  We present an empirical method of assessing the star formation rate (SFR) of
star-forming galaxies based on their locations in the rest-frame color-color
diagram (NUV-r) vs (r-K). By using the Spitzer 24 micron sample in the COSMOS
field (~16400 galaxies with 0.2 < z < 1.3) and a local GALEX-SDSS-SWIRE sample
(~700 galaxies with z < 0.2), we show that the mean infrared excess <IRX>= <
L_IR / L_UV > can be described by a single vector, NRK, that combines the two
colors. The calibration between <IRX> and NRK allows us to recover the IR
luminosity, L_IR, with an accuracy of ~0.21 dex for the COSMOS sample and ~0.27
dex for the local one. The SFRs derived with this method agree with the ones
based on the observed (UV+IR) luminosities and on the spectral energy
distribution fitting for the vast majority (~85 %) of the star-forming
population. Thanks to a library of model galaxy SEDs with realistic
prescriptions for the star formation history, we show that we need to include a
two-component dust model (i.e., birth clouds and diffuse ISM) and a full
distribution of galaxy inclinations in order to reproduce the behavior of the
<IRX> stripes in the NUVrK diagram. In conclusion, the NRK method, based only
on rest-frame UV and optical colors available in most of the extragalactic
fields, offers a simple alternative of assessing the SFR of star-forming
galaxies in the absence of far-IR or spectral diagnostic observations.


  Accurate temperature regulation is critical for amperometric DNA analysis to
achieve high fidelity, reliability, and throughput. In this work, a 9x6 cell
array of mixed-signal CMOS distributed temperature regulators for on-CMOS
multi-modal amperometric DNA analysis is presented. Three DNA analysis methods
are supported, including constant potential amperometry (CPA), cyclic
voltammetry (CV), and impedance spectroscopy (IS). In-cell heating and
temperature sensing elements are implemented in standard CMOS technology
without post-processing. Using proportional-integral-derivative (PID) control,
the local temperature can be regulated to within +/-0.5C of any desired value
between 20C and 90C. The two computationally intensive operations in the PID
algorithm, multiplication, and subtraction, are performed by an in-cell
dual-slope multiplying ADC in the mixed-signal domain, resulting in a small
area and low power consumption. Over 95% of the circuit blocks are
synergistically shared among the four operating modes, including CPA, CV, IS,
and the proposed temperature regulation mode. A 3mmx3mm CMOS prototype
fabricated in a 0.13um CMOS technology has been fully experimentally
characterized. Each channel occupies an area of 0.06mm2 and consumes 42uW from
a 1.2V supply. The proposed distributed temperature regulation design and the
mixed-signal PID implementation can be applied to a wide range of sensory and
other applications.


  Head pose estimation plays a vital role in various applications, e.g.,
driverassistance systems, human-computer interaction, virtual reality
technology, and so on. We propose a novel geometry based algorithm for
accurately estimating the head pose from a single 2D face image at a very low
computational cost. Specifically, the rectangular coordinates of only four
non-coplanar feature points from a predefined 3D facial model as well as the
corresponding ones automatically/ manually extracted from a 2D face image are
first normalized to exclude the effect of external factors (i.e., scale factor
and translation parameters). Then, the four normalized 3D feature points are
represented in spherical coordinates with reference to the uniquely determined
sphere by themselves. Due to the spherical parameterization, the coordinates of
feature points can then be morphed along all the three directions in the
rectangular coordinates effectively. Finally, the rotation matrix indicating
the head pose is obtained by minimizing the Euclidean distance between the
normalized 2D feature points and the 2D re-projections of morphed 3D feature
points. Comprehensive experimental results over two popular databases, i.e.,
Pointing'04 and Biwi Kinect, demonstrate that the proposed algorithm can
estimate head poses with higher accuracy and lower run time than
state-of-the-art geometry based methods. Even compared with start-of-the-art
learning based methods or geometry based methods with additional depth
information, our algorithm still produces comparable performance.


  We investigate low-scale resonant leptogenesis in an $SU(5) \times
\mathcal{T}_{13}$ model where a single high energy phase in the complex
Tribimaximal seesaw mixing produces the yet-to-be-observed low energy Dirac and
Majorana ${CP}$ phases. A fourth right-handed neutrino, required to generate
viable light neutrino masses within this scenario, also turns out to be
necessary for successful resonant leptogenesis where $CP$ asymmetry is produced
by the same high energy phase. We derive a lower bound on the right-handed
neutrino mass spectrum in the $\mathrm{GeV}$ range, where part of the parameter
space, although in tension with Big Bang Nucleosynthesis constrains, can be
probed in planned high intensity experiments like DUNE. We also find the
existence of a curious upper bound ($\text{TeV}$-scale) on the right-handed
neutrino mass spectrum in majority of the parameter space due to significant
washout of the resonant asymmetry by lighter right-handed neutrinos. While in
most of the parameter space of our model classical Boltzmann equations are
sufficient, when right-handed neutrino masses are below the electroweak
sphalerons freeze-out temperature we resort to the more general density matrix
formalism to take into account decays and oscillations of the right-handed
neutrinos as well as their helicities which are relevant when they are
relativistic.


  We compute the 1-loop correction to the effective action for the string
solution in AdS_5 x S^5 dual to the circular Wilson loop. More generically, the
method we use can be applied whenever the two dimensional spectral problem
factorizes, to regularize and define the fluctuation determinants in terms of
solutions of one-dimensional differential equations. A such it can be applied
to non-homogeneous solutions both for open and closed strings and to various
boundary conditions. In the case of the circular Wilson loop, we obtain, for
the 1-loop partition function a result which up to a factor of two matches the
expectation from the exact gauge theory computation. The discrepancy can be
attributed to an overall constant in the string partition function coming from
the normalization of zero modes, which we have not fixed.


  We present results from an asymptotic magnetohydrodynamic model that is
suited for studying the rapidly rotating, low viscosity regime typical of the
electrically conducting fluid interiors of planets and stars. We show that the
presence of sufficiently strong magnetic fields prevents the formation of
large-scale vortices and saturates the inverse cascade at a finite
length-scale. This saturation corresponds to an equilibrated state in which the
energetics of the depth-averaged flows are characterized by a balance of
convective power input and ohmic dissipation. A quantitative criteria
delineating the transition between finite-size flows and domain-filling
(large-scale) vortices in electrically conducting fluids is found. By making
use of the inferred and observed properties of planetary interiors, our results
suggest that convection-driven large-scale vortices do not form in the
electrically conducting regions of many bodies.


  We introduce extremely symmetric primes and provide some elementary
properties of these.


  Multi-label classification, which predicts a set of labels for an input, has
many applications. However, multiple recent studies showed that multi-label
classification is vulnerable to adversarial examples. In particular, an
attacker can manipulate the labels predicted by a multi-label classifier for an
input via adding carefully crafted, human-imperceptible perturbation to it.
Existing provable defenses for multi-class classification achieve sub-optimal
provable robustness guarantees when generalized to multi-label classification.
In this work, we propose MultiGuard, the first provably robust defense against
adversarial examples to multi-label classification. Our MultiGuard leverages
randomized smoothing, which is the state-of-the-art technique to build provably
robust classifiers. Specifically, given an arbitrary multi-label classifier,
our MultiGuard builds a smoothed multi-label classifier via adding random noise
to the input. We consider isotropic Gaussian noise in this work. Our major
theoretical contribution is that we show a certain number of ground truth
labels of an input are provably in the set of labels predicted by our
MultiGuard when the $\ell_2$-norm of the adversarial perturbation added to the
input is bounded. Moreover, we design an algorithm to compute our provable
robustness guarantees. Empirically, we evaluate our MultiGuard on VOC 2007,
MS-COCO, and NUS-WIDE benchmark datasets. Our code is available at:
\url{https://github.com/quwenjie/MultiGuard}


  This paper considers a generic convex minimization template with affine
constraints over a compact domain, which covers key semidefinite programming
applications. The existing conditional gradient methods either do not apply to
our template or are too slow in practice. To this end, we propose a new
conditional gradient method, based on a unified treatment of smoothing and
augmented Lagrangian frameworks. The proposed method maintains favorable
properties of the classical conditional gradient method, such as cheap linear
minimization oracle calls and sparse representation of the decision variable.
We prove $\mathcal{O}(1/\sqrt{k})$ convergence rate of our method in the
objective residual and the feasibility gap. This rate is essentially the same
as the state of the art CG-type methods for our problem template, but the
proposed method is significantly superior to existing methods in various
semidefinite programming applications.


  The challenge of fairness arises when Automatic Speech Recognition (ASR)
systems do not perform equally well for all sub-groups of the population. In
the past few years there have been many improvements in overall speech
recognition quality, but without any particular focus on advancing Equality and
Equity for all user groups for whom systems do not perform well. ASR fairness
is therefore also a robustness issue. Meanwhile, data privacy also takes
priority in production systems. In this paper, we present a privacy preserving
approach to improve fairness and robustness of end-to-end ASR without using
metadata, zip codes, or even speaker or utterance embeddings directly in
training. We extract utterance level embeddings using a speaker ID model
trained on a public dataset, which we then use in an unsupervised fashion to
create acoustic clusters. We use cluster IDs instead of speaker utterance
embeddings as extra features during model training, which shows improvements
for all demographic groups and in particular for different accents.


  In this article, we present a novel approach to reconstruct the topology of
networked linear dynamical systems with latent nodes. The network is allowed to
have directed loops and bi-directed edges. The main approach relies on the
unique decomposition of the inverse of power spectral density matrix (IPSDM)
obtained from observed nodes as a sum of sparse and low-rank matrices. We
provide conditions and methods for decomposing the IPSDM of the observed nodes
into sparse and low-rank components. The sparse component yields the moral
graph associated with the observed nodes, and the low-rank component retrieves
parents, children and spouses (the Markov Blanket) of the hidden nodes. The
article provides necessary and sufficient conditions for the unique
decomposition of a given skew symmetric matrix into sum of a sparse skew
symmetric and a low-rank skew symmetric matrices. It is shown that for a large
class of systems, the unique decomposition of imaginary part of the IPSDM of
observed nodes, a skew symmetric matrix, into the sparse and the low-rank
components is sufficient to identify the moral graph of the observed nodes as
well as the Markov Blanket of latent nodes. For a large class of systems, all
spurious links in the moral graph formed by the observed nodes can be
identified. Assuming conditions on hidden nodes required for identifiability,
links between the hidden and observed nodes can be reconstructed, resulting in
the retrieval of the exact topology of the network from the availability of
IPSDM. Moreover, for finite number of data samples, we provide concentration
bounds on the entry-wise distance between the true IPSDM and the estimated
IPSDM.


