized setting, but we explain precisely
how to perform these constructions. All of these constructions can be performed
explicitly, without resorting to such acts of desperation as straightening. The
key results of this Expos\'e are: (1) a universal characterization of the
$T$-$\infty$-category of $T$-objects in any $\infty$-category, (2) the
existence of an internal Hom for $T$-$\infty$-categories, and (3) a
parametrized Yoneda lemma.


  Using molecular dynamics computer simulations we study the dynamics of a
molecular liquid by means of a general class of time-dependent correlators
S_{ll'}^m(q,t) which explicitly involve translational (TDOF) and orientational
degrees of freedom (ODOF). The system is composed of rigid, linear molecules
with Lennard- Jones interactions. The q-dependence of the static correlators
S_{ll'}^m(q) strongly depend on l, l' and m. The time dependent correlators are
calculated for l=l'. A thorough test of the predictions of mode coupling theory
(MCT) is performed for S_{ll}^m(q,t) and its self part S_{ll}^{(s)m}(q,t), for
l=1,..,6. We find a clear signature for the existence of a single temperature
T_c, at which the dynamics changes significantly. The first scaling law of MCT,
which involves the critical correlator G(t), holds for l>=2, but no critical
law is observed. Since this is true for the same exponent parameter lambda as
obtained for the TDOF, we obtain a consistent description of both, the TDOF and
ODOF, with the exception of l=1. This different behavior for l \ne 1 and l=1
can also be seen from the corresponding susceptibilities
(chi'')_{ll}^m(q,omega) which exhibit a minimum at about the same frequency
omega_{min} for all q and all l \ne 1, in contrast to (chi'')_{11}^m(q,omega)
for which omega'_{min} approx 10 omega_{min} . The asymptotic regime, for which
the first scaling law holds, shrinks with increasing l. The second scaling law
of MCT (time-temperature superposition principle) is reasonably fulfilled for l
\ne 1 but not for l=1. Furthermore we show that the q- and (l,m)-dependence of
the self part approximately factorizes, i.e. S_{ll}^{(s)m}(q,t) \cong
C_l^{(s)}(t) F_s(q,t) for all m.


  We present improved constraints on the formation time scale of massive
cluster galaxies based on rest-frame optical spectra of galaxies in a forming
cluster located at z=2.16. The spectra are obtained with MOIRCS on the Subaru
telescope with an integration time of ~7 hours. We achieve accurate redshift
measurements by fitting SEDs using the spectra and broad-band photometry
simultaneously, allowing us to identify probable cluster members. Clusters at
low redshifts are dominated by quiescent galaxies, but we find that quiescent
galaxies and star forming galaxies co-exist in this z=2 system. Interestingly,
the quiescent galaxies form a weak red sequence in the process of forming. By
stacking the spectra of star forming galaxies, we observe strong emission lines
such as [OII] and [OIII] and we obtain a tentative hint of AGN activities in
these galaxies. On the other hand, the stacked spectrum of the quiescent
galaxies reveals a clear 4000A break with a possible CaII H+K absorption
feature and strong emission lines such as [OII] are absent in the spectrum,
confirming the quiescent nature of these galaxies. We then perform detailed
spectral analyses of the stacked spectrum, which suggest that these massive
quiescent galaxies formed at redshifts between 3 and 4 on a time scale of <~0.5
Gyr. This short formation time scale is not reproduced in recent numerical
simulations. We discuss possible mechanisms for how these galaxies form 10^11
Msun stellar mass on a short time scale and become red and quiescent by z=2.


  Energetic Neutral Atom (ENA) imaging has been noticed as a powerful tool for
remote sensing the plasma-neutral interaction in space. Particularly, the
technique is used for investigation of space plasma near planetary bodies. Hear
we provide a short review of recent low-energy ENA observations (up to ~1 keV)
near Mars, Venus and the Moon.


