  We generally study whether or not the information of an open quantum system
could be totally erased by its surrounding environment in the long time. For a
harmonic oscillator coupled to a bath of a spectral density with zero-value
regions, we quantitatively present a threshold of system-bath coupling
\eta_{c}, above which the initial information of the system can remains
partially as its long time stablization deviates from the usual thermalization.
This non-thermal stabilization happens as a non-Markovian effect.


  A characterization of multiplicative (and additive) arithmetical functions is
given. Using this characterization, we show that the group of multiplicative
arithmetical functions is isomorphic to the group of additive arithmetical
functions.


  We investigate the circular motion of charged test particles in the
gravitational field of a charged mass described by the Reissner-Nordstr\"om
(RN) spacetime. We study in detail all the spatial regions where circular
motion is allowed around either black holes or naked singularities. The effects
of repulsive gravity are discussed by finding all the circles at which a
particle can have vanishing angular momentum. We show that the geometric
structure of stable accretion disks, made of only test particles moving along
circular orbits around the central body, allows us to clearly distinguish
between black holes and naked singularities.


  We describe a criterion for a real or complex hyperbolic lattice to admit a
RFRS tower that consists entirely of congruence subgroups. We use this to show
that certain Bianchi groups $\mathrm{PSL}(\mathcal{O}_d)$ are virtually fibered
on congruence subgroups, and also exhibit the first examples of RFRS K\"ahler
groups that are not a subgroup of a product of surface groups and abelian
groups.


  In this paper, we study the monitoring and control of long-term voltage
stability considering load tap-changer (LTC) dynamics. We show that under
generic conditions, the LTC dynamics always admit a unique stable equilibrium.
For the stable equilibrium, we characterize an explicit inner approximation of
its region of attraction (ROA). Compared to existing results, the computational
complexity of the ROA characterization is drastically reduced. A quadratically
constrained linear program formulation for the ROA characterization problem is
proposed. In addition, we formulate a second-order cone program for online
voltage stability monitoring and control exploiting the proposed ROA
characterization, along with an ADMM-based distributed algorithm to solve the
problem. The efficacy of the proposed formulations and algorithms is
demonstrated using a standard IEEE test system.


  The leading beta_0^(n-1) alpha_s^n terms in the Wilson coefficient and
anomalous dimension of the chromomagnetic operator in the heavy-quark effective
Lagrangian are summed to all orders of perturbation theory. The perturbation
series for the anomalous dimension is well behaved, while that for the Wilson
coefficient exhibits a divergent behaviour already in low orders, caused by a
nearby infrared renormalon singularity. The resulting ambiguity is commensurate
with terms of order 1/m^2 in the effective Lagrangian, whose corresponding
ultraviolet renormalons are identified. An excellent approximation for the
scheme-invariant Wilson coefficient at next-to-next-to-leading order in
renormalization-group improved perturbation theory is obtained.


  We propose a new method to extract |Vtd/Vts| from the ratio of the decay
distributions dR/ds = dB(B->Xdl+l-)/ds/dB(B->Xsl+l-)/ds. This ratio depends
only on the KM ratio |Vtd/Vts| with 15% theoretical uncertainties, if dilepton
invariant mass-squared s is away from the peaks of the possible resonance
states, J/psi, psiprime, and etc. We also give a detailed analytical and
numerical analysis on dB(B-Xql+l-)/ds (q=d,s) and dR/ds.


  The Pontryagin's Maximum Principle allows, in most cases, the design of
optimal controls of affine nonlinear control systems by considering the sign of
a smooth function. There are cases, although, where this function vanishes on a
whole time interval and the Pontryagin's Maximum Principle alone does not give
enough information to design the control. In these cases one considers the time
derivatives of this function until a k-order derivative that explicitly depends
on the control variable. The number q=k/2 is called problem order and it is the
same to all the extremals. The local order is a related concept used in
literature, but depending on each particular extremal. The confusion between
these two concepts led to misunderstandings in past works, where the problem
order was assumed to be an integer number. In this work we prove that this is
true if the control system has a single input but, in general, it is not true
if the control system has a multiple input.


  The problem of clustering large complex networks plays a key role in several
scientific fields ranging from Biology to Sociology and Computer Science. Many
approaches to clustering complex networks are based on the idea of maximizing a
network modularity function. Some of these approaches can be classified as
global because they exploit knowledge about the whole network topology to find
clusters. Other approaches, instead, can be interpreted as local because they
require only a partial knowledge of the network topology, e.g., the neighbors
of a vertex. Global approaches are able to achieve high values of modularity
but they do not scale well on large networks and, therefore, they cannot be
applied to analyze on-line social networks like Facebook or YouTube. In
contrast, local approaches are fast and scale up to large, real-life networks,
at the cost of poorer results than those achieved by local methods. In this
article we propose a glocal method to maximizing modularity, i.e., our method
uses information at the global level, yet its scalability on large networks is
comparable to that of local methods. The proposed method is called COmplex
Network CLUster DEtection (or, shortly, CONCLUDE.) It works in two stages: in
the first stage it uses an information-propagation model, based on random and
non-backtracking walks of finite length, to compute the importance of each edge
in keeping the network connected (called edge centrality.) Then, edge
centrality is used to map network vertices onto points of an Euclidean space
and to compute distances between all pairs of connected vertices. In the second
stage, CONCLUDE uses the distances computed in the first stage to partition the
network into clusters. CONCLUDE is computationally efficient since in the
average case its cost is roughly linear in the number of edges of the network.