  This article considers "compressive learning," an approach to large-scale
machine learning where datasets are massively compressed before learning (e.g.,
clustering, classification, or regression) is performed. In particular, a
"sketch" is first constructed by computing carefully chosen nonlinear random
features (e.g., random Fourier features) and averaging them over the whole
dataset. Parameters are then learned from the sketch, without access to the
original dataset. This article surveys the current state-of-the-art in
compressive learning, including the main concepts and algorithms, their
connections with established signal-processing methods, existing theoretical
guarantees -- on both information preservation and privacy preservation, and
important open problems.


  Pulling back the weight systems associated with the exceptional Lie algebras
and their standard representations by a modification of the universal
Vassiliev-Kontsevich invariant yields link invariants; extending them to
coloured 3-nets, we derive for each of them a skein relation.


  Exploiting small angle X-ray and neutron scattering (SAXS/SANS) on the same
sample volume at the same time provides complementary nanoscale structural
information at two different contrast situations. Compared with an independent
experimental approach, the truly combined SAXS/SANS experimental approach
ensures the exactness of the probed samples particularly for in-situ studies.
Here, we introduce an advanced portable SAXS system that is dimensionally
suitable for installation at D22 zone of ILL. The SAXS apparatus is based on a
RIGAKU copper/molybdenum switchable microfocus rotating anode X-ray generator
and a DECTRIS detector with a changeable sample-to-detector distance of up to
1.6 m in a vacuum chamber. A science case has been presented to demonstrate the
uniqueness of the newly established method at ILL. Temporal structural
rearrangements of both, organic stabilizing agents and organically capped gold
colloidal particles during gold nanoparticle growth are simultaneously probed,
enabling immediate correlated structural information. The newly established
nano-analytical method at ILL will open the way for real time investigations of
a wide range of innovative nanomaterials and will enable comprehensive in-situ
studies on biological systems. A potential development of a fully-automated
SAXS/SANS system with a common control environment and additional sample
environments, permitting a continual and efficient operation of the system at
the hands of ILL users, has also been introduced.


  The present work is a continuation of the previous papers written by the
author on the subject. In terms of the measurability (or measurable quantities)
notion introduced in a minimal length theory, first the consideration is given
to a quantum theory in the momentum representation. The same terms are used to
consider the Markov gravity model that here illustrates the general approach to
studies of gravity in terms of measurable quantities. This paper is dedicated
to the 75th Anniversary of Professor Vladimir Grigor'evich Baryshevsky.


  We consider an open system of non-interacting electrons consisting of a small
sample connected to several reservoirs and temperature or voltage probes. We
study the non-linear system of equations that determines the probe parameters.
We show that it has a unique solution, which can be computed with a fast
converging iterative algorithm. We illustrate our method with two well-known
models: the three-terminal system and the open Aharovov-Bohm interferometer.


  We consider a dynamical field theory (Active Model B+) that minimally extends
the equilibrium Model B for diffusive phase separation of a scalar field, by
adding leading-order terms that break time-reversal symmetry. It was recently
shown that such active terms can cause the bulk phase separation of Model B to
be replaced by a steady state of microphase separation at a finite length
scale. This phenomenon was understood at mean-field level as due to the
activity-induced reversal of the Ostwald ripening mechanism, which provides the
kinetic pathway to bulk phase separation in passive fluids. This reversal
occurs only in certain ranges for the activity parameters. In this paper we go
beyond such a mean-field analysis and develop a $1$-loop Renormalisation Group
(RG) approach. We first show that, in the parameter range where bulk phase
separation is still present, the critical point belongs formally to the same
(Wilson-Fisher) universality class as the passive Model B. In contrast, in a
parameter range associated with microphase separation, we find that an unstable
non-equilibrium fixed point of the RG flow arises for $d\geq 2$, colliding with
the Wilson-Fisher point in $d\to 2^+$ and making it unstable in $d=2$. At large
activity, the flow in this region is towards strong coupling. We argue that the
phase transition to microphase separation in active systems, in the physically
relevant dimensions $d=2$ and $3$, very probably belongs to a new
non-equilibrium universality class. Because it is governed by the
strong-coupling regime of the RG flow, our perturbative analysis leaves open
the quantitative characterization of this new class.


  Combination of low-tensor rank techniques and the Fast Fourier transform
(FFT) based methods had turned out to be prominent in accelerating various
statistical operations such as Kriging, computing conditional covariance,
geostatistical optimal design, and others. However, the approximation of a full
tensor by its low-rank format can be computationally formidable. In this work,
we incorporate the robust Tensor Train (TT) approximation of covariance
matrices and the efficient TT-Cross algorithm into the FFT-based Kriging. It is
shown that here the computational complexity of Kriging is reduced to
$\mathcal{O}(d r^3 n)$, where $n$ is the mode size of the estimation grid, $d$
is the number of variables (the dimension), and $r$ is the rank of the TT
approximation of the covariance matrix. For many popular covariance functions
the TT rank $r$ remains stable for increasing $n$ and $d$. The advantages of
this approach against those using plain FFT are demonstrated in synthetic and
real data examples.


  The stochastic linear bandit problem proceeds in rounds where at each round
the algorithm selects a vector from a decision set after which it receives a
noisy linear loss parameterized by an unknown vector. The goal in such a
problem is to minimize the (pseudo) regret which is the difference between the
total expected loss of the algorithm and the total expected loss of the best
fixed vector in hindsight. In this paper, we consider settings where the
unknown parameter has structure, e.g., sparse, group sparse, low-rank, which
can be captured by a norm, e.g., $L_1$, $L_{(1,2)}$, nuclear norm. We focus on
constructing confidence ellipsoids which contain the unknown parameter across
all rounds with high-probability. We show the radius of such ellipsoids depend
on the Gaussian width of sets associated with the norm capturing the structure.
Such characterization leads to tighter confidence ellipsoids and, therefore,
sharper regret bounds compared to bounds in the existing literature which are
based on the ambient dimensionality.


  In this talk I present the complete 1-loop perturbative computation of the
renormalization constants and mixing coefficients of quark and gluon lattice
operators of rank two and three whose hadronic elements enter in the
determination of the first and second moment of Deep Inelastic Scattering
Structure Functions, making use of the nearest-neighbor improved
``clover-leaf'' lattice QCD action.
  To perform the huge amount of calculations required for the evaluation of all
the relevant Feynman diagrams, extensive use of symbolic manipulation languages
like Schoonschip and Form has been made.


  We give a complete algorithm and source code for constructing what we refer
to as heterotic risk models (for equities), which combine: i) granularity of an
industry classification; ii) diagonality of the principal component factor
covariance matrix for any sub-cluster of stocks; and iii) dramatic reduction of
the factor covariance matrix size in the Russian-doll risk model construction.
This appears to prove a powerful approach for constructing out-of-sample stable
short-lookback risk models. Thus, for intraday mean-reversion alphas based on
overnight returns, Sharpe ratio optimization using our heterotic risk models
sizably improves the performance characteristics compared to weighted
regressions based on principal components or industry classification. We also
give source code for: a) building statistical risk models; and ii) Sharpe ratio
optimization with homogeneous linear constraints and position bounds.


  comment on J. Schmalian and P. Wolynes, Phys. Rev. Lett. {\bf 85}, 836
(2000).


  Machine-learning models are capable of capturing the structure-property
relationship from a dataset of computationally demanding ab initio
calculations. Over the past two years, the Organic Materials Database (OMDB)
has hosted a growing number of calculated electronic properties of previously
synthesized organic crystal structures. The complexity of the organic crystals
contained within the OMDB, which have on average 82 atoms per unit cell, makes
this database a challenging platform for machine learning applications. In this
paper, the focus is on predicting the band gap which represents one of the
basic properties of a crystalline materials. With this aim, a consistent
dataset of 12 500 crystal structures and their corresponding DFT band gap are
released, freely available for download at https://omdb.mathub.io/dataset. An
ensemble of two state-of-the-art models reach a mean absolute error (MAE) of
0.388 eV, which corresponds to a percentage error of 13% for an average band
gap of 3.05 eV. Finally, the trained models are employed to predict the band
gap for 260 092 materials contained within the Crystallography Open Database
(COD) and made available online so that the predictions can be obtained for any
arbitrary crystal structure uploaded by a user.


  The thermodynamic properties of proton rich systems are explored in a mean
field approach which is generated from a Skyrme interaction. The addition of
Coulomb interactions result in asymmetries which modify the chemical and
mechanical instability of the system and its equilibrium properties. These
properties are studied for systems with proton fraction $y$ on the proton
richer side of the valley of $\beta$-stability as well as the neutron rich
side. Coulomb induced instabilities lead to proton diffusion processes on the
proton richer side and also large asymmetries in chemical and mechanical
instabilities and coexistence curves. Considering the whole range of $0 \le y
\le 1$, we can study how the symmetry about $y=1/2$ is broken by asymmetric
interaction and we can also explicitly show that the role between proton and
neutron is exchanged around $y_E$. It is shown that there are two asymmetric
coexistence surfaces in $(y, P, T)$ space, one for $y < y_E$ and another for $y
> y_E$ and touching each other at $y_E$. These asymmetries in instabilities
show up as new branches, one for $y < y_E$ and one for $y > y_E$, and thus form
a closed loop in pressure versus $\rho$ for both chemical instability and
coexistence regions. The branch of $y > 1/2 > y_E$ was not previously
investigated since only the $y < 1/2$ region is usually considered. In our
simplified model, mechanical instability is still symmetric around a point $y_E
\ne 1/2$ even with Coulomb forces present.


  We introduce fractional flat space, described by a continuous geometry with
constant non-integer Hausdorff and spectral dimensions. This is the analogue of
Euclidean space, but with anomalous scaling and diffusion properties. The basic
tool is fractional calculus, which is cast in a way convenient for the
definition of the differential structure, distances, volumes, and symmetries.
By an extensive use of concepts and techniques of fractal geometry, we clarify
the relation between fractional calculus and fractals, showing that fractional
spaces can be regarded as fractals when the ratio of their Hausdorff and
spectral dimension is greater than one. All the results are analytic and
constitute the foundation for field theories living on multi-fractal
spacetimes, which are presented in a companion paper.