  We calculate the orbital evolution of binary systems where the primary star
is an evolved red giant branch (RGB) star, while the secondary star is a
low-mass main sequence (MS) star or a brown dwarf. The evolution starts with a
tidal interaction causes the secondary to spiral-in. Than either a common
envelope (CE) is formed in a very short time, or alternatively the system
reaches synchronization and the spiraling-in process substantially slows down.
Some of the latter systems later enter a CE phase. We find that for a large
range of system parameters, binary systems reach stable synchronized orbits
before the onset of a CE phase. Such stable synchronized orbits allow the RGB
star to lose mass prior to the onset of the CE phase. Even after the secondary
enters the giant envelope, the rotational velocity is high enough to cause an
enhanced mass-loss rate. Our results imply that it is crucial to include the
pre-CE evolution when studying the outcome of the CE phase. We find that many
more systems survive the CE phase than would be the case if these preceding
spin-up and mass-loss phases had not been taken into account. Although we have
made the calculations for RGB stars, the results have implications for other
evolved stars that interact with close companions.


  Studies of Feshbach resonance phenomena in fermionic alkali gases have drawn
heavily on the intuition afforded by a Fermi-Bose theory which presents the
Feshbach molecule as a featureless Bose particle. While this model may provide
a suitable platform to explore the lithium-6 system, we argue that its
application to potassium-40, where the hyperfine structure is inverted, is
inappropriate. Introducing a three-state Fermi model, where a spin state is
shared by the open and closed channel states, we show that effects of ``Pauli
blocking'' are recorded in the internal structure of the condensate wave
function.


  In this paper we consider the continuity of the band functions and Bloch
functions of the differential operators generated by the differential
expressions with periodic matrix coefficients.


  The star forming processes strongly influence the ISM chemistry. Nowadays,
there are available many high-quality databases at millimeter wavelengths.
Using them, it is possible to carry out studies that review and deepen previous
results. If these studies involve large samples of sources, it is preferred to
use direct tools to study the molecular gas. With the aim of testing these
tools such as the use of the HCN/HNC ratio as a thermometer, and the use of
H$^{13}$CO$^{+}$, HC$_{3}$N, N$_{2}$H$^{+}$, and C$_{2}$H as "chemical clocks",
we present a molecular line study towards 55 sources representing massive young
stellar objects (MYSOs) at different evolutive stages: infrared dark clouds
(IRDCs), high-mass protostellar objects (HMPOs), hot molecular cores (HMCs) and
ultracompact HII regions (UCHII). We found that the use of HCN/HNC ratio as an
universal thermometer in the ISM should be taken with care because the HCN
optical depth is a big issue that can affect the method. Hence, this tool
should be used only after a careful analysis of the HCN spectrum, checking that
no line, neither the main nor the hyperfine ones, present absorption features.
We point out that the analysis of the emission of H$^{13}$CO$^{+}$, HC$_{3}$N,
N$_{2}$H$^{+}$, and C$_{2}$H could be useful to trace and distinguish regions
among IRDCs, HMPOs and HMCs. The molecular line widths of these four species
increase from the IRDC to the HMC stage, which can be a consequence of the gas
dynamics related to the star-forming processes taking place in the molecular
clumps. Our results do not only contribute with more statistics regarding to
probe such chemical tools, useful to obtain information in large samples of
sources, but also complement previous works through the analysis on other types
of sources.


  The Gysin map of a map between compact oriented manifolds is the map in
cohomology induced by the push-forward map in homology. In enumerative
algebraic geometry, formulas for the Gysin map of a flag bundle play a vital
role. These formulas are usually proven by algebraic or combinatorial means.
This article shows how the localization formula in equivariant cohomology
provides a systematic method for calculating the Gysin homomorphism in the
ordinary cohomology of a fiber bundle. As examples, we recover classical
pushforward formulas for generalized flag bundles. Our method extends the
classical formulas to fiber bundles with equivariantly formal fibers.


  A branch vertex in a tree is a vertex of degree at least three. We prove
that, for all $s\geq 1$, every connected graph on $n$ vertices with minimum
degree at least $(\frac{1}{s+3}+o(1))n$ contains a spanning tree having at most
$s$ branch vertices. Asymptotically, this is best possible and solves, in less
general form, a problem of Flandrin, Kaiser, Ku\u{z}el, Li and Ryj\'a\u{c}ek,
which was originally motivated by an optimization problem in the design of
optical networks.


  The process of contact tracing to reduce the spread of highly infectious and
life-threatening diseases has traditionally been a primarily manual process
managed by public health entities. This process becomes challenged when faced
with a pandemic of the proportions of SARS-CoV2. Digital contact tracing has
been proposed as way to augment manual contact tracing and lends itself to
widely proliferated devices such as cell phones and wearables. This paper
describes a method and analysis of determining whether two cell phones, carried
by humans, were in persistent contact of no more than 6 feet over 15 minutes
using Bluetooth Low Energy signals. The paper describes the approach to
detecting these signals, as well as a data-driven performance analysis showing
that larger numbers of samples coupled with privacy preserving auxiliary
information improves detection performance.


