  The recently discovered high redshift galaxy, 53W091, with accurate age
measurements (Dunlop et al 1996) provides a measure of the small-scale power of
the primordial density field and, as we show, a crucial test of the
inflation-inspired models. It allows $\Omega$=1 cosmologies only for low values
of $H_0$, but then pushes formation of that galaxy to redshift much greater
than allowed for by the cold-dark-matter density field. Cold-dark-matter (CDM)
models with cosmological constant ($\Lambda$) and low $\Omega$ would decrease
the redshift at which this galaxy has collapsed. However, in CDM models
decreasing $\Omega$ suppresses the small scale power in the density field and
this effect turns out to be dominant. We estimate the mass of the galaxy and
show that it represents a very rare and unlikely event in the density field of
such models. Similar problems would occur in other modifications of the CDM
cosmogonies.


  Within the framework of Classical Molecular Dynamics, we study the collision
Au + Au at an incident energy of 35 MeV/nucleon. It is found that the system
shows a critical behaviour at peripheral impact parameters, revealed through
the analysis of conditional moments of charge distributions, Campi Scatter
Plot, and the occurrence of large fluctuations in the region of the Campi plot
where this critical behaviour is expected. When applying the experimental
filters of the MULTICS-MINIBALL apparatus, it is found that criticality signals
can be hidden due to the inefficiency of the experimental apparatus. The
signals are then recovered by identifying semi-peripheral and peripheral
collisions looking to the velocity distribution of the largest fragment, then
by selecting the most complete events.


  Could we enjoy starry skies in our cities again? Arguably yes. The actual
number of visible stars will depend, among other factors, on the spatial
density of the overall city light emissions. In this paper it is shown that
reasonably dark skies could be achieved in urban settings, even at the center
of large metropolitan areas, if the light emissions are kept within admissible
levels and direct glare from the light sources is avoided. These results may
support the adoption of science-informed, democratic public decisions on the
use of light in our municipalities, with the goal of recovering the possibility
of contemplating the night sky everywhere in our planet.


  A gauge theory of solids with conformal symmetry is formulated to model
various electromechanical and magnetomechanical coupling phenomena. If the
pulled back metric of the current configuration (the right Cauchy-Green tensor)
is scaled with a constant, the volumetric part of the Lagrange density changes
while the isochoric part remains invariant. However, upon a position dependent
scaling, the isochoric part also loses invariance. In order to restore the
invariance of the isochoric part, a 1-form compensating field is introduced and
the notion of a gauge covariant derivative is utilized to minimally replace the
Lagrangian. In view of obvious similarities with the Weyl geometry, the Weyl
condition is imposed through the Lagrangian and a minimal coupling is employed
so the 1-form could evolve. On deriving the Euler-Lagrange equations based on
the action functional, we observe a close similarity with the governing
equations for flexoelectricity under isochoric deformation if the exact part of
1-form is interpreted as the electric field and the anti-exact part as the
polarization vector. Next, we model piezoelectricity and electrostriction
phenomena by contracting the Weyl condition in various ways. Applying the Hodge
decomposition theorem on the 1-form which leads to the curl of a pseudo-vector
field and a vector field, we also model magnetomechanical phenomena.
Identifying the pseudo-vector field with magnetic potential and the vector part
with magnetization, flexomagnetism, piezomagnetism and magnetostriction
phenomena under isochoric deformation are also modeled. Finally, we consider an
analytical solution of the equations for piezoelectricity to provide an
illustration on the insightful information that the present approach
potentially provides.


  We review recent one and two loop MSbar Landau gauge calculations using the
Gribov-Zwanziger Lagrangian. The behaviour of the gluon and Faddeev-Popov ghost
propagators as well as the renormalization group invariant effective coupling
constant is examined in the infrared limit.


  Let $K$ be a fixed field. We attach to each column-finite quiver $E$ a von
Neumann regular $K$-algebra $Q(E)$ in a functorial way. The algebra $Q(E)$ is a
universal localization of the usual path algebra $P(E)$ associated with $E$.
The monoid of isomorphism classes of finitely generated projective right
$Q(E)$-modules is explicitly computed.


  Surface Enhanced Raman Scattering (SERS) and Surface-Enhanced Fluorescence
(SEF) are studied within the framework of modified Spontaneous Emission (SE),
and similarities and differences are highlighted. This description sheds new
light into several aspects of the SERS electromagnetic enhancement. In
addition, combined with the optical reciprocity theorem it also provides a
rigorous justification of a generalized version of the widely used SERS
enhancement factor proportional to the fourth power of the field ($|E|^4$). We
show, in addition, that this approach also applies to the calculation of
Surface-Enhanced Fluorescence cross-sections thus presenting both phenomena
SERS and SEF within a unified framework.


  This paper presents the first comprehensive study on automatic readability
assessment of Turkish texts. We combine state-of-the-art neural network models
with linguistic features at lexical, morphosyntactic, syntactic and discourse
levels to develop an advanced readability tool. We evaluate the effectiveness
of traditional readability formulas compared to modern automated methods and
identify key linguistic features that determine the readability of Turkish
texts.


  We calculate the Z boson propagator correction, as described by the S
parameter, in technicolor theories with extended technicolor interactions
included. Our method is to solve the Bethe-Salpeter equation for the requisite
current-current correlation functions. Our results suggest that the inclusion
of extended technicolor interactions has a relatively small effect on S.


  Quality assurance is crucial in the smart manufacturing industry as it
identifies the presence of defects in finished products before they are shipped
out. Modern machine learning techniques can be leveraged to provide rapid and
accurate detection of these imperfections. We, therefore, propose a transfer
learning approach, namely TransferD2, to correctly identify defects on a
dataset of source objects and extend its application to new unseen target
objects. We present a data enhancement technique to generate a large dataset
from the small source dataset for building a classifier. We then integrate
three different pre-trained models (Xception, ResNet101V2, and
InceptionResNetV2) into the classifier network and compare their performance on
source and target data. We use the classifier to detect the presence of
imperfections on the unseen target data using pseudo-bounding boxes. Our
results show that ResNet101V2 performs best on the source data with an accuracy
of 95.72%. Xception performs best on the target data with an accuracy of 91.00%
and also provides a more accurate prediction of the defects on the target
images. Throughout the experiment, the results also indicate that the choice of
a pre-trained model is not dependent on the depth of the network. Our proposed
approach can be applied in defect detection applications where insufficient
data is available for training a model and can be extended to identify
imperfections in new unseen data.


  Let $\Lambda$ be the von Mangoldt function and $(r_G(n) = \sum_{m_1 + m_2 =
n} \Lambda(m_1) \Lambda(m_2))$ be the counting function for the Goldbach
numbers. Let $N \geq 2$ be an integer. We prove that $$\begin{align} &\sum_{n
\le N} r_G(n) \frac{(1 - n/N)^k}{\Gamma(k + 1)} = \frac{N^2}{\Gamma(k + 3)} - 2
\sum_\rho \frac{\Gamma(\rho)}{\Gamma(\rho + k + 2)} N^{\rho+1}\\ &\qquad+
\sum_{\rho_1} \sum_{\rho_2} \frac{\Gamma(\rho_1) \Gamma(\rho_2)}{\Gamma(\rho_1
+ \rho_2 + k + 1)} N^{\rho_1 + \rho_2} + \mathcal{O}_k(N^{1/2}), \end{align}$$
for $k > 1$, where $\rho$, with or without subscripts, runs over the
non-trivial zeros of the Riemann zeta-function $\zeta(s)$.


  BOREXINO, a real-time device for low energy neutrino spectroscopy is nearing
completion of construction in the underground laboratories at Gran Sasso, Italy
(LNGS). The experiment's goal is the direct measurement of the flux of 7Be
solar neutrinos of all flavors via neutrino-electron scattering in an
ultra-pure scintillation liquid. Seeded by a series of innovations which were
brought to fruition by large scale operation of a 4-ton test detector at LNGS,
a new technology has been developed for BOREXINO. It enables sub-MeV solar
neutrino spectroscopy for the first time. This paper describes the design of
BOREXINO, the various facilities essential to its operation, its spectroscopic
and background suppression capabilities and a prognosis of the impact of its
results towards resolving the solar neutrino problem. BOREXINO will also
address several other frontier questions in particle physics, astrophysics and
geophysics.


  We consider parallel computation for Gaussian process calculations to
overcome computational and memory constraints on the size of datasets that can
be analyzed. Using a hybrid parallelization approach that uses both threading
(shared memory) and message-passing (distributed memory), we implement the core
linear algebra operations used in spatial statistics and Gaussian process
regression in an R package called bigGP that relies on C and MPI. The approach
divides the matrix into blocks such that the computational load is balanced
across processes while communication between processes is limited. The package
provides an API enabling R programmers to implement Gaussian process-based
methods by using the distributed linear algebra operations without any C or MPI
coding. We illustrate the approach and software by analyzing an astrophysics
dataset with n=67,275 observations.


  Terrain classification is a critical component of any autonomous mobile robot
system operating in unknown real-world environments. Over the years, several
proprioceptive terrain classification techniques have been introduced to
increase robustness or act as a fallback for traditional vision based
approaches. However, they lack widespread adaptation due to various factors
that include inadequate accuracy, robustness and slow run-times. In this paper,
we use vehicle-terrain interaction sounds as a proprioceptive modality and
propose a deep Long-Short Term Memory (LSTM) based recurrent model that
captures both the spatial and temporal dynamics of such a problem, thereby
overcoming these past limitations. Our model consists of a new Convolution
Neural Network (CNN) architecture that learns deep spatial features,
complemented with LSTM units that learn complex temporal dynamics. Experiments
on two extensive datasets collected with different microphones on various
indoor and outdoor terrains demonstrate state-of-the-art performance compared
to existing techniques. We additionally evaluate the performance in adverse
acoustic conditions with high ambient noise and propose a noise-aware training
scheme that enables learning of more generalizable models that are essential
for robust real-world deployments.


  A U(2,2|4)-invariant A-model constructed from fermionic superfields has
recently been proposed as a sigma model for the superstring on AdS_5xS^5. After
explaining the relation of this A-model with the pure spinor formalism, the
A-model action is expressed as a gauged linear sigma model. In the zero radius
limit, the Coulomb branch of this sigma model is interpreted as D-brane holes
which are related to gauge-invariant N=4 d=4 super-Yang-Mills operators. As in
the worldsheet derivation of open-closed duality for Chern-Simons theory, this
construction may lead to a worldsheet derivation of the Maldacena conjecture.
Intriguing connections to the twistorial formulation of N=4 Yang-Mills are also
noted.


