  Method comparison studies are essential for development in medical and
clinical fields. These studies often compare a cheaper, faster, or less
invasive measuring method with a widely used one to see if they have sufficient
agreement for interchangeable use. In the clinical and medical context, the
response measurement is usually impacted not only by the measuring method but
by the rater as well. This paper proposes a model-based approach to assess
agreement of two measuring methods for paired repeated binary measurements
under the scenario when the agreement between two measuring methods and the
agreement among raters are required to be studied in a unified framework. Based
upon the generalized linear mixed models (GLMM), the decision on the adequacy
of interchangeable use is made by testing the equality of fixed effects of
methods. Approaches for assessing method agreement, such as the Bland-Altman
diagram and Cohen's kappa, are also developed for repeated binary measurements
based upon the latent variables in GLMMs. We assess our novel model-based
approach by simulation studies and a real clinical research application, in
which patients are evaluated repeatedly for delirium with two validated
screening methods: the Confusion Assessment Method and the 3-Minute Diagnostic
Interview for Confusion Assessment Method. Both the simulation studies and the
real data analyses demonstrate that our new approach can effectively assess
method agreement.


  We study a new class of compact orientable manifolds, called big polygon
spaces. They are intersections of real quadrics and related to polygon spaces,
which appear as their fixed point set under a canonical torus action.
  What makes big polygon spaces interesting is that they exhibit remarkable new
features in equivariant cohomology: The Chang-Skjelbred sequence can be exact
for them and the equivariant Poincare pairing perfect although their
equivariant cohomology is never free as a module over the cohomology ring of
BT. More generally, big polygon spaces show that a certain bound on the syzygy
order of the equivariant cohomology of compact orientable T-manifolds obtained
by Allday, Puppe and the author is sharp.


  Recent results from the CLEO experiment on decays and partial widths of
various bottomonium and charmonium resonances are presented. New measurements
of the di-electron partial widths for the 3 bound-state Upsilons and the J/psi
are discussed. A determination of the total hadronic cross section for the
psi(3770) is made, which solves a 20-year-old puzzle. The Y(4260) state is
confirmed and its decay into 2 new modes is measured.


  We introduce a predictor-corrector discretisation scheme for the numerical
integration of a class of stochastic differential equations and prove that it
converges with weak order 1.0. The key feature of the new scheme is that it
builds up sequentially (and recursively) in the dimension of the state space of
the solution, hence making it suitable for approximations of high-dimensional
state space models. We show, using the stochastic Lorenz 96 system as a test
model, that the proposed method can operate with larger time steps than the
standard Euler-Maruyama scheme and, therefore, generate valid approximations
with a smaller computational cost. We also introduce the theoretical analysis
of the error incurred by the new predictor-corrector scheme when used as a
building block for discrete-time Bayesian filters for continuous-time systems.
Finally, we assess the performance of several ensemble Kalman filters that
incorporate the proposed sequential predictor-corrector Euler scheme and the
standard Euler-Maruyama method. The numerical experiments show that the filters
employing the new sequential scheme can operate with larger time steps, smaller
Monte Carlo ensembles and noisier systems.


  We derived atmospheric parameters and elemental abundances of Fe, O and Na
for about 120 red giant stars in the Galactic globular cluster NGC 2808. Our
results are based on the analysis of medium-high resolution (R=22000-24000)
GIRAFFE spectra acquired with the FLAMES spectrograph at VLT-UT2 as a part of a
project aimed at studying the Na-O anticorrelation as a function of physical
parameters in globular clusters. We present here the anticorrelation of Na and
O abundances in NGC 2808, and we discuss the distribution function of stars
along this relation. Besides a bulk of O-normal stars, with composition typical
of field halo stars, NGC 2808 seems to host two other groups of O-poor and
super O-poor stars. In this regard, NGC 2808 is similar to M 13, the template
cluster for the Na-O anticorrelation. However, at variance with M 13, most
stars in NGC 2808 are O-rich. This might be related to the horizontal branch
morphologies which are very different in these two clusters. The average
metallicity we found for NGC 2808 is [Fe/H]=-1.10 (rms=0.065 dex, from 123
stars). We also found some evidence of a small intrinsic spread in metallicity,
but more definitive conclusions are hampered by the presence of a small
differential reddening.


  Learning conditional densities and identifying factors that influence the
entire distribution are vital tasks in data-driven applications. Conventional
approaches work mostly with summary statistics, and are hence inadequate for a
comprehensive investigation. Recently, there have been developments on
functional regression methods to model density curves as functional outcomes. A
major challenge for developing such models lies in the inherent constraint of
non-negativity and unit integral for the functional space of density outcomes.
To overcome this fundamental issue, we propose Wasserstein Distributional
Learning (WDL), a flexible density-on-scalar regression modeling framework that
starts with the Wasserstein distance $W_2$ as a proper metric for the space of
density outcomes. We then introduce a heterogeneous and flexible class of
Semi-parametric Conditional Gaussian Mixture Models (SCGMM) as the model class
$\mathfrak{F} \otimes \mathcal{T}$. The resulting metric space $(\mathfrak{F}
\otimes \mathcal{T}, W_2)$ satisfies the required constraints and offers a
dense and closed functional subspace. For fitting the proposed model, we
further develop an efficient algorithm based on Majorization-Minimization
optimization with boosted trees. Compared with methods in the previous
literature, WDL better characterizes and uncovers the nonlinear dependence of
the conditional densities, and their derived summary statistics. We demonstrate
the effectiveness of the WDL framework through simulations and real-world
applications.


  In this paper, we study intersecting sets in primitive and quasiprimitive
permutation groups. Let $G \leqslant \mathrm{Sym}(\Omega)$ be a transitive
permutation group, and ${S}$ an intersecting set. Previous results show that if
$G$ is either 2-transitive or a Frobenius group, then
$|{S}|\leqslant|G_{\omega}|$ (for some $\omega \in \Omega$). Furthermore, for
some 2-transitive groups, $|{S}|=|G_{\omega}|$ if and only if ${S}$ is a coset
of a stabilizer. In this paper, we prove that these statements are far from the
truth for general transitive groups. In particular, we show that in the case of
primitive groups, there is even no absolute constant $c$ such that
$|{S}|\leqslant c|G_\omega|$. In the case $G$ is a primitive permutation group
isomorphic to $\mathrm{PSL(2,p)}$, we characterize the subgroups of $G$ which
are intersecting sets. We also show that if $G \leqslant \mathrm{Sym}(\Omega)$
is a permutation group of prime power degree, then for any intersecting set
$S$, we have $|S|\leq |G_{\omega}|$ (for some $\omega \in \Omega$). This proves
a part of a conjecture in \cite{MRS}.


  The nature of long-range interactions between dust grains in plasma is
discussed. The dust grain interaction potential within a cell model of dusty
plasma is introduced. The attractive part of intergrain potential is described
by multipole interaction between two electro-neutral cells. This allowed us to
draw an analogy with molecular liquids where the attraction between molecules
is determined by dispersion forces. The main ideas of the fluctuation theory
for electrostatic field in a cell model are formulated, and the dominating
contribution to the attractive part of intergrain potential is obtained.


  Any 3D tracking algorithm has to deal with occlusions: multiple targets get
so close to each other that the loss of their identities becomes likely. In the
best case scenario, trajectories are interrupted, thus curbing the completeness
of the data-set; in the worse case scenario, identity switches arise,
potentially affecting in severe ways the very quality of the data. Here, we
present a novel tracking method that addresses the problem of occlusions within
large groups of featureless objects by means of three steps: i) it represents
each target as a cloud of points in 3D; ii) once a 3D cluster corresponding to
an occlusion occurs, it defines a partitioning problem by introducing a cost
function that uses both attractive and repulsive spatio-temporal proximity
links; iii) it minimizes the cost function through a semi-definite optimization
technique specifically designed to cope with link frustration. The algorithm is
independent of the specific experimental method used to collect the data. By
performing tests on public data-sets, we show that the new algorithm produces a
significant improvement over the state-of-the-art tracking methods, both by
reducing the number of identity switches and by increasing the accuracy of the
actual positions of the targets in real space.


  Blow-up in second and fourth order semi-linear parabolic partial differential
equations (PDEs) is considered in bounded regions of one, two and three spatial
dimensions with uniform initial data. A phenomenon whereby singularities form
at multiple points simultaneously is exhibited and explained by means of a
singular perturbation theory. In the second order case we pre- dict that points
furthest from the boundary are selected by the dynamics of the PDE for
singularity. In the fourth order case, singularities can form simultaneously at
multiple locations, even in one spatial dimension. In two spatial dimensions,
the singular perturbation theory reveals that the set of possible singularity
points depends subtly on the geometry of the domain and the equation
parameters. In three spatial dimensions, preliminary numerical simulations
indicate that the multiplicity of singularities can be even more complex. For
the aforementioned scenarios, the analysis highlights the dichotomy of
behaviors exhibited between the second and fourth order cases.


  In this paper, we demonstrate that at leading order in post Minkowskian (PM)
expansion, the stress-energy tensor of Kerr-Newman can be recovered to all
orders in spin from three sets of minimal coupling: the electric and
gravitational minimal coupling for higher-spin particles, and the "minimal
coupling" for massive spin-2 decay. These couplings are uniquely defined from
kinematic consideration alone. This is shown by extracting the classical piece
of the one-loop stress-energy tensor form factor, which we provide a basis that
is valid to all orders in spin. The 1 PM stress tensor, and the metric in the
harmonic gauge, is then recovered from the classical spin limit of the form
factor.


  A method has been proposed for the determination of $\gamma$ to $\pi^0$ ratio
in high energy pp and nucleus-nucleus collisions at large transverse momentum
($p_T$). In photon measuring device, it is proposed that shower shape analysis
is made to select only cases with wide showers.
  These candidates come mostly from $\pi^0$. Correlation is measured between
those photon candidates as trigger particles and associated charged particles
above selected $p_T$.
  The ratio of yields of near and far angle correlation peaks for $\pi^0$
events is compared with correlation peaks from other set of events where
trigger particle contains photons for direct-photon jets alongwith $\pi^0$.
  The comparative study in reduction of yield of near angle peak is used to
extract photon fraction.


  We present the preliminary results of a two phases description of the ISM
suited to numerical N Body T-SPH models of galaxy formation and evolution.