  In connection with Fulkerson's conjecture on cycle covers, Fan and Raspaud
proposed a weaker conjecture: For every bridgeless cubic graph $G$, there are
three perfect matchings $M_1$, $M_2$, and $M_3$ such that $M_1\cap M_2 \cap
M_3=\emptyset$. We call the property specified in this conjecture the three
matching intersection property (and 3PM property for short). We study this
property on matching covered graphs. The main results are a necessary and
sufficient condition and its applications to characterization of special
graphs, such as the Halin graphs and 4-regular graphs.


  Diffusion of colored dye on water saturated paper substrates has been
traditionally exploited with great skill by renowned water color artists. The
same physics finds more recent practical applications in paper based diagnostic
devices deploying chemicals that react with a bodily fluid yielding
colorimetric signals for disease detection. During spontaneous imbibition
through the tortuous pathways of a porous electrolyte saturated paper matrix, a
dye molecule undergoes diffusion in a complex network of pores. The advancing
front forms a strongly correlated interface that propagates diffusively but
with an enhanced effective diffusivity. We measure this effective diffusivity
and show that it is several orders of magnitude greater than the free solution
diffusivity and has a significant dependence on the solution pH and salt
concentration in the background electrolyte. We attribute this to electrically
mediated interfacial interactions between the ionic species in the liquid dye
and spontaneous surface charges developed at porous interfaces, and introduce a
simple theory to explain this phenomenon.


  For any integer $r\ge2$, define a sequence of numbers
$\{c_k^{(r)}\}_{k=0}^\infty$, independent of the parameter $n$, by $$
\sum_{k=0}^n{\binom nk}^r{\binom{n+k}k}^r =\sum_{k=0}^n\binom
nk\binom{n+k}kc_k^{(r)}, \qquad n=0,1,2,...c. $$ We prove that all the numbers
$c_k^{(r)}$ are integers.


  We use Quantum Monte Carlo method employing stochastic-series-expansion
technique to study the ground state properties of the $t_2-V_1$ model on a
square lattice. We find that, away from half-fillings, the minimal combination
of nearest-neighbor repulsion $V_1$ and next-nearest-neighbor hopping $t_2$ may
give rise to checkerboard supersolidity. The nature of the quantum phase
transition, where the superfluid changes to a checkerboard supersolid, depends
on the relative strength of $V_1/t_2$ and the average site occupancy.
Interestingly, the model exhibits a mixed-order transition near half filling;
at a higher (lower) filling, tricriticality is witnessed followed by a
second-order transition at densities even further away from half filling. Close
to half filling, the model displays the extreme Thouless effect and transits
from a superfluid to a checkerboard solid.


  We present the implementation and validation of an immersed boundary volume
penalization method in the computational fluid dynamics solver CODA (from
ONERA, DLR, and Airbus). Our goal is to model and simulate turbulent fluid
flows in complex 3D aerodynamic configurations through the numerical solution
of the Reynolds--averaged Navier--Stokes equations using the Spalart--Allmaras
turbulent model. To do that, an immersed boundary method has been implemented
in CODA and an efficient preprocessing tool for the construction of
unstructured hexahedral meshes with adaptive mesh refinement around immersed
geometries has been developed. We report several numerical examples, including
subsonic and transonic flow past a NACA0012 airfoil, subsonic flow past an
MDA30P30N multi-element airfoil, and subsonic flow around the NASA high-lift
CRM aircraft. These simulations have been performed in the CODA solver with a
second-order finite volume scheme as spatial discretization and an implicit
backward Euler scheme based on the matrix-free GMRES block-Jacobi iterative
method. The reported numerical simulations are in very good agreement with
their corresponding experimental data. We conclude that the implemented
immersed boundary method is efficient, flexible, and accurate and can therefore
be used for aeronautical applications in industry.


  In this paper we introduce a certain class of families of Hessenberg
varieties arising from Springer theory for symmetric spaces. We study the
geometry of those Hessenberg varieties and investigate their monodromy
representations in detail using the geometry of complete intersections of
quadrics. We obtain decompositions of these monodromy representations into
irreducibles and compute the Fourier transforms of the IC complexes associated
to these irreducible representations. The results of the paper refine (part of)
the Springer correspondece for the split symmetric pair (SL(N),SO(N)) in
[CVX2].