  We study instanton effects along the Coulomb branch of an N=2 supersymmetric
Yang-Mills theory with gauge group SU(2) on Asymptotically Locally Euclidean
(ALE) spaces. We focus our attention on an Eguchi-Hanson gravitational
background and on gauge field configurations of lowest Chern class.


  GaN/AlN nanowire heterostructures can display photoluminescence (PL) decay
times on the order of microseconds that persist up to room temperature. Doping
the GaN nanodisk insertions with Ge can reduce these PL decay times by two
orders of magnitude. These phenomena are explained by the three-dimensional
electric field distribution within the GaN nanodisks, which has an axial
component in the range of a few MV/cm associated to the spontaneous and
piezoelectric polarization, and a radial piezoelectric contribution associated
to the shear components of the lattice strain. At low dopant concentrations, a
large electron-hole separation in both the axial and radial directions is
present. The relatively weak radial electric fields, which are about one order
of magnitude smaller than the axial fields, are rapidly screened by doping.
This bidirectional screening leads to a radial and axial centralization of the
hole underneath the electron, and consequently, to large decreases in PL decay
times, in addition to luminescence blue shifts.


  Dome A, Antarctica has been thought to be one of the best astronomical sites
on the earth since decades ago. From it was first visited by astronomers in
2008, dozens of facilities for astronomical observation and site testing were
deployed. Due to its special geographical location, the data and message
exchange between Dome A and the domestic control center could only depend on
Iridium. Because the link bandwidth of Iridium is extremely limited, meanwhile
the network traffic cost is quite expensive and the network is rather unstable,
the commonly used data transfer tools, such as rsync and scp, are not suitable
in this case. In this paper, we design and implement a data transfer tool
called NBFTP (narrow bandwidth file transfer protocol) for the astronomical
observation of Dome A. NBFTP uses a uniform interface to arrange all types of
data and matches specific transmission schemes for different data types
according to rules. Break-point resuming and extensibility functions are also
implemented. Our experimental results show that NBFTP consumes 60% less network
traffic than rsync when detecting the data pending to be transferred. And when
transferring small files of 1KB, the network traffic consumption of NBFTP is
40% less than rsync. However, as the file size increases, the network traffic
consumption of NBFTP tends to approach rsync, but it is still smaller than
rsync.


  Lavelle-McMullan symmetry of QED is examined at classical and quantum levels.
It is shown that Lavelle-McMullan symmetry does not give any new non-trivial
information in QED by examining the Ward-Takahashi identities. Being inspired
by the examination of Ward-Takahashi identity, we construct the generalized
non-local and non-covariant symmetries of QED.


  Due to numerous public information sources and services, many methods to
combine heterogeneous data were proposed recently. However, general end-to-end
solutions are still rare, especially systems taking into account different
context dimensions. Therefore, the techniques often prove insufficient or are
limited to a certain domain. In this paper we briefly review and rigorously
evaluate a general framework for data matching and merging. The framework
employs collective entity resolution and redundancy elimination using three
dimensions of context types. In order to achieve domain independent results,
data is enriched with semantics and trust. However, the main contribution of
the paper is evaluation on five public domain-incompatible datasets.
Furthermore, we introduce additional attribute, relationship, semantic and
trust metrics, which allow complete framework management. Besides overall
results improvement within the framework, metrics could be of independent
interest.


  The last few decades have seen considerable research progress in
microelectronics and integrated circuits, system-on-chip design, wireless
communication, and sensor technology. This progress has enabled the seamless
integration of autonomous wireless sensor nodes around a human body to create a
Body Sensor Network (BSN). The development of a proactive and ambulatory BSN
induces a number of enormous issues and challenges. This paper presents the
technical hurdles during the design and implementation of a low-power Medium
Access Control (MAC) protocol for in-body and on-body sensor networks. We
analyze the performance of IEEE 802.15.4 protocol for the on-body sensor
network. We also provide a comprehensive insight into the heterogeneous
characteristics of the in-body sensor network. A low-power technique called
Pattern-Based Wake-up Table is proposed to handle the normal traffic in a BSN.
The proposed technique provides a reliable solution towards low-power
communication in the in-body sensor network.


  We construct a monoidal category of open transition systems that generate
material history as transitions unfold, which we call situated transition
systems. The material history generated by a composite system is composed of
the material history generated by each component. The construction is
parameterized by a symmetric strict monoidal category, understood as a resource
theory, from which material histories are drawn. We pay special attention to
the case in which this category is compact closed. In particular, if we begin
with a compact closed category of integers then the resulting situated
transition systems can be understood as systems of double-entry bookkeeping
accounts.


  This paper presents a novel mesh-update technique for unsteady free-surface
Newtonian flows using spectral element method and relying on the arbitrary
Lagrangian--Eulerian kinematic description for moving the grid. Selected
results showing compatibility of this mesh-update technique with spectral
element method are given.


  N-of-1 trials are randomized multi-crossover trials in single participants
with the purpose of investigating the possible effects of one or more
treatments.
  Research in the field of N-of-1 trials has primarily focused on scalar
outcomes. However, with the increasing use of digital technologies, we propose
to adapt this design to multimodal outcomes, such as audio, video, or image
data or also sensor measurements, that can easily be collected by the trial
participants on their personal mobile devices.
  We present here a fully automated approach for analyzing multimodal N-of-1
trials by combining unsupervised deep learning models with statistical
inference. First, we train an autoencoder on all images across all patients to
create a lower-dimensional embedding. In the second step, the embeddings are
reduced to a single dimension by projecting on the first principal component,
again using all images. Finally, we test on an individual level whether
treatment and non-treatment periods differ with respect to the component.
  We apply our proposed approach to a published series of multimodal N-of-1
trials of 5 participants who tested the effect of creams on acne captured
through images over 16 days. We compare several parametric and non-parametric
statistical tests, and we also compare the results to an expert analysis that
rates the pictures directly with respect to their acne severity and applies a
t-test on these scores. The results indicate a treatment effect for one
individual in the expert analysis. This effect was replicated with the proposed
unsupervised pipeline.
  In summary, our proposed approach enables the use of novel data types in
N-of-1 trials while avoiding the need for manual labels. We anticipate that
this can be the basis for further explorations of valid and interpretable
approaches and their application in clinical multimodal N-of-1 trials.


  We present a short overview over recent MD simulations of systems of fully
flexible polyelectrolyte chains with explicitly treated counter ions using the
full Coulomb potential. The main emphasis is given on the conformational
properties of the polymers, with a short discussion on counter ion
condensation.


  A precision measurement of the $B_{c}^{+}$ meson mass is performed using
proton-proton collision data collected with the LHCb experiment at
centre-of-mass energies of $7, 8$ and $13$ TeV, corresponding to a total
integrated luminosity of $9.0 \,{\rm fb}^{-1}$. The $B_{c}^{+}$ mesons are
reconstructed via the decays $B_{c}^{+} \rightarrow J\mskip -3mu/\mskip
-2mu\psi\mskip 2mu \pi^+$, $B_{c}^{+} \rightarrow J\mskip -3mu/\mskip
-2mu\psi\mskip 2mu \pi^+ \pi^- \pi^+$, $B_{c}^{+} \rightarrow J\mskip
-3mu/\mskip -2mu\psi\mskip 2mu p \bar{p} \pi^+$, $B_{c}^{+} \rightarrow J\mskip
-3mu/\mskip -2mu\psi\mskip 2mu D_{s}^{+}$, $B_{c}^{+} \rightarrow J\mskip
-3mu/\mskip -2mu\psi\mskip 2mu D^{0} K^{+}$ and $B_{c}^{+} \rightarrow
B_{s}^{0} \pi^{+}$. Combining the results of the individual decay channels, the
$B_{c}^{+}$ mass is measured to be $6274.47 \pm 0.27 \,({\rm stat}) \pm 0.17
\,({\rm syst}) \mathrm{\,Me\kern -0.1em V}/c^{2}$. This is the most precise
measurement of the $B_{c}^{+}$ mass to date. The difference between the
$B_{c}^{+}$ and $B_{s}^{0}$ meson masses is measured to be $907.75 \pm 0.37
\,({\rm stat}) \pm 0.27 \,({\rm syst}) \mathrm{\,Me\kern -0.1em V}/c^{2}$.


  The [O II] 3727 emission line is often used as an indicator of star formation
rate in extragalactic surveys, and it can be an equally effective tracer of
star formation in systems containing luminous active galactic nuclei (AGNs). In
order to investigate the ongoing star formation rate of the host galaxies of
AGNs, we measured the strength of [O II] and other optical emission lines from
a large sample (~ 3600) of broad-line (Type 1) AGNs selected from the Sloan
Digital Sky Survey. We performed a set of photoionization calculations to help
evaluate the relative contribution of stellar and nonstellar photoionization to
the observed strength of [O II]. Consistent with the recent study of Ho (2005),
we find that the observed [O II] emission can be explained entirely by
photoionization from the AGN itself, with little or no additional contribution
from HII regions. This indicates that the host galaxies of Type 1 AGNs
experience very modest star formation concurrent with the optically active
phase of the nucleus. By contrast, we show that the sample of ``Type 2''
quasars selected from the Sloan Digital Sky Survey does exhibit substantially
stronger HII emission consistent with an elevated level of star formation, a
result that presents a challenge to the simplest form of the AGN unification
model.


  To make sense of their surroundings, intelligent systems must transform
complex sensory inputs to structured codes that are reduced to task-relevant
information such as object category. Biological agents achieve this in a
largely autonomous manner, presumably via self-supervised learning. Whereas
previous attempts to model the underlying mechanisms were largely
discriminative in nature, there is ample evidence that the brain employs a
generative model of the world. Here, we propose that eye movements, in
combination with the focused nature of primate vision, constitute a generative,
self-supervised task of predicting and revealing visual information. We
construct a proof-of-principle model starting from the framework of masked
image modeling (MIM), a common approach in deep representation learning. To do
so, we analyze how core components of MIM such as masking technique and data
augmentation influence the formation of category-specific representations. This
allows us not only to better understand the principles behind MIM, but to then
reassemble a MIM more in line with the focused nature of biological perception.
We find that MIM disentangles neurons in latent space without explicit
regularization, a property that has been suggested to structure visual
representations in primates. Together with previous findings of invariance
learning, this highlights an interesting connection of MIM to latent
regularization approaches for self-supervised learning. The source code is
available under https://github.com/RobinWeiler/FocusMIM


  Automated scoring engines are increasingly being used to score the free-form
text responses that students give to questions. Such engines are not designed
to appropriately deal with responses that a human reader would find alarming
such as those that indicate an intention to self-harm or harm others, responses
that allude to drug abuse or sexual abuse or any response that would elicit
concern for the student writing the response. Our neural network models have
been designed to help identify these anomalous responses from a large
collection of typical responses that students give. The responses identified by
the neural network can be assessed for urgency, severity, and validity more
quickly by a team of reviewers than otherwise possible. Given the anomalous
nature of these types of responses, our goal is to maximize the chance of
flagging these responses for review given the constraint that only a fixed
percentage of responses can viably be assessed by a team of reviewers.