  We characterize the image of radial positive measures $\theta$'s on a
harmonic $NA$ group $S$ which satisfies $\int_S\phi_0(x)\,d\theta(x)<\infty$
under the spherical transform, where $\phi_0$ is the elementary spherical
function.


  In this paper, we prove that for $\frac{n}{2}+\frac{1}{4}<\alpha
\leq\frac{n+1}{2} $, the convolution operator $$S_{\alpha} f(x)=\int_{|y| \geq
1} f(x-y)\left(|y|^{2}-1\right)^{-\alpha} d y$$ is bounded from $L^p$ to $L^q$
for certain values of $p$ and $q$.


  The Friedman--Mineyev theorem, earlier known as the (strengthened) Hanna
Neumann conjecture, gives a sharp estimate for the rank of the intersection of
two subgroups in a free group. We obtain an analogue of this inequality for any
two subgroups in a virtually free group (or, more generally, in a group
containing a free product of left-orderable groups as a finite-index subgroup).


  Proportional electroluminescence (EL) is the physical effect used in
two-phase detectors for dark matter searches, to optically record (in the gas
phase) the ionization signal produced by particle scattering in the liquid
phase. In our previous work the presence of a new EL mechanism, namely that of
neutral bremsstrahlung (NBrS), was demonstrated in two-phase argon detectors
both theoretically and experimentally, in addition to the ordinary EL mechanism
due to excimer emission. In this work the similar theoretical approach is
applied to all noble gases, i.e. overall to helium, neon, argon, krypton and
xenon, to calculate the EL yields and spectra both for NBrS and excimer EL. The
relevance of the results obtained to the development of two-phase dark matter
detectors is discussed.


  We explicitly prove the quantum modularity of partial theta series with even
or odd periodic coefficients. As an application, we show that the
Kontsevich-Zagier series $\mathscr{F}_t(q)$ which matches (at a root of unity)
the colored Jones polynomial for the family of torus knots $T(3,2^t)$, $t \geq
2$, is a weight $3/2$ quantum modular form. This generalizes Zagier's result on
the quantum modularity for the "strange" series $F(q)$.


  Pairing Correlations are studied numerically in the hole-doped spin-fermion
model for cuprates. Simulations performed on up to 12x12 clusters provide
robust indications of D-wave superconductivity away from half-filling. The
pairing correlations are the strongest in the direction perpendicular to the
dynamic stripe-like inhomogeneities that appear in the ground state at some
densities. An optimal doping, where the correlations reach a maximum value, was
observed at about 25% doping, in qualitative agreement with hight T_{c}
cuprates' experiments. On the other hand, pairing correlations are suppressed
by static stripe inhomogeneities.


  The tables of this title are a first attempt to understand empirically the
sizes of certain distinguished sets, introduced by Hankyung Ko, of elements in
affine Weyl groups. The sizes are relevant to the computational efficiency of
direct approaches to computing characters of modular representations of
algebraic groups from characters of corresponding irreducible representations
of quantum groups.


  In this paper, we study the geometric phase (GP) of two-mode entangled
squeezed-coherent states (ESCSs), undergoing a unitary cyclic evolution. It is
revealed that by increasing the squeezing parameter of the first or the second
mode of a balanced ESCS, the GP compresses in an elliptical manner along the
axis of the coherence parameter of the corresponding mode. While in the case of
unbalanced ESCS, the GP compresses in a hyperbolic manner by increasing the
squeezing parameters of either mode. By generalizing to higher
constituting-state dimensions, it is found that the GPs of both balanced and
unbalanced ESCSs, increase for a specific value of the coherence parameter.
Based on these findings, using the interferometry approach, we suggest a
theoretical scheme for the physical generation of the balanced ESCS.


  We show that any star-shaped convex hypersurface with constant Weingarten
curvature in the deSitter-Schwarzschild manifold is a sphere of symmetry.
Moreover, we study an isoperimetric problem for bounded domains in the doubled
Schwarzschild manifold. We prove the existence of an isoperimetric surface for
any value of the enclosed volume, and we completely describe the isoperimetric
surfaces for very large enclosed volume. This complements work in H. Bray's
thesis, where isoperimetric surfaces homologous to the horizon are studied.