  Evanescent wave amplification has been predicted under the ideal condition n
= -1 + i 0 precisely, in the absence of retardation effects, but is difficult
to observe in practice because current metamaterial designs suffer from high
losses. We present results on a new metamaterial design that employs
superconducting Niobium metals and low-loss dielectric materials to reduce the
losses. We present transmission data on a wire medium, a split-ring resonator
medium, and a combination of the two at temperatures between 4.2 K and room
temperature. Evidence of negative effective permittivity, permeability, and a
negative effective index passband are seen in the superconducting state between
50 MHz and 18 GHz. We find a dielectric loss of \epsilon_{eff,2} = 3 x 10^{-3}
in a superconducting wire array at 10.75 GHz.


  We performed spin-polarized scanning tunneling spectroscopy on
biatomic-layer-high Co nanoislands grown on Cu(111) in magnetic fields oriented
normal to the sample surface, with Fe-coated W tips. Increasing the temperature
from 10 to 30 K, we observe a reduced slope of the differential conductance
around zero field. A quantitative analysis of the field- and
temperature-dependent differential conductance data in the framework of
superparamagnetism as described by a Langevin function gives an excellent
description of the experimental results. The analysis suggests that a Fe
nano-apex at the W tip, which is composed of 220-300 Fe atoms, determines the
magnetic response of the tip.


  For small number of equations, systems of linear (and sometimes nonlinear)
equations can be solved by simple classical techniques. However, for large
number of systems of linear (or nonlinear) equations, solutions using classical
method become arduous. On the other hand evolutionary algorithms have mostly
been used to solve various optimization and learning problems. Recently,
hybridization of evolutionary algorithm with classical Gauss-Seidel based
Successive Over Relaxation (SOR) method has successfully been used to solve
large number of linear equations; where a uniform adaptation (UA) technique of
relaxation factor is used. In this paper, a new hybrid algorithm is proposed in
which a time-variant adaptation (TVA) technique of relaxation factor is used
instead of uniform adaptation technique to solve large number of linear
equations. The convergence theorems of the proposed algorithms are proved
theoretically. And the performance of the proposed TVA-based algorithm is
compared with the UA-based hybrid algorithm in the experimental domain. The
proposed algorithm outperforms the hybrid one in terms of efficiency.


  We investigate course registration data of 18 semesters at a Korean
University to portray the time evolution of students' positions in the network
of fellow students. Apart from being a study of the social positions of
students, the present work is also an example of how large-scale, time
resolved, affiliation networks can be analyzed. For example we discuss the
proper definitions of weights, and propose a redefined weighted clustering
coefficient. Among other things, we find that the students enter the network at
the center and are gradually diffusing towards the periphery. On the other
hand, the ties to the classmates of the first semester (still present at the
university) will, on average, become stronger as time progresses.


  We review recent results obtained in the physics of the thermal Casimir force
acting between two dielectrics, dielectric and metal, and between metal and
semiconductor. The detailed derivation for the low-temperature behavior of the
Casimir free energy, pressure and entropy in the configuration of two real
dielectric plates is presented. For dielectrics with finite static dielectric
permittivity it is shown that the Nernst heat theorem is satisfied. Hence, the
Lifshitz theory of the van der Waals and Casimir forces is demonstrated to be
consistent with thermodynamics. The nonzero dc conductivity of dielectric
plates is proved to lead to a violation of the Nernst heat theorem and, thus,
is not related to the phenomenon of dispersion forces. The low-temperature
asymptotics of the Casimir free energy, pressure and entropy are derived also
in the configuration of one metal and one dielectric plate. The results are
shown to be consistent with thermodynamics if the dielectric plate possesses a
finite static dielectric permittivity. If the dc conductivity of a dielectric
plate is taken into account this results in the violation of the Nernst heat
theorem. We discuss both the experimental and theoretical results related to
the Casimir interaction between metal and semiconductor with different charge
carrier density. Discussions in the literature on the possible influence of
spatial dispersion on the thermal Casimir force are analyzed. In conclusion,
the conventional Lifshitz theory taking into account only the frequency
dispersion remains the reliable foundation for the interpretation of all
present experiments.


  Water collection from natural and industrial fogs has recently been viewed as
a viable freshwater source. An interesting outgrowth of the relevant research
as focused on arresting of the drift losses (un-evaporated and re-condensed
water droplets present in the exhaust plume from industrial cooling towers.
Such exploits in fog collection have implemented metal and polyester meshes as
fog water collectors (FWC). Fog droplets impinge and deposit on mesh fibers.
They coalesce with previously deposited liquid to evolve as larger drops before
detaching from the fibers under their own weight, an event largely dependent on
the mesh fiber wettability, diameter and its arrangement relative to the fog
flow. To better estimate drainage and hence collection from these fibers, the
study, focuses on droplet detachment from differently wetted horizontally
positioned cylindrical fibers of various diameters, placed orthogonally in the
path of an oncoming fog. Droplet detachment volume is found to increase with
fiber diameter and fiber surface wettability. Interestingly, in a typical
fogging condition, the detachment volume is also found to exhibit a
time-dependent behaviour, altering the droplet detachment criteria otherwise
predicted from emulation. Our current study sheds light on this unexplored
phenomenon.


  Deep learning has gained tremendous success and great popularity in the past
few years. However, deep learning systems are suffering several inherent
weaknesses, which can threaten the security of learning models. Deep learning's
wide use further magnifies the impact and consequences. To this end, lots of
research has been conducted with the purpose of exhaustively identifying
intrinsic weaknesses and subsequently proposing feasible mitigation. Yet few
are clear about how these weaknesses are incurred and how effective these
attack approaches are in assaulting deep learning. In order to unveil the
security weaknesses and aid in the development of a robust deep learning
system, we undertake an investigation on attacks towards deep learning, and
analyze these attacks to conclude some findings in multiple views. In
particular, we focus on four types of attacks associated with security threats
of deep learning: model extraction attack, model inversion attack, poisoning
attack and adversarial attack. For each type of attack, we construct its
essential workflow as well as adversary capabilities and attack goals. Pivot
metrics are devised for comparing the attack approaches, by which we perform
quantitative and qualitative analyses. From the analysis, we have identified
significant and indispensable factors in an attack vector, e.g., how to reduce
queries to target models, what distance should be used for measuring
perturbation. We shed light on 18 findings covering these approaches' merits
and demerits, success probability, deployment complexity and prospects.
Moreover, we discuss other potential security weaknesses and possible
mitigation which can inspire relevant research in this area.


  We study the instanton effects of the ABJM partition function using the Fermi
gas formalism. We compute the exact values of the partition function at the
Chern-Simons levels k=1,2,3,4,6 up to N=44,20,18,16,14 respectively, and
extract non-perturbative corrections from these exact results. Fitting the
resulting non-perturbative corrections by their expected forms from the Fermi
gas, we determine unknown parameters in them. After separating the oscillating
behavior of the grand potential, which originates in the periodicity of the
grand partition function, and the worldsheet instanton contribution, which is
computed from the topological string theory, we succeed in proposing an
analytical expression for the leading D2-instanton correction. Just as the
perturbative result, the instanton corrections to the partition function are
expressed in terms of the Airy function.


  In this article the stability of the Standard Model (SM) vacuum in the
presence of radiative corrections and for a Higgs boson with a mass in the
vicinity of 125 GeV is discussed. The central piece in this discussion will be
the Higgs self-interaction $\lambda$ and its evolution with the energy scale of
a given physical process. This is described by the $\beta$-function to which we
recently computed analytically the dominant three-loop contributions. These are
mainly the QCD and top-Yukawa corrections as well as the contributions from the
Higgs self-interaction itself. We will see that for a Higgs boson with a mass
of about 125 GeV the question whether the SM vacuum is stable and therefore
whether the SM could be valid up to Planck scale cannot be answered with
certainty due to large experimental uncertainties, mainly in the top quark
mass.


  The Maximum Entropy Theory of Ecology (METE) predicts a universal
species-area relationship (SAR) that can be fully characterized using only the
total abundance (N) and species richness (S) at a single spatial scale. This
theory has shown promise for characterizing scale dependence in the SAR.
However, there are currently four different approaches to applying METE to
predict the SAR and it is unclear which approach should be used due to a lack
of empirical evaluation. Specifically, METE can be applied recursively or a
non-recursively and can use either a theoretical or observed species-abundance
distribution (SAD). We compared the four different combinations of approaches
using empirical data from 16 datasets containing over 1000 species and 300,000
individual trees and herbs. In general, METE accurately downscaled the SAR
(R^2> 0.94), but the recursive approach consistently under-predicted richness,
and METEs accuracy did not depend strongly on using the observed or predicted
SAD. This suggests that best approach to scaling diversity using METE is to use
a combination of non-recursive scaling and the theoretical abundance
distribution, which allows predictions to be made across a broad range of
spatial scales with only knowledge of the species richness and total abundance
at a single scale.


  Automating molecular design using deep reinforcement learning (RL) holds the
promise of accelerating the discovery of new chemical compounds. Existing
approaches work with molecular graphs and thus ignore the location of atoms in
space, which restricts them to 1) generating single organic molecules and 2)
heuristic reward functions. To address this, we present a novel RL formulation
for molecular design in Cartesian coordinates, thereby extending the class of
molecules that can be built. Our reward function is directly based on
fundamental physical properties such as the energy, which we approximate via
fast quantum-chemical methods. To enable progress towards de-novo molecular
design, we introduce MolGym, an RL environment comprising several challenging
molecular design tasks along with baselines. In our experiments, we show that
our agent can efficiently learn to solve these tasks from scratch by working in
a translation and rotation invariant state-action space.


  We study the decay properties of a heavy-light meson. We reformulate the
decay amplitudes for the heavy-light systems and find a new way to calculate
decay rates. Applying this formulation, we find a new sum rule for the
radiative decays of one heavy-light meson into another, $H_1\to H_2+\gamma$
with various combinations of $H_i$.