  Let $\Gamma\backslash\mathbb H^3$ be a finite-volume quotient of the
upper-half space, where $\Gamma\subset {\rm SL}(2,\mathbb C)$ is a discrete
subgroup. To a finite dimensional unitary representation $\chi$ of $\Gamma$ one
associates the Selberg zeta function $Z(s;\Gamma;\chi)$. In this paper we prove
the Artin formalism for the Selberg zeta function. Namely, if $\tilde\Gamma$ is
a finite index group extension of $\Gamma$ in ${\rm SL}(2,\mathbb C)$, and
$\pi={\rm Ind}_{\Gamma}^{\tilde\Gamma}\chi$ is the induced representation, then
$Z(s;\Gamma;\chi)=Z(s;\tilde\Gamma;\pi)$. In the second part of the paper we
prove by a direct method the analogous identity for the scattering function,
namely $\phi(s;\Gamma;\chi)=\phi(s;\tilde\Gamma;\pi)$, for an appropriate
normalization of the Eisenstein series.


  Layered Co oxide NaxCoO2.yH2O with the superconducting transition temperature
Tc =4.5 K has been studied by 59Co-NMR. The Knight shift K estimated from the
observed spectra for powder sample exhibits almost temperature(T)-independent
behavior above Tc and decreases with decreasing T below Tc. This result and the
existence of the coherence peak in the spin-lattice-relaxation-rate versus T
curve reported by the present authors indicate, naively speaking, that the
singlet order parameter with s-wave symmetry is realized in NaxCoO2.yH2O.
Differences of the observed behaviors between the spectra of the non-aligned
sample and the one aligned in epoxy adhesive by applying the external magnetic
field are discussed.


  We introduce a one-dimensional model of Bose-Einstein condensates (BECs),
combining the double-well potential, which is a well-known setting for the
onset of spontaneous-symmetry-breaking (SSB) effects, and time-periodic
modulation of the nonlinearity, which may be implemented by means of the
Feshbach-resonance-management (FRM) technique. Both cases of the nonlinearity
which is repulsive or attractive on the average are considered. In the former
case, the main effect produced by the application of the FRM is spontaneous
self-trapping of the condensate in either of the two potential wells in
parameter regimes where it would remain untrapped in the absence of the
management. In the weakly nonlinear regime, the frequency of intrinsic
oscillations in the FRM-induced trapped state is very close to half the FRM
frequency, suggesting that the effect is accounted for by a parametric
resonance. In the case of the attractive nonlinearity, the FRM-induced effect
is the opposite, i.e., enforced detrapping of a state which is self-trapped in
its unmanaged form. In the latter case, the frequency of oscillations of the
untrapped mode is close to a quarter of the driving frequency, suggesting that
a higher-order parametric resonance may account for this effect.


  A new pseudospectral calculation of collapsing Euler vortices \cite{HouLi06}
has called into question the long-term conclusions of singular behavior
described earlier in \cite{Kerr93,Kerr05}. This review is designed to: improve
the discussion of the detailed analysis of one test initial condition designed
find sources of errors, to compare that with calculations showing no evidence
of a singularity, and to document two sets of discussions. Those prior to 1993
between competing teams. And recent discussions of what is needed to reach more
convincing conclusions.


  Multivariate time series (MTS) forecasting is crucial in many real-world
applications. To achieve accurate MTS forecasting, it is essential to
simultaneously consider both intra- and inter-series relationships among time
series data. However, previous work has typically modeled intra- and
inter-series relationships separately and has disregarded multi-order
interactions present within and between time series data, which can seriously
degrade forecasting accuracy. In this paper, we reexamine intra- and
inter-series relationships from the perspective of mutual information and
accordingly construct a comprehensive relationship learning mechanism tailored
to simultaneously capture the intricate multi-order intra- and inter-series
couplings. Based on the mechanism, we propose a novel deep coupling network for
MTS forecasting, named DeepCN, which consists of a coupling mechanism dedicated
to explicitly exploring the multi-order intra- and inter-series relationships
among time series data concurrently, a coupled variable representation module
aimed at encoding diverse variable patterns, and an inference module
facilitating predictions through one forward step. Extensive experiments
conducted on seven real-world datasets demonstrate that our proposed DeepCN
achieves superior performance compared with the state-of-the-art baselines.