  A keyword search on constrained clustering on Web-of-Science returned just
under 3,000 documents. We ran automatic analyses of those, and compiled our own
bibliography of 183 papers which we analysed in more detail based on their
topic and experimental study, if any. This paper presents general trends of the
area and its sub-topics by Pareto analysis, using citation count and year of
publication. We list available software and analyse the experimental sections
of our reference collection. We found a notable lack of large comparison
experiments. Among the topics we reviewed, applications studies were most
abundant recently, alongside deep learning, active learning and ensemble
learning.


  Laser accelerated protons can be a complimentary source for treatment of
oncological diseases to the existing hadron therapy facilities. We demonstrate
how the protons, accelerated from near-critical density plasmas by laser pulses
having relatively small power, reach energies which may be of interest for
medical applications. When an intense laser pulse interacts with near-critical
density plasma it makes a channel both in the electron and then in the ion
density. The propagation of a laser pulse through such a self-generated channel
is connected with the acceleration of electrons in the wake of a laser pulse
and generation of strong moving electric and magnetic fields in the propagation
channel. Upon exiting the plasma the magnetic field generates a quasi-static
electric field that accelerates and collimates ions from a thin filament formed
in the propagation channel. Two-dimensional Particle-in-Cell simulations show
that a 100 TW laser pulse tightly focused on a near-critical density target is
able to accelerate protons up to energy of 250 MeV. Scaling laws and optimal
conditions for proton acceleration are established considering the energy
depletion of the laser pulse.


  We theoretically discuss several aspects of sequential superradiant
scattering from atomic Bose-Einstein condensates. Our treatment is based on the
semiclassical description of the process in terms of the Maxwell-Schroedinger
equations for the coupled matter-wave and optical fields. First, we investigate
sequential scattering in the weak-pulse regime and work out the essential
mechanisms responsible for bringing about the characteristic fan-shaped
side-mode distribution patterns. Second, we discuss the transition between the
Kapitza-Dirac and Bragg regimes of sequential scattering in the strong-pulse
regime. Finally, we consider the situation where superradiance is initiated by
coherently populating an atomic side mode through Bragg diffraction, as in
studies of matter-wave amplification, and describe the effect on the sequential
scattering process.


  Theoretically expected natures of a supernova driven by a wind/jet are
discussed. Approximate analytical formulations are derived to clarify basic
physical processes involved in the wind/jet-driven explosions, and it is shown
that the explosion properties are characterized by the energy injection rate
(Edot_iso) and the mass injection rate (Mdot_iso). To explain observations of
SN 1998bw associated with Gamma-Ray Burst (GRB) 980425, the following
conditions are required: Edot_iso Mdot_iso > ~ 10^{51} erg M_sun s^{-2} and
Edot_iso > ~ 2 x 10^{52} erg s^{-1} (if the wind Lorentz factor Gamma_w ~ 1) or
Edot_iso > ~ 7 x 10^{52} erg s^{-1} (if Gamma_w >> 1). In SN 1998bw, 56Ni (~
0.4M_sun) is probably produced in the shocked stellar mantle, not in the wind.
The expected natures of SNe, e.g., ejected 56Ni masses and ejecta masses, vary
depending on Edot_iso and Mdot_iso. The sequence of the SN properties from high
Edot_iso and Mdot_iso to low Edot_iso and Mdot_iso is the following: SN
1998bw-like -- intermediate case -- low mass ejecta (< ~ 1M_sun$) where 56Ni is
from the wind -- whole collapse. This diversity may explain the diversity of
supernovae associated with GRBs. Our result can be used to constrain natures of
the wind/jet, which is linked to the central engine of GRBs, by studying
properties of the associated supernovae.


  The autocorrelation function and the run structure are two basic notions for
binary sequences, and have been used as two independent postulates to test
randomness of binary sequences ever since Golomb 1955. In this paper, we prove
for binary sequence that the autocorrelation function is in fact completely
determined by its run structure.


  We show that existing data suggest a simple scenario in which the nucleon,
and the Delta and Roper resonances act as chiral partners in a reducible
representation of the full QCD chiral symmetry group. We discuss the peculiar
interpretation of this scenario using spin-flavor symmetries of the naive
constituent quark model, as well as the consistency of the scenario with
large-Nc expectations.


  Simultaneous measurements of tunneling currents and atomic forces on surfaces
and adsorbates provide new insights into the electronic and structural
properties of matter on the atomic scale. We report on experimental
observations and calculations of a strong impact the tunneling current can have
on the measured force, which arises when the resistivity of the sample cannot
be neglected. We present a study on Si(111)-7\times7 with various doping
levels, but this effect is expected to occur on other low-conductance samples
like adsorbed molecules, and is likely to strongly affect Kelvin probe
measurements on the atomic scale.


  The hints for a new resonance at 750 GeV from ATLAS and CMS have triggered a
significant amount of attention. Since the simplest extensions of the standard
model cannot accommodate the observation, many alternatives have been
considered to explain the excess. Here we focus on several proposed
renormalisable weakly-coupled models and revisit results given in the
literature. We point out that physically important subtleties are often missed
or neglected. To facilitate the study of the excess we have created a
collection of 40 model files, selected from recent literature, for the
Mathematica package SARAH. With SARAH one can generate files to perform
numerical studies using the tailor-made spectrum generators FlexibleSUSY and
SPheno. These have been extended to automatically include crucial higher order
corrections to the diphoton and digluon decay rates for both CP-even and CP-odd
scalars. Additionally, we have extended the UFO and CalcHep interfaces of
SARAH, to pass the precise information about the effective vertices from the
spectrum generator to a Monte-Carlo tool. Finally, as an example to demonstrate
the power of the entire setup, we present a new supersymmetric model that
accommodates the diphoton excess, explicitly demonstrating how a large width
can be obtained. We explicitly show several steps in detail to elucidate the
use of these public tools in the precision study of this model.


  Particle tracking is a fundamental part of the event analysis in high energy
and nuclear physics. Events multiplicity increases each year along with the
drastic growth of the experimental data which modern HENP detectors produce, so
the classical tracking algorithms such as the well-known Kalman filter cannot
satisfy speed and scaling requirements. At the same time, breakthroughs in the
study of deep learning open an opportunity for the application of
high-performance deep neural networks for solving tracking problems in a dense
environment of experiments with heavy ions. However, there are no
well-documented software libraries for deep learning track reconstruction yet.
We introduce Ariadne, the first open-source library for particle tracking based
on the PyTorch deep learning framework. The goal of our library is to provide a
simple interface that allows one to prepare train and test datasets and to
train and evaluate one of the deep tracking models implemented in the library
on the data from your specific experiment. The user experience is greatly
facilitated because of the system of gin-configurations. The modular structure
of the library and abstract classes let the user develop his data processing
pipeline and deep tracking model easily. The proposed library is open-source to
facilitate academic research in the field of particle tracking based on deep
learning.


  The concept of forming harmonious coalitions is introduced to both classical
and quantum symmetric cooperative game. In both cases, players are motivated to
form coalitions. Also, the main feature of the cooperative game is conserved.


  We present a collocated-grid framework for Direct Numerical Simulations of
polydisperse particles submerged in a viscous fluid. The fluid-particle forces
are coupled with the Immersed Boundary Method (IBM) while the particle-particle
forces are modeled with a combination of contact and lubrication models,
adapted for collocated grids. Our method is modified from the staggered-grid
IBM of previous authors to a collocated-grid IBM by adapting the fluid and
particle solvers. The method scales well on high-performance parallel computing
platforms. It has been validated against various cases and is able to reproduce
experimental results. Tuning parameters have been thoroughly calibrated to
ensure the accuracy of the method. Finally, we demonstrate the capability of
the method to simulate both monodispersed and bidispersed fluidized beds and
reproduce the power law relationship between the inflow velocity and the
porosity.


  Although the hypothetic sterile neutrino $\nu_s$ is probably not involved
significantly in the deficits of solar $\nu_e$'s and atmospheric $\nu_\mu$'s,
it may cause the possible LSND effect. In fact, we face such a situation, when
the popular nearly bimaximal texture of active neutrinos $\nu_e$, $\nu_\mu$,
$\nu_\tau$ is perturbed through a small rotation in the 14 plane, where $\nu_4$
is the extra neutrino mass state induced by the sterile neutrino $\nu_s$. Then,
with $m^2_1\simeq m^2_2$ we predict in the simplest case of $s_{13}\to0$ that
$\sin^22\theta_{\rm LSND}=s^4_{14}/2$ and $\Delta m^2_{\rm LSND} = |\Delta
m^2_{41}|$. However, the negative CHOOZ experiment imposes on $s^4_{14}/2$ the
upper bound $1.3\times10^{-3}$, suggesting a reduction of the amplitude of
possible LSND effect.


  Stars between two and three solar masses rotate rapidly on the main sequence,
and their rotation rates in the core helium burning (secondary clump) phase can
therefore be used to test models of angular momentum loss used for
gyrochronology in a new regime. Because both their core and surface rotation
rates can be measured, these stars can also be used to set strong constraints
on angular momentum transport inside stars. We find that they are rotating
slower than angular momentum conservation and rigid rotation would predict. Our
results are insensitive to the degree of core-envelope coupling because of the
small moment of inertia of the radiative core. We discuss two possible
mechanisms for slowing down the surfaces of these stars: (1) substantial
angular momentum loss, and (2) radial differential rotation in the surface
convection zone. Modern angular momentum loss prescriptions used for solar-type
stars predict secondary clump surface rotation rates in much better agreement
with the data than prior variants used in the literature, and we argue that
such enhanced loss is required to understand the combination of core and
surface rotation rates. However, we find that the assumed radial differential
rotation profile in convective regions has a strong impact on the predicted
surface rotation rates, and that a combination of enhanced loss and radial
differential rotation in the surface convection zone is also consistent with
the data. We discuss future tests that can quantify the impact of both
phenomena. Current data tentatively suggests that some combination of the two
processes fits the data better than either one alone.