  We extend the framework of efficient coding, which has been used to model the
development of sensory processing in isolation, to model the development of the
perception/action cycle. Our extension combines sparse coding and reinforcement
learning so that sensory processing and behavior co-develop to optimize a
shared intrinsic motivational signal: the fidelity of the neural encoding of
the sensory input under resource constraints. Applying this framework to a
model system consisting of an active eye behaving in a time varying
environment, we find that this generic principle leads to the simultaneous
development of both smooth pursuit behavior and model neurons whose properties
are similar to those of primary visual cortical neurons selective for different
directions of visual motion. We suggest that this general principle may form
the basis for a unified and integrated explanation of many perception/action
loops.


  We search for high-redshift dropout galaxies behind the Hubble Frontier
Fields (HFF) galaxy cluster MACS J1149.5+2223, a powerful cosmic lens that has
revealed a number of unique objects in its field. Using the deep images from
the Hubble and Spitzer space telescopes, we find 11 galaxies at z>7 in the MACS
J1149.5+2223 cluster field, and 11 in its parallel field. The high-redshift
nature of the bright z~9.6 galaxy MACS1149-JD, previously reported by Zheng et
al., is further supported by non-detection in the extremely deep optical images
from the HFF campaign. With the new photometry, the best photometric redshift
solution for MACS1149-JD reduces slightly to z=9.44 +/- 0.12. The young galaxy
has an estimated stellar mass of (7 +/- 2)X10E8 Msun, and was formed at z=13.2
+1.9-1.6 when the universe was ~300 Myr old. Data available for the first four
HFF clusters have already enabled us to find faint galaxies to an intrinsic
magnitude of M(UV) ~ -15.5, approximately a factor of ten deeper than the
parallel fields.


  This paper presents a new method for dynamic texture recognition based on
spatiotemporal Gabor filters. Dynamic textures have emerged as a new field of
investigation that extends the concept of self-similarity of texture image to
the spatiotemporal domain. To model a dynamic texture, we convolve the sequence
of images to a bank of spatiotemporal Gabor filters. For each response, a
feature vector is built by calculating the energy statistic. As far as the
authors know, this paper is the first to report an effective method for dynamic
texture recognition using spatiotemporal Gabor filters. We evaluate the
proposed method on two challenging databases and the experimental results
indicate that the proposed method is a robust approach for dynamic texture
recognition.


  We briefly survey open questions in cosmology that either have been or could
potentially be addressed with the help of the causal set theory approach to
quantum gravity. Our discussion includes topics ranging from dark matter and
dark energy to primordial quantum fluctuations and horizon entropy. By putting
together all in one place these cosmologically relevant directions of work
within causal set theory, we hope to impart a bird's-eye view of this important
research theme.


  Quenching solutions to a Kawarada problem with a Caputo time-fractional
derivative and a fractional Laplacian are considered. The solutions to such
problems may only exist locally in time when quenching occurs. Quenching and
non-quenching solutions are shown to remain positive and be monotonically
increasing in time under minor restrictions. Conditions for quenching to occur
are demonstrated and shown to depend on the domain size.


  We use the Calogero equation to illustrate the following two aspects of the
Painleve analysis of nonlinear PDEs. First, if a nonlinear equation passes the
Painleve test for integrability, the singular expansions of its solutions
around characteristic hypersurfaces can be neither single-valued functions of
independent variables nor single-valued functionals of data. Second, if the
truncation of singular expansions of solutions is consistent, the truncation
not necessarily leads to the simplest, or elementary, auto-Backlund
transformation related to the Lax pair.


  In recent years there has been a major interest in developing all solid state
batteries, for the sake of safety (issues due to toxic and flammable organic
liquid electrolytes are well known) as well as of high energy density
\cite{SCHNELL2018160,Zheng2018}. Side by side to experimental investigations,
computational simulations \cite{GrazioliEtAlCM2016} unveil the several physics
that interconnect at different scales \cite{LiMonroeARCBM2020} during battery
operations. %Several advanced mathematical models have therefore been published
\cite{bistriM2020}. We propose herein a new advanced model, which is multiscale
compatible and fully three dimensional in nature. Furthermore, we review some
classical or inspiring models, highlighting the conceptual evolutions that are
ultimately collected in our work. The model is validated against experimental
evidences of a Li/LiPON/LiCoO$_2$ thin film battery published in
\cite{Danilovetal2011}.


  We extend the recently introduced genetic column generation algorithm for
high-dimensional multi-marginal optimal transport from symmetric to general
problems. We use the algorithm to calculate accurate mesh-free Wasserstein
barycenters and cubic Wasserstein splines.


  The space representations of linear canonical transformations were studied by
Moshinsky and Quesne in 1972. For a few decades, the bilinear hamiltonian
remained as the only exactly solvable representative for such problems. In this
work we show that the Mello-Moshinsky equations can be solved exactly for a
class of problems with discrete symmetry, leading to exact propagators for
Wannier-Stark ladders in one and two dimensional crystals. We give a detailed
study for a particle in a triangular lattice under the influence of a
time-dependent electric field. A more general set of Mello-Moshinsky equations
for arbitrary lattices is presented.


  We compute to all loop orders correlation function of four heavy BPS
operators in $\mathcal{N}$= 4 SYM with special polarisations considered
recently by Frank Coronado. Our main result is an expression for the octagon
form factor as determinant of a semi-infinite matrix. We find that at weak
coupling the entries of this matrix are linear combinations of ladder functions
with simple rational coefficients and give the full perturbative expansion of
the octagon.


  Earthshine is sunlight that has been reflected from the dayside Earth onto
the dark side of the Moon and back again to Earth. In recent times, there has
been renewed interest in ground-based visible and near-infrared measurements of
earthshine as a proxy for exoplanet observations. Observations of earthshine
allow us to explore and characterize the globally integrated photometric,
spectral and polarimetric features of the Earth, and to extract precise
information on the distinctive characteristics of our planet, and life in
particular. They also allow us to quantify how this feature changes with time
and orbital configuration. Here we present a brief review of the main
earthshine observations and results.


  We propose a novel semi-supervised, Multi-Level Sequential Generative
Adversarial Network (MLS-GAN) architecture for group activity recognition. In
contrast to previous works which utilise manually annotated individual human
action predictions, we allow the models to learn it's own internal
representations to discover pertinent sub-activities that aid the final group
activity recognition task. The generator is fed with person-level and
scene-level features that are mapped temporally through LSTM networks.
Action-based feature fusion is performed through novel gated fusion units that
are able to consider long-term dependencies, exploring the relationships among
all individual actions, to learn an intermediate representation or `action
code' for the current group activity. The network achieves its semi-supervised
behaviour by allowing it to perform group action classification together with
the adversarial real/fake validation. We perform extensive evaluations on
different architectural variants to demonstrate the importance of the proposed
architecture. Furthermore, we show that utilising both person-level and
scene-level features facilitates the group activity prediction better than
using only person-level features. Our proposed architecture outperforms current
state-of-the-art results for sports and pedestrian based classification tasks
on Volleyball and Collective Activity datasets, showing it's flexible nature
for effective learning of group activities.


  Today, users are reading the news through social platforms. These platforms
are built to facilitate crowd engagement, but not necessarily disseminate
useful news to inform the masses. Hence, the news that is highly engaged with
may not be the news that best informs. While predicting news popularity has
been well studied, it has not been studied in the context of crowd
manipulations. In this paper, we provide some preliminary results to a longer
term project on crowd and platform manipulations of news and news popularity.
In particular, we choose to study known features for predicting news popularity
and how those features may change on reddit.com, a social platform used
commonly for news aggregation. Along with this, we explore ways in which users
can alter the perception of news through changing the title of an article. We
find that news on reddit is predictable using previously studied sentiment and
content features and that posts with titles changed by reddit users tend to be
more popular than posts with the original article title.


  Recently a new phenomenological Hamiltonian has been proposed to describe the
superconducting cuprates. This so-called Gossamer Hamiltonian is an apt model
for a superconductor with strong on-site Coulomb repulsion betweenthe
electrons. It is shown that as one approaches half-filling the Gossamer
superconductor, and hence the superconducting state, with strong repulsion is
unstable toward an antiferromagnetic insulator an can undergo a quantum phase
transition to such an insulator if one increases the on-site Coulomb repulsion.


  Let $\mathbb D=G/K$ be a complex bounded symmetric domain of tube type in a
Jordan algebra $V_{\mathbb C}$, and let $D=H/L =\mathbb D\cap V$ be its real
form in a Jordan algebra $V\subset V_{\mathbb C}$. The analytic continuation of
the holomorphic discrete series on $\mathbb D$ forms a family of interesting
representations of $G$. We consider the restriction on $D$ of the scalar
holomorphic representations of $G$, as a representation of $H$. The unitary
part of the restriction map gives then a generalization of the Segal-Bargmann
transform. The group $L$ is a spherical subgroup of $K$ and we find a canonical
basis of $L$-invariant polynomials in components of the Schmid decomposition
and we express them in terms of the Jack symmetric polynomials. We prove that
the Segal-Bargmann transform of those $L$-invariant polynomials are, under the
spherical transform on $D$, multi-variable Wilson type polynomials and we give
a simple alternative proof of their orthogonality relation. We find the
expansion of the spherical functions on $D$, when extended to a neighborhood in
$\mathbb D$, in terms of the $L$-spherical holomorphic polynomials on $\mathbb
D$, the coefficients being the Wilson polynomials.


  The acceleration of CNNs has gained increasing atten-tion since their success
in computer vision. With the heterogeneous functional layers that cannot be
pro-cessed by the accelerators proposed for convolution layers only, modern
end-to-end CNN acceleration so-lutions either transform the diverse computation
into matrix/vector arithmetic, which loses data reuse op-portunities in
convolution, or introduce dedicated functional unit to each kind of layer,
which results in underutilization and high update expense. To enhance the
whole-life cost efficiency, we need an acceleration solution that is efficient
in processing CNN layers and has the generality to apply to all kinds of
existing and emerging layers. To this end, we pro-pose GCONV Chain, a method to
convert the entire CNN computation into a chain of standard general
convolutions (GCONV) that can be efficiently pro-cessed by the existing CNN
accelerators. This paper comprehensively analyzes the GCONV Chain model and
proposes a full-stack implementation to support GCONV Chain. On one hand, the
results on seven var-ious CNNs demonstrate that GCONV Chain improves the
performance and energy efficiency of existing CNN accelerators by an average of
3.4x and 3.2x re-spectively. On the other hand, we show that GCONV Chain
provides low whole-life costs for CNN accelera-tion, including both developer
efforts and total cost of ownership for the users.