  We study versions of the tree pigeonhole principle, $\mathsf{TT}^1$, in the
context of Weihrauch-style computable analysis. The principle has previously
been the subject of extensive research in reverse mathematics. Two outstanding
questions from the latter investigation are whether $\mathsf{TT}^1$ is
$\Pi^1_1$-conservative over the ordinary pigeonhole principle, $\mathsf{RT}^1$,
and whether it is equivalent to any first-order statement of second-order
arithmetic. Using the recently introduced notion of the first-order part of an
instance-solution problem, we formulate, and answer in the affirmative, the
analogue of the first question for Weihrauch reducibility. We then use this, in
combination with other results, to answer in the negative the analogue of the
second question. Our proofs develop a new combinatorial machinery for
constructing and understanding solutions to instances of $\mathsf{TT}^1$.


  Based on the theory of relativistic superstrong magnetic fields(SMFs), by
using the method of the Thomas-Fermi-Dirac approximations, we investigate the
problem of strong electron screening(SES) in SMFs, and the influence of SES on
the nuclear reaction of $^{23}$Mg $(p, \gamma)$$^{24}$Al. Our calculations show
that the nuclear reaction will be markedly effected by the SES in SMFs in the
surface of magnetars. Our calculated screening rates can increase two orders of
magnitude due to SES in SMFs.


  In many electron spin qubit systems coherent control is impaired by the
fluctuating nuclear spin bath of the host material. Previous experiments have
shown dynamic nuclear polarization with feedback to significantly prolong the
inhomogeneous dephasing time $T_2^*$ by narrowing the distribution of nuclear
Overhauser field fluctuations. We present a model relating the achievable
narrowing of the Overhauser field to both the pump rate and the noise magnitude
and find reasonable agreement with experimental data. It shows that former
experiments on gated GaAs quantum dots were limited by the pump rate of the
pumping mechanism used. Here we propose an alternative feedback scheme using
electron dipole spin resonance. Sequentially applying two ac electric fields
with frequencies slightly detuned from the desired Larmor frequency results in
a pump curve with a stable fixed point. Our model predicts that $T_2^*$ values
on the order of microseconds can be achieved.


  Timings of human activities are marked by circadian clocks which in turn are
entrained to different environmental signals. In an urban environment the
presence of artificial lighting and various social cues tend to disrupt the
natural entrainment with the sunlight. However, it is not completely understood
to what extent this is the case. Here we exploit the large-scale data analysis
techniques to study the mobile phone calling activity of people in large cities
to infer the dynamics of urban daily rhythms. From the calling patterns of
about 1,000,000 users spread over different cities but lying inside the same
time-zone, we show that the onset and termination of the calling activity
synchronizes with the east-west progression of the sun. We also find that the
onset and termination of the calling activity of users follows a yearly
dynamics, varying across seasons, and that its timings are entrained to solar
midnight. Furthermore, we show that the average mid-sleep time of people living
in urban areas depends on the age and gender of each cohort as a result of
biological and social factors.


  We investigate linear perturbations of spin-s fields in the Kerr-AdS black
hole and in its near-horizon geometry (NHEK-AdS), using the Teukolsky master
equation and the Hertz potential. In the NHEK-AdS geometry we solve the
associated angular equation numerically and the radial equation exactly. Having
these explicit solutions at hand, we search for linear mode instabilities. We
do not find any (non-)axisymmetric instabilities with outgoing boundary
conditions. This is in agreement with a recent conjecture relating the
linearized stability properties of the full geometry with those of its
near-horizon geometry. Moreover, we find that the asymptotic behaviour of the
metric perturbations in NHEK-AdS violates the fall-off conditions imposed in
the formulation of the Kerr/CFT correspondence (the only exception being the
axisymmetric sector of perturbations).


  An extended version of the antisymmetrized molecular dynamics to study
structure of $p$-$sd$ shell hypernuclei is developed. By using an effective
$\Lambda N$ interaction, we investigate energy curves of $^9_\Lambda$Be,
$^{13}_\Lambda$C and $^{20,21}_\Lambda$Ne as function of nuclear quadrupole
deformation. Change of nuclear deformation caused by $\Lambda$ particle is
discussed. It is found that the $\Lambda$ in p-wave enhances nuclear
deformation, while that in s-wave reduces it. This effect is most prominent in
$^{13}_\Lambda$C. The possibility of the parity inversion in $^{20}_\Lambda$Ne
is also examined.