  The majority of massive stars are formed in binary systems. It is hence
reasonable to expect that most core-collapse supernovae (CCSNe) take place in
binaries and the existence of a companion star may leave some imprints in
observed features. Having this in mind, we have conducted two-dimensional
hydrodynamical simulations of the collisions of CCSNe ejecta with the companion
star in an almost-equal-mass ($\sim 10M_\odot$) binary to find out possible
consequences of such events. In particular we pay attention to the amount of
mass removed and its dependence on the binary separation. In contrast to the
previous surmise, we find that the companion mass is stripped not by momentum
transfer but by shock heating. Up to $25\%$ of the original mass can be removed
for the closest separations and the removed mass decreases as $M_{ub} \propto
a^{-4.3}$ with the binary separation $a$. By performing some experimental
computations with artificially-modified densities of incident ejecta, we show
that if the velocity of ejecta is fixed, the density of incident ejecta is the
single important parameter that actually determines the removed mass as $M_{ub}
\propto \rho_{ej} ^{1.4} $. On the other hand, another set of simulations with
modified velocities of incident ejecta demonstrate that the strength of the
forward shock, which heats up the stellar material and causes the mass loss of
the companion star, is actually the key parameter for the removed mass.


  In the present paper we investigate in how far stars with an initial mass
larger than 40Mo affect the chemical enrichment of the Galaxy. We illustrate
the importance for chemical yields of a most up to date treatment of the
various stellar wind mass loss episodes in stellar evolutionary codes and we
discuss the effects of a possible supernova-like outburst prior to massive
black hole formation.


  In this paper, the results obtained from the polarimetric study of a Bok
globule CB17 in both optical and sub-millimeter wavelength are presented. The
optical polarimetric observations in R-band ($\lambda$ = 630 nm, $\Delta
\lambda$ = 120 nm) were conducted from 1.04-meter Sampurnanand Telescope,
ARIES, Nainital, India on 9th March 2016, while, the sub-mm polarimetric data
are taken from the SCUPOL data archive which has been reanalyzed. The contours
of Herschel\footnote{Herschel is an ESA space observatory with science
instruments provided by European-led Principal Investigator consortia and with
important participation from NASA.} SPIRE 500$\mu m$ dust continuum emissions
of CB17 (typically a cometary-shaped globule) are overlaid on the DSS image of
CB17 along with polarization vectors (optical and submm). The magnetic field
strength at the core of the globule is estimated to be $99\mu$G. Using the
Near-Infrared photometric technique and \emph{Gaia} data, the distance to CB17
is found to be $253 \pm 43$ parsec. A correlation between the various
quantities of the globule is also studied. It is observed that the magnetic
field in the cloud core as revealed by polarization measurements at the
sub-millimeter dust emission is found to be almost aligned along the minor axis
of the globule which fits the magnetically regulated star formation model. The
misalignment between core-scale magnetic field direction and molecular outflow
direction is also found.


  The purpose of this paper is to study rank metric codes over Galois rings. In
particular, we prove MacWilliams identities for finite chain rings relating the
sequences of $q$-binomial moments of a code and its dual and for Gabidulin
analogues of free codes over Galois rings we prove the corresponding
MacWilliams identity as a functional expression relating the weight enumerator
of the dual with the MacWilliams transform of the weight enumerator of the
original code plus one extra term attached to the zero divisors.


  According to idealized models, a strong Kerr non-linearity may be used to
build optical quantum gates for optical quantum information processing by
inducing conditional phase shifts on quantum states. Recently, Shapiro (PRA 73,
062305 (2006)) argued that for a Kerr medium with non-instantaneous but fast
response, essentially no phase shift is induced on two-single-photon input
states, and thus a quantum gate build from such a medium cannot work. Here we
show that a fast response Kerr medium induces some but very little phase shifts
on a two-single-photon input state, and it is insufficient for high fidelity
quantum computation. We point out that this is caused by the medium imparting
spectral entanglement to the input photons. We further show that a way to
circumvent this problem and achieve a high fidelity gate, is to engineer the
dispersion properties of the medium to give a dominant spectral effect over the
non-instantaneous response, in addition to satisfying a phase matching
condition.


  In this paper, we propose a class of linear codes and obtain their weight
distribution. Some of these codes are almost optimal. Moreover, several classes
of constant composition codes(CCCs) are constructed as subcodes of linear
codes.


  Random walks of particles on a lattice are a classical paradigm for the
microscopic mechanism underlying diffusive processes. In deterministic walks,
the role of space and time can be reversed, and the microscopic dynamics can
produce quite different types of behavior such as directed propagation and
organization, which appears to be generic behaviors encountered in an important
class of systems. The various aspects of classical and not so classical walks
on latices are reviewed with emphasis on the physical phenomena that can be
treated through a lattice dynamics approach.


  Many subjective experiments have been performed to develop objective speech
intelligibility measures, but the novel coronavirus outbreak has made it very
difficult to conduct experiments in a laboratory. One solution is to perform
remote testing using crowdsourcing; however, because we cannot control the
listening conditions, it is unclear whether the results are entirely reliable.
In this study, we compared speech intelligibility scores obtained in remote and
laboratory experiments. The results showed that the mean and standard deviation
(SD) of the remote experiments' speech reception threshold (SRT) were higher
than those of the laboratory experiments. However, the variance in the SRTs
across the speech-enhancement conditions revealed similarities, implying that
remote testing results may be as useful as laboratory experiments to develop an
objective measure. We also show that the practice session scores correlate with
the SRT values. This is a priori information before performing the main tests
and would be useful for data screening to reduce the variability of the SRT
distribution.