  Data protection regulations, such as GDPR and CCPA, require websites and
embedded third-parties, especially advertisers, to seek user consent before
they can collect and process user data. Only when the users opt in, can these
entities collect, process, and share user data. Websites typically incorporate
Consent Management Platforms (CMPs), such as OneTrust and CookieBot, to solicit
and convey user consent to the embedded advertisers, with the expectation that
the consent will be respected. However, neither the websites nor the regulators
currently have any mechanism to audit advertisers' compliance with the user
consent, i.e., to determine if advertisers indeed do not collect, process, and
share user data when the user opts out.
  In this paper, we propose an auditing framework that leverages advertisers'
bidding behavior to empirically assess the violations of data protection
regulations. Using our framework, we conduct a measurement study to evaluate
four of the most widely deployed CMPs, i.e., Didomi, Quantcast, OneTrust, and
CookieBot, as well as advertiser-offered opt-out controls, i.e., National
Advertising Initiative's opt-out, under GDPR and CCPA. Our results indicate
that in many cases user data is unfortunately still being collected, processed,
and shared even when users opt-out. We also find that some CMPs are better than
the others at conveying user consent and that several ad platforms ignore user
consent. Our results also indicate that advertiser-offered opt-out are equally
ineffective at protecting user privacy.


  We define horizontal diffusion in $C^1$ path space over a Riemannian manifold
and prove its existence. If the metric on the manifold is developing under the
forward Ricci flow, horizontal diffusion along Brownian motion turns out to be
length preserving. As application, we prove contraction properties in the
Monge-Kantorovich minimization problem for probability measures evolving along
the heat flow. For constant rank diffusions, differentiating a family of
coupled diffusions gives a derivative process with a covariant derivative of
finite variation. This construction provides an alternative method to filtering
out redundant noise.


  It is shown that an exact chiral symmetry can be described for Dirac-Kahler
fermions using the two complexes of the geometric discretization. This
principle is extended to describe exact flavour projection and it is shown that
this necessitates the introduction of a new operator and two new structures of
complex. To describe simultaneous chiral and flavour projection, eight
complexes are needed in all and it is shown that projection leaves a single
flavour of chiral field on each.


  The most succinct manifestation of the second law of thermodynamics is the
limitation the Landauer principle imposes on the amount of heat a Maxwell demon
(MD) can convert into free energy per single bit of information obtained in a
measurement. We suggest and experimentally realize a reversible electronic MD
based on a single-electron box operated as a Szilard engine, providing the
first demonstration of this limitation: extraction of kT ln 2 of heat from the
reservoir at temperature T per one bit of created information. The information
is encoded in the position of an extra electron in the box.


  We argue that the success of DFT can be understood in terms of a
semiclassical expansion around a very specific limit. This limit was identified
long ago by Lieb and Simon for the total electronic energy of a system. This is
a universal limit of all electronic structure: atoms, molecules, and solids.
For the total energy, Thomas-Fermi theory becomes relatively exact in the
limit. The limit can also be studied for much simpler model systems, including
non-interacting fermions in a one-dimensional well, where the WKB approximation
applies for individual eigenvalues and eigenfunctions. Summation techniques
lead to energies and densities that are functionals of the potential. We
consider several examples in one dimension (fermions in a box, in a harmonic
well, in a linear half-well, and in the P\"oschl-Teller well. The effects of
higher dimension are also illustrated with the three-dimensional harmonic well
and the Bohr atom, non-interacting fermions in a Coulomb well. Modern density
functional calculations use the Kohn-Sham scheme almost exclusively. The same
semiclassical limit can be studied for the Kohn-Sham kinetic energy, for the
exchange energy, and for the correlation energy. For all three, the local
density approximation appears to become relatively exact in this limit. Recent
work, both analytic and numerical, explores how this limit is approached, in an
effort to deduce the leading corrections to the local approximation. A simple
scheme, using the Euler-Maclaurin summation formula, is the result of many
different attempts at this problem. In very simple cases, the correction
formulas are much more accurate than standard density functionals. Several
functionals are already in widespread use in both chemistry and materials that
incorporate these limits, and prospects for the future are discussed.


  These lectures were presented at the TASI 2012 summer school to a mixture of
graduate students in particle theory and cosmology. They serve as an elementary
introduction to the Minimal Supersymmetric Standard Model (MSSM) and discuss
the implications of a 125 GeV Higgs boson for this theory. Some familiarity
with the Standard Model is assumed.


  We develop a non-perturbative theory to study large-scale quantum dynamics of
Dirac particles in disordered scalar potentials (the so-called "topological
metal"). For general disorder strength and carrier doping, we find that at
large times, superdiffusion occurs. I.e., the mean squared displacement grows
as $\sim t\ln t$. In the static limit, our analytical theory shows that the
conductance of a finite-size system obeys the scaling equation identical to
that found in previous numerical studies. These results suggest that in the
topological metal, there exist some transparent channels -- where waves
propagate "freely" -- dominating long-time transport of the system. We discuss
the ensuing consequence -- the transverse superdiffusion in photonic materials
-- that might be within the current experimental reach.


  Constant-roll warm inflation is introduced in this work. A novel approach to
finding an exact solution for Friedman equations coupled to scalar field
equation of motion is presented for cold inflation and is extended to warm
inflation with the constant dissipative parameter $Q=\frac{\Gamma}{3H}$. The
evolution of the primordial inhomogeneities of a scalar field in a thermal bath
is also studied. The $1\sigma$ consistency between the theoretical predictions
of the model and observational constraints has been proven for a range of $Q$
and $\beta=\frac{\ddot{\phi}}{3H\phi}$ (constant rate of inflaton roll). In
addition, we briefly investigate the possible enhancement of super-horizon
perturbations beyond the slow-roll approximation.


  We explore the chemodynamical properties of a sample of barred galaxies in
the Auriga magneto-hydrodynamical cosmological zoom-in simulations, which form
boxy/peanut (b/p) bulges, and compare these to the Milky Way (MW). We show that
the Auriga galaxies which best reproduce the chemodynamical properties of
stellar populations in the MW bulge have quiescent merger histories since
redshift $z\sim3.5$: their last major merger occurs at $t_{\rm
lookback}>12\,\rm Gyrs$, while subsequent mergers have a stellar mass ratio of
$\leq$1:20, suggesting an upper limit of a few percent for the mass ratio of
the recently proposed Gaia Sausage/Enceladus merger. These Auriga MW-analogues
have a negligible fraction of ex-situ stars in the b/p region ($<1\%$), with
flattened, thick disc-like metal-poor stellar populations. The average fraction
of ex-situ stars in the central regions of all Auriga galaxies with b/p's is 3%
-- significantly lower than in those which do not host a b/p or a bar. While
the central regions of these barred galaxies contain the oldest populations,
they also have stars younger than 5Gyrs (>30%) and exhibit X-shaped age and
abundance distributions. Examining the discs in our sample, we find that in
some cases a star-forming ring forms around the bar, which alters the
metallicity of the inner regions of the galaxy. Further out in the disc,
bar-induced resonances lead to metal-rich ridges in the $V_{\phi}-r$ plane --
the longest of which is due to the Outer Lindblad Resonance. Our results
suggest the Milky Way has an uncommonly quiet merger history, which leads to an
essentially in-situ bulge, and highlight the significant effects the bar can
have on the surrounding disc.


  In this paper we explore the impact of an era -right after reheating-
dominated by mini black holes and radiation on the spectrum of the relic
gravitational waves. This era may lower the spectrum several orders of
magnitude.


  MAGIC is a system of two Imaging Atmospheric Cherenkov Telescopes located on
the Canary Island of La Palma and dedicated to the study of very high energy
gamma rays above 30 GeV. MAGIC has recently demonstrated its capability as a
neutrino detector, by exploiting the Earth-skimming technique. The
neutrino-event selection has been studied by pointing the telescopes towards
the sea a few degrees below the horizon, with no pre-defined source direction.
An upper limit to the $\nu_\tau$ flux was set. In this work, a follow-up
strategy of given source directions is presented. This new approach is
characterised by pointing to targets passing through the sea window observable
with MAGIC and for which a trigger from dedicated neutrino observatories is
issued with large significance. Above a few tens of PeV, the acceptance of
MAGIC to $\nu_\tau$ is considerably large and compelling results can be
obtained for transient events of short duration. The performance of this new
method is tested on a sample of data collected by pointing MAGIC for a few days
from March to May 2016 towards the direction of a multi-PeV neutrino that
IceCube detected on June 11th 2014 (reconstructed direction (J2000.0) RA:
110.34$^\circ$ and Dec.: 11.48$^\circ$). A selection cut is studied in order to
discriminate $\tau$-lepton-induced air showers from the background of very
inclined cosmic-ray-induced air showers. An upper limit on the neutrino flux
from the above given neutrino direction is presented.


  Design/methodology/approach We compared the awareness of 813 people in Wuhan
city from January to March 2023 (Wuhan 2023) and 2,973 people in East and South
China from February to May 2020 (China 2020) using responses to questionnaires
conducted at Japanese local subsidiaries during each period. Purpose As the
coronavirus pandemic becomes less terrifying than before, there is a trend in
countries around the world to abolish strict behavioral restrictions imposed by
governments. How should overseas subsidiaries change the way they manage human
resources in response to these system changes? To find an answer to this
question, this paper examines what changes occurred in the mindset of employees
working at local subsidiaries after the government's strict behavioral
restrictions were introduced and lifted during the COVID-19 pandemic. Findings
The results showed that the analytical model based on conservation of resources
(COR) theory can be applied to both China 2020 and Wuhan 2023. However, the
relationship between anxiety, fatigue, compliance, turnover intention, and
psychological and social resources of employees working at local subsidiaries
changed after the initiation and removal of government behavioral restrictions
during the pandemic, indicating that managers need to adjust their human
resource management practices in response to these changes. Originality/value
This is the first study that compares data after the start of government
regulations and data after the regulations were lifted. Therefore, this
research proposes a new analytical framework that companies, especially
foreign-affiliated companies that lack local information, can refer to respond
appropriately to disasters, which expand damage while changing its nature and
influence while anticipating changes in employee awareness.