  Weakly supervised object detection (WSOD), which is an effective way to train
an object detection model using only image-level annotations, has attracted
considerable attention from researchers. However, most of the existing methods,
which are based on multiple instance learning (MIL), tend to localize instances
to the discriminative parts of salient objects instead of the entire content of
all objects. In this paper, we propose a WSOD framework called the Spatial
Likelihood Voting with Self-knowledge Distillation Network (SLV-SD Net). In
this framework, we introduce a spatial likelihood voting (SLV) module to
converge region proposal localization without bounding box annotations.
Specifically, in every iteration during training, all the region proposals in a
given image act as voters voting for the likelihood of each category in the
spatial dimensions. After dilating the alignment on the area with large
likelihood values, the voting results are regularized as bounding boxes, which
are then used for the final classification and localization. Based on SLV, we
further propose a self-knowledge distillation (SD) module to refine the feature
representations of the given image. The likelihood maps generated by the SLV
module are used to supervise the feature learning of the backbone network,
encouraging the network to attend to wider and more diverse areas of the image.
Extensive experiments on the PASCAL VOC 2007/2012 and MS-COCO datasets
demonstrate the excellent performance of SLV-SD Net. In addition, SLV-SD Net
produces new state-of-the-art results on these benchmarks.


  For a given positive operator $G$ we consider the cones of linear maps
between Banach spaces of trace class operators characterized by the
Stinespring-like representation with $\sqrt{G}$-bounded and
$\sqrt{G}$-infinitesimal operators correspondingly. We prove the completeness
of both cones w.r.t. the energy-constrained diamond norm induced by $G$ (as an
energy observable) and the coincidence of the second cone with the completion
of the cone of CP linear maps w.r.t. this norm.
  We show that the sets of quantum channels and quantum operations are complete
w.r.t. the energy-constrained diamond norm for any energy observable $G$.
  Some properties of the maps belonging to the introduced cones are described.
In particular, the corresponding generalization of the
Kretschmann-Schlingemann-Werner theorem is obtained.
  We also give a nonconstructive description of the completion of the set of
all Hermitian-preserving completely bounded linear maps w.r.t. the ECD norm.


  We consider various models of three-dimensional gravity with torsion or
nonmetricity (metric affine gravity), and show that they can be written as
Chern-Simons theories with suitable gauge groups. Using the groups ISO(2,1),
SL(2,C) or SL(2,R) x SL(2,R), and the fact that they admit two independent
coupling constants, we obtain the Mielke-Baekler model for zero, positive or
negative effective cosmological constant respectively. Choosing SO(3,2) as
gauge group, one gets a generalization of conformal gravity that has zero
torsion and only the trace part of the nonmetricity. This characterizes a Weyl
structure. Finally, we present a new topological model of metric affine gravity
in three dimensions arising from an SL(4,R) Chern-Simons theory.


  Since the day of its explosion, supernova (SN) 1987A has been closely
monitored to study its evolution and to detect its central compact relic. In
fact, the formation of a neutron star is strongly supported by the detection of
neutrinos from the SN. However, besides the detection in the Atacama Large
Millimeter/submillimeter Array (ALMA) data of a feature that is compatible with
the emission arising from a proto-pulsar wind nebula (PWN), the only hint for
the existence of such elusive compact object is provided by the detection of
hard emission in NuSTAR data up to ~ 20 keV. We report on the simultaneous
analysis of multi-epoch observations of SN 1987A performed with Chandra,
XMM-Newton and NuSTAR. We also compare the observations with a state-of-the-art
3D magnetohydrodynamic (MHD) simulation of SN 1987A. A heavily absorbed
power-law, consistent with the emission from a PWN embedded in the heart of SN
1987A, is needed to properly describe the high-energy part of the observed
spectra. The spectral parameters of the best-fit power-law are in agreement
with the previous estimate, and exclude diffusive shock acceleration as a
possible mechanism responsible for the observed non-thermal emission. The
information extracted from our analysis are used to infer the physical
characteristics of the pulsar and the broad-band emission of its nebula, in
agreement with the ALMA data. Analysis of the synthetic spectra also show that,
in the near future, the main contribution to Fe K emission line will originate
in the outermost shocked ejecta of SN 1987A.


  While vehicular sensor networks (VSNs) have earned the stature of a mobile
sensing paradigm utilizing sensors built into cars, they have limited sensing
scopes since car drivers only opportunistically discover new events.
Conversely, social sensing is emerging as a new sensing paradigm where
measurements about the physical world are collected from humans. In contrast to
VSNs, social sensing is more pervasive, but one of its key limitations lies in
its inconsistent reliability stemming from the data contributed by unreliable
human sensors. In this paper, we present DASC, a road Damage-Aware
Social-media-driven Car sensing framework that exploits the collective power of
social sensing and VSNs for reliable disaster response applications. However,
integrating VSNs with social sensing introduces a new set of challenges: i) How
to leverage noisy and unreliable social signals to route the vehicles to
accurate regions of interest? ii) How to tackle the inconsistent availability
(e.g., churns) caused by car drivers being rational actors? iii) How to
efficiently guide the cars to the event locations with little prior knowledge
of the road damage caused by the disaster, while also handling the dynamics of
the physical world and social media? The DASC framework addresses the above
challenges by establishing a novel hybrid social-car sensing system that
employs techniques from game theory, feedback control, and Markov Decision
Process (MDP). In particular, DASC distills signals emitted from social media
and discovers the road damages to effectively drive cars to target areas for
verifying emergency events. We implement and evaluate DASC in a reputed vehicle
simulator that can emulate real-world disaster response scenarios. The results
of a real-world application demonstrate the superiority of DASC over current
VSNs-based solutions in detection accuracy and efficiency.


  Very massive primordial stars (140 Msol < M < 260 Msol) are supposed to end
their lives as PISN. Such an event can be traced by a typical chemical
signature in low metallicity stars, but at the present time, this signature is
lacking in the extremely metal-poor stars we are able to observe. Does it mean
that those very massive objects were not formed, contrarily to the primordial
star formation scenarios ? Could it be possible that they avoided this tragical
fate ?
  We explore the effects of rotation, anisotropical mass loss and magnetic
field on the core size of very massive Population III models. We find that
magnetic fields provide the strong coupling that is lacking in standard
evolution metal-free models and our 150 Msol Population III model avoids indeed
the pair-instability explosion.


  We consider the Cauchy problem for the incompressible Navier--Stokes
equations on the whole space $\mathbb{R}^3$, with initial value $\vec u_0\in
{\rm BMO}^{-1}$ (as in Koch and Tataru's theorem) and with force $\vec f=\Div
\mathbb{F}$ where smallness of $\mathbb{F}$ ensures existence of a mild
solution in absence of initial value. We study the interaction of the two
solutions and discuss the existence of global solution for the complete problem
(i.e. in presence of initial value and forcing term) under smallness
assumptions. In particular, we discuss the interaction between Koch and Tataru
solutions and Lei-Lin's solutions (in $L^2\mathcal{F}^{-1}L^1$) or solutions in
the multiplier space $\mathcal{M}(\dot H^{1/2,1}_{t,x}\mapsto L^2_{t,x})$.


  We propose an online object-level SLAM system which builds a persistent and
accurate 3D graph map of arbitrary reconstructed objects. As an RGB-D camera
browses a cluttered indoor scene, Mask-RCNN instance segmentations are used to
initialise compact per-object Truncated Signed Distance Function (TSDF)
reconstructions with object size-dependent resolutions and a novel 3D
foreground mask. Reconstructed objects are stored in an optimisable 6DoF pose
graph which is our only persistent map representation. Objects are
incrementally refined via depth fusion, and are used for tracking,
relocalisation and loop closure detection. Loop closures cause adjustments in
the relative pose estimates of object instances, but no intra-object warping.
Each object also carries semantic information which is refined over time and an
existence probability to account for spurious instance predictions. We
demonstrate our approach on a hand-held RGB-D sequence from a cluttered office
scene with a large number and variety of object instances, highlighting how the
system closes loops and makes good use of existing objects on repeated loops.
We quantitatively evaluate the trajectory error of our system against a
baseline approach on the RGB-D SLAM benchmark, and qualitatively compare
reconstruction quality of discovered objects on the YCB video dataset.
Performance evaluation shows our approach is highly memory efficient and runs
online at 4-8Hz (excluding relocalisation) despite not being optimised at the
software level.


  We study the minimization of the expected costs under stochastic constraint
at the terminal time. The first and the main result says that for a power type
of costs, the value function is the minimal positive solution of a second order
semi--linear ordinary differential equation (ODE). Moreover, we establish the
optimal control. In the second example we show that the case of exponential
costs leads to a trivial optimal control.


  We study the Low Rank Phase Retrieval (LRPR) problem defined as follows:
recover an $n \times q$ matrix $X^*$ of rank $r$ from a different and
independent set of $m$ phaseless (magnitude-only) linear projections of each of
its columns. To be precise, we need to recover $X^*$ from $y_k := |A_k{}'
x^*_k|, k=1,2,\dots, q$ when the measurement matrices $A_k$ are mutually
independent. Here $y_k$ is an $m$ length vector, $A_k$ is an $n \times m$
matrix, and $'$ denotes matrix transpose. The question is when can we solve
LRPR with $m \ll n$? A reliable solution can enable fast and low-cost phaseless
dynamic imaging, e.g., Fourier ptychographic imaging of live biological
specimens. In this work, we develop the first provably correct approach for
solving this LRPR problem. Our proposed algorithm, Alternating Minimization for
Low-Rank Phase Retrieval (AltMinLowRaP), is an AltMin based solution and hence
is also provably fast (converges geometrically). Our guarantee shows that
AltMinLowRaP solves LRPR to $\epsilon$ accuracy, with high probability, as long
as $m q \ge C n r^4 \log(1/\epsilon)$, the matrices $A_k$ contain i.i.d.
standard Gaussian entries, and the right singular vectors of $X^*$ satisfy the
incoherence assumption from matrix completion literature. Here $C$ is a
numerical constant that only depends on the condition number of $X^*$ and on
its incoherence parameter. Its time complexity is only $ C mq nr
\log^2(1/\epsilon)$. Since even the linear (with phase) version of the above
problem is not fully solved, the above result is also the first complete
solution and guarantee for the linear case. Finally, we also develop a simple
extension of our results for the dynamic LRPR setting.


  The model of dipole fluid for the ionic liquids similar to the molten NaCl is
proposed. The estimates for the critical parameters are obtained with the help
of the van der Waals equation of state. The influence of the rotation on the
characteristics of a dipole pair and the location of the critical point is
discussed. The dissociation of such fluid near the critical point is
considered.