  In this paper, we present a framework for resource allocations for multicast
device-to-device (D2D) communications underlaying a cellular network. The
objective is to maximize the sum throughput of active cellular users (CUs) and
feasible D2D groups in a cell, while meeting a certain
signal-to-interferenceplus- noise ratio (SINR) constraint for both the CUs and
D2D groups. We formulate the problem of power and channel allocation as a mixed
integer nonlinear programming (MINLP) problem where one D2D group can reuse the
channels of multiple CUs and the channel of each CU can be reused by multiple
D2D groups. Distinct from existing approaches in the literature, our
formulation and solution methods provide an effective and flexible means to
utilize radio resources in cellular networks and share them with multicast
groups without causing harmful interference to each other. A variant of the
generalized bender decomposition (GBD) is applied to optimally solve the MINLP
problem. A greedy algorithm and a low-complexity heuristic solution are then
devised. The performance of all schemes is evaluated through extensive
simulations. Numerical results demonstrate that the proposed greedy algorithm
can achieve closeto- optimal performance, and the heuristic algorithm provides
good performance, though inferior than that of the greedy, with much lower
complexity.


  We exhibit the dynamical scattering of multi-solitons in the Skyrme model for
configurations with charge two, three and four. First, we construct maximally
attractive configurations from a simple profile function and the product
ansatz. Then using a sophisticated numerical algorithm, initially
well-separated skyrmions in approximately symmetric configurations are shown to
scatter through the known minimum energy configurations. These scattering
events illustrate a number of similarities to BPS monopole configurations of
the same charge. A simple modification of the dynamics to a dissipative regime,
allows us to compute the minimal energy skyrmions for baryon numbers one to
four to within a few percent.


  In this paper, we present a novel factor graph formulation to estimate the
pose and velocity of a quadruped robot on slippery and deformable terrain. The
factor graph introduces a preintegrated velocity factor that incorporates
velocity inputs from leg odometry and also estimates related biases. From our
experimentation we have seen that it is difficult to model uncertainties at the
contact point such as slip or deforming terrain, as well as leg flexibility. To
accommodate for these effects and to minimize leg odometry drift, we extend the
robot's state vector with a bias term for this preintegrated velocity factor.
The bias term can be accurately estimated thanks to the tight fusion of the
preintegrated velocity factor with stereo vision and IMU factors, without which
it would be unobservable. The system has been validated on several scenarios
that involve dynamic motions of the ANYmal robot on loose rocks, slopes and
muddy ground. We demonstrate a 26% improvement of relative pose error compared
to our previous work and 52% compared to a state-of-the-art proprioceptive
state estimator.


  Let $q=p^n$ with $p$ be an odd prime. Let $0\leq k\leq n-1$ and $k\neq n/2$.
In this paper we determine the value distribution of following
exponential(character) sums \[\sum\limits_{x\in \bF_q}\zeta_p^{\Tra_1^n(\alpha
x^{p^{3k}+1}+\beta x^{p^k+1})}\quad(\alpha\in \bF_{p^m},\beta\in \bF_{q})\] and
\[\sum\limits_{x\in \bF_q}\zeta_p^{\Tra_1^n(\alpha x^{p^{3k}+1}+\beta
x^{p^k+1}+\ga x)}\quad(\alpha\in \bF_{p^m},\beta,\ga\in \bF_{q})\] where
$\Tra_1^n: \bF_q\ra \bF_p$ and $\Tra_1^m: \bF_{p^m}\ra\bF_p$ are the canonical
trace mappings and $\zeta_p=e^{\frac{2\pi i}{p}}$ is a primitive $p$-th root of
unity. As applications: (1). We determine the weight distribution of the cyclic
codes $\cC_1$ and $\cC_2$ over $\bF_{p^t}$ with parity-check polynomials
$h_2(x)h_3(x)$ and $h_1(x)h_2(x)h_3(x)$ respectively where $t$ is a divisor of
$d=\gcd(n,k)$, and $h_1(x)$, $h_2(x)$ and $h_3(x)$ are the minimal polynomials
of $\pi^{-1}$, $\pi^{-(p^k+1)}$ and $\pi^{-(p^{3k}+1)}$ over $\bF_{p^t}$
respectively for a primitive element $\pi$ of $\bF_q$. (2). We determine the
correlation distribution among a family of m-sequences.