  Let $\{Z_n\}_{n\geq 0 }$ be a critical or subcritical $d$-dimensional
branching random walk started from a Poisson random measure whose intensity
measure is the Lebesugue measure on $\mathbb{R}^d$. Denote by
$R_n:=\sup\{u>0:Z_n(\{x\in\mathbb{R}^d:|x|<u\})=0\}$ the radius of the largest
empty ball centered at the origin of $Z_n$. In this work, we prove that after
suitable renormalization, $R_n$ converges in law to some non-degenerate
distribution as $n\to\infty$. Furthermore, our work shows that the
renormalization scales depend on the offspring law and the dimension of the
branching random walk, which completes the results of \cite{reves02} for the
critical binary branching Wiener process.


  We review various attempts to localize the discrete spectra of
semirelativistic Hamiltonians of the form H = \beta \sqrt{m^2 + p^2} + V(r)
(w.l.o.g. in three spatial dimensions) as entering, for instance, in the
spinless Salpeter equation. Every Hamiltonian in this class of operators
consists of the relativistic kinetic energy \beta \sqrt{m^2 + p^2} (where \beta
> 0 allows for the possibility of more than one particles of mass m) and a
spherically symmetric attractive potential V(r), r = |x|. In general, accurate
eigenvalues of a nonlocal Hamiltonian operator can only be found by the use of
a numerical approximation procedure. Our main emphasis, however, is on the
derivation of rigorous semi-analytical expressions for both upper and lower
bounds to the energy levels of such operators. We compare the bounds obtained
within different approaches and present relationships existing between the
bounds.


  Anomalous radio flux ratios in four-image gravitational lens systems can be
explained by adding a clumpy cold dark matter (CDM) component to the potential
of the lens galaxy. Evans & Witt (2003) recently suggested that smooth
multipole perturbations can provide a reasonable alternative to CDM
substructure in some but not all cases. We generalize their method in two ways
so as to determine whether multipole models can explain highly anomalous
systems. We carry the multipole expansion to higher order, and also include
external tidal shear as a free parameter. Fitting for the shear proves crucial
to finding a physical (positive-definite density) model. For B1422+231, working
to order k = 5 (and including shear) yields a model that is physical but
implausible. Going to higher order (k >~ 9) reduces global departures from
ellipticity at the cost of introducing small scale wiggles near the bright
images. These localized undulations are more pronounced in B2045+265, where k ~
17 multipoles are required to smooth out large scale deviations from elliptical
symmetry. Such modes surely cannot be taken at face value; they must indicate
that the models are trying to reproduce some other sort of structure. Our
formalism naturally finds models that fit the data exactly, but we use
B0712+472 to show that measurement uncertainties have little effect on our
results. Finally, we consider the system B1933+503, where two sources are
lensed by the same foreground galaxy. The additional constraints provided by
the images of the second source render the multipole model unphysical. We
conclude that external shear must be taken into account to obtain plausible
models, and that a purely smooth angular structure for the lens galaxy does not
provide a viable alternative to the prevailing CDM clump hypothesis.


  We study the Fermi-edge singularity appearing in the current-voltage
characteristics for resonant tunneling through a localized level at finite
temperature. An explicit expression for the current at low temperature and near
the threshold for the tunneling process is presented which allows to coalesce
data taken at different temperatures to a single curve. Based on this scaling
function for the current we analyze experimental data from a GaAs-AlAs-GaAs
tunneling device with embedded InAs quantum dots obtained at low temperatures
in high magnetic fields.


  We obtain the two-loop effective potential for general renormalizable
theories, using a generalized gauge-fixing scheme that includes as special
cases the background-field $R_\xi$ gauges, the Fermi gauges, and the familiar
Landau gauge, and using dimensional regularization in the bare and \MSbar
renormalization schemes. As examples, the results are then specialized to the
Abelian Higgs model and to the Standard Model. In the case of the Standard
Model, we study how the vacuum expectation value and the minimum vacuum energy
depend numerically on the gauge-fixing parameters. The results at fixed
two-loop order exhibit non-convergent behavior for sufficiently large
gauge-fixing parameters; this can presumably be addressed by a resummation of
higher-order contributions.


  The estimation of the degree of risk of steel storage tanks from an
industrial or nuclear power plant during an earthquake event is a very
difficult task since the dynamic behaviour of the tank-liquid system is highly
complex. The seismic response of steel storage tanks is quite different from
building structures not only due to hydrodynamic effects acting on the shell
and bottom plate but also because of many sources of nonlinear behaviour
mechanisms. For the earthquake-resistant design of tanks, it is important to
use a rational and reliable nonlinear dynamic analysis procedure, which is
capable of capturing the seismic behaviour of the tanks under artificial or
real earthquakes. The present paper deals with the nonlinear finite element
modelling of steel storage tanks subjected to seismic loadings. The interaction
effects of fluid and structure are modelled using a surface-based
acoustic-structural interaction in the ABAQUS software. The successive contact
and separation between the bottom plate and its rigid foundation caused by
sliding and uplift are taken into account by a contact modelling approach.
Reduced scales of both slender and broad cylindrical steel storage tanks from a
shaking table campaign within the framework of the INDUSE-2-SAFETY project are
selected for the study. The seismic responses of the tanks including the
hydrodynamic pressure distribution acting on the shell plate, the elevation of
the liquid free surface, and the uplift response of the bottom plate when the
tank is unanchored are presented and compared with the experimental results.
The responses obtained from the refined models are also compared with those
obtained using a simplified approach, which is based on the lumped mass model
of the liquid motion.


  Ultraluminous X-ray sources (ULXs) with 10^39 < L_x < 10^41 erg/s have been
discovered in great numbers in external galaxies with ROSAT, Chandra, and
XMM-Newton. The central question regarding this important class of sources is
whether they represent an extension in the luminosity function of binary X-ray
sources containing neutron stars and stellar-mass black holes (BHs), or a new
class of objects, e.g., systems containing intermediate-mass black holes (100 -
1000 M_sun). We suggest searching for X-ray and optical eclipses in these
systems to provide another diagnostic to help distinguish between these two
possibilities. The sense of the effect is that ULXs with stellar-mass black
hole accretors should be at least twice as likely to exhibit eclipses as
intermediate-mass black hole systems - and perhaps much more than a factor of
two. Among other system parameters, the orbital period would follow. This would
provide considerable insight as to the nature of the binary.


  We consider physics-informed neural networks (PINNs) [Raissi et al.,
J.~Comput. Phys. 278 (2019) 686-707] for forward physical problems. In order to
find optimal PINNs configuration, we introduce a hyper-parameter optimization
(HPO) procedure via Gaussian processes-based Bayesian optimization. We apply
the HPO to Helmholtz equation for bounded domains and conduct a thorough study,
focusing on: (i) performance, (ii) the collocation points density $r$ and (iii)
the frequency $\kappa$, confirming the applicability and necessity of the
method. Numerical experiments are performed in two and three dimensions,
including comparison to finite element methods.


  A result of Bleher, Chinburg, Greenberg, Kakde, Pappas, Sharifi and Taylor
has initiated the topic of higher codimension Iwasawa theory. As a
generalization of the classical Iwasawa main conjecture, they prove a
relationship between analytic objects (a pair of Katz's $2$-variable $p$-adic
$L$-functions) and algebraic objects (two "everywhere unramified'' Iwasawa
modules) involving codimension two cycles in a $2$-variable Iwasawa algebra. We
prove a result by considering the restriction to an imaginary quadratic field
$K$ (where an odd prime $p$ splits) of an elliptic curve $E$, defined over
$\mathbb{Q}$, with good supersingular reduction at $p$. On the analytic side,
we consider eight pairs of $2$-variable $p$-adic $L$-functions in this setup
(four of the $2$-variable $p$-adic $L$-functions have been constructed by
Loeffler and a fifth $2$-variable $p$-adic $L$-function is due to Hida). On the
algebraic side, we consider modifications of fine Selmer groups over the
$\mathbb{Z}_p^2$-extension of $K$. We also provide numerical evidence, using
algorithms of Pollack, towards a pseudo-nullity conjecture of Coates-Sujatha.


  Fix a monoidal category C. The 2-category of monads in the 2-category of
C-actegories, colax C-equivarant functors, and C-equivariant natural
transformations of colax functors, may be recast in terms of pairs consisting
of a usual monad and a distributive law between the monad and the action of C,
morphisms of monads respecting the distributive law, and transformations of
monads satisfying some compatibility with the actions and distributive laws
involved. The monads in this picture may be generalized to actions of monoidal
categories, and actions of PRO-s in particular. If C is a PRO as well, then in
special cases one gets various distributive laws of a given classical type, for
example between a comonad and an endofunctor or between a monad and a comonad.
The usual pentagons are in general replaced by multigons, and there are also
``mixed'' multigons involving two distinct distributive laws. Beck's bijection
between the distributive laws and lifts of one monad to the Eilenberg-Moore
category of another monad is here extended to an isomorphism of 2-categories.
The lifts of maps of above mentioned pairs are colax C-equivariant. We finish
with a short treatment of relative distributive laws between two pseudoalgebra
structures which are relative with respect to the distributivity of two
pseudomonads involved, what gives a hint toward the generalizations.


  Weather Forecasting is an attractive challengeable task due to its influence
on human life and complexity in atmospheric motion. Supported by massive
historical observed time series data, the task is suitable for data-driven
approaches, especially deep neural networks. Recently, the Graph Neural
Networks (GNNs) based methods have achieved excellent performance for
spatio-temporal forecasting. However, the canonical GNNs-based methods only
individually model the local graph of meteorological variables per station or
the global graph of whole stations, lacking information interaction between
meteorological variables in different stations. In this paper, we propose a
novel Hierarchical Spatio-Temporal Graph Neural Network (HiSTGNN) to model
cross-regional spatio-temporal correlations among meteorological variables in
multiple stations. An adaptive graph learning layer and spatial graph
convolution are employed to construct self-learning graph and study hidden
dependency among nodes of variable-level and station-level graph. For capturing
temporal pattern, the dilated inception as the backbone of gate temporal
convolution is designed to model long and various meteorological trends.
Moreover, a dynamic interaction learning is proposed to build bidirectional
information passing in hierarchical graph. Experimental results on three
real-world meteorological datasets demonstrate the superior performance of
HiSTGNN beyond 7 baselines and it reduces the errors by 4.2% to 11.6%
especially compared to state-of-the-art weather forecasting method.