  Space-air-ground integrated networks (SAGINs) are emerging as a pivotal
element in the evolution of future wireless networks. Despite their potential,
the joint design of communication and computation within SAGINs remains a
formidable challenge. In this paper, the problem of energy efficiency in
SAGIN-enabled probabilistic semantic communication (PSC) system is
investigated. In the considered model, a satellite needs to transmit data to
multiple ground terminals (GTs) via an unmanned aerial vehicle (UAV) acting as
a relay. During transmission, the satellite and the UAV can use PSC technique
to compress the transmitting data, while the GTs can automatically recover the
missing information. The PSC is underpinned by shared probability graphs that
serve as a common knowledge base among the transceivers, allowing for
resource-saving communication at the expense of increased computation resource.
Through analysis, the computation overhead function in PSC is a piecewise
function with respect to the semantic compression ratio. Therefore, it is
important to make a balance between communication and computation to achieve
optimal energy efficiency. The joint communication and computation problem is
formulated as an optimization problem aiming to minimize the total
communication and computation energy consumption of the network under latency,
power, computation capacity, bandwidth, semantic compression ratio, and UAV
location constraints. To solve this non-convex non-smooth problem, we propose
an iterative algorithm where the closed-form solutions for computation capacity
allocation and UAV altitude are obtained at each iteration. Numerical results
show the effectiveness of the proposed algorithm.


  [abridged] Efficient absorption of stellar UV and visible radiation by TiO
and VO is predicted to drive temperature inversions in the upper atmospheres of
hot Jupiters. However, few inversions or detections of TiO or VO have been
reported, and results are often contradictory. Using the improved ExoMol Toto
line list, we searched for TiO emission in the dayside spectrum of WASP-33b
using the same data in which the molecule was previously detected with an older
line list at 4.8$\sigma$. We intended to confirm the molecular detection and
quantify the signal improvement offered by the ExoMol Toto line list. Data from
the High Dispersion Spectrograph on the Subaru Telescope was extracted and
reduced in an identical manner to the previous study. Stellar and telluric
contamination were then removed. High-resolution TiO emission models of
WASP-33b were created using the radiative transfer code petitRADTRANS and
cross-correlated with the data. We measure a 4.3$\sigma$ TiO emission signature
using the ExoMol Toto models, corresponding to a WASP-33b orbital velocity
semi-amplitude of $K_\mathrm{p}=252.9^{+5.0}_{-5.3}\ \mathrm{km\ s^{-1}}$ and a
system velocity of $v_\mathrm{sys}=-23.0^{+4.7}_{-4.6}\ \mathrm{km\ s^{-1}}$.
Injection-recovery tests using models based on the new and earlier line lists
indicate that if the new models provide a perfect match to the planet spectrum,
the significance of the TiO detection should have increased by a factor of
$\sim$2. Although the TiO signal we find is statistically significant,
comparison with previous works makes our result too ambiguous to claim a
clear-cut detection. Unexpectedly, the new ExoMol Toto models provide a weaker
signal than that found previously, which is offset in
$K_\mathrm{p}$-$v_\mathrm{sys}$ space. This sheds some doubt on both
detections, especially in light of a recently published TiO non-detection using
a different dataset.


  The spin-1/2 XXZ diamond chain is considered within the Jordan-Wigner
fermionization. The fermionized Hamiltonian contains the interacting terms
which are treated within the Hartree-Fock approximation. We obtain the
ground-state magnetization curve of the model for some particular cases and
compare the results with the exact diagonalization data for finite chains of 30
spins and known exact results. We also analyze the validity of the suggested
approximation.


  We consider positron propagation in the interstellar medium and show that the
positrons from the beta-plus decay chains of the radioactive nuclei Ni-56,
Ti-44, and Al-26, produced in Galactic supernovae, can fully account for all
the features of the diffuse Galactic 511 keV annihilation radiation observed by
INTEGRAL/SPI. We also predict additional measurable features that can further
test the origin of positrons and provide new information on the nature of the
interstellar medium.


  We investigate dynamical analogues of the $L^2$-Betti numbers for modules
over integral group ring of a discrete sofic group. In particular, we show that
the $L^2$-Betti numbers exactly measure the failure of addition formula for
dynamical invariants.


  We study the electron transport through a magnetic molecular transistor in
the Kondo limit using the slave boson technique. We include the electron-phonon
coupling and analyze the cases where the spin of the molecule is either S=1/2
or S=1. We use the Schrieffer-Wolff transformation to write down a low energy
Hamiltonian for the system. In the presence of electron-phonon coupling, and
for $S\smeq1$, the resulting Kondo Hamiltonian has two active channels. At low
temperature, these two channels interfere destructively, leading to a zero
conductance.


  The discovery that externally-driven nonlinear optical resonators can sustain
ultrashort pulses corresponding to coherent optical frequency combs has enabled
landmark advances in applications from telecommunications to sensing. The main
research focus has hitherto been on resonators with purely cubic (Kerr-type)
nonlinearity that are externally-driven with a monochromatic continuous wave
laser -- in such systems, the solitons manifest themselves as unique attractors
whose carrier frequency coincides with that of the external driving field.
Recent experiments have, however, shown that a qualitatively different type of
temporal soliton can arise via parametric down-conversion in resonators with
simultaneous quadratic and cubic nonlinearity. In contrast to conventional
solitons in pure-Kerr resonators, these parametrically driven solitons come in
two different flavours with opposite phases, and they are spectrally centred at
half of the frequency of the driving field. Here, we theoretically predict and
experimentally demonstrate that parametrically driven solitons can also arise
in resonators with pure Kerr nonlinearity under conditions of bichromatic
driving. In this case, the solitons arise through four-wave mixing mediated
phase-sensitive amplification, come with two distinct phases, and have a
carrier frequency in between the two external driving fields. Our experiments
are performed in an integrated silicon nitride microcavity, and we observe
frequency comb spectra in good agreement with theoretical predictions. In
addition to representing a fundamental discovery of a new type of temporal
dissipative soliton, our results constitute the first unequivocal realisation
of parametrically driven soliton frequency combs in a microcavity platform
compatible with foundry-ready mass fabrication.


  It is known that a backward Schramm--Loewner evolution (SLE) is coupled with
a free boundary Gaussian free field (GFF) with boundary perturbation to give
conformal welding of quantum surfaces. Motivated by a generalization of
conformal welding for quantum surfaces with multiple marked boundary points, we
propose a notion of multiple backward SLE. To this aim, we investigate the
commutation relation between two backward Loewner chains, and consequently, we
find that the driving process of each backward Loewner chain has to have a
drift term given by logarithmic derivative of a partition function, which is
determined by a system of Belavin--Polyakov--Zamolodchikov-like equations so
that these Loewner chains are commutative. After this observation, we define a
multiple backward SLE as a tuple of mutually commutative backward Loewner
chains. It immediately follows that each backward Loewner chain in a multiple
backward SLE is obtained as a Girsanov transform of a backward SLE. We also
discuss coupling of a multiple backward SLE with a GFF with boundary
perturbation and find that a partition function and a boundary perturbation are
uniquely determined so that they are coupled with each other.


  A wide range of mechanisms predict present-day s-wave dark matter (DM)
annihilation cross-sections that are orders of magnitude below current
experimental sensitivity. We explore the capability of DM density spikes around
the Milky Way's supermassive black hole to probe such faint signals of DM
annihilations, considering a range of possible spike and halo distributions. As
an exemplar of a theory with a suppressed s-wave annihilation cross-section, we
consider a hidden sector axion portal model of DM. In this model, the leading
contribution to the annihilation cross-section in the early universe is p-wave,
while s-wave annihilations occur at higher order in the coupling constant. We
provide a unified treatment of DM freezeout in this model including both s- and
p-wave annihilations and analytically determine the photon spectrum for the
dominant DM annihilation process in the universe today. We find that Fermi and
H.E.S.S. observations of the Galactic Center offer excellent sensitivity to
this model over a wide range of parameter space, with prospects depending
sensitively on the properties of the DM spike as well as the central halo.


  The adoption of deep learning-based healthcare decision support systems such
as the detection of irregular cardiac rhythm is hindered by challenges such as
lack of access to quality data and the high costs associated with the
collection and annotation of data. The collection and processing of large
volumes of healthcare data is a continuous process. The performance of
data-hungry Deep Learning models (DL) is highly dependent on the quantity and
quality of the data. While the need for data quantity has been established
through research adequately, we show how a selection of good quality data
improves deep learning model performance. In this work, we take
Electrocardiogram (ECG) data as a case study and propose a model performance
improvement methodology for algorithm developers, that selects the most
informative data samples from incoming streams of multi-class ECG data. Our
Core-Set selection methodology uses metrics-based explanations to select the
most informative ECG data samples. This also provides an understanding (for
algorithm developers) as to why a sample was selected as more informative over
others for the improvement of deep learning model performance. Our experimental
results show a 9.67% and 8.69% precision and recall improvement with a
significant training data volume reduction of 50%. Additionally, our proposed
methodology asserts the quality and annotation of ECG samples from incoming
data streams. It allows automatic detection of individual data samples that do
not contribute to model learning thus minimizing possible negative effects on
model performance. We further discuss the potential generalizability of our
approach by experimenting with a different dataset and deep learning
architecture.


  In this article, we utilize machine learning to dynamically determine if a
point on the computational grid requires implicit numerical dissipation for
large eddy simulation (LES). The decision making process is learnt through
\emph{a priori} training on quantities derived from direct numerical simulation
(DNS) data. In particular, we compute eddy-viscosities obtained through the
coarse graining of DNS quantities and utilize their distribution to categorize
areas that require dissipation. If our learning determines that closure is
necessary, an upwinded scheme is utilized for computing the non-linear
Jacobian. In contrast, if it is determined that closure is unnecessary, a
symmetric and second-order accurate energy and enstrophy preserving Arakawa
scheme is utilized instead. This results in a closure framework that precludes
the specification of any model-form for the small scale contributions of
turbulence but deploys an appropriate numerical dissipation from explicit
closure driven hypotheses. This methodology is deployed for the Kraichnan
turbulence test-case and assessed through various statistical quantities such
as angle-averaged kinetic energy spectra and vorticity structure functions. Our
framework thus establishes a direct link between the use of explicit LES
ideologies for closure and numerical scheme-based modeling of turbulence
leading to improved statistical fidelity of \emph{a posteriori} simulations.