  The calibration of a model refers to the process by which one can estimate
some parameters by comparisons with observed data. Due to the dynamical nature
of the environment, variations between predicted and observed values occur.
Thus, the environmental parameters may vary due to random temperature changes,
time of discharge flow, time of the day, and other conditions. Such variations
can be minimized by identifying and optimizing some parameters of the transport
model, like the values of diffusion coefficients in x and y directions and the
kinetic parameter that describes the process of removing pollutants. This paper
presents results concerning the calibration of transport parameters for
two-dimensional problems of water quality (fecal coliform control) at Igap\'o I
Lake, located in Londrina, Paran\'a, Brazil. Thus, the
convection-diffusion-reaction equation, which describes mathematically the
process studied in this work, is resolved by a semidiscrete finite element
method (SUPG) which combines finite differences in time and finite elements in
space.


  For any countable directed graph E we describe the primitive ideal space of
the corresponding generalized Cuntz-Krieger algebra C*(E).


  In the framework of functional integration the non-leading terms to leading
eikonal behavior of the Planckian-energy scattering amplitude are calculated by
the straight-line path approximation. We show that the allowance for the
first-order correction terms leads to the appearance of retardation effect. The
singular character of the correction terms at short distances is also noted,
and they may be lead ultimately to the appearance of non-eikonal contributions
to the scattering amplitudes.


  We construct a new class of solutions to the dispersionless hyper--CR
equation, and show how any solution to this equation gives rise to a
supersymmetric Einstein--Maxwell cosmological space--time in
$(3+1)$--dimensions.


  We report on a set of AGN that match the Seyfert 2 galaxy classification
criteria, but display unusually wide "narrow" lines, with the 4959 {\AA} and
5007 {\AA} nebular lines overlapping with each other. This spectral line
broadening is in most cases evidence of a complex profile with multiple
components. It indicates an unusual narrow line region with diverse gas clouds
and a range of velocity systems. We list 14 such objects with these
characteristics identified in a set of Sloan Digital Sky Survey spectra. We
measure the strengths of all lines visible in the spectrum, and attempt to fit
multiple Gaussian profiles to the nebular lines. We quantify the line
parameters of all multiple velocity systems discovered. We compare the spectral
characteristics of our sample with those of other, 'conventional' type 2
Seyferts and attempt to determine whether other systematic spectral differences
exist. We consider whether the investigated sample constitutes a clear
sub-class of the Seyfert 2 population. In conclusion we offer possible
explanations for the unusual line profiles.


  We study transport through a lateral quantum dot in the vicinity of the
singlet-triplet transition in its ground state. This transition, being sharp in
an isolated dot, is broadened to a crossover by the exchange interaction of the
dot electrons with the conduction electrons in the leads. For a generic set of
system's parameters, the linear conductance has a maximum in the crossover
region. At zero temperature and magnetic field, the maximum is the strongest.
It becomes less pronounced at finite Zeeman splitting, which leads to an
increase of the background conductance and a decrease of the conductance in the
maximum.


  Distinguishing gastrointestinal stromal tumors (GISTs) from other
intra-abdominal tumors and GISTs molecular analysis is necessary for treatment
planning, but challenging due to its rarity. The aim of this study was to
evaluate radiomics for distinguishing GISTs from other intra-abdominal tumors,
and in GISTs, predict the c-KIT, PDGFRA,BRAF mutational status and mitotic
index (MI). All 247 included patients (125 GISTS, 122 non-GISTs) underwent a
contrast-enhanced venous phase CT. The GIST vs. non-GIST radiomics model,
including imaging, age, sex and location, had a mean area under the curve (AUC)
of 0.82. Three radiologists had an AUC of 0.69, 0.76, and 0.84, respectively.
The radiomics model had an AUC of 0.52 for c-KIT, 0.56 for c-KIT exon 11, and
0.52 for the MI. Hence, our radiomics model was able to distinguish GIST from
non-GISTS with a performance similar to three radiologists, but was not able to
predict the c-KIT mutation or MI.