  We study solutions to the inverse mean curvature flow which evolve by
homotheties of a given submanifold with arbitrary dimension and codimension. We
first show that the closed ones are necessarily spherical minimal immersions
and so we reveal the strong rigidity of the Clifford torus in this setting.
Mainly we focus on the Lagrangian case, obtaining numerous examples and
uniqueness results for some products of circles and spheres that generalize the
Clifford torus to arbitrary dimension. We also characterize the pseudoumbilical
ones in terms of soliton curves for the inverse curve shortening flow and
minimal Legendrian immersions in odd-dimensional spheres. As a consequence, we
classify the rotationally invariant Lagrangian homothetic solitons for the
inverse mean curvature flow.


  Using the boundary state formalism and thermo field dynamics approach, we
study a D$p$-brane at finite temperature in which the background Kalb-Ramond
field, a $U(1)$ gauge potential, and tachyon field are turned on together with
a general tangential dynamics. The thermal entropy of the brane will be
studied. In addition, the behavior of the entropy after the tachyon
condensation process will be investigated and some thermodynamic
interpretations will be extracted.


  We consider the lossless compression bound of any individual data sequence.
If we fit the data by a parametric model, the entropy quantity $nH({\hat
\theta}_n)$ obtained by plugging in the maximum likelihood estimate is an
underestimate of the bound, where $n$ is the number of words. Shtarkov showed
that the normalized maximum likelihood (NML) distribution or code length is
optimal in a minimax sense for any parametric family. We show by the local
asymptotic normality that the NML code length for the exponential families is
$nH(\hat \theta_n) +\frac{d}{2}\log \, \frac{n}{2\pi} +\log \int_{\Theta}
|I(\theta)|^{1/2}\, d\theta+o(1)$, where $d$ is the model dimension or
dictionary size, and $|I(\theta)|$ is the determinant of the Fisher information
matrix. We also demonstrate that sequentially predicting the optimal code
length for the next word via a Bayesian mechanism leads to the mixture code,
whose pathwise length is given by $nH({\hat \theta}_n) +\frac{d}{2}\log \,
\frac{n}{2\pi} +\log \frac{|\, I({\hat \theta}_n)|^{1/2}}{w({\hat
\theta}_n)}+o(1) $, where $w(\theta)$ is a prior. The asymptotics apply to not
only discrete symbols but also continuous data if the code length for the
former is replaced by the description length for the latter. The analytical
result is exemplified by calculating compression bounds of protein-encoding DNA
sequences under different parsing models. Typically, the highest compression is
achieved when the parsing is in phase of the amino acid codons. On the other
hand, the compression rates of pseudo-random sequences are larger than 1
regardless parsing models. These model-based results are in consistency with
that random sequences are incompressible as asserted by the Kolmogorov
complexity theory. The empirical lossless compression bound is particularly
more accurate when dictionary size is relatively large.


  Tangentially viewing fast camera footage of the low-field side snowflake
minus divertor in TCV is analysed across a four point scan in which the
proximity of the two X-points is varied systematically. The motion of
structures observed in the post- processed movie shows two distinct regions of
the camera frame exhibiting differing patterns. One type of motion in the outer
scrape-off layer remains present throughout the scan whilst the other, apparent
in the inner scrape-off layer between the two nulls, becomes increasingly
significant as the X-points contract towards one another. The spatial structure
of the fluctuations in both regions is shown to conform to the equilibrium
magnetic field. When the X-point gap is wide the fluctuations measured in the
region between the X-points show a similar structure to the fluctuations
observed above the null region, remaining coherent for multiple toroidal turns
of the magnetic field and indicating a physical connectivity of the
fluctuations between the upstream and downstream regions. When the X-point gap
is small the fluctuations in the inner scrape-off layer between the nulls are
decorrelated from fluctuations upstream, indicating local production of
filamentary structures. The motion of filaments in the inter-null region
differs, with filaments showing a dominantly poloidal motion along magnetic
flux surfaces when the X-point gap is large, compared to a dominantly radial
motion across flux-surfaces when the gap is small. This demonstrates an
enhancement to cross-field tranport between the nulls of the TCV low-field-side
snowflake minus when the gap between the nulls is small.


  In 1968, Erd\"os and Lov\'asz conjectured that for every graph $G$ and all
integers $s,t\geq 2$ such that $s+t-1=\chi(G) > \omega(G)$, there exists a
partition $(S,T)$ of the vertex set of $G$ such that $\chi(G|S)\geq s$ and
$\chi(G|T)\geq t$. For general graphs, the only settled cases of the conjecture
are when $s$ and $t$ are small. Recently, the conjecture was proved for a few
special classes of graphs: graphs with stability number 2 \cite{quasi-line},
line graphs \cite{line} and quasi-line graphs \cite{quasi-line}. In this paper,
we consider the conjecture for claw-free graphs and present some progress on
it.


  We present nonlinear resistive MHD simulations of the response of a rotating
plasma to an error field when the plasma has weakly damped linear tearing modes
(TM's), stabilized by pressure gradient and favorable curvature. Favorable
curvature leads to the Glasser effect: the occurrence of real frequencies and
stabilization with positive stability index $\Delta'$. A cylinder with hollow
pressure is used to model the toroidal favorable curvature. Linear simulations
with rotation and an error field $\tilde{\psi}_w$ show, in agreement with
analytic results, that the peak reconnected flux occurs for a rotation rate
near the TM phase velocity. Nonlinear simulations with small $\tilde{\psi}_w$
show that the real frequency and stabilization by favorable average curvature
are masked by a nonlinear effect that occurs for very thin islands: flattening
of the pressure across the island, mainly due to sound wave propagation. This
flattening causes the disappearance of real frequencies destabilization of the
mode, allowing it to grow to large amplitude similar to a $\beta=0$ unstable
TM. The flattening of the current for larger islands saturates the mode
nonlinearly. In the post-saturation phase, the interaction of the error field
with the destabilized spontaneous tearing mode, which rotates with the plasma,
leads to oscillations in the Maxwell torque and therefore modulations in the
plasma rotation. The islands also rotate with modulated phase velocity,
undergoing small-amplitude oscillations due to these modulations. We also
present a quasilinear model with an unstable spontaneous TM and error fields,
showing that the superposition of these fields results in similar oscillations.


  This paper presents and discusses an implementation of a multiple target
tracking method, which is able to deal with target interactions and prevent
tracker failures due to hijacking. The referenced approach uses a Markov Chain
Monte Carlo (MCMC) sampling step to evaluate the filter and constructs an
efficient proposal density to generate new samples. This density integrates
target interaction terms based on Markov Random Fields (MRFs) generated per
time step. The MRFs model the interactions between targets in an attempt to
reduce tracking ambiguity that typical particle filters suffer from when
tracking multiple targets. A test sequence of 662 grayscale frames containing
20 interacting ants in a confined space was used to test both the proposed
approach and a set of importance sampling based independent particle filters,
to establish a performance comparison. It is shown that the implemented
approach of modeling target interactions using MRF successfully corrects many
of the tracking errors made by the independent, interaction unaware, particle
filters.


  We consider the physics motivations and perspectives for the study of spin
phenomena at the future high energies accelerators. The possibilities to use
the already operating machines are also discussed. It is emphasized that the
present status of QCD spin studies necessarily requires a wide range of spin
measurements


  We present analysis of deep CCD photometry for the very rich, old open star
cluster NGC 6819. These CFH12K data results represent the first of nineteen
open star clusters which were imaged as a part of the CFHT Open Star Cluster
Survey. We find a tight, very rich, main-sequence and turn-off consisting of
over 2900 cluster stars in the V, B-V color-magnitude diagram (CMD).
Main-sequence fitting of the un-evolved cluster stars with the Hyades star
cluster yields a distance modulus of (m-M)v = 12.30 +/- 0.12, for a reddening
of E(B-V) = 0.10. These values are consistent with a newly calculated
theoretical stellar isochrone of age 2.5 Gyrs, which we take to be the age of
the cluster. Detailed star counts indicate a much larger cluster extent (R =
9.5' +/- 1.0'), by a factor of ~2 over some previous estimates. Incompleteness
tests confirm a slightly negatively sloped luminosity function extending to
faint (V ~ 23) magnitudes which is indicative of a dynamically evolved cluster.
Further luminosity function and mass segregation tests indicate that low mass
objects (M < 0.65Mo) predominate in the outer regions of the cluster, 3.5 < R <
9.5. The estimation of the number of white dwarfs in NGC 6819 are in good
agreement with the observed number. For those white dwarf candidates which pass
both a statistical and image classification tests, we show comparisons to white
dwarf isochrones and cooling models which suggest the need for spectroscopy to
confirm the white dwarf nature of the brighter objects.


  We present an axiomatic frame (in Prt I of this book) in which many results
of the K-theory for C*-algebras are proved. Then we construct an example for
this axiomatic theory (in Part II), which generalizes the classical theory for
C*-algebras. This last theory starts by associating to each C*-algebra F the
C*-algebras of square matrices with entries in F. Every such C*-algebra of
square matrices can be obtained as the projective representation of a certain
group with respect to a complex valued Schur function (also called normalized
factor set or multiplier or two-co-cocycle in the mathematical literature) for
this group. The above mentioned generalization consist in replacing this Schur
function by an arbitrary Schur function which satisfies some axiomatic
conditions. Moreover this Schur function can take its values in a commutative
unital C*-algebra E. In this case this K-theory deos not apply to the category
of C*-algebras but to the category of E-C*-algebras, which are C*-algebras
endowed with a supplementary structure obtained by an exterior multiplication
with elements of E (every C*-algebra can be endowed with such a supplementary
structure). Up to some definitions and notation Part II is independent of Part
I.


  We consider the following random graph process: starting with n isolated
vertices, add edges uniformly at random provided no such edge creates a copy of
C_4. We show that, with probability tending to 1 as $n \to \infty$, the final
graph produced by this process has maximum degree O((n \log n)^{1/3}) and
consequently size O(n^{4/3}\log(n)^{1/3}), which are sharp up to constants.
This confirms conjectures of Bohman and Keevash and of Osthus and Taraz, and
improves upon previous bounds due to Bollob\'as and Riordan and Osthus and
Taraz.