  The origin of ultra-high energy cosmic rays (UHECR) has been widely regarded
as one of the major questions in the frontiers of particle astrophysics. Gamma
ray bursts (GRB), the most violent explosions in the universe second only to
the Big Bang, have been a popular candidate site for UHECR productions. The
recent IceCube report on the non-observation of GRB induced neutrinos therefore
attracts wide attention. This dilemma requires a resolution: either the
assumption of GRB as UHECR accelerator is to be abandoned or the expected GRB
induced neutrino yield was wrong. It has been pointed out that IceCube has
overestimated the neutrino flux at GRB site by a factor of $\sim 5$. In this
paper we point out that, in addition to the issue of neutrino production at
source, the neutrino oscillation and the possible neutrino decay during their
flight from GRB to Earth should further reduce the detectability of IceCube,
which is most sensitive to the muon-neutrino flavor as far as point-source
identification is concerned. Specifically, neutrino oscillation will reduce the
muon-neutrino flavor ratio from 2/3 per neutrino at GRB source to 1/3 on Earth,
while neutrino decay, if exists and under the assumption of normal hierarchy of
mass eigenstates, would result in a further reduction of muon-neutrino ratio to
1/8. With these in mind, we note that there have been efforts in recent years
in pursuing other type of neutrino telescopes based on Askaryan effect, which
can in principle observe and distinguish all three flavors with comparable
sensitivities. Such new approach may therefore be complementary to IceCube in
shedding more lights on this cosmic accelerator question.


  Cross-domain image retrieval aims at retrieving images across different
domains to excavate cross-domain classificatory or correspondence
relationships. This paper studies a less-touched problem of cross-domain image
retrieval, i.e., unsupervised cross-domain image retrieval, considering the
following practical assumptions: (i) no correspondence relationship, and (ii)
no category annotations. It is challenging to align and bridge distinct domains
without cross-domain correspondence. To tackle the challenge, we present a
novel Correspondence-free Domain Alignment (CoDA) method to effectively
eliminate the cross-domain gap through In-domain Self-matching Supervision
(ISS) and Cross-domain Classifier Alignment (CCA). To be specific, ISS is
presented to encapsulate discriminative information into the latent common
space by elaborating a novel self-matching supervision mechanism. To alleviate
the cross-domain discrepancy, CCA is proposed to align distinct domain-specific
classifiers. Thanks to the ISS and CCA, our method could encode the
discrimination into the domain-invariant embedding space for unsupervised
cross-domain image retrieval. To verify the effectiveness of the proposed
method, extensive experiments are conducted on four benchmark datasets compared
with six state-of-the-art methods.


  A continuum individual-based model of hopping and coalescing particles is
introduced and studied. Its microscopic dynamics are described by a hierarchy
of evolution equations obtained in the paper. Then the passage from the micro-
to mesoscopic dynamics is performed by means of a Vlasov-type scaling. The
existence and uniqueness of the solutions of the corresponding kinetic equation
are proved.


  We re-investigate the vector and axial-vector vacuum susceptibilities by
taking advantage of the vector and axial-vector Ward-Takahashi identities. We
show analytically that, in the chiral limit, the vector vacuum susceptibility
is zero and the axial-vector vacuum susceptibility equals three fourths of the
square of the pion decay constant. Besides, our analysis reproduces the
Weinberg sum rule.


  Zhu, Stone, and Rafikov (2012) found in 3D shearing box simulations a new
form of planet-disk interaction that they attributed to a vertical buoyancy
resonance in the disk. We describe an analytic linear model for this
interaction. We adopt a simplified model involving azimuthal forcing that
produces the resonance and permits an analytic description of its structure. We
derive an analytic expression for the buoyancy torque and show that the
vertical torque distribution agrees well with results of Athena simulations and
a Fourier method for linear numerical calculations carried out with the same
forcing. The buoyancy resonance differs from the classic Lindblad and
corotation resonances in that the resonance lies along tilted planes. Its width
depends on damping effects and is independent of the gas sound speed. The
resonance does not excite propagating waves. At a given large azimuthal
wavenumber k_y > 1/h (for disk thickness h), the buoyancy resonance exerts a
torque over a region that lies radially closer to the corotation radius than
the Lindblad resonance. Because the torque is localized to the region of
excitation, it is potentially subject to the effects of nonlinear saturation.
In addition, the torque can be reduced by the effects of radiative heat
transfer between the resonant region and its surroundings. For each azimuthal
wavenumber, the resonance establishes a large scale density wave pattern in a
plane within the disk.


  GaN-based lateral Schottky diodes (SBDs) have attracted great attention for
high-power applications due to its combined high electron mobility and large
critical breakdown field. However, the breakdown voltage (BV) of the SBDs are
far from exploiting the material advantages of GaN at present, limiting the
desire to use GaN for ultra-high voltage (UHV) applications. Then, a golden
question is whether the excellent properties of GaN-based materials can be
practically used in the UHV field? Here we demonstrate UHV AlGaN/GaN SBDs on
sapphire with a BV of 10.6 kV, a specific on-resistance of 25.8 m{\Omega}.cm2,
yielding a power figure of merit of more than 3.8 GW/cm2. These devices are
designed with single channel and 85-{\mu}m anode-to-cathode spacing, without
other additional electric field management, demonstrating its great potential
for the UHV application in power electronics.


  Ultrasound velocity measurements of cubic spinel GeCo$_2$O$_4$ in single
crystal were performed for the investigation of shear and compression moduli.
The shear moduli in the paramagnetic state reveal an absence of Jahn-Teller
activity despite the presence of orbital degeneracy in the Co$^{2+}$ ions. Such
a Jahn-Teller inactivity indicates that the intersite orbital-orbital
interaction is much stronger than the Jahn-Teller coupling. The compression
moduli in the paramagnetic state near the N$\acute{e}$el temperature $T_N$
reveal that the most relevant exchange path for the antiferromagnetic
transition lies in the [111] direction. This exchange-path anisotropy is
consistent with the antiferromagnetic structure with the wave vector $q
\parallel$ [111], suggesting the presence of bond frustration due to
competition among a direct ferromagnetic and several distant-neighbors
antiferromagnetic interactions. In the JT-inactive condition, the bond
frustration can be induced by geometrical orbital frustration of
$t_{2g}$-$t_{2g}$ interaction between the Co$^{2+}$ ions which can be realized
in the pyrochlore lattice of the high spin Co$^{2+}$ with $t_{2g}$-orbital
degeneracy. In GeCo$_2$O$_4$, the tetragonal elongation below $T_N$ releases
the orbital frustration by quenching the orbital degeneracy.


  Jackson and Lee proved that certain six-element monoid generates a
hereditarily finitely based variety $\mathbb E^1$ whose lattice of subvarieties
contains an infinite ascending chain. We identify syntactic monoids which
generate finitely generated subvarieties of $\mathbb E^1$ and show that one of
these finite monoids together with certain seven-element monoid generates a new
limit variety.


  The measurement of the internal $^{222}$Rn activity in the NEXT-White
detector during the so-called Run-II period with $^{136}$Xe-depleted xenon is
discussed in detail, together with its implications for double beta decay
searches in NEXT. The activity is measured through the alpha production rate
induced in the fiducial volume by $^{222}$Rn and its alpha-emitting progeny.
The specific activity is measured to be $(38.1\pm 2.2~\mathrm{(stat.)}\pm
5.9~\mathrm{(syst.)})$~mBq/m$^3$. Radon-induced electrons have also been
characterized from the decay of the $^{214}$Bi daughter ions plating out on the
cathode of the time projection chamber. From our studies, we conclude that
radon-induced backgrounds are sufficiently low to enable a successful NEXT-100
physics program, as the projected rate contribution should not exceed
0.1~counts/yr in the neutrinoless double beta decay sample.


  The cosmological models exhibiting tracker properties have great significance
in the context of dark energy as they can reach the present value of dark
energy density from a wide range of initial conditions, thereby alleviating
both the fine-tuning and the cosmic coincidence problem. The
$\alpha$-attractors, which are originally discussed in the context of
inflation, can exhibit the properties of dark energy as they can behave like
cosmological trackers at early times and show the late time behaviour of a
cosmological constant. In the present paper, we study the Oscillatory Tracker
Model (OTM), which belongs to the family of $\alpha$-attractor dark energy
models. Using the current observational data sets like Cosmic Microwave
Background (CMB), Baryon Acoustic Oscillation (BAO) and type 1a supernova data
(Pantheon compilation), we constrain the parameters of the model and estimate
both the mean and best-fit values. Although the oscillatory tracker model
contains a larger set of parameters than the usual LCDM model, the common set
of parameters of both agree within $1\, \sigma$ error limits. Our observations
using both high redshift and low redshift data supports Hubble parameter value
$H_0 = 67.4$ Kms$^{-1}$Mpc$^{-1}$. We study the effect of the OTM on the CMB
temperature and polarization power spectra, matter power spectrum and $f
\sigma_8$. Our analysis of the CMB power spectrum and matter power spectrum
suggests that the oscillatory tracker dark energy model has noticeable
differences from usual LCDM predictions. Yet, in most cases, the agreement is
very close.


  Recent observations indicate that mm/cm-sized grains may exist in the
embedded protostellar disks. How such large grains grow from the micron size
(or less) in the earliest phase of star formation remains relatively
unexplored. In this study we take a first step to model the grain growth in the
protostellar environment, using two-dimensional (2D axisymmetric) radiation
hydrodynamic and grain growth simulations. We show that the grain growth
calculations can be greatly simplified by the "terminal velocity
approximation", where the dust drift velocity relative to the gas is
proportional to its stopping time, which is proportional to the grain size. We
find that the grain-grain collision from size-dependent terminal velocity alone
is too slow to convert a significant fraction of the initially micron-sized
grains into mm/cm sizes during the deeply embedded Class 0 phase. Substantial
grain growth is achieved when the grain-grain collision speed is enhanced by a
factor of 4. The dust growth above and below the disk midplane enables the
grains to settle faster towards the midplane, which increases the local
dust-to-gas ratio, which, in turn, speeds up further growth there. How this
needed enhancement can be achieved is unclear, although turbulence is a strong
possibility that deserves further exploration.