  With a goal toward deriving the physical conditions in external galaxies, we
present a survey of the formaldehyde emission in a sample of starburst systems.
By extending a technique used to derive the spatial density in star formation
regions in our own Galaxy, we show how the relative intensity of the
1(10)-1(11) and 2(11)-2(12) K-doublet transitions of H2CO can provide an
accurate densitometer for the active star formation environments found in
starburst galaxies. Relying upon an assumed kinetic temperature and co-spatial
emission and absorption from both H2CO transitions, our technique is applied to
a sample of nineteen IR-bright galaxies which exhibit various forms of
starburst activity. In the five galaxies of our sample where both H2CO
transitions were detected we have derived spatial densities. We also use H2CO
to estimate the dense gas mass in our starburst galaxy sample, finding similar
mass estimates for the dense gas forming stars in these objects as derived
using other dense gas tracers. A related trend can be seen when one compares
L_IR to our derived n(H2) for the five galaxies within which we have derived
spatial densities. Even though our number statistics are small, there appears
to be a trend toward higher spatial density for galaxies with higher infrared
luminosity. This is likely another representation of the L_IR-M_dense
correlation.


  An individual's social group may be represented by their ego-network, formed
by the links between the individual and their acquaintances. Ego-networks
present an internal structure of increasingly large nested layers (or circles)
of decreasing relationship intensity, whose size exhibits a precise scaling
ratio. Starting from the notion of limited social bandwidth, and assuming fixed
costs for the links in each layer, we propose a null model built on a
grand-canonical ensemble that generates the observed hierarchical social
structure. The observed internal structure of ego-networks becomes a natural
outcome to expect when we assume the existence of layers demanding different
amounts of resources. In the thermodynamic limit, reached when the number of
ego-network copies is large, the specific layer degrees follow a Poisson
distribution. We also find that, under certain conditions, equispaced layer
costs are necessary to obtain a constant group size scaling. Our model presents
interesting analogies to a Bose-Einstein gas, that we briefly discuss. Finally,
we fit and compare the model with an empirical social network.


  Facial action unit (AU) detection in the wild is a challenging problem, due
to the unconstrained variability in facial appearances and the lack of accurate
annotations. Most existing methods depend on either impractical labor-intensive
labeling or inaccurate pseudo labels. In this paper, we propose an end-to-end
unconstrained facial AU detection framework based on domain adaptation, which
transfers accurate AU labels from a constrained source domain to an
unconstrained target domain by exploiting labels of AU-related facial
landmarks. Specifically, we map a source image with label and a target image
without label into a latent feature domain by combining source landmark-related
feature with target landmark-free feature. Due to the combination of source
AU-related information and target AU-free information, the latent feature
domain with transferred source label can be learned by maximizing the
target-domain AU detection performance. Moreover, we introduce a novel landmark
adversarial loss to disentangle the landmark-free feature from the
landmark-related feature by treating the adversarial learning as a multi-player
minimax game. Our framework can also be naturally extended for use with
target-domain pseudo AU labels. Extensive experiments show that our method
soundly outperforms lower-bounds and upper-bounds of the basic model, as well
as state-of-the-art approaches on the challenging in-the-wild benchmarks. The
code is available at https://github.com/ZhiwenShao/ADLD.


  We envision a mobile edge computing (MEC) framework for machine learning (ML)
technologies, which leverages distributed client data and computation resources
for training high-performance ML models while preserving client privacy. Toward
this future goal, this work aims to extend Federated Learning (FL), a
decentralized learning framework that enables privacy-preserving training of
models, to work with heterogeneous clients in a practical cellular network. The
FL protocol iteratively asks random clients to download a trainable model from
a server, update it with own data, and upload the updated model to the server,
while asking the server to aggregate multiple client updates to further improve
the model. While clients in this protocol are free from disclosing own private
data, the overall training process can become inefficient when some clients are
with limited computational resources (i.e. requiring longer update time) or
under poor wireless channel conditions (longer upload time). Our new FL
protocol, which we refer to as FedCS, mitigates this problem and performs FL
efficiently while actively managing clients based on their resource conditions.
Specifically, FedCS solves a client selection problem with resource
constraints, which allows the server to aggregate as many client updates as
possible and to accelerate performance improvement in ML models. We conducted
an experimental evaluation using publicly-available large-scale image datasets
to train deep neural networks on MEC environment simulations. The experimental
results show that FedCS is able to complete its training process in a
significantly shorter time compared to the original FL protocol.


  The ATLAS experiment at the Large Hadron Collider (LHC) employs a trigger
system consisting of a first-level hardware trigger (L1) and a software-based
high-level trigger. The L1 muon trigger system selects muon candidates, assigns
them to the correct LHC bunch crossing and classifies them into one of six
transverse-momentum threshold classes. The L1 muon trigger system uses
resistive-plate chambers (RPCs) to generate the muon-induced trigger signals in
the central (barrel) region of the ATLAS detector. The ATLAS RPCs are arranged
in six concentric layers and operate in a toroidal magnetic field with a
bending power of 1.5 to 5.5 Tm. The RPC detector consists of about 3700 gas
volumes with a total surface area of more than 4000 m$^2$. This paper reports
on the performance of the RPC detector and L1 muon barrel trigger using 60.8
fb$^{-1}$ of proton-proton collision data recorded by the ATLAS experiment in
2018 at a centre-of-mass energy of 13 TeV. Detector and trigger performance are
studied using $Z$ boson decays into a muon pair. Measurements of the RPC
detector response, efficiency, and time resolution are reported. Measurements
of the L1 muon barrel trigger efficiencies and rates are presented, along with
measurements of the properties of the selected sample of muon candidates.
Measurements of the RPC currents, counting rates and mean avalanche charge are
performed using zero-bias collisions. Finally, RPC detector response and
efficiency are studied at different high voltage and front-end discriminator
threshold settings in order to extrapolate detector response to the higher
luminosity expected for the High Luminosity LHC.


  Search engines decide what we see for a given search query. Since many people
are exposed to information through search engines, it is fair to expect that
search engines are neutral. However, search engine results do not necessarily
cover all the viewpoints of a search query topic, and they can be biased
towards a specific view since search engine results are returned based on
relevance, which is calculated using many features and sophisticated algorithms
where search neutrality is not necessarily the focal point. Therefore, it is
important to evaluate the search engine results with respect to bias. In this
work we propose novel web search bias evaluation measures which take into
account the rank and relevance. We also propose a framework to evaluate web
search bias using the proposed measures and test our framework on two popular
search engines based on 57 controversial query topics such as abortion, medical
marijuana, and gay marriage. We measure the stance bias (in support or
against), as well as the ideological bias (conservative or liberal). We observe
that the stance does not necessarily correlate with the ideological leaning,
e.g. a positive stance on abortion indicates a liberal leaning but a positive
stance on Cuba embargo indicates a conservative leaning. Our experiments show
that neither of the search engines suffers from stance bias. However, both
search engines suffer from ideological bias, both favouring one ideological
leaning to the other, which is more significant from the perspective of
polarisation in our society.


  We herein introduce a new method of interpretable clustering that uses
unsupervised binary trees. It is a three-stage procedure, the first stage of
which entails a series of recursive binary splits to reduce the heterogeneity
of the data within the new subsamples. During the second stage (pruning),
consideration is given to whether adjacent nodes can be aggregated. Finally,
during the third stage (joining), similar clusters are joined together, even if
they do not descend from the same node originally. Consistency results are
obtained, and the procedure is used on simulated and real data sets.


  Weyl fermions as emergent quasiparticles can arise in Weyl semimetals (WSMs)
in which the energy bands are nondegenerate, resulting from inversion or
time-reversal symmetry breaking. Nevertheless, experimental evidence for
magnetically induced WSMs is scarce. Here, using photoemission spectroscopy, we
observe that the degeneracy of Bloch bands is already lifted in the
paramagnetic phase of EuCd$_2$As$_2$. We attribute this effect to the itinerant
electrons experiencing quasistatic and quasi-long-range ferromagnetic
fluctuations. Moreover, the spin nondegenerate band structure harbors a pair of
ideal Weyl nodes near the Fermi level. Hence, we show that long-range magnetic
order and the spontaneous breaking of time-reversal symmetry are not an
essential requirement for WSM states in centrosymmetric systems, and that WSM
states can emerge in a wider range of condensed-matter systems than previously
thought.


  We present version 2.2 of the High Energy Jets (HEJ) Monte Carlo event
generator for hadronic scattering processes at high energies. The new version
adds support for two further processes of central phenomenological interest,
namely the production of a W boson pair with equal charge together with two or
more jets and the production of a Higgs boson with at least one jet.
Furthermore, a new prediction for charged lepton pair production with high jet
multiplicities is provided in the high-energy limit. The accuracy of HEJ 2.2
can be increased further through an enhanced interface to standard predictions
based on conventional perturbation theory. We describe all improvements and
provide extensive usage examples. HEJ 2.2 can be obtained from
https://hej.hepforge.org.


  A common thread in designing electrochemically-based renewable energy devices
comprises materials that exploit nano-scale morphologies, e.g.,
supercapacitors, batteries, fuel cells, and bulk heterojunction organic
photovoltaics. In these devices, however, Coulomb forces often influence the
fine nano-details of the morphological structure of active layers leading to a
notorious decrease in performance. By focusing on bulk heterojunction organic
photovoltaics as a case model, a self-consistent mean-field framework that
combines binary (bi-stable) and ternary (tri-stable) morphologies with
electrokinetics is presented and analyzed, i.e., undertaking the coupling
between the spatiotemporal evolution of the material and charge dynamics along
with charge transfer at the device electrodes. Particularly, it is shown that
tri-stable composition may stabilize stripe morphology that is ideal bulk
heterojuction. Moreover, since the results rely on generic principles they are
expected to be applicable to a broad range of electrically charged
amphiphilic-type mixtures, such as emulsions, polyelectrolytes, and ionic
liquids.


  We show that if the lepton flavor violating $\mu \rightarrow e \gamma$
process is observed in the MEG II experiment, the initial density of primordial
black holes (PBHs) can be constrained with the scotogenic dark matter. As a
benchmark case, if the PBH evaporation occurs in the radiation dominated era,
the initial density may be $2\times 10^{-17} \lesssim \beta \lesssim 3 \times
10^{-16}$ for $\mathcal{O}$ (TeV) scale dark sector in the scotogenic model
where $\beta=\rho_{\rm PBH}/\rho_{\rm rad}$ is the ratio of the PBH density
$\rho_{\rm PBH}$ to the radiation density $\rho_{\rm rad}$ at the time of PBH
formation. As an other benchmark case, if PBHs evaporate in the PBH dominated
era, the initial density may be $1 \times 10^{-8} \lesssim \beta \lesssim 3
\times 10^{-7}$ for $\mathcal{O}$ (GeV) scale dark matter with other
$\mathcal{O}$ (TeV) scale particles in the scotogenic model.