  We present a study of exclusive neutral pion production in neutrino-nucleus
Neutral Current interactions using data from the NOMAD experiment at the CERN
SPS. The data correspond to $1.44 \times 10^6$ muon-neutrino Charged Current
interactions in the energy range $2.5 \leq E_{\nu} \leq 300$ GeV. Neutrino
events with only one visible $\pi^0$ in the final state are expected to result
from two Neutral Current processes: coherent $\pi^0$ production, {\boldmath
$\nu + {\cal A} \to \nu + {\cal A} + \pi^0$} and single $\pi^0$ production in
neutrino-nucleon scattering. The signature of coherent $\pi^0$ production is an
emergent $\pi^0$ almost collinear with the incident neutrino while $\pi^0$'s
produced in neutrino-nucleon deep inelastic scattering have larger transverse
momenta. In this analysis all relevant backgrounds to the coherent $\pi^0$
production signal are measured using data themselves. Having determined the
backgrounds, and using the Rein-Sehgal model for the coherent $\pi^0$
production to compute the detection efficiency, we obtain {\boldmath $4630 \pm
522 (stat) \pm 426 (syst)$} corrected coherent-$\pi^0$ events with $E_{\pi^0}
\geq 0.5$ GeV. We measure {\boldmath $\sigma (\nu {\cal A} \to \nu {\cal A}
\pi^0) = [ 72.6 \pm 8.1(stat) \pm 6.9(syst) ] \times 10^{-40} cm^2/nucleus$}.
This is the most precise measurement of the coherent $\pi^0$ production to
date.


  We have performed a low temperature scanning tunneling microscopy and
spectroscopy study of the iron chalcogenide superconductor FeSe_{0.4}Te_{0.6}
with T_{C}~14 K. Spatially resolved measurements of the superconducting gap
reveal substantial inhomogeneity on a nanometer length scale. Analysis of the
structure of the gap seen in tunneling spectra by comparison with calculated
spectra for different superconducting order parameters (s-wave, d-wave, and
anisotropic s-wave) yields the best agreement for an order parameter with
anisotropic s-wave symmetry with an anisotropy of ~40%. The temperature
dependence of the superconducting gap observed in places with large and small
gap size indicates that it is indeed the superconducting transition temperature
which is inhomogeneous. The temperature dependence of the gap size is
substantially larger than would be expected from BCS theory. An analysis of the
local gap size in relation with the local chemical composition shows almost no
correlation with the local concentration of Se-/Te-atoms at the surface.


  On an algebraic curve there are Tate symbols, which satisfy Weil reciprocity
law. The analogues in higher dimensions are the Parshin symbols, which satisfy
Kato-Parshin reciprocity laws. We give a refinement of the Parshin symbol for
surfaces, using iterated integrals in the sense of Chen. The product of the
refined symbol over the cyclic permutations of the functions recovers the
Parshin symbol. Also, we construct a logarithmic version of the Parshin symbol.
We prove reciprocity laws for both the refined symbol and a logarithm of the
Parshin symbol.


  This paper presents and analyzes an incremental algorithm for the
construction of Acyclic Non-deterministic Finite-state Automata (NFA). Automata
of this type are quite useful in computational linguistics, especially for
storing lexicons. The proposed algorithm produces compact NFAs, i.e. NFAs that
do not contain equivalent states. Unlike Deterministic Finite-state Automata
(DFA), this property is not sufficient to ensure minimality, but still the
resulting NFAs are considerably smaller than the minimal DFAs for the same
languages.


  We discuss an approach to the component separation of microwave,
multi-frequency sky maps as those typically produced from Cosmic Microwave
Background (CMB) Anisotropy data sets. The algorithm is based on the two step,
parametric, likelihood-based technique recently elaborated on by Eriksen et
al., (2006), where the foreground spectral parameters are estimated prior to
the actual separation of the components. In contrast with the previous
approaches, we accomplish the former task with help of an analytically-derived
likelihood function for the spectral parameters, which, we show, yields
estimates equal to the maximum likelihood values of the full multi-dimensional
data problem. We then use these estimates to perform the second step via the
standard, generalized-least-square-like procedure. We demonstrate that the
proposed approach is equivalent to a direct maximization of the full data
likelihood, which is recast in a computationally tractable form. We use the
corresponding curvature matrices to characterize statistical properties of the
recovered parameters. We incorporate in the formalism some of the essential
features of the CMB data sets, such as inhomogeneous pixel domain noise,
unknown map offsets as well as calibration errors and study their consequences
for the separation. We find that the calibration is likely to have a dominant
effect on the precision of the spectral parameter determination for a realistic
CMB experiment. We apply the algorithm to simulated data and discuss the
results. Our focus is on partial-sky, total-intensity and polarization, CMB
experiments such as planned balloon-borne and ground-based efforts, however,
the techniques presented here should be also applicable to the full-sky data as
for instance, those produced by WMAP and anticipated from Planck.


  In semiconducting solar-cell absorbers, high absorption coefficient (alpha)
near the band-edge region is critical to maximize the photocurrent generation
and collection. Nevertheless, despite the importance of the band-edge
absorption characteristics, the quantitative analysis of the band-edge optical
transitions has not been performed. In this study, we have implemented
systematic density functional theory (DFT) calculation, focusing on the
band-edge oscillator strength of seven practical solar cell absorbers (GaAs,
InP, CdTe, CuInSe2, CuGaSe2, Cu2ZnSnSe4, and Cu2ZnSnS4) with zincblende,
chalcopyrite and kesterite structures. We find that all these crystals exhibit
the giant oscillator strength near the band gap region, revealing the fact that
alpha in the band gap region is enhanced significantly by the anomalous high
oscillator strength. In high-energy optical transitions, however, the
oscillator strength reduces sharply and the absorption properties are
determined primarily by the joint density-of-state contribution. Based on DFT
results, we show that the giant oscillator strength in the band edge region
originates from a unique tetrahedral-bonding structure, with a negligible
effect of constituent atoms.