  The Brownian web is a collection of one-dimensional coalescing Brownian
motions starting from every point in space and time, while the Brownian net is
an extension that also allows branching. We show here that the Brownian net is
the universal scaling limit of one-dimensional branching-coalescing random
walks with weak binary branching and arbitrary increment distributions that
have finite $(3+\varepsilon)$-th moment. This gives the first example in the
domain of attraction of the Brownian net where paths can cross without
coalescing.


  This paper is primarily studying the behaver of the twin-accumulator
suspension over the conventional passive system focusing on ride quality
behavior and road holding. Therefore, a dynamic modeling of passive and
twin-accumulator suspension for a quarter model is constructed. MATLAB Simulink
environment is used to develop the suspension models. The simulation is applied
with two different road disturbances, namely, step input and random input to
disturb the suspension system. The optimum solution is obtained numerically by
utilizing a multi-objective evolutionary strategy algorithm and employing a
cost function that seeks to minimize the RMS value of the body acceleration,
the suspension displacement as well as the dynamic tire load. Moreover, in this
work, an active suspension system with PI controller is presented in order to
improve the suspension performance criteria. The simulation results of passive,
optimized twin accumulator suspension and active suspension consist of body
displacement, wheel deflection, vehicle body acceleration, suspension travel
and dynamic tire load are compared and analyzed. Results show that the
twin-accumulator suspension system gives worthwhile improvements in ride
behavior compared with the passive suspension. Finally, it can be observed that
the performance of body displacement and wheel displacement can be improved by
using the proposed PI controller.


  We show that the spin period of the white dwarf in the magnetic CV EX Hydrae
represents an equilibrium state in which the corotation radius is comparable
with the distance from the white dwarf to the inner Lagrange point. We also
show that a continuum of spin equilibria exists at which Pspin is significantly
longer than \sim 0.1 Porb. Most systems occupying these equilibrium states
should have orbital periods below the CV period gap, as observed.


  "Thick" or "microformal" morphisms of supermanifolds generalize ordinary
maps. They were discovered as a tool for homotopy algebras. Namely, the
corresponding pullbacks provide $L_{\infty}$-morphisms for $S_{\infty}$ or
Batalin--Vilkovisky algebras. It was clear from the start that constructions
used for thick morphisms closely resemble some fundamental notions in quantum
mechanics and their classical limits (such as action, Schr\"{o}dinger and
Hamilton--Jacobi equations, etc.) There was also a natural question about any
connection of thick morphisms with spinor representation. We answer both
questions here. We establish relations of thick morphisms with fundamental
concepts of quantum mechanics. We also show that in the linear setup quantum
thick morphisms with quadratic action give (a version of) the spinor
representation for a certain category of canonical linear relations, which is
an analog of the Berezin--Neretin representation and a generalization of the
metaplectic representation (and ordinary spinor representation).


  All maximal supergravities in four space-time dimensions are presented. The
ungauged Lagrangians can be encoded in an E_7(7)\Sp(56,R)/GL(28) matrix
associated with the freedom of performing electric/magnetic duality
transformations. The gauging is defined in terms of an embedding tensor which
encodes the subgroup of E_7(7) that is realized as a local invariance. This
embedding tensor may imply the presence of magnetic charges which require
corresponding dual gauge fields. The latter can be incorporated by using a
recently proposed formulation that involves tensor gauge fields in the adjoint
representation of E_7(7). In this formulation the results take a universal form
irrespective of the electric/magnetic duality basis. We present the general
class of supersymmetric and gauge invariant Lagrangians and discuss a number of
applications.


  The thickness evolution of in-plane magnetization reversal in ultrathin films
is studied with a theoretical model that takes account of surface roughness
typical of epitaxial growth. Guided by N\'{e}el's model, step edge sites of
monolayer-height islands are assigned a two-fold anisotropy in addition to a
four-fold anisotropy at all sites. Coercivity is found to depend essentially on
both the film thickness and the partial coverage of the topmost layer. Its
qualitative features are determined primarily by sample geometry and the size
of the step anisotropy compared to the domain wall energy. Magnetostatic
interactions change the results quantitatively, but not qualitatively. Their
effect is understood by comparing calculations with and without their
inclusion.


  We present a model for big bang nucleosynthesis which combines baryon
inhomogeneities with the effects of the decays of massive particles (masses
higher than a few GeV). Those particles, with half-lives longer than the
standard nucleosynthesis epoch, give rise to both electromagnetic and hadron
cascades which modify the abundances of the light nuclides resulting from the
previous, inhomogeneous thermonuclear nucleosynthesis stage. We find a region
in the parameter space of this composite model where there is agreement with
currently inferred primordial abundances for values of $\Omega_{b}h^{2}_{50}$
as high as 0.35 ($\Omega_{b}$ being the baryon fraction of the closure density
and $h_{50}$ the Hubble constant in units of 50 km/s/Mpc). Possible
improvements of the model are pointed out.


  A local dwarf galaxy, NGC 5253, has a young super star cluster that may
provide an example of highly efficient star formation. Here we report the
detection and imaging, with the Submillimeter Array, of the J= 3-2 rotational
transition of CO at the location of the massive cluster associated with the
supernebula. The gas cloud is hot, dense, quiescent, and extremely dusty. Its
gas-to-dust ratio is lower than the Galactic value, which we attribute to dust
enrichment by Wolf-Rayet stars within the embedded star cluster. Its star
formation efficiency exceeds 50%, ten times higher than clouds in the Milky
Way: this cloud is a factory of stars and soot. We suggest that high efficiency
results from the force-feeding of star formation by a streamer of gas falling
into the galaxy.


  I argue that the cold dark matter (CDM) model requires that even within a few
kpc of the center of a galactic halo a significant fraction (greater than a few
percent) of the surface density is contained in substructures with masses >
10^3 solar masses. These structures should be light enough to avoid dynamical
friction and dense enough to avoid tidal disruption. I then show using the
results of numerical simulations that this substructure will significantly
alter the flux ratios of multiply imaged quasars (QSOs) without changing the
image positions. The degree to which this occurs will depend on the angular
size of the QSO and thus the wavelength of the observations.


  This is the fourth in a series of papers that deal with angular momentum
transport by internal gravity waves in stellar interiors. Here, we want to
examine the potential role of waves in other evolutionary phases than the main
sequence. We study the evolution of a 3Msun Population I model from the
pre-main sequence to the early-AGB phase and examine whether waves can lead to
angular momentum redistribution and/or element diffusion at the external
convection zone boundary. We find that, although waves produced by the surface
convection zone can be ignored safely for such a star during the main sequence,
it is not the case for later evolutionary stages. In particular, angular
momentum transport by internal waves could be quite important at the end of the
sub-giant branch and during the early-AGB phase. Wave-induced mixing of
chemicals is expected during the early-AGB phase.


  Astronomical instrumentation is most of the time faced with challenging
requirements in terms of sensitivity, stability, complexity, etc., and
therefore leads to high performance developments that at first sight appear to
be suitable only for the specific design application at the telescope. However,
their usefulness in other disciplines and for other applications is not
excluded. The ERA2 facility is a lab demonstrator, based on a high-performance
astronomical spectrograph, which is intended to explore the innovation
potential of fiber-coupled multi-channel spectroscopy for spatially resolved
spectroscopy in life science, material sciences, and other areas of research.


  The well-posedness of a phase-field approximation to the Willmore flow with
volume constraint is established. The existence proof relies on the underlying
gradient flow structure of the problem: the time discrete approximation is
solved by a variational minimization principle.


  The reversible transfer of the quantum information between a photon, an
information carrier, and a quantum memory with high fidelity and reliability is
the prerequisite for realizing a long-distance quantum communication and a
quantum network. Encoding photons into higher-dimensional states could
significantly increase their information-carrying capability and network
capacity. Moreover, the large-alphabet quantum key distribution affords a more
secure flux of information. Quantum memories have been realized in different
physical systems, such as atomic ensembles and solid systems etc., but to date,
all quantum memories only realize the storage and retrieval of the photons
lived in a two-dimensional space spanned for example by orthogonal
polarizations, therefore only a quantum bit could be stored there. Here, we
report on the first experimental realization of a quantum memory storing a
photon lived in a three-dimensional space spanned by orbital angular momentums
via electromagnetically induced transparency in a cold atomic ensemble. We
reconstruct the storage process density matrix with the fidelity of 85.3% by
the aid of a 4-f imaging system experimentally. The ability to store a
high-dimensional quantum state with high fidelity is very promising for
building a high-dimensional quantum network.


  The central molecular zone (CMZ) plays an essential role in regulating the
nuclear ecosystem of our Galaxy. To get an insight into the magnetic fields of
the CMZ, we employ the Gradient Technique (GT), which is rooted in the
anisotropy of magnetohydrodynamic turbulence. Our analysis is based on the data
of multiple wavelengths, including molecular emission lines, radio 1.4 GHz
continuum image, and Herschel 70 $\mu$m image, as well as ionized [Ne II] and
Paschen-alpha emissions. The results are compared with the observations of
Planck 353 GHz and High-resolution Airborne Wideband Camera Plus (HWAC+) 53
$\mu$m polarized dust emissions. We map the orientation of the magnetic field
at multiple wavelengths across the central molecular zone, including close-ups
of the Radio Arc and Sagittarius A West regions, on multi scales from $\sim$
0.1 pc to 10 pc. The magnetic fields towards the central molecular zone traced
by GT are globally compatible with the polarization measurements, accounting
for the contribution from the galactic foreground and background. This
correspondence suggests that the magnetic field and turbulence are dynamically
crucial in the galactic center. We find that the magnetic fields associated
with the Arched filaments and the thermal components of the Radio Arc are in
good agreement with the HAWC+ polarization. Our measurement towards the
non-thermal Radio Arc reveals the poloidal magnetic field components in the
galactic center. For Sagittarius A West region, we find a great agreement
between the GT measurement using [Ne II] emission and HWAC+ 53 $\mu$m
observation. We use GT to predict the magnetic fields associated with ionized
Paschen-alpha gas down to scales of 0.1 pc.