  The evolution of the photospheric magnetic field plays a key role in the
energy transport into the chromosphere and the corona. In active regions, newly
emerging magnetic flux interacts with the pre-existent magnetic field, which
can lead to reconnection events that convert magnetic energy to thermal energy.
We aim to study the heating caused by a strong reconnection event that was
triggered by magnetic flux cancellation. We use imaging-spectropolarimetric
data in the Fe I 6301A, Fe I 6302A, Ca II 8542A and Ca II K obtained with the
CRISP and CHROMIS instruments at the Swedish 1-m Solar Telescope. This data was
inverted using multi-atom, multi-line non-LTE inversions using the STiC code.
The inversion yielded a three-dimensional model of the reconnection event and
surrounding atmosphere, including temperature, velocity, microturbulence,
magnetic file configuration, and the radiative loss rate. The model atmosphere
shows the emergence of magnetic loops with a size of several arcsecs into a
pre-existing predominantly unipolar field. Where the reconnection region is
expected to be, we see an increase in the chromospheric temperature of roughly
2000 K as well as bidirectional flows of the order of 10 km s$^{-1}$ emanating
from the region. We see bright blobs of roughly 0.2 arcsec diameter in the Ca
II K moving at a plane-of-the-sky velocity of order 100 km s$^{-1}$ and a
blueshift of 100 km s$^{-1}$, which we interpret as plasmoids ejected from the
same region. This evidence is consistent with theoretical models of
reconnection and we thus conclude that reconnection is taking place. The
chromospheric radiative losses at the reconnection site in our inferred model
are as high as 160 kW m$^{-2}$, providing a quantitative constraint on
theoretical models that aim to simulate reconnection caused by flux emergence
in the chromosphere.


  The sensitivity to $B_s$ meson mixing phenomena can be significantly improved
by distinguishing the initial meson flavour. The flavour tagging techniques
used in the ATLAS measurement of the angular amplitudes contributing to $B_s
\rightarrow J/\psi\phi$ decays are presented using 4.9 fb$^{-1}$ of $pp$ data
at $\sqrt{s}$ = 7 TeV from 2011. The methods, their performance and calibration
on self-tagged $B^\pm \rightarrow J/\psi K^\pm$ data are shown.


  The existing state-of-the-art method for audio-visual conditioned video
prediction uses the latent codes of the audio-visual frames from a multimodal
stochastic network and a frame encoder to predict the next visual frame.
However, a direct inference of per-pixel intensity for the next visual frame is
extremely challenging because of the high-dimensional image space. To this end,
we decouple the audio-visual conditioned video prediction into motion and
appearance modeling. The multimodal motion estimation predicts future optical
flow based on the audio-motion correlation. The visual branch recalls from the
motion memory built from the audio features to enable better long term
prediction. We further propose context-aware refinement to address the
diminishing of the global appearance context in the long-term continuous
warping. The global appearance context is extracted by the context encoder and
manipulated by motion-conditioned affine transformation before fusion with
features of warped frames. Experimental results show that our method achieves
competitive results on existing benchmarks.


  An important problem in the implementation of Markov Chain Monte Carlo
algorithms is to determine the convergence time, or the number of iterations
before the chain is close to stationarity. For many Markov chains used in
practice this time is not known. Even in cases where the convergence time is
known to be polynomial, the theoretical bounds are often too crude to be
practical. Thus, practitioners like to carry out some form of statistical
analysis in order to assess convergence. This has led to the development of a
number of methods known as convergence diagnostics which attempt to diagnose
whether the Markov chain is far from stationarity. We study the problem of
testing convergence in the following settings and prove that the problem is
hard in a computational sense: Given a Markov chain that mixes rapidly, it is
hard for Statistical Zero Knowledge (SZK-hard) to distinguish whether starting
from a given state, the chain is close to stationarity by time t or far from
stationarity at time ct for a constant c. We show the problem is in AM
intersect coAM. Second, given a Markov chain that mixes rapidly it is coNP-hard
to distinguish whether it is close to stationarity by time t or far from
stationarity at time ct for a constant c. The problem is in coAM. Finally, it
is PSPACE-complete to distinguish whether the Markov chain is close to
stationarity by time t or far from being mixed at time ct for c at least 1.


  Nonlinear processes involving frequency-mixing of light fields set the basis
for ultrafast coherent spectroscopy of collective modes in solids. In certain
semimetals and semiconductors, generation of coherent phonon modes can occur by
a displacive force on the lattice at the difference-frequency mixing of a laser
pulse excitation on the electronic system. Here, as a low-frequency counterpart
of this process, we demonstrate that coherent phonon excitations can be induced
by the sum-frequency components of an intense terahertz light field, coupled to
intraband electronic transitions. This nonlinear process leads to
charge-coupled coherent dynamics of Raman-active phonon modes in the strongly
correlated metal V$_2$O$_3$. Our results show a new up-conversion pathway for
the optical control of Raman-active modes in solids mediated by
terahertz-driven electronic excitation.


  We construct some new classes of topological black hole solutions in the
context of mimetic gravity. We study the uncharged and charged black holes,
separately. In the absence of a potential for the mimetic field, our solutions
can address the flat rotation curves of spiral galaxies and alleviate the dark
matter problem without invoking any kind of particle dark matter. Thus, mimetic
gravity can provide a theoretical background for understanding flat galactic
rotation curves through modification of the Schwarzschild spacetime. We also
investigate the casual structure and physical properties of the solutions. The
presence of the mimetic field changes the asymptotic behaviour of the
spacetime. We observe that in the absence of a potential, our solutions are not
asymptotically flat, while, in the presence of a negative constant potential
for the mimetic field, the asymptotic behaviour of the solutions can be anti
de-Sitter (AdS). Finally, we explore the motion of massless and massive
particles and give a list of the types of orbits. We study the differences of
geodesic motion in Einstein gravity and in mimentic gravity. In contrast to
Einstein gravity, massive particles always move on bound orbits and cannot
escape the black hole in mimentic gravity. Furthermore, we find stable bound
orbits for massless particles.


  Singular Finsler metrics, such as Kropina metrics and $m$-Kropina metrics,
have a lot of applications in the real world. In this paper, we classify a
class of singular $(\alpha,\beta)$-metrics which are locally projectively flat
with constant flag curvature in dimension $n= 2$ and $n \ge 3$ respectively.
Further, we determine the local structure of $m$-Kropina metrics and
particularly Kropina metrics which are projectively flat with constant flag
curvature and prove that such metrics must be locally Minkowskian but are not
necessarily flat-parallel.


  In this work various methods and algorithms for face and eyes detection are
examined in order to decide which of them are applicable for use in a driver
fatigue monitoring system. In the case of face detection the standard
Viola-Jones face detector has shown best results, while the method of finding
the eye centers by means of gradients has proven to be most appropriate in the
case of eyes detection. The later method has also a potential for retrieving
behavioral parameters needed for estimation of the level of driver fatigue.
This possibility will be examined in future work.


  Various promising qubit concepts have been put forward recently based on
engineered superconductor (SC) subgap states like Andreev bound states,
Majorana zero modes or the Yu-Shiba-Rusinov (Shiba) states. The coupling of
these subgap states via a SC strongly depends on their spatial extension and is
an essential next step for future quantum technologies. Here we investigate the
spatial extension of a Shiba state in a semiconductor quantum dot coupled to a
SC for the first time. With detailed transport measurements and numerical
renormalization group calculations we find a remarkable more than 50 nm
extension of the zero energy Shiba state, much larger than the one observed in
very recent scanning tunneling microscopy (STM) measurements. Moreover, we
demonstrate that its spatial extension increases substantially in magnetic
field.


  We study the property of the field which is a mixing of two multi-mode
thermal fields. We accomplish a general theoretical analysis and show that the
mode of the mixed field, characterized by its intensity correlation function
$g^{(2)}$, is determined by the two-photon interference between the two
independent multi-mode thermal fields. Our analysis reveals that the mode
structures of the two thermal fields play an important role in the
interference. Comparing with $g^{(2)}$ for one of the individual field with
less average mode number, $g^{(2)}$ of the mixed field always decreases due to
the change of mode distribution, but the amount of drop depends on the relative
overlap between the mode structures of the two thermal fields and their
relative strength. Moreover, we verify the theoretical analysis by performing
the experiments when the modes of two multi-mode thermal fields are identical,
orthogonal and partially overlapped, respectively. The experimental results
agree with theoretical predictions. Our investigation is useful for analyzing
the signals carried by the intensity correlation of multi-mode thermal fields.


  We present a new definition of Euler Gamma function. From the complex
analysis and transalgebraic viewpoint, it is a natural characterization in the
space of finite order meromorphic functions. We show how the classical theory
and formulas develop naturally, and we discuss the relation with other
definitions. We show in a companion article, that this definition generalizes
to higher gamma functions and provides an unifying framework for their
definition which is more natural than the usual Bohr-Mollerup or Lerch
approaches.


  We propose to use image captions from the Web as a previously underutilized
resource for paraphrases (i.e., texts with the same "message") and to create
and analyze a corresponding dataset. When an image is reused on the Web, an
original caption is often assigned. We hypothesize that different captions for
the same image naturally form a set of mutual paraphrases. To demonstrate the
suitability of this idea, we analyze captions in the English Wikipedia, where
editors frequently relabel the same image for different articles. The paper
introduces the underlying mining technology, the resulting Wikipedia-IPC
dataset, and compares known paraphrase corpora with respect to their syntactic
and semantic paraphrase similarity to our new resource. In this context, we
introduce characteristic maps along the two similarity dimensions to identify
the style of paraphrases coming from different sources. An annotation study
demonstrates the high reliability of the algorithmically determined
characteristic maps.


  Overdamped Langevin dynamics are reversible stochastic differential equations
which are commonly used to sample probability measures in high-dimensional
spaces, such as the ones appearing in computational statistical physics and
Bayesian inference. By varying the diffusion coefficient, there are in fact
infinitely many overdamped Langevin dynamics which are reversible with respect
to the target probability measure at hand. This suggests to optimize the
diffusion coefficient in order to increase the convergence rate of the
dynamics, as measured by the spectral gap of the generator associated with the
stochastic differential equation. We analytically study this problem here,
obtaining in particular necessary conditions on the optimal diffusion
coefficient. We also derive an explicit expression of the optimal diffusion in
some appropriate homogenized limit. Numerical results, both relying on
discretizations of the spectral gap problem and Monte Carlo simulations of the
stochastic dynamics, demonstrate the increased quality of the sampling arising
from an appropriate choice of the diffusion coefficient.