  We propose a simple and efficient scheme based on adaptive finite elements
over conforming quadtree meshes for collapse plastic analysis of structures.
Our main interest in kinematic limit analysis is concerned with both purely
cohesive-frictional and cohesive materials. It is shown that the most
computational efficiency for collapse plastic problems is to employ an adaptive
mesh strategy on quadtree meshes. However, a major difficulty in finite element
formulations is the appearance of hanging nodes during adaptive process. This
can be resolved by a definition of conforming quadtree meshes in the context of
polygonal elements. Piecewise-linear shape functions enhanced with generalized
bubble functions in barycentric coordinates are used to approximate the
velocity field. Numerical results prove the reliability and benefit of the
present approach.


  Magnesium and its alloys are ideal for biodegradable implants due to their
biocompatibility and their low-stress shielding. However, they can corrode too
rapidly in the biological environment. The objective of this research was to
develop heat treatments to slow the corrosion of high purified magnesium and
AZ31 alloy in simulated body fluid at 37{\deg}C. Heat treatments were performed
at different temperatures and times. Hydrogen evolution, weight loss, PDP, and
EIS methods were used to measure the corrosion rates. Results show that heat
treating can increase the corrosion resistance of HP-Mg by 2x and AZ31 by 10x.


  The precision measurements of the cosmic microwave background power spectrum
put a strong constraint on the dark matter annihilation cross section since the
electromagnetic energy injection by the dark matter annihilation affects the
ionization history of the universe. In this paper, we update our previous
simulation code for calculating the ionization history with the effect of dark
matter annihilation by including Helium interactions and improving the
precision of calculations. We give an updated constraint on the annihilation
cross section and mass of dark matter using the modified RECFAST code with the
Planck 2018 datasets.


  We study the long-range directed polymer model on $\mathbbm{Z}$ in a random
environment, where the underlying random walk lies in the domain of attraction
of an $\alpha$-stable process for some $\alpha\in(0,2]$. Similar to the more
classic nearest-neighbor directed polymer model, as the inverse temperature
$\beta$ increases, the model undergoes a transition from a weak disorder regime
to a strong disorder regime. We extend most of the important results known for
the nearest-neighbor directed polymer model on $\mathbbm{Z}^d$ to the
long-range model on $\mathbbm{Z}$. More precisely, we show that in the entire
weak disorder regime, the polymer satisfies an analogue of invariance
principle, while in the so-called very strong disorder regime, the polymer end
point distribution contains macroscopic atoms and under some mild conditions,
the polymer has a super-$\alpha$-stable motion. Furthermore, for $\alpha \in
(1,2]$, we show that the model is in the very strong disorder regime whenever
$\beta>0$, and we give explicit bounds on the free energy.


  In this paper, we study the stability and instability of the ground states
for the focusing inhomogeneous nonlinear Schr\"{o}dinger equation with
inverse-square potential (for short, INLS$_c$ equation): \[iu_{t} +\Delta
u+c|x|^{-2}u+|x|^{-b} |u|^{\sigma } u=0,\; u(0)=u_{0}(x) \in H^{1},\;(t,x)\in
\mathbb R\times\mathbb R^{d},\] where $d\ge3$, $0<b<2$,
$0<\sigma<\frac{4-2b}{d-2}$ and $c\neq 0$ be such that
$c<c(d):=\left(\frac{d-2}{2}\right)^{2}$. In the mass-subcritical case
$0<\sigma<\frac{4-2b}{d}$, we prove the stability of the set of ground states
for the INLS$_{c}$ equation. In the mass-critical case $\sigma=\frac{4-2b}{d}$,
we first prove that the solution of the INLS$_c$ equation with initial data
$u_{0}$ satisfying $E(u_0)<0$ blows up in finite or infinite time. Using this
fact, we then prove that the ground state standing waves are unstable by
blow-up. In the intercritical case $\frac{4-2b}{d}<\sigma<\frac{4-2b}{d-2}$, we
finally show the instability of ground state standing waves for the INLS$_c$
equation.


  In financial time series there are periods in which the value increases or
decreases monotonically. We call those periods elemental trends and study the
probability distribution of their duration for the indices DJIA, NASDAQ and
IPC. It is found that the trend duration distribution often differs from the
one expected under no memory. The expected and observed distributions are
compared by means of the Anderson-Darling test.