  In the past years, deep convolutional neural networks have been pushing the
frontier of face recognition (FR) techniques in both verification and
identification scenarios. Despite the high accuracy, they are often criticized
for lacking explainability. There has been an increasing demand for
understanding the decision-making process of deep face recognition systems.
Recent studies have investigated the usage of visual saliency maps as an
explanation, but they often lack a discussion and analysis in the context of
face recognition. This paper concentrates on explainable face verification
tasks and conceives a new explanation framework. Firstly, a definition of the
saliency-based explanation method is provided, which focuses on the decisions
made by the deep FR model. Secondly, a new model-agnostic explanation method
named CorrRISE is proposed to produce saliency maps, which reveal both the
similar and dissimilar regions of any given pair of face images. Then, an
evaluation methodology is designed to measure the performance of general visual
saliency explanation methods in face verification. Finally, substantial visual
and quantitative results have shown that the proposed CorrRISE method
demonstrates promising results in comparison with other state-of-the-art
explainable face verification approaches.


  We study whether dry merger-driven size growth of massive elliptical galaxies
depends on their initial structural concentration, and analyse the validity of
the homology hypothesis for virial mass determination in massive ellipticals
grown by dry mergers. High-resolution simulations of a few realistic merger
trees, starting with compact progenitors of different structural concentrations
(S\'ersic indices n), show that galaxy growth has little dependence on the
initial S\'ersic index (larger n leads to slightly larger size growth), and
depends more on other particulars of the merger history. We show that the
deposition of accreted matter in the outer parts leads to a systematic and
predictable breaking of the homology between remnants and progenitors, which we
characterize through the evolution, during the course of the merger history, of
virial coefficients K = GM/Re \sigma^2 associated to the most commonly-used
dynamical and stellar mass parameters. The virial coefficient for the luminous
mass, K , is about 50 per cent larger at the z = 2 start of the merger
evolution than in z = 0 remnants. Ignoring virial evolution leads to biased
virial mass estimates. We provide K corresponding to a variety of dynamical and
stellar mass parameters, and provide recipes for the dynamical determination of
galaxy masses. For massive, non-compact ellipticals, the popular expression M =
5 Re \sigma^2 / G underestimates the dynamical mass within the luminous body by
factors of up to 4; it instead provides an approximation to the total stellar
mass with smaller uncertainty than current stellar population models.


  A perturbative QCD calculation of heavy flavor quark fragmentation into heavy
flavor baryons is developed along the lines of corresponding heavy meson
models. The non-perturbative formation of the baryon is accomplished by
implementing the quark-diquark model of the baryons. Diquark color form factors
are used to enable the integration over the virtual heavy quark momentum. The
resulting spin independent functions for charmed and bottom quarks to fragment
into charmed and bottom baryons with spin 1/2 and 3/2 are compared with recent
data. Predictions are made for the spin dependent fragmentation functions as
well, particularly for the functions $\hat{g}_1$ and $\hat{h}_1$ in the case of
spin 1/2 baryons.


  We investigate numerically the localization-delocalization transition in
quantum Hall systems with long-range disorder potential with respect to
multifractal properties. Wavefunctions at the transition energy are obtained
within the framework of the generalized Chalker--Coddington network model. We
determine the critical exponent $\alpha_0$ characterizing the scaling behavior
of the local order parameter for systems with potential correlation length $d$
up to $12$ magnetic lengths $l$. Our results show that $\alpha_0$ does not
depend on the ratio $d/l$. With increasing $d/l$, effects due to classical
percolation only cause an increase of the microscopic length scale, whereas the
critical behavior on larger scales remains unchanged. This proves that systems
with long-range disorder belong to the same universality class as those with
short-range disorder.


  We discuss thermalization in de Sitter space and argue, from two different
points of view, that the typical time needed for thermalization is of order
$R^{3}/l_{pl}^{2}$, where $R$ is the radius of the de Sitter space in question.
This time scale gives plenty of room for non-thermal deviations to survive
during long periods of inflation. We also speculate in more general terms on
the meaning of the time scale for finite quantum systems inside isolated boxes,
and comment on the relation to the Poincar\'{e} recurrence time.


  We study the Cebyshev-Halley methods applied to the family of polynomials
$f_{n,c}(z)=z^n+c$, for $n\ge 2$ and $c\in \mathbb{C}^{*}$. We prove the
existence of parameters such that the immediate basins of attraction
corresponding to the roots of unity are infinitely connected. We also prove
that, for $n \ge 2$, the corresponding dynamical plane contains a connected
component of the Julia set, which is a quasiconformal deformation of the Julia
set of the map obtained by applying Newton's method to $f_{n,-1}$.


  We present the results of optical identifications and spectroscopic redshifts
measurements for galaxy clusters from 2-nd Planck catalogue of
Sunyaev-Zeldovich sources (PSZ2), located at high redshifts, $z\approx0.7-0.9$.
We used the data of optical observations obtained with Russian-Turkish 1.5-m
telescope (RTT150), Sayan observatory 1.6-m telescope, Calar Alto 3.5-m
telescope and 6-m SAO RAS telescope (Bolshoi Teleskop Alt-azimutalnyi, BTA).
Spectroscopic redshift measurements were obtained for seven galaxy clusters,
including one cluster, PSZ2 G126.57+51.61, from the cosmological sample of PSZ2
catalogue. In central regions of two clusters, PSZ2 G069.39+68.05 and PSZ2
G087.39-34.58, the strong gravitationally lensed background galaxies are found,
one of them at redshift $z=4.262$. The data presented below roughly double the
number of known galaxy clusters in the second Planck catalogue of
Sunyaev-Zeldovich sources at high redshifts, $z\approx0.8$.


  Suppose a matrix $A \in \mathbb{R}^{m \times n}$ of rank $r$ with singular
value decomposition $A = U_{A}\Sigma_{A} V_{A}^{T}$, where $U_{A} \in
\mathbb{R}^{m \times r}$, $V_{A} \in \mathbb{R}^{n \times r}$ are orthonormal
and $\Sigma_{A} \in \mathbb{R}^{r \times r}$ is a diagonal matrix. The
statistical leverage scores of a matrix $A$ are the squared row-norms defined
by $\ell_{i} = \|(U_{A})_{i,:}\|_2^2$, where $i \in [m]$, and the matrix
coherence is the largest statistical leverage score. These quantities play an
important role in machine learning algorithms such as matrix completion and
Nystr\"{o}m-based low rank matrix approximation as well as large-scale
statistical data analysis applications, whose usual algorithm complexity is
polynomial in the dimension of the matrix $A$. As an alternative to the
conventional approach, and inspired by recent development on dequantization
techniques, we propose a quantum-inspired algorithm for approximating the
statistical leverage scores. We then analyze the accuracy of the algorithm and
perform numerical experiments to illustrate the feasibility of our algorithm.
Theoretical analysis shows that our novel algorithm takes time polynomial in an
integer $k$, condition number $\kappa$ and logarithm of the matrix size.


  High pressure experiments in diamond anvil cells as well as in geophysics
show that at certain discrete values of pressure abrupt changes of the mass
density and changes of the material structure occur. The aim of this paper is
to discuss the influence of high external pressure on atoms and molecules using
the $3D$ square well potential as a simple solvable quantum mechanical example.
Values of external pressure needed for a transition between energy levels with
different values of the main quantum number $n$, as well as the pressure needed
to expel the particle from this system are calculated. In both cases discrete
values of pressure are obtained.


  The Lov\'{a}sz Local Lemma (LLL) is a cornerstone principle in the
probabilistic method of combinatorics, and a seminal algorithm of Moser &
Tardos (2010) provides an efficient randomized algorithm to implement it. This
can be parallelized to give an algorithm that uses polynomially many processors
and runs in $O(\log^3 n)$ time on an EREW PRAM, stemming from $O(\log n)$
adaptive computations of a maximal independent set (MIS). Chung et al. (2014)
developed faster local and parallel algorithms, potentially running in time
$O(\log^2 n)$, but these algorithms require more stringent conditions than the
LLL.
  We give a new parallel algorithm that works under essentially the same
conditions as the original algorithm of Moser & Tardos but uses only a single
MIS computation, thus running in $O(\log^2 n)$ time on an EREW PRAM. This can
be derandomized to give an NC algorithm running in time $O(\log^2 n)$ as well,
speeding up a previous NC LLL algorithm of Chandrasekaran et al. (2013).
  We also provide improved and tighter bounds on the run-times of the
sequential and parallel resampling-based algorithms originally developed by
Moser & Tardos. These apply to any problem instance in which the tighter
Shearer LLL criterion is satisfied.


  The assessed binary phase diagram of boron-carbon exhibits a single alloy
phase designated "B4C" with rhombohedral symmetry occupying a broad composition
range that falls just short of the nominal carbon content of 20%. As this
composition range is nearly temperature independent, the phase diagram suggests
a violation of the third law of thermodynamics, which typically requires
compounds to achieve a definite stoichiometry at low temperatures. By means of
first principles total energy calculations we predict the existence of two
stoichiometric phases at T=0K: one of composition B4C with monoclinic symmetry;
the other of composition B13C2 with rhombohedral symmetry. Using statistical
mechanics to extend to finite temperatures, we demonstrate that the monoclinic
phase reverts to the rhombohedral phase above T=600K, along with a slight
reduction on carbon content.


  With the random matrix theory, we study the spatial structure of the Chinese
stock market, American stock market and global market indices. After taking
into account the signs of the components in the eigenvectors of the
cross-correlation matrix, we detect the subsector structure of the financial
systems. The positive and negative subsectors are anti-correlated each other in
the corresponding eigenmode. The subsector structure is strong in the Chinese
stock market, while somewhat weaker in the American stock market and global
market indices. Characteristics of the subsector structures in different
markets are revealed.


  Large sensor-based science infrastructures for radio astronomy like the SKA
will be among the most intensive data-driven projects in the world, facing very
high demanding computation, storage, management, and above all power demands.
The geographically wide distribution of the SKA and and its associated
processing requirements in the form of tailored High Performance Computing
(HPC) facilities, require a Greener approach towards the Information and
Communications Technologies (ICT) adopted for the data processing to enable
operational compliance to potentially strict power budgets. Addressing the
reduction of electricity costs, improve system power monitoring and the
generation and management of electricity at system level is paramount to avoid
future inefficiencies and higher costs and enable fulfillments of Key Science
Cases. Here we outline major characteristics and innovation approaches to
address power efficiency and long-term power sustainability for radio astronomy
projects, focusing on Green ICT for science and Smart power monitoring and
control.