  We update Jaffe's estimate of the strange isoscalar radius and magnetic
moment of the nucleon. We make use of a recent dispersion--theoretical fit to
the nucleon electromagnetic form factors and an improved description of
symmetry breaking in the vector nonet. We find $\mu_s = -0.24 \pm 0.03$~n.m.
and $r_s^2 = 0.21 \pm 0.03$~fm$^2$. The strange formfactor $F_2^s (t)$ follows
a dipole with a cut--off mass of 1.46~GeV, $F_2^s (t)= \mu_s (1-t/2.14 \, {\rm
GeV}^2 )^{-2}$. These numbers should be considered as upper limits on the
strange vector current matrix--elements in the nucleon.


  We discuss the effect of CP-violating $Zb\bar{b}$, $Zb\bar{b}G$ and
$Zb\bar{b}\gamma$ couplings on the width $\Gamma(Z\rightarrow b\bar bX)$. The
presence of such couplings leads in a natural way to an increase of this width
relative to the prediction of the standard model. Various strategies of a
direct search for such CP-violating couplings by using CP-odd observables are
outlined. The number of $Z$ bosons required to obtain significant information
on the couplings in this way is well within the reach of present LEP
experiments.


  In this paper we have enlightened the spin related issues of tilted Electron
vortex beams. We have shown that in the skyrmionic model of electron we can
have the spin Hall current considering the tilted type of electron vortex beam.
We have considered the monopole charge of the tilted vortex as time dependent
and through the time variation of the monopole charge we can explain the spin
Hall effect of electron vortex beams. Besides, with an external magnetic field
we can have a spin filter configuration.


  The growth of the supermassive black holes (BHs) that reside at the centres
of most galaxies is intertwined with the physical processes that drive the
formation of the galaxies themselves. The evolution of the relations between
the mass of the BH, m_BH, and the properties of its host therefore represent
crucial aspects of the galaxy formation process. We use a cosmological
simulation, as well as an analytical model, to investigate how and why the
scaling relations for BHs evolve with cosmic time. We find that a simulation
that reproduces the observed redshift zero relations between m_BH and the
properties of its host galaxy, as well as the thermodynamic profiles of the
intragroup medium, also reproduces the observed evolution in the ratio m_BH/m_s
for massive galaxies, although the evolution of the m_BH/sigma relation is in
apparent conflict with observations. The simulation predicts that the relations
between m_BH and the binding energies of both the galaxy and its dark matter
halo do not evolve, while the ratio m_BH/m_halo increases with redshift. The
simple, analytic model of Booth & Schaye (2010), in which the mass of the BH is
controlled by the gravitational binding energy of its host halo, quantitatively
reproduces the latter two results. Finally, we can explain the evolution in the
relations between m_BH and the mass and binding energy of the stellar component
of its host galaxy for massive galaxies (m_s~10^11 M_sun) at low redshift (z<1)
if these galaxies grow primarily through dry mergers.


  Hypercomputation or super-Turing computation is a ``computation'' that
transcends the limit imposed by Turing's model of computability. The field
still faces some basic questions, technical (can we mathematically and/or
physically build a hypercomputer?), cognitive (can hypercomputers realize the
AI dream?), philosophical (is thinking more than computing?). The aim of this
paper is to address the question: can we mathematically build a hypercomputer?
We will discuss the solutions of the Infinite Merchant Problem, a decision
problem equivalent to the Halting Problem, based on results obtained in
\cite{Coins,acp}. The accent will be on the new computational technique and
results rather than formal proofs.


  We study the (relative) SL(2,C) character varieties of the four-holed sphere
and the action of the mapping class group on it. We describe a domain of
discontinuity for this action, and, in the case of real characters, show that
this domain of discontinuity may be non-empty on the components where the
relative euler class is non-maximal.


  Sentence simplification aims to simplify the content and structure of complex
sentences, and thus make them easier to interpret for human readers, and easier
to process for downstream NLP applications. Recent advances in neural machine
translation have paved the way for novel approaches to the task. In this paper,
we adapt an architecture with augmented memory capacities called Neural
Semantic Encoders (Munkhdalai and Yu, 2017) for sentence simplification. Our
experiments demonstrate the effectiveness of our approach on different
simplification datasets, both in terms of automatic evaluation measures and
human judgments.


  Historical optical data are combined with more recent optical, extreme
ultraviolet, and X-ray data to update the spin ephemeris of the cataclysmic
variable EX Hya.


  We study classical Hamiltonian systems in which the intrinsic proper time
evolution parameter is related through a probability distribution to the
physical time, which is assumed to be discrete. In this way, a physical clock
with discrete states is introduced, which presently is still treated as
decoupled from the system. This is motivated by the recent discussion of
``timeless'' reparametrization invariant models, where discrete physical time
has been constructed based on quasi-local observables. Employing the
path-integral formulation of classical mechanics developed by Gozzi et al., we
show that these deterministic classical systems can be naturally described as
unitary quantum mechanical models. We derive the emergent quantum Hamiltonian
in terms of the underlying classical one. Such Hamiltonians typically need a
regularization - here performed by discretization - in order to arrive at
models with a stable groundstate in the continuum limit. This is demonstrated
in several examples, recovering and generalizing a model advanced by 't Hooft.


  Constructing large structures with robots is a challenging task with many
potential applications that requires mobile manipulation capabilities. We
present two systems for autonomous wall building that we developed for the
Mohamed Bin Zayed International Robotics Challenge 2020. Both systems
autonomously perceive their environment, find bricks, and build a predefined
wall structure. While the UGV uses a 3D LiDAR-based perception system which
measures brick poses with high precision, the UAV employs a real-time
camera-based system for visual servoing. We report results and insights from
our successful participation at the MBZIRC 2020 Finals, additional lab
experiments, and discuss the lessons learned from the competition.


  Mutually unbiased bases (MUBs) are a crucial ingredient for many protocols in
quantum information processing. Measurements performed in these bases are
unbiased to the maximally possible extent, which is used to prove randomness or
secrecy of measurement results. In this work we show that certain properties of
sets of MUBs crucially depend on their specific choice, including, somewhat
surprisingly, measurement outcome labelling. If measurements are chosen in a
coherent way, the secrecy of the result can be completely lost for specific
sets of MUB measurements, while partially retained for others. This can
potentially impact a broad spectrum of applications, where MUBs are utilized.


  We perform a multifractal analysis of the evolution of London's street
network from 1786 to 2010. First, we show that a single fractal dimension,
commonly associated with the morphological description of cities, does not su
ce to capture the dynamics of the system. Instead, for a proper
characterization of such a dynamics, the multifractal spectrum needs to be
considered. Our analysis reveals that London evolves from an inhomogeneous
fractal structure, that can be described in terms of a multifractal, to a
homogeneous one, that converges to monofractality. We argue that London's
multifractal to monofracal evolution might be a special outcome of the
constraint imposed on its growth by a green belt. Through a series of
simulations, we show that multifractal objects, constructed through di usion
limited aggregation, evolve towards monofractality if their growth is
constrained by a non-permeable boundary.


  In this study, we determine a violation of the Leggett-Garg inequalities due
to gravitational interaction in a hybrid system consisting of a harmonic
oscillator and a spatially localized superposed particle. The violation of the
Leggett-Garg inequalities is discussed using the two-time quasiprobability in
connection with the entanglement negativity generated by gravitational
interaction. It is demonstrated that the entanglement suppresses the violation
of the Leggett-Garg inequalities when one of the two times of the
quasiprobability t_1 is chosen as the initial time. Further, it is shown that
the Leggett-Garg inequalities are generally violated due to gravitational
interaction by properly choosing the configuration of the parameters, including
t_1 and t_2, which are the times of the two-time quasiprobability. The
feasibility of detecting violations of the Leggett-Garg inequalities in hybrid
systems is also discussed.


  The electromagnetic coupling axion-photon in a microwave cavity is revisited
with the Boundary Integral - Resonant Mode Expansion (BI-RME) 3D technique.
Such full-wave modal technique has been applied for the rigorous analysis of
the excitation of a microwave cavity with an axion field. In this scenario, the
electromagnetic field generated by the axion-photon coupling can be assumed to
be driven by equivalent electrical charge and current densities. These
densities have been inserted in the general BI-RME 3D equations, which express
the RF electromagnetic field existing within a cavity as an integral involving
the Dyadic Green functions of the cavity (under Coulomb gauge) as well as such
densities. This method is able to take into account any arbitrary spatial and
temporal variation of both magnitude and phase of the axion field. Next, we
have obtained a simple network driven by the axion current source, which
represents the coupling between the axion field and the resonant modes of the
cavity. With this approach, it is possible to calculate the extracted and
dissipated RF power as a function of frequency along a broad band and without
Cauchy-Lorentz approximations, obtaining the spectrum of the electromagnetic
field generated in the cavity, and dealing with modes relatively close to the
axion resonant mode. Moreover, with this technique we have a complete knowledge
of the signal extracted from the cavity, not only in magnitude but also in
phase. This can be an interesting issue for future analysis where the axion
phase is an important parameter.


  Micromagnetic tomography aims at reconstructing large numbers of individual
magnetizations of magnetic particles from combining high-resolution magnetic
scanning techniques with micro X-ray computed tomography (microCT). Previous
work demonstrated that dipole moments can be robustly inferred, and
mathematical analysis showed that the potential field of each particle is
uniquely determined. Here, we describe a mathematical procedure to recover
higher orders of the magnetic potential of the individual magnetic particles in
terms of their spherical harmonic expansions (SHE). We test this approach on
data from scanning superconducting quantum interference device microscopy and
microCT of a reference sample. For particles with high signal-to-noise ratio of
the magnetic scan we demonstrate that SHE up to order $n=3$ can be robustly
recovered. This additional level of detail restricts the possible internal
magnetization structures of the particles and provides valuable rock magnetic
information with respect to their stability and reliability as paleomagnetic
remanence carriers. Micromagnetic tomography therefore enables a new approach
for detailed rock magnetic studies on large ensembles of individual particles.