  As the title implies the article describes the possibility of taking into
account the relativistic correction to the field current density of the field
emission of electrons from the metal. The article provides the reader with some
analytic generalization of the Fowler-Nordheim equation with the relativistic
correction. The relativistic correction to the Fowler-Nordheim equation makes
it possible to take into account the influence of the relativism on the field
emission current. It is especially noted that the consideration of this
correction is necessary in the case of sufficiently strong electric fields and
relatively large interelectrode distances. It should be stressed that this
correction is valid for fixed interelectrode distances that decrease with
increasing electric field strength. It means that for the electric field
strength of 0.1 to 1 GV/m the interelectrode distance should not exceed values
of 1 to 0.1 cm. First in the article it is spoken in detail about finding of
the electron wave function. Next the field emission current calculations are
given. As a result the transmission coefficient of the potential step from the
Klein-Gordon equation within the framework of the Fowler-Nordheim approximation
is found. It is shown that in the case of the interelectrode distance less than
1 cm, an analytical expression for the field electron emission current density
is obtained. The conclusion that usually relativistic correction does not
exceed a tenth of a percent is made. But in the case of the field electron
emission from pulsars (where the work function and electric field strength are
much higher) the contribution of the relativistic correction about 10 % has
been established.


  Given a graph $G$ with $n$ vertices and maximum degree $\Delta$, it is known
that $G$ admits a vertex coloring with $\Delta + 1$ colors such that no edge of
$G$ is monochromatic. This can be seen constructively by a simple greedy
algorithm, which runs in time $O(n\Delta)$.
  Very recently, a sequence of results (e.g., [Assadi et. al. SODA'19, Bera et.
al. ICALP'20, Alon Assadi Approx/Random'20]) show randomized algorithms for
$(\epsilon + 1)\Delta$-coloring in the query model making
$\tilde{O}(n\sqrt{n})$ queries, improving over the greedy strategy on dense
graphs. In addition, a lower bound of $\Omega(n\sqrt n)$ for any
$O(\Delta)$-coloring is established on general graphs.
  In this work, we give a simple algorithm for $(1 + \epsilon)\Delta$-coloring.
This algorithm makes $O(\epsilon^{-1/2}n\sqrt{n})$ queries, which matches the
best existing algorithms as well as the classical lower bound for sufficiently
large $\epsilon$. Additionally, it can be readily adapted to a quantum query
algorithm making $\tilde{O}(\epsilon^{-1}n^{4/3})$ queries, bypassing the
classical lower bound. Complementary to these algorithmic results, we show a
quantum lower bound of $\Omega(n)$ for $O(\Delta)$-coloring.


  The stability (or instability) of finite sized magnetic island could play a
significant role in disruption avoidance or disruption mitigation dynamics.
Especially, various current and pressure profile modifications, such as the
current drive and heating caused by electron cyclotron wave, or the radiative
cooling and current expulsion caused by the Shattered Pellet Injection could be
applied within the island to modify its stability, thus change the ensuing
dynamics. In this study, we calculate the mode structure modification caused by
such profile changes within the island using the perturbed equilibrium
approach, thus obtain the change of stability criterion $\gD'$ and assess the
corresponding quasi-linear island stability. The positive helical current
perturbation is found to always stabilize the island, while the negative one is
found to do the opposite, in agreement with previous results. The pressure bump
or hole within the island has a more complicated stability impact. In the small
island regime, its contribution is monotonic, with pressure bump tends to
stabilize the island while pressure hole destabilizes it. This effect is
relatively weak, though, due to the cancellation of the pressure term's odd
parity contribution in the second derivatives of the mode structure. In the
large island regime, such cancellation is broken due to the island asymmetry,
and the pressure contribution to stability is manifested, which is
non-monotonic. The stability analysis in this paper helps to more accurately
clarify the expected island response in the presence of profile modifications
caused by disruption avoidance or mitigation systems.


  Quest for new states of matter near an ordered phase is a promising route for
making modern physics forward. By probing thermal properties of a ferroelectric
(FE) crystal Ba1-xSrxAl2O4, we have clarified that low-energy excitation of
acoustic phonons is remarkably enhanced with critical behavior at the border of
the FE phase. The phonon spectrum is significantly damped toward the FE phase
boundary and transforms into glasslike phonon excitation which is reminiscent
of a boson peak. This system thus links long-standing issues of amorphous
solids and structural instability in crystals to pave the way to controlling
lattice fluctuation as a new tuning parameter.