  In this paper, we study existence of boundary blow-up solutions for elliptic
equations involving regional fractional Laplacian. We also discuss the
optimality of our results.


  We present the calculation of the inclusive x_F-distributions of charmed
hadrons, produced in high-energy $\Sigma^-$-beam. Our calculation is based on
the modified mechanism of charmed quarks fragmentation as well as on the
mechanism of c-quark recombination with the valence quarks from initial
hadrons.


  We present a method for depth estimation with monocular images, which can
predict high-quality depth on diverse scenes up to an affine transformation,
thus preserving accurate shapes of a scene. Previous methods that predict
metric depth often work well only for a specific scene. In contrast, learning
relative depth (information of being closer or further) can enjoy better
generalization, with the price of failing to recover the accurate geometric
shape of the scene. In this work, we propose a dataset and methods to tackle
this dilemma, aiming to predict accurate depth up to an affine transformation
with good generalization to diverse scenes. First we construct a large-scale
and diverse dataset, termed Diverse Scene Depth dataset (DiverseDepth), which
has a broad range of scenes and foreground contents. Compared with previous
learning objectives, i.e., learning metric depth or relative depth, we propose
to learn the affine-invariant depth using our diverse dataset to ensure both
generalization and high-quality geometric shapes of scenes. Furthermore, in
order to train the model on the complex dataset effectively, we propose a
multi-curriculum learning method. Experiments show that our method outperforms
previous methods on 8 datasets by a large margin with the zero-shot test
setting, demonstrating the excellent generalization capacity of the learned
model to diverse scenes. The reconstructed point clouds with the predicted
depth show that our method can recover high-quality 3D shapes. Code and dataset
are available at: https://tinyurl.com/DiverseDepth


  Molybdenum disulfide (MoS$_2$) is a promising material for making
two-dimensional crystals and flexible electronic and optoelectronic devices at
the nanoscale. MoS$_2$ flakes can show high mobilities and have even been
integrated in nanocircuits . A fundamental requirement for such use is
efficient thermal transport. Electronic transport generates heat which needs to
be evacuated, more crucially so in nanostructures. Anharmonic phonon-phonon
scattering is the dominant intrinsic limitation to thermal transport in
insulators. Here, using appropriate samples, ultra-low energy Raman
spectroscopy and first principles calculations, we provide a full experimental
and theoretical description of compression and shear modes of few-layer (FL)
MoS$_2$. We demonstrate that the compression modes are strongly anharmonic with
a marked enhancement of phonon-phonon scattering as the number of layers is
reduced, most likely a general feature of nanolayered materials with weak
interlayer coupling.


  Impulsively generated sausage wave trains in coronal structures are important
for interpreting a substantial number of observations of quasi-periodic signals
with quasi-periods of order seconds. We have previously shown that the Morlet
spectra of these wave trains in coronal tubes depend crucially on the
dispersive properties of trapped sausage waves, the existence of cutoff axial
wavenumbers and the monotonicity of the dependence of the axial group speed on
the axial wavenumber in particular. This study examines the difference a slab
geometry may introduce, for which purpose we conduct a comprehensive eigenmode
analysis, both analytically and numerically, on trapped sausage modes in
coronal slabs with a considerable number of density profiles. For the profile
descriptions examined, coronal slabs can trap sausage waves with longer axial
wavelengths, and the group speed approaches the internal Alfv\'en speed more
rapidly at large wavenumbers in the cylindrical case. However, common to both
geometries, cutoff wavenumbers exist only when the density profile falls
sufficiently rapidly at distances far from coronal structures. Likewise, the
monotonicity of the group speed curves depends critically on the profile
steepness right at the structure axis. Furthermore, the Morlet spectra of the
wave trains are shaped by the group speed curves for coronal slabs and tubes
alike. Consequently, we conclude that these spectra have the potential for
telling the sub-resolution density structuring inside coronal structures,
although their detection requires an instrumental cadence of better than $\sim
1$ second.


  Obesity affects a rising percentage of the children and adolescent
population, contributing to decreased quality of life and increased risk for
comorbidities. Although the major causes of obesity are known, the obesogenic
behaviors manifest as a result of complex interactions of the individual with
the living environment. For this reason, addressing childhood obesity remains a
challenging problem for public health authorities. The BigO project
(https://bigoprogram.eu) relies on large-scale behavioral and environmental
data collection to create tools that support policy making and intervention
design. In this work, we propose a novel analysis approach for modeling the
expected population behavior as a function of the local environment. We
experimentally evaluate this approach in predicting the expected physical
activity level in small geographic regions using urban environment
characteristics. Experiments on data collected from 156 children and
adolescents verify the potential of the proposed approach. Specifically, we
train models that predict the physical activity level in a region, achieving
81% leave-one-out accuracy. In addition, we exploit the model predictions to
automatically visualize heatmaps of the expected population behavior in areas
of interest, from which we draw useful insights. Overall, the predictive models
and the automatic heatmaps are promising tools in gaining direct perception for
the spatial distribution of the population's behavior, with potential uses by
public health authorities.


  Differential privacy is a widely accepted formal privacy definition that
allows aggregate information about a dataset to be released while controlling
privacy leakage for individuals whose records appear in the data. Due to the
unavoidable tension between privacy and utility, there have been many works
trying to relax the requirements of differential privacy to achieve greater
utility. One class of relaxation, which is starting to gain support outside the
privacy community is embodied by the definitions of individual differential
privacy (IDP) and bootstrap differential privacy (BDP). The original version of
differential privacy defines a set of neighboring database pairs and achieves
its privacy guarantees by requiring that each pair of neighbors should be
nearly indistinguishable to an attacker. The privacy definitions we study,
however, aggressively reduce the set of neighboring pairs that are protected.
Both IDP and BDP define a measure of "privacy loss" that satisfies formal
privacy properties such as postprocessing invariance and composition, and
achieve dramatically better utility than the traditional variants of
differential privacy. However, there is a significant downside - we show that
they allow a significant portion of the dataset to be reconstructed using
algorithms that have arbitrarily low privacy loss under their privacy
accounting rules. We demonstrate these attacks using the preferred mechanisms
of these privacy definitions. In particular, we design a set of queries that,
when protected by these mechanisms with high noise settings (i.e., with claims
of very low privacy loss), yield more precise information about the dataset
than if they were not protected at all.


  To investigate the structural dynamics of the homology pairing of polymers,
we mod- eled the scenario of homologous chromosome pairings during meiosis in
Schizosaccharomyces pombe, one of the simplest model organisms of eukaryotes.
We consider a simple model consist- ing of pairs of homologous polymers with
the same structures that are confined in a cylindrical container, which
represents the local parts of chromosomes contained in an elongated nucleus of
S. pombe. Brownian dynamics simulations of this model showed that the excluded
volume effects among non-homological chromosomes and the transitional dynamics
of nuclear shape serve to enhance the pairing of homologous chromosomes.


  The second author and Norbury initiated the enumeration of lattice points in
the Deligne-Mumford compactifications of moduli spaces of curves. They showed
that the enumeration may be expressed in terms of polynomials, whose top and
bottom degree coefficients store psi-class intersection numbers and orbifold
Euler characteristics of $\overline{\mathcal M}_{g,n}$, respectively.
Furthermore, they ask whether the enumeration is governed by the topological
recursion and whether the intermediate coefficients also store
algebro-geometric information. In this paper, we prove that the enumeration
does indeed satisfy the topological recursion, although with a modification to
the initial spectral curve data. Thus, one can consider this to be one of the
first known instances of a natural enumerative problem governed by the
so-called local topological recursion. Combining the present work with the
known relation between local topological recursion and cohomological field
theory should uncover the geometric meaning of the intermediate coefficients of
the aforementioned polynomials.


  I present a streamlined review of how the separate universe approach to
cosmological perturbation theory can be used to study the dynamics of
long-wavelength scalar perturbations in loop quantum cosmology, and then use it
to calculate how long-wavelength curvature perturbations evolve across the loop
quantum cosmology bounce assuming a constant equation of state. A similar
calculation is possible for tensor modes using results from a complementary
approach to cosmological perturbation theory in loop quantum cosmology based on
an effective Hamiltonian constraint. An interesting result is that the
tensor-to-scalar ratio can be suppressed or amplified by quantum gravity
effects during the bounce, depending on the equation of state of the matter
field dominating the dynamics. In particular, if the equation of state lies
between -1/3 and 1, the value of the tensor-to-scalar ratio will be suppressed
during the bounce, in some cases significantly.


  It is well known that cohomology with compact supports is not a homotopy
invariant but only a proper homotopy one. However, as the proper category lacks
of general categorical properties, a Brown representability theorem type does
not seem reachable. However, by proving such a theorem for the so called
exterior cohomology in the complete and cocomplete exterior category, we show
that the $n$-th cohomology with compact supports of a given countable, locally
finite, finite dimensional relative CW-complex $(X,\mathbb{R}_+)$ is naturally
identified with the set $[X,K_n]^{\mathbb{R}_+}$ of exterior based homotopy
classes from a "classifying space" $K_n$. We also show that this space has the
exterior homotopy type of the exterior Eilenberg-MacLane space for
Brown-Grossman homotopy groups of type $(R^\infty,n)$, $R$ being the fixed
coefficient ring.


  Information distance can be defined not only between two strings but also in
a finite multiset of strings of cardinality greater than two. We give an
elementary proof for expressing the information distance in terms of plain
Kolmogorov complexity. It is exact since for each cardinality of the multiset
the lower bound for some multiset equals the upper bound for all multisets up
to a constant additive term.


  In this article, the results from a series of muon flux measurements
conducted at the Kimballton Underground Research Facility (KURF), Virginia,
United States, are presented. The detector employed for these investigations,
is made of plastic scintillator bars readout by wavelength shifting fibers and
multianode photomultiplier tubes. Data was taken at several locations inside
KURF, spanning rock overburden values from ~ 200 to 1450 m.w.e. From the
extracted muon rates an empirical formula was devised, that estimates the muon
flux inside the mine as a function of the overburden. The results are in good
agreement with muon flux calculations based on analytical models and MUSIC.