  Magnetar magnetospheres are strongly twisted, and are able to power sudden
energetic events through the rapid release of stored electromagnetic energy. In
this paper, we investigate twisted relativistic force-free axisymmetric
magnetospheres of rotating neutron stars. We obtain numerical solutions of such
configurations using the method of simultaneous relaxation for the magnetic
field inside and outside the light-cylinder. We introduce a toroidal magnetic
field in the region of closed field-lines that is associated with a poloidal
electric current distribution in that region, and explore various mathematical
expressions for that distribution. We find that, by increasing the twist, a
larger fraction of magnetic field-lines crosses the light-cylinder and opens up
to infinity, thus increasing the size of the polar caps and enhancing the
spin-down rate. We also find that, for moderately to strongly twisted
magnetospheres, the region of closed field-lines ends at some distance inside
the light-cylinder. We discuss the implications of these solutions on the
variation of magnetar spin-down rates, moding and nulling of pulsars, the
relation between the angular shear and the twist and the overall shape of the
magnetosphere.


  Recent research has highlighted the practical benefits of subjective
interestingness measures, which quantify the novelty or unexpectedness of a
pattern when contrasted with any prior information of the data miner
(Silberschatz and Tuzhilin, 1995; Geng and Hamilton, 2006). A key challenge
here is the formalization of this prior information in a way that lends itself
to the definition of an interestingness subjective measure that is both
meaningful and practical.
  In this paper, we outline a general strategy of how this could be achieved,
before working out the details for a use case that is important in its own
right.
  Our general strategy is based on considering prior information as constraints
on a probabilistic model representing the uncertainty about the data. More
specifically, we represent the prior information by the maximum entropy
(MaxEnt) distribution subject to these constraints. We briefly outline various
measures that could subsequently be used to contrast patterns with this MaxEnt
model, thus quantifying their subjective interestingness.


  A budget neutral strategy is proposed for NSF to lead the implementation of
multimessenger astronomy and astrophysics, as outlined in the Astro2010 Decadal
Survey. The emerging capabilities for simultaneous measurements of physical and
astronomical data through the different windows of electromagnetic, hadronic
and gravitational radiation processes call for a vigorous pursuit of new
synergies. The proposed approach is aimed at the formation of new
collaborations and multimessenger data-analysis, to transcend the scientific
inquiries made within a single window of observations. In view of budgetary
constraints, we propose to include the multimessenger dimension in the ranking
of proposals submitted under existing NSF programs.


  We consider independent anisotropic bond percolation on $\mathbb{Z}^d\times
\mathbb{Z}^s$ where edges parallel to $\mathbb{Z}^d$ are open with probability
$p<p_c(\mathbb{Z}^d)$ and edges parallel to $\mathbb{Z}^s$ are open with
probability $q$, independently of all others. We prove that percolation occurs
for $q\geq 8d^2(p_c(\mathbb{Z}^d)-p)$. This fact implies that the so-called
Dimensional Crossover critical exponent, if it exists, is greater than 1. In
particular, using known results, we conclude the proof that, for $d\geq 11$,
the crossover critical exponent exists and equals 1.


  In text mining, information retrieval, and machine learning, text documents
are commonly represented through variants of sparse Bag of Words (sBoW) vectors
(e.g. TF-IDF). Although simple and intuitive, sBoW style representations suffer
from their inherent over-sparsity and fail to capture word-level synonymy and
polysemy. Especially when labeled data is limited (e.g. in document
classification), or the text documents are short (e.g. emails or abstracts),
many features are rarely observed within the training corpus. This leads to
overfitting and reduced generalization accuracy. In this paper we propose Dense
Cohort of Terms (dCoT), an unsupervised algorithm to learn improved sBoW
document features. dCoT explicitly models absent words by removing and
reconstructing random sub-sets of words in the unlabeled corpus. With this
approach, dCoT learns to reconstruct frequent words from co-occurring
infrequent words and maps the high dimensional sparse sBoW vectors into a
low-dimensional dense representation. We show that the feature removal can be
marginalized out and that the reconstruction can be solved for in closed-form.
We demonstrate empirically, on several benchmark datasets, that dCoT features
significantly improve the classification accuracy across several document
classification tasks.


  Recommender systems have become ubiquitous in our digital lives, from
recommending products on e-commerce websites to suggesting movies and music on
streaming platforms. Existing recommendation datasets, such as Amazon Product
Reviews and MovieLens, greatly facilitated the research and development of
recommender systems in their respective domains. While the number of mobile
users and applications (aka apps) has increased exponentially over the past
decade, research in mobile app recommender systems has been significantly
constrained, primarily due to the lack of high-quality benchmark datasets, as
opposed to recommendations for products, movies, and news. To facilitate
research for app recommendation systems, we introduce a large-scale dataset,
called MobileRec. We constructed MobileRec from users' activity on the Google
play store. MobileRec contains 19.3 million user interactions (i.e., user
reviews on apps) with over 10K unique apps across 48 categories. MobileRec
records the sequential activity of a total of 0.7 million distinct users. Each
of these users has interacted with no fewer than five distinct apps, which
stands in contrast to previous datasets on mobile apps that recorded only a
single interaction per user. Furthermore, MobileRec presents users' ratings as
well as sentiments on installed apps, and each app contains rich metadata such
as app name, category, description, and overall rating, among others. We
demonstrate that MobileRec can serve as an excellent testbed for app
recommendation through a comparative study of several state-of-the-art
recommendation approaches. The quantitative results can act as a baseline for
other researchers to compare their results against. The MobileRec dataset is
available at https://huggingface.co/datasets/recmeapp/mobilerec.


  Instance shadow detection, crucial for applications such as photo editing and
light direction estimation, has undergone significant advancements in
predicting shadow instances, object instances, and their associations. The
extension of this task to videos presents challenges in annotating diverse
video data and addressing complexities arising from occlusion and temporary
disappearances within associations. In response to these challenges, we
introduce ViShadow, a semi-supervised video instance shadow detection framework
that leverages both labeled image data and unlabeled video data for training.
ViShadow features a two-stage training pipeline: the first stage, utilizing
labeled image data, identifies shadow and object instances through contrastive
learning for cross-frame pairing. The second stage employs unlabeled videos,
incorporating an associated cycle consistency loss to enhance tracking ability.
A retrieval mechanism is introduced to manage temporary disappearances,
ensuring tracking continuity. The SOBA-VID dataset, comprising unlabeled
training videos and labeled testing videos, along with the SOAP-VID metric, is
introduced for the quantitative evaluation of VISD solutions. The effectiveness
of ViShadow is further demonstrated through various video-level applications
such as video inpainting, instance cloning, shadow editing, and text-instructed
shadow-object manipulation.


  We discuss the shape of threshold signals in production cross sections of the
reaction e+ + e- --> D* + antiD*, at the opening of the D(s)* antiD(s)* and
Lambda(c)+ Lambda(c)- channels. Furthermore, evidence for the 3D, 5S, 4D, 6S,
5D, 7S, 6D, and 8S charmonium vector resonances is presented, on the basis of
data recently published by the BaBar Collaboration. Central masses and
resonance widths are estimated. Confirmation of these resonances would be a
huge step in lifting the precision level of hadron spectroscopy towards that of
atomic spectroscopy, with far-reaching consequences for theory.


  The paper presents many facets of medical imaging investigations radiological
risks. The total volume of prescribed medical investigations proves a serious
lack in monitoring and tracking of the cumulative radiation doses in many
health services. Modern radiological investigations equipment is continuously
reducing the total dose of radiation due to improved technologies, so a
decrease in per caput dose can be noticed, but the increasing number of
investigations has determined a net increase of the annual collective dose.
High doses of radiation are cumulated from Computed Tomography investigations.
An integrated system for radiation safety of the patients investigated by
radiological imaging methods, based on smart cards and Public Key
Infrastructure allow radiation absorbed dose data storage.


  Using the IRAM NOrthern Extended Millimeter Array (NOEMA), we conducted a
program to measure redshifts for 13 bright galaxies detected in the Herschel
Astrophysical Large Area Survey (H-ATLAS) with $S_{500{\mu}\rm m}\ge$80 mJy. We
report reliable spectroscopic redshifts for 12 individual sources, which are
derived from scans of the 3 and 2 mm bands, covering up to 31 GHz in each band,
and are based on the detection of at least two emission lines. The
spectroscopic redshifts are in the range $2.08<z<4.05$ with a median value of
$z=2.9\pm$0.6. The sources are unresolved or barely resolved on scales of 10
kpc. In one field, two galaxies with different redshifts were detected. In two
cases the sources are found to be binary galaxies with projected distances of
~140 kpc. The linewidths of the sources are large, with a mean value for the
full width at half maximum of 700$\pm$300 km/s and a median of 800 km/s. We
analyse the nature of the sources with currently available ancillary data to
determine if they are lensed or hyper-luminous $L_{\rm FIR} > 10^{13}\,L_\odot$
galaxies. We also present a reanalysis of the spectral energy distributions
including the continuum flux densities measured at 3 and 2 mm to derive the
overall properties of the sources. Future prospects based on these efficient
measurements of redshifts of high-z galaxies using NOEMA are outlined,
including a comprehensive survey of all the brightest Herschel galaxies.


  A comparative analysis of the Dirichlet and Neumann boundary conditions (BCs)
of the one-dimensional (1D) quantum well extracts similarities and differences
of the R\'{e}nyi $R(\alpha)$ as well as Tsallis $T(\alpha)$ entropies between
these two geometries. It is shown, in particular, that for either BC the
dependencies of the R\'{e}nyi position components on the parameter $\alpha$ are
the same for all orbitals but the lowest Neumann one for which the
corresponding functional $R$ is not influenced by the variation of $\alpha$.
Lower limit $\alpha_{TH}$ of the semi infinite range of the dimensionless
R\'{e}nyi/Tsallis coefficient where {\em momentum} entropies exist crucially
depends on the {\em position} BC and is equal to one quarter for the Dirichlet
requirement and one half for the Neumann one. At $\alpha$ approaching this
critical value, the corresponding momentum functionals do diverge. The gap
between the thresholds $\alpha_{TH}$ of the two BCs causes different behavior
of the R\'{e}nyi uncertainty relations as functions of $\alpha$. For both
configurations, the lowest-energy level at $\alpha=1/2$ does saturate either
type of the entropic inequality thus confirming an earlier surmise about it. It
is also conjectured that the threshold $\alpha_{TH}$ of one half is
characteristic of any 1D non-Dirichlet system. Other properties are discussed
and analyzed from the mathematical and physical points of view.