  The ability to enhance resonant signals and eliminate the non-resonant
background is analyzed for Coherent Anti-Stokes Raman Scattering (CARS). The
analysis is done at a specific frequency as well as for broadband excitation
using femtosecond pulse-shaping techniques. An appropriate objective functional
is employed to balance resonant signal enhancement against non-resonant
background suppression. Optimal enhancement of the signal and minimization of
the background can be achieved by shaping the probe pulse alone while keeping
the pump and Stokes pulses in transform-limited-form (TLF). In some cases
analytical forms for the probe pulse can be found, and numerical simulations
are carried out for other circumstances. It is found that a good approximate
solution for the optimal pulse in the two-pulse CARS is a superposition of
linear and arctangent type phases for the pump. The well-known probe delay
method is shown to be a quasi-optimal scheme for background suppression. The
results should provide a basis to improve the performance of CARS spectroscopy
and microscopy.


  In this paper we study $\widetilde{J}$-tangent affine hyperspheres, where
$\widetilde{J}$ is the canonical para-complex structure on $\mathbb{R}^{2n+2}$.
The main purpose of this paper is to give a classification of
$\widetilde{J}$-tangent affine hyperspheres of an arbitrary dimension with an
involutive distribution $\mathcal{D}$. In particular, we classify all such
hyperspheres in the $3$-dimensional case. We also show that there is a direct
relation between $\widetilde{J}$-tangent affine hyperspheres and Calabi
products. As an application we obtain certain classification results. In
particular, we show that, with one exception, all odd dimensional proper flat
affine hyperspheres are, after a suitable affine transformation,
$\widetilde{J}$-tangent. Some examples of $\widetilde{J}$-tangent affine
hyperspheres are also given.


  We prove that complete Riemannian manifolds with polynomial growth and Ricci
curvature bounded from below, admit uniform Poincar\'e inequalities. A global,
uniform Poincar\'e inequality for horospheres in the universal cover of a
closed, $n$-dimensional Riemannian manifold with pinched negative sectional
curvature follows as a corollary.


  Massive Open Online Courses (MOOCs) exhibit a remarkable heterogeneity of
students. The advent of complex "big data" from MOOC platforms is a challenging
yet rewarding opportunity to deeply understand how students are engaged in
MOOCs. Past research, looking mainly into overall behavior, may have missed
patterns related to student diversity. Using a large dataset from a MOOC
offered by FutureLearn, we delve into a new way of investigating hidden
patterns through both machine learning and statistical modelling. In this
paper, we report on clustering analysis of student activities and comparative
analysis on both behavioral patterns and demographical patterns between student
subpopulations in the MOOC. Our approach allows for a deeper understanding of
how MOOC students behave and achieve. Our findings may be used to design
adaptive strategies towards an enhanced MOOC experience


  PyPartMC is a Pythonic interface to PartMC, a stochastic, particle-resolved
aerosol model implemented in Fortran. Both PyPartMC and PartMC are free, libre,
and open-source. PyPartMC reduces the number of steps and mitigates the effort
necessary to install and utilize the resources of PartMC. Without PyPartMC,
setting up PartMC requires: working with UNIX shell, providing Fortran and C
libraries, and performing standard Fortran and C source code configuration,
compilation and linking. This can be challenging for those less experienced
with computational research or those intending to use PartMC in environments
where provision of UNIX tools is less straightforward (e.g., on Windows).
PyPartMC offers a single-step installation/upgrade process of PartMC and all
dependencies through the pip Python package manager on Linux, macOS, and
Windows. This allows streamlined access to the unmodified and versioned Fortran
internals of the PartMC codebase from both Python and other interoperable
environments (e.g., Julia through PyCall). Consequently, users of PyPartMC can
setup, run, process and visualize output of PartMC simulations using a single
general-purpose programming language.


  We present in this paper a study on the ability and the benefits of using a
keystroke dynamics authentication method for collaborative systems.
Authentication is a challenging issue in order to guarantee the security of use
of collaborative systems during the access control step. Many solutions exist
in the state of the art such as the use of one time passwords or smart-cards.
We focus in this paper on biometric based solutions that do not necessitate any
additional sensor. Keystroke dynamics is an interesting solution as it uses
only the keyboard and is invisible for users. Many methods have been published
in this field. We make a comparative study of many of them considering the
operational constraints of use for collaborative systems.