  For the symbiotic branching model introduced by Etheridge/Fleischmann (2004),
it is shown that aging and intermittency exhibit different behaviour for
negative, zero, and positive correlations. Our approach also provides an
alternative, elementary proof and refinements of classical results concerning
second moments of the parabolic Anderson model with Brownian potential. Some
refinements to more general (also infinite range) kernels of recent aging
results of Dembo/Deuschel (2007) for interacting diffusions are given.


  On the basis of the handbag approach we study cross sections and spin
asymmetries for leptoproduction of various vector and pseudoscalar mesons. Our
results are in good agrement with high energy experiments. We analyse what
information about Generalized Parton Distributions (GPDs) can be obtained from
these reactions.


  A new derivation of the propagation direction of light is given for a
3-parameter family of static, spherically symmetric space-times within the
post-post-Newtonian framework. The emitter and the observer are both located at
a finite distance. The case of a ray emitted at infinity is also treated.


  It is well known that supersymmetric models allow new sources for CP
violation that arise from soft supersymmetry breaking terms. If unsuppressed,
these new CP-violating phases would give too large a neutron electric dipole
moment. We discuss a mechanism for suppressing SUSY phases in string-inspired
supergravity models in which supersymmetry is assumed to be broken by the
auxiliary components of the dilaton and moduli superfields. (To appear in the
Proceeding of the Third KEK Topical Conference on CP Violation, its Implication
to Particle Physics and Cosmology)


  We study the five-dimensional SU(3)_c x U(1)_C gauge theory on the orbifold
S^1/Z_2 with a mixed Chern-Simons term. We particularly pay attention to the
realization of the dynamical rearrangement of the theta parameter for SU(3)_c.
It is shown that the physics remains invariant under a large gauge
transformation which even changes the action, completely removing the theta
parameter, because of the Hosotani mechanism for the U(1)_C gauge interactions.
In other words, we show that the theta parameter can be regarded as a boundary
condition for the orbifolding in light of the dynamical rearrangement.


  During the Arizona Winter School 2008 (held in Tucson, AZ) we worked on the
following problems:
  a) (Expanding a remark by S. Lang). Define $E_0 = \overline{\mathbb{Q}}$
Inductively, for $n \geq 1$, define $E_n$ as the algebraic closure of the field
generated over $E_{n-1}$ by the numbers $\exp(x)=e^x$, where $x$ ranges over
$E_{n-1}$. Let $E$ be the union of $E_n$, $n \geq 0$. Show that Schanuel's
Conjecture implies that the numbers $\pi, \log \pi, \log \log \pi, \log \log
\log \pi, \ldots $ are algebraically independent over $E$.
  b) Try to get a (conjectural) generalization involving the field $L$ defined
as follows. Define $L_0 = \overline{\mathbb{Q}}$. Inductively, for $n \geq 1$,
define $L_n$ as the algebraic closure of the field generated over $L_{n-1}$ by
the numbers $y$, where $y$ ranges over the set of complex numbers such that
$e^y\in L_{n-1}$. Let $L$ be the union of $L_n$, $n \geq 0$.
  We were able to prove that Schanuel's Conjecture implies $E$ and $L$ are
linearly disjoint over $\overline{\mathbb{Q}}$.


  The solution of the Drinfeld equation corresponding to the full set of
different carrier subalgebras in sl(3) are explicitly constructed. The obtained
Hopf structures are studied. It is demonstrated that the presented twist
deformations can be considered as limits of the corresponding quantum analogues
(q-twists) defined for the q-quantized algebras.


  We study Slavnov's inner products for open Temperley-Lieb chains and their
relations with the KP hierarchy. We show that when (s=1/2) the quantum group
invariant XXZ spin chain has Slavnov products given by the quotient of tau
functions. The Schur polynomials expansion and a matrix construction for the
Baker-Akhiezer functions are also briefly considered.


  Multimodal normal incestual systems are investigated in terms of multiple
categories. The different sorted composition of operators are exhibited as
2-cells in multiple categories built up from 2-categories giving rise to
different axioms. Subsequently, coherence results are proved pointing the
connections with (usual and mixed) Distributive Laws. This is given as a
geometrical description of certain axioms inside various systems with a number
of necessity and possibility operators.


  In this paper we introduce a micro-clustering strategy for Functional
Boxplots. The aim is to summarize a set of streaming time series splitted in
non overlapping windows. It is a two step strategy which performs at first, an
on-line summarization by means of functional data structures, named Functional
Boxplot micro-clusters; then it reveals the final summarization by processing,
off-line, the functional data structures. Our main contribute consists in
providing a new definition of micro-cluster based on Functional Boxplots and,
in defining a proximity measure which allows to compare and update them. This
allows to get a finer graphical summarization of the streaming time series by
five functional basic statistics of data. The obtained synthesis will be able
to keep track of the dynamic evolution of the multiple streams.


  An automated approach to text readability assessment is essential to a
language and can be a powerful tool for improving the understandability of
texts written and published in that language. However, the Persian language,
which is spoken by over 110 million speakers, lacks such a system. Unlike other
languages such as English, French, and Chinese, very limited research studies
have been carried out to build an accurate and reliable text readability
assessment system for the Persian language. In the present research, the first
Persian dataset for text readability assessment was gathered and the first
model for Persian text readability assessment using machine learning was
introduced. The experiments showed that this model was accurate and could
assess the readability of Persian texts with a high degree of confidence. The
results of this study can be used in a number of applications such as medical
and educational text readability evaluation and have the potential to be the
cornerstone of future studies in Persian text readability assessment.


  Zhikov showed 1986 with his famous checkerboard example that functionals with
variable exponents can have a Lavrentiev gap. For this example it was crucial
that the exponent had a saddle point whose value was exactly the dimension. In
1997 he extended this example to the setting of the double phase potential.
Again it was important that the exponents crosses the dimensional threshold.
Therefore, it was conjectured that the dimensional threshold plays an important
role for the Lavrentiev gap. We show that this is not the case. Using fractals
we present new examples for the Lavrentiev gap and non-density of smooth
functions. We apply our method to the setting of variable exponents, the double
phase potential and weighted p-energy.


  We present comprehensive photometric R-band observations of the fading
optical afterglow of the X-Ray Flash XRF050824, from 11 minutes to 104 days
after the burst. The R-band lightcurve of the afterglow resembles the
lightcurves of long duration Gamma-Ray Bursts (GRBs), i.e., a power-law albeit
with a rather shallow slope of alpha=0.6. Our late R-band images reveal the
host galaxy with a rest-frame B-band luminosity corresponding to roughly 0.5
Lstar. The star-formation rate as determined from the [O II] emission line
luminosity is about 1.8 Msun per year. When accounting for the host
contribution, the slope is alpha=0.65+-0.01 and a break in the lightcurve is
also suggested. A potential lightcurve bump at 2 weeks can be interpreted as a
supernova only if this is a supernova with a fast rise and a fast decay.
However, the overall fit still show excess scatter in the lightcurve due to
wiggles and bumps. The flat lightcurves in the optical and X-rays could be
explained by a continuous energy injection scenario with an on-axis viewing
angle and a wide jet opening angle (theta_j>10 deg). If the energy injections
are episodic, this could potentially help explain the bumps and wiggles.
Spectroscopy of the afterglow give a redshift of z=0.828+-0.005 from both
absorption and emission lines. The spectral energy distribution (SED) of the
afterglow has a power-law shape with slope beta=0.56+-0.04. This can be
compared to the X-ray spectral index which is betaX=1.0+-0.1. The curvature of
the SED constrain the dust reddening towards the burst to Av<0.5 mag.
(abridged)


  Recent Herschel/SPIRE maps of the Small and Large Magellanic Clouds (SMC,
LMC) exhibit in each thousands of clouds. Observed at 250 microns, they must be
cold, T ~ 15 K, hence the name "Herschel cold clouds" (HCCs). From the observed
rotational velocity profile and the assumption of spherical symmetry, the
Galactic mass density is modeled in a form close to that of an isothermal
sphere. If the HCCs constitute a certain fraction of it, their angular size
distribution has a specified shape. A fit to the data deduced from the SMC/LMC
maps supports this and yields for their radius 2.5 pc, with a small change when
allowing for a spread in HCC radii. There are so many HCCs that they will make
up all the missing Halo mass density if there is spherical symmetry and their
average mass is of order 15,000 Mo. This compares well with the Jeans mass of
circa 40,000 Mo and puts forward that the HCCs are in fact Jeans clusters,
constituting all the Galactic dark matter and much of its missing baryons, a
conclusion deduced before from a different field of the sky (Nieuwenhuizen,
Schild and Gibson 2011). A preliminary analysis of the intensities yields that
the Jeans clusters themselves may consist of some billion MACHOs of a few dozen
Earth masses. With a size of dozens of solar radii, they would mostly obscure
stars in the LMC, SMC and towards the Galactic center, and may thus have been
overlooked in microlensing.


  We study gain without inversion due to coherence effects in a
Doppler-broadened degenerate three-level system of a rubidium-hydrogen mixture
in a miniaturized micron scale custom vapor cell. The cell miniaturization
gives rise to collisions of atoms with the walls of the cell. This, combined
with the high collision rate with the hydrogen buffer gas allows us to observe
gain in the absorption spectra. Furthermore, we analyze the role of cell
miniaturization in the evolution of the gain profile. In addition to
fundamental interest, the observation of gain without inversion in our
miniaturized cells paves the way for applications such as miniaturized lasers
without inversion.


  We have performed a census of the young stellar populations near the Corona
Australis molecular cloud using photometric and kinematic data from several
sources, particularly Gaia EDR3, and spectroscopy of hundreds of candidate
members. We have compiled a catalog of 393 members of Corona Australis, (39 at
>M6), 293 (36) of which are spectroscopically classified for the first time in
this work. We find that Corona Australis can be described in terms of two
stellar populations, a younger one (few Myr) that is partially embedded in the
cloud (the Coronet Cluster) and an older one (~15 Myr) that surrounds and
extends beyond the cloud (Upper Corona Australis). These populations exhibit
similar space velocities, and we find no evidence for distinct kinematic
populations in Corona Australis, in contrast to a recent study based on Gaia
DR2. The distribution of spectral types in Corona Australis reaches a maximum
at M5 (~0.15 M_sol), indicating that the IMF has a similar characteristic mass
as other nearby star-forming regions. Finally, we have compiled mid-infrared
photometry from the Wide-field Infrared Survey Explorer and the Spitzer Space
Telescope for the members of Corona Australis and we have used those data to
identify and classify their circumstellar disks. Excesses are detected for 122
stars, a third of which are reported for the first time in this work.