  For a graph $G = (V(G), E(G))$, let $i(G)$ be the number of isolated vertices
in $G$. The {\it isolated toughness} of $G$ is defined as $I(G) =
min\{|S|/i(G-S) : S\subseteq V(G), i(G-S)\geq 2\}$ if $G$ is not complete;
$I(G)=|V(G)|-1$ otherwise. In this paper, several sufficient conditions in
terms of isolated toughness are obtained for the existence of $[a, b]$-factors
avoiding given subgraphs, e.g., a set of vertices, a set of edges and a
matching, respectively.


  Superconducting quantum coherent circuits have opened up a novel area of
fundamental low-temperature science since they could potentially be the element
base for future quantum computers. Here we report a quasi-three-level coherent
system, the so-called superconducting qutrit, which has some advantages over a
two-level information cell (qubit), and is based on the qutrit readout circuit
intended to measure individually the states of each qubit in a quantum
computer. The designed and implemented radio-frequency superconducting qutrit
detector (rf SQUTRID) with atomic-size ScS-type contact utilizes the
coherent-state superposition in the three-well potential with energy splitting
Delta E_01/k_B=1.5 K at the 30th quantized energy level with good isolation
from the electromagnetic environment. The reason why large values of Delta E_01
(and thus using atomic-size Nb-Nb contact) are required is to ensure an
adiabatic limit for the quantum dynamics of magnetic flux in the rf SQUTRID.


  We present a phase-resolved ROSAT HRI X-ray light curve of the dwarf nova OY
Car in quiescence. The X-ray flux is eclipsed at the same time as the optical
eclipse of the primary, and the region of X -ray emission is comparable in size
to the white dwarf. We use subsequent optical observations to update the
orbital ephemeris of the system.


  We investigate the distortion of the Assouad dimension and (regularized)
spectrum of sets under planar quasiregular maps. While the respective results
for the Hausdorff and upper box-counting dimension follow immediately from
their quasiconformal counterparts by employing elementary properties of these
dimension notions (e.g. countable stability and Lipschitz stability), the
Assouad dimension and spectrum do not share such properties. We obtain upper
bounds on the Assouad dimension and spectrum of images of compact sets under
planar quasiregular maps by studying their behavior around their critical
points. As an application the invariance of porosity of compact subsets of the
plane under quasiregular maps is established.


  We extensively study BPS solutions of the low energy effective theory of
M5-brane in large C-field background. This provides us an opportunity to
explore the interactions turned on by C-field background through the
Nambu-Poisson structure. The BPS states considered in this paper include the
M-waves, the self-dual string (M2 ending on M5), tilted M5-brane, holomorphic
embedding of M5-brane and the intersection of two M5-branes along a 3-brane.


  The number of maximal abelian subgroups of a finite p-group is shown to be
congruent to 1 modulo p.


  Blockchain governance is a subject of ongoing research and an
interdisciplinary view of blockchain governance is vital to aid in further
research for establishing a formal governance framework for this nascent
technology. In this paper, the position of blockchain governance within the
hierarchy of Institutional governance is discussed. Blockchain governance is
analyzed from the perspective of IT governance using Nash equilibrium to
predict the outcome of different governance decisions. A payoff matrix for
blockchain governance is created and simulation of different strategy profiles
is accomplished for computation of all Nash equilibria. The paper elaborates
upon payoff matrices for different kinds of blockchain governance, which are
used in the proposition of novel mathematical formulae usable to predict the
best governance strategy that minimizes the occurrence of a hard fork as well
as predicts the behavior of the majority during protocol updates. The paper
also includes validation of the proposed formulae using real Ethereum data.


  We provide an ergodicity criterion for uniformly differentiable modulo $p$
functions on ${\mathbb Z}_p$ in regard to the minimal level of the reduced
functions by showing that ergodic conditions are explicitly found in terms of
the coefficients of Mahler or van der Put for each prime $p.$ To this end, it
is essential to give an alternative, natural proof of Memi$\acute{c}$'s result
regarding Mahler's coefficients estimation for uniformly differentiable modulo
$p$ functions on ${\mathbb Z}_p.$


  We consider a random, uniformly elliptic coefficient field $a$ on the lattice
$\mathbb{Z}^d$. The distribution $\langle \cdot \rangle$ of the coefficient
field is assumed to be stationary. Delmotte and Deuschel showed that the
gradient and second mixed derivative of the parabolic Green function $G(t,x,y)$
satisfy optimal annealed estimates which are $L^2$ resp. $L^1$ in probability,
i.e. they obtained bounds on $\langle |\nabla_x G(t,x,y)|^2
\rangle^{\frac{1}{2}}$ and $\langle |\nabla_x \nabla_y G(t,x,y)| \rangle$, see
T. Delmotte and J.-D. Deuschel: On estimating the derivatives of symmetric
diffusions in stationary random environments, with applications to the
$\nabla\phi$ interface model, Probab. Theory Relat. Fields 133 (2005),
358--390. In particular, the elliptic Green function $G(x,y)$ satisfies optimal
annealed bounds. In a recent work, the authors extended these elliptic bounds
to higher moments, i.e. $L^p$ in probability for all $p<\infty$, see D.
Marahrens and F. Otto: {Annealed estimates on the Green function},
arXiv:1304.4408 (2013). In this note, we present a new argument that relies
purely on elliptic theory to derive the elliptic estimates (see Proposition 1.2
below) for $\langle |\nabla_x G(x,y)|^2 \rangle^{\frac{1}{2}}$ and $\langle
|\nabla_x \nabla_y G(x,y)| \rangle$.


  Let $b$ be a positive integer such that $2 \leq b \leq 10$. In this study, we
find all Pell or Pell-Lucas numbers as concatenations of two repdigits in base
$b$. As a corollary, it is show that the largest Pell or Pell-Lucas numbers
which can be expressible as a concatenations of two repdigits in base $b$ are
$P_{11} = 5741$ and $Q_5 = 82$, respectively.


  The Fock-like representations of the Relative Parabose Set (\textsc{Rpbs})
algebra in a single parabosonic and a single parafermionic degree of freedom
are investigated. It is shown that there is an infinite family (parametrized by
the values of a positive integer $p$) of infinite dimensional, non-equivalent,
irreducible representations. For each one of them, explicit expressions are
computed for the action of the generators and they are shown to be ladder
operators (creation-annihilation operators) on the specified Fock-spaces. It is
proved that each one of these inf. dim. Fock-spaces is irreducible under the
action of the whole algebra or in other words that it is a simple module over
the \textsc{Rpbs} algebra. Finally, $(\mathbb{Z}_{2} \times
\mathbb{Z}_{2})$-gradings are introduced for both the algebra $P_{BF}^{(1,1)}$
and the Fock-spaces, the constructed representations are shown to be
$(\mathbb{Z}_{2} \times \mathbb{Z}_{2})$-graded, $P_{BF}^{(1,1)}$-modules and
the relation between our present approach and similar works in the literature
is briefly discussed.


  SUMMARY This work aims at quantifying the effect of inherent uncertainties
from cardiac output on the sensitivity of a human compliant arterial network
response based on stochastic simulations of a reduced-order pulse wave
propagation model. A simple pulsatile output form is utilized to reproduce the
most relevant cardiac features with a minimum number of parameters associated
with left ventricle dynamics. Another source of critical uncertainty is the
spatial heterogeneity of the aortic compliance which plays a key role in the
propagation and damping of pulse waves generated at each cardiac cycle. A
continuous representation of the aortic stiffness in the form of a generic
random field of prescribed spatial correlation is then considered. Resorting to
a stochastic sparse pseudospectral method, we investigate the spatial
sensitivity of the pulse pressure and waves reflection magnitude with respect
to the different model uncertainties. Results indicate that uncertainties
related to the shape and magnitude of the prescribed inlet flow in the proximal
aorta can lead to potent variation of both the mean value and standard
deviation of blood flow velocity and pressure dynamics due to the interaction
of different wave propagation and reflection features. These results have
potential physiological and pathological implications. They will provide some
guidance in clinical data acquisition and future coupling of arterial pulse
wave propagation reduced-order model with more complex beating heart models.


  N. Katz has shown that any irreducible representation of the Galois group of
F_q((t)) has unique extension to a special representation of the Galois group
of k(t) unramified outside 0 and infinity and tamely ramified at infinity. In
this paper we analyze the number of not necessarily special such extensions and
relate this question to a description of bases in irreducible representations
of multiplicative groups of division algebras.


  Nonorthogonal multiple access (NOMA) is a promising technology to meet the
demands of the next generation wireless networks on massive connectivity, high
throughput and reliability, improved fairness, and low latency. In this
context, code-domain NOMA which attempts to serve $K$ users in $M\leq K$
orthogonal resource blocks, using a pattern matrix, is of utmost interest.
However, extending the pattern matrix dimensions severely increases the
detection complexity and hampers on the significant advantages that can be
achieved using large pattern matrices. In this paper, we propose a novel
approach toward code-domain NOMA which factorizes the pattern matrix as the
Kronecker product of some other factor matrices each with a smaller dimension.
Therefore, both the pattern matrix design at the transmitter side and the mixed
symbols' detection at the receiver side can be performed over much smaller
dimensions and with a remarkably reduced complexity and latency. As a
consequence, the system can significantly be overloaded to effectively support
the requirements of the next generation wireless networks without any
considerable increase on the system complexity.


  The standard description of Fermi acceleration, developing in a class of
time-dependent billiards, is given in terms of a diffusion process taking place
in momentum space. Within this framework the evolution of the probability
density function (PDF) of the magnitude of particle velocities as a function of
the number of collisions $n$ is determined by the Fokker-Planck equation (FPE).
In the literature the FPE is constructed by identifying the transport
coefficients with the ensemble averages of the change of the magnitude of
particle velocity and its square in the course of one collision. Although this
treatment leads to the correct solution after a sufficiently large number of
collisions has been reached, the transient part of the evolution of the PDF is
not described. Moreover, in the case of the Fermi-Ulam model (FUM), if a
stadanrd simplification is employed, the solution of the FPE is even
inconsistent with the values of the transport coefficients used for its
derivation. The goal of our work is to provide a self-consistent methodology
for the treatment of Fermi acceleration in time-dependent billiards. The
proposed approach obviates any assumptions for the continuity of the random
process and the existence of the limits formally defining the transport
coefficients of the FPE. Specifically, we suggest, instead of the calculation
of ensemble averages, the derivation of the one-step transition probability
function and the use of the Chapman-Kolmogorov forward equation. This approach
is generic and can be applied to any time-dependent billiard for the treatment
of Fermi-acceleration. As a first step, we apply this methodology to the FUM,
being the archetype of time-dependent billiards to exhibit Fermi acceleration.