  Disentangling the dynamics of electrons and nuclei during nonadiabatic
molecular transformations remains a considerable experimental challenge. Here
we have investigated photoinduced electron transfer dynamics following a
metal-to-ligand charge-transfer (MLCT) excitation of the [Fe(bmip)2]2+
photosensitizer, where bmip = 2,6-bis(3-methyl-imidazole-1- ylidine)-pyridine,
with simultaneous femtosecond-resolution Fe K{\alpha} and K\b{eta} X-ray
Emission Spectroscopy (XES) and Wide Angle X-ray Scattering (WAXS). This
measurement clearly shows temporal oscillations in the XES and WAXS difference
signals with the same 278 fs period oscillation. The oscillatory signal
originates from an Fe-ligand stretching mode vibrational wavepacket on a
triplet metal-centered (3MC) excited state surface. The vibrational wavepacket
is created by 40% of the excited population that undergoes electron transfer
from the non-equilibrium MLCT excited state to the 3MC excited state with a 110
fs time constant, while the other 60% relaxes to a 3MLCT excited state in
parallel. The sensitivity of the K{\alpha} XES spectrum to molecular structure
results from core-level vibronic coupling, due to a 0.7% average Fe-ligand bond
length difference in the lowest energy geometry of the 1s and 2p core-ionized
states. These results highlight the importance of vibronic effects in
time-resolved XES experiments and demonstrate the role of metal-centered
excited states in the electronic excited state relaxation dynamics of an Fe
carbene photosensitizer.


  We have measured the Fundamental Plane (FP) parameters for a sample of 30
field early-type galaxies (E/S0) in the redshift range 0.1<z<0.66. We find
that: i) the FP is defined and tight out to the highest redshift bin; ii) the
intercept \gamma evolves as d\gamma/dz=0.58+0.09-0.13 (for \Omega=0.3,
\Omega_{\Lambda}=0.7), or, in terms of average effective mass to light ratio,
as d\log(M/L_B)/dz=-0.72+0.11-0.16, i.e. faster than is observed for cluster
E/S0 -0.49+-0.05. In addition, we detect [OII] emission >5\AA in 22% of an
enlarged sample of 42 massive E/S0 in the range 0.1<z<0.73, in contrast with
the quiescent population observed in clusters at similar z. We interpret these
findings as evidence that a significant fraction of massive field E/S0
experiences secondary episodes of star-formation at z<1.


  In this chapter, we present our recent invention, i.e., the notion of the
value of information$\unicode{x2014}$a semantic metric that is fundamental for
networked control systems tasks. We begin our analysis by formulating a causal
tradeoff between the packet rate and the regulation cost, with an encoder and a
decoder as two distributed decision makers, and show that the valuation of
information is conceivable and quantifiable grounded on this tradeoff. More
precisely, we characterize an equilibrium, and quantify the value of
information there as the variation in a value function with respect to a piece
of sensory measurement that can be communicated from the encoder to the decoder
at each time. We prove that, in feedback control of a dynamical process over a
noiseless channel, the value of information is a function of the discrepancy
between the state estimates at the encoder and the decoder, and that a data
packet containing a sensory measurement at each time should be exchanged only
if the value of information at that time is nonnegative. Finally, we prove that
the characterized equilibrium is in fact globally optimal.


  In this paper, we investigate fast algorithms in the small fraction order
regime to approximate the Caputo derivative $^C_0D_t^\alpha u(t)$ when $\alpha$
is small. We focus on two fast algorithms, i.e. FIR and FIDR, both relying on
the sum-of-exponential approximation to reduce the cost of evaluating the
history part. FIR is the numerical scheme originally proposed in [16], and FIDR
is an alternative scheme proposed in [26], and we show that the latter is
superior when $\alpha$ is small. With quantitative estimates, we prove that
given a certain error threshold, the computational cost of evaluating the
history part of the Caputo derivative can be decreased as $\alpha$ gets small.
Hence, only minimal cost for the fast evaluation is required in the small
$\alpha$ regime, which matches prevailing protocols in engineering practice. We
also present improved stability and error analysis of FIDR for solving linear
fractional diffusion equations, which achieves clear dependence of the error
bound on the fraction order $\alpha$. Finally, we carry out systematic
numerical studies for the performances of both FIR and FIDR schemes, where we
explore the trade-off between accuracy and efficiency when $\alpha$ is small.


  In the recent decade, the research field using arrays of high-index-contrast
near-wavelength dieletric structures on flat surfaces, known as high-contrast
metastructures (HCMs) or metasurfaces, has emerged and expanded rapidly.
Although the HCMs and metasurfaces share great similarities in physical
structures with photonic crystals (PhCs), i.e. periodic nanostructures, many
differences exist in their design, analysis, operation conditions, and
applications. In this paper, we provide a generalized theoretical understanding
of the two subjects and show their intrinsic connections. We further discuss
the simulation and design approaches, categorized by their functionalities and
applications. The similarity and differences between HCMs, metasurfaces and
PhCs are also discussed. New findings are presented regarding the physical
connection between the PhC band structures and the 1D and 2D HCM scattering
spectra under transverse and longitudinal tilt incidence. Novel designs using
HCMs as holograms, spatial light modulators, and surface plasmonic couplers are
discussed. Recent advances on HCMs, metasurfaces and PhCs are reviewed and
compared for applications such as broadband mirrors, waveguides, couplers,
resonators, and reconfigurable optics.