  The article examines Nikolskii and Besov spaces with norms defined using
"$L_p$-averaged" mixed moduli of continuity of functions of appropriate orders,
instead of mixed moduli of continuity of known orders for certain mixed
derivative functions. The author builds continuous linear mappings of such
spaces of functions defined on cube $ I^d, $ to ordinary Nikolskii and Besov
spaces of mixed smoothness in $ \mathbb R^d, $ that are function extension
operators, thus incurring coincidence of both kinds of spaces on the cube $
I^d. $


  Transport properties of Nd$_{2-x}$Ce$_x$CuO$_{4+\delta}$ single crystal films
are investigated in magnetic fields $B$ up to 9T at $T$=(0.4-4.2)K. An analysis
of normal state (at $B>B_{c2}$) Hall coefficient $R_H$$^n$ dependence on Ce
doping takes us to a conclusion about the existence both of electron-like and
hole-like contributions to transport in nominally electron-doped system. In
accordance with $R_H$$^n$(x) analysis an anomalous sign reversal of Hall effect
in mixed state at $B<B_{c2}$ may be ascribed to a flux-flow regime for two
types of carriers with opposite charges.


  Recent experiments have revealed the substantial impact of broken rotational
symmetry on the superconductivity. In the pursuit of understanding the role
played by this symmetry breaking particularly in cuprate and nickelate
superconductors on their superconductivity, we investigated two characteristic
symmetry breaking mechanisms arising from (1) structurally orthogonal
distortions from $C_4$ to $C_2$ symmetry and (2) anisotropic hybridization
between $d_{x^2-y^2}$ orbital and an additional metallic band within the
framework of the Hubbard model by employing dynamic cluster quantum Monte Carlo
calculations. We discovered that the anisotropy is generically detrimental to
the $d$-wave pairing so that the experimental findings of much lower
superconducting $T_c$ of infinite-layer nickelates compared with the cuprates
may be connected to the intrinsic anisotropy. Our exploration sheds light on
the fundamental anisotropy factors governing superconductivity in nickelates
and cuprates and offer insights contributing to the broader understanding of
unconventional superconductors in anisotropic environment.


  The hemispheric pattern of solar filaments is considered in the context of
the global magnetic field of the solar corona. In recent work Mackay and van
Ballegooijen have shown how, for a pair of interacting magnetic bipoles, the
observed chirality pattern could be explained by the dominant range of bipole
tilt angles and helicity in each hemisphere. This study aims to test this
earlier result through a direct comparison between theory and observations,
using newly-developed simulations of the actual surface and 3D coronal magnetic
fields over a 6-month period, on a global scale.
  In this paper we consider two key components of the study; firstly the
observations of filament chirality for the sample of 255 filaments, and
secondly our new simulations of the large-scale surface magnetic field. Based
on a flux-transport model, these will be used as the lower boundary condition
for the future 3D coronal simulations. Our technique differs significantly from
those of other authors, where the coronal field is either assumed to be purely
potential, or has to be reset back to potential every 27 days in order that the
photospheric field remain accurate. In our case we ensure accuracy by the
insertion of newly-emerging bipolar active regions, based on observed
photospheric synoptic magnetograms. The large-scale surface field is shown to
remain accurate over the 6-month period, without any resetting. This new
technique will enable future simulations to consider the long-term build-up and
transport of helicity and shear in the coronal magnetic field, over many months
or years.


  We show that the theory of the free group -- and more generally the theory of
any torsion-free hyperbolic group -- is $n$-ample for any $n\geq 1$. We give
also an explicit description of the imaginary algebraic closure in free groups.


  The first detection of gravitational waves from a neutron star-neutron star
merger, GW170817, has opened up a new avenue for constraining the
ultradense-matter equation of state (EOS). The deviation of the observed
waveform from a point-particle waveform is a sensitive probe of the EOS
controlling the merging neutron stars' structure. In this topical review, I
discuss the various constraints that have been made on the EOS in the year
following the discovery of GW170817. In particular, I review the surprising
relationship that has emerged between the effective tidal deformability of the
binary system and the neutron star radius. I also report new results that make
use of this relationship, finding that the radius inferred from GW170817 lies
between 9.8 and 13.2 km at 90% confidence, with distinct likelihood peaks at
10.8 and 12.3 km. I compare these radii, as well as those inferred in the
literature, to X-ray measurements of the neutron star radius. I also summarize
the various maximum mass constraints, which point towards a maximum mass < 2.3
M_sun, depending on the fate of the remnant, and which can be used to
additionally constrain the high-density EOS. I review the constraints on the
EOS that have been performed directly, through Bayesian inference schemes.
Finally, I comment on the importance of disentangling thermal effects in future
EOS constraints from neutron star mergers.


  Proton stability is guaranteed in the MSSM by assuming a discrete symmetry,
R-parity. However, there are additional R-parity conserving higher dimensional
operators which violate lepton and baryon numbers and induce fast proton decay.
Here we study the possibility that all renormalizable, as well as the most
dangerous non-renormalizable, R-parity violating operators are forbidden by a
flavor symmetry, providing a common origin for fermion mixing and proton and
dark matter stability. We propose a specific model based on the Delta(27)
discrete symmetry.


  We prove a convergence property for some families of finely harmonic
functions on a fine domain $U$ of $\RR^n$ ($n\ge 2$), and we apply it to prove
some regularity of the fine Green kernel of $U$.


  We construct examples of families of curves of genus 2 or 3 over Q whose
Jacobians split completely and have various large rational torsion subgroups.
For example, the rational points on a certain elliptic surface over P^1 of
positive rank parameterize a family of genus-2 curves over Q whose Jacobians
each have 128 rational torsion points. Also, we find the genus-3 curve
15625(X^4 + Y^4 + Z^4) - 96914(X^2 Y^2 + X^2 Z^2 + Y^2 Z^2) = 0, whose Jacobian
has 864 rational torsion points.
  This paper has appeared in Forum Math. 12 (2000) 315-364.


  Multilayers of Co90Fe10/Pd with different bilayer thicknesses, have been
deposited by dc-magnetron sputtering on thermally oxidized Si wafers.
Transmission electron microscopy showed that the highly textured crystalline
films had columnar structure, while scanning transmission electron microscopy
and atomic force microscopy respectively indicated some layer waviness and
surface roughness. The magnetic domain structure and perpendicular magnetic
anisotropy (PMA) of the Co90Fe10/Pd multilayers were investigated by off-axis
electron holography and magnetic force microscopy. The Co90Fe10 layer thickness
was the primary factor determining the magnetic domain size and the
perpendicular magnetization: both decreased as the thickness increased. The
strongest PMA was observed in the sample with the thinnest magnetic layer of
0.45 nm.


  The MEDUSAE method (Multispectral Exoplanet Detection Using Simultaneous
Aberration Estimation) is dedicated to the detection of exoplanets and disks
features in multispectral high-contrast images. The concept of MEDUSAE is to
retrieve both the speckle field and the object map via a stochastic approach to
inverse problem (taking into account the statistics of the noise) in the
Bayesian framework (using parametric regularization). One fundamental aspect of
MEDUSAE is that the model of the coronagraphic PSF is analytic and parametrized
by the optical path difference which, contrary to the phase, is achromatic. The
speckle field is thus estimated by a phase retrieval, using the spectral
diversity to disentangle the planetary signal from the residual starlight. The
object map is restored via a non-myopic deconvolution under adequate
regularization. The basis of this MEDUSAE method have been previously published
and validated on an inverse crime. In this communication, we present its
application to realistic simulated data, in preparation for real data
application. The solution we proposed to attempt bypassing the main differences
between the model used for the inversion and the real data is not sufficient:
it is now necessary to make the model of the coronagraphic PSF more realistic.


  This is the second of two coupled papers estimating the mean values of
multiplicative functions, of unknown support, on arithmetic progressions with
large differences. Applications are made to the study of primes in arithmetic
progression and to the Fourier coefficients of automorphic cusp forms.


  In this note two cosmological models representing the flat Friedmann Universe
filled with a Chaplygin fluid, with or without dust, are analyzed in terms of
the recently proposed "statefinder" parameters. Trajectories of both models in
the parameter plane are shown to be significantly different w.r.t. "quiessence"
and "tracker" models. The generalized Chaplygin gas model with an equation of
state of the form $p = -A/\rho^{\alpha}$ is also analyzed in terms of the
statefinder parameters.


  We investigate the effects of dissipation in the deconfinement transition for
pure SU(2) and SU(3) gauge theories. Using an effective theory for the order
parameter, we study its Langevin evolution numerically. Noise effects are
included for the case of SU(2). We find that both dissipation and noise have
dramatic effects on the spinodal decomposition of the order parameter and delay
considerably its thermalization. For SU(3) the effects of dissipation are even
larger than for SU(2).


  The influence of electron-phonon interaction on magnetotransport in
two-dimensional electron systems under microwave irradiation is studied
theoretically. Apart from the phonon-induced resistance oscillations which
exist in the absence of microwaves, the magnetoresistance of irradiated samples
contains oscillating contributions due to electron scattering on both
impurities and acoustic phonons. The contributions due to electron-phonon
scattering are described as a result of the interference of phonon-induced and
microwave-induced resistance oscillations. In addition, microwave heating of
electrons leads to a special kind of phonon-induced oscillations. The relative
strength of different contributions and their dependence on parameters are
discussed. The interplay of numerous oscillating contributions suggests a
peculiar magnetoresistance picture in high-mobility layers at the temperatures
when electron-phonon scattering becomes important.


  SELEX (Systematic Evolution of Ligands by Exponential Enrichment) is an
experimental procedure that allows extracting, from an initially random pool of
DNA, those oligomers with high affinity for a given DNA-binding protein. We
address what is a suitable experimental and computational procedure to infer
parameters of transcription factor-DNA interaction from SELEX experiments. To
answer this, we use a biophysical model of transcription factor-DNA
interactions to quantitatively model SELEX. We show that a standard procedure
is unsuitable for obtaining accurate interaction parameters. However, we
theoretically show that a modified experiment in which chemical potential is
fixed through different rounds of the experiment allows robust generation of an
appropriate data set. Based on our quantitative model, we propose a novel
bioinformatic method of data analysis for such modified experiment and apply it
to extract the interaction parameters for a mammalian transcription factor
CTF/NFI. From a practical point of view, our method results in a significantly
improved false positive/false negative trade-off, as compared to both the
standard information theory based method and a widely used empirically
formulated procedure.