  We consider a family of optimal control problems in the plane with dynamics
and running costs possibly discontinuous across a two-scale oscillatory
interface. Typically, the amplitude of the oscillations is of the order of
$\epsilon$ while the period is of the order of $\epsilon$ 2. As $\epsilon$
$\rightarrow$ 0, the interfaces tend to a straight line $\Gamma$. We study the
asymptotic behavior of the value function as $\epsilon$ $\rightarrow$ 0. We
prove that the value function tends to the solution of Hamilton-Jacobi
equations in the two half-planes limited by $\Gamma$, with an effective
transmission condition on $\Gamma$ keeping track of the oscillations.


  Deep-learning models for language generation tasks tend to produce repetitive
output. Various methods have been proposed to encourage lexical diversity
during decoding, but this often comes at a cost to the perceived fluency and
adequacy of the output. In this work, we propose to ameliorate this cost by
using an Imitation Learning approach to explore the level of diversity that a
language generation model can reliably produce. Specifically, we augment the
decoding process with a meta-classifier trained to distinguish which words at
any given timestep will lead to high-quality output. We focus our experiments
on concept-to-text generation where models are sensitive to the inclusion of
irrelevant words due to the strict relation between input and output. Our
analysis shows that previous methods for diversity underperform in this
setting, while human evaluation suggests that our proposed method achieves a
high level of diversity with minimal effect to the output's fluency and
adequacy.


  With much higher sensitivities due to coherence effects, it is often assumed
that the first evidence for direct dark matter detection will come from
experiments probing spin-independent interactions. We explore models that would
be invisible in such experiments, but detectable via spin-dependent
interactions. The existence of much larger (or even only) spin-dependent
tree-level interactions is not sufficient, due to potential spin-independent
subdominant or loop-induced interactions. We find that in such a way most
models with detectable spin-dependent interactions would also generate
detectable spin-independent interactions. Models in which a light pseudoscalar
acts as the mediator seem to uniquely evade this conclusion. We present a
particular viable dark matter model generating such an interaction.


  Clear power excess in a frequency range typical for solar-type oscillations
in red giants has been detected in more than 1000 stars, which have been
observed during the first 138 days of the science operation of the NASA Kepler
satellite. This sample includes stars in a wide mass and radius range with
spectral types G and K, extending in luminosity from the bottom of the giant
branch up to high-luminous red giants. The high-precision asteroseismic
observations with Kepler provide a perfect source for testing stellar structure
and evolutionary models, as well as investigating the stellar population in our
Galaxy. We fit a global model to the observed frequency spectra, which allows
us to accurately estimate the granulation background signal and the global
oscillation parameters, such as the frequency of maximum oscillation power. We
find regular patterns of radial and non-radial oscillation modes and use a new
technique to automatically identify the mode degree and the characteristic
frequency separations between consecutive modes of the same spherical degree.
In most cases, we can also measure the small separation. The seismic parameters
are used to estimate stellar masses and radii and to place the stars in an H-R
diagram by using an extensive grid of stellar models that covers a wide
parameter range. Using Bayesian techniques throughout our analysis allows us to
determine reliable uncertainties for all parameters. We provide accurate
seismic parameters and their uncertainties for a large sample of red giants and
determine their asteroseismic fundamental parameters. We investigate the
influence of the stars' metallicities on their positions in the H-R diagram. We
study the red-giant populations in the red clump and bump and compare them to a
synthetic population and find a mass and metallicity gradient in the red clump
and clear evidence of a secondary-clump population.


  During the research cruise AL547 with RV ALKOR (October 20-31, 2020), a
collaborative underwater network of ocean observation systems was deployed in
Boknis Eck (SW Baltic Sea, German exclusive economic zone (EEZ)) in the context
of the project ARCHES (Autonomous Robotic Networks to Help Modern Societies).
This network was realized via a Digital Twin Prototype approach. During that
period different scenarios were executed to demonstrate the feasibility of
Digital Twins in an extreme environment such as underwater. One of the
scenarios showed the collaboration of stage IV Digital Twins with their
physical counterparts on the seafloor. This way, we address the research
question, whether Digital Twins represent a feasible approach to operate mobile
ad hoc networks for ocean and coastal observation.


  To handle with inverse problems, two probabilistic approaches have been
proposed: the maximum entropy on the mean (MEM) and the Bayesian estimation
(BAYES). The main object of this presentation is to compare these two
approaches which are in fact two different inference procedures to define the
solution of an inverse problem as the optimizer of a compound criterion.
Keywords: Inverse problems, Maximum Entropy on the Mean, Bayesian inference,
Convex analysis.


  The pronounced dependence of the nonlinear parameters of both dielectric and
semiconductor materials on the wavelength, and the nonlinear interaction
between the ultra-short laser pulse and the material requires precise control
of the wavelength of the pulse, in addition to the precise control of the pulse
energy, pulse duration and focusing optics. This becomes particularly important
for fine sub-wavelength single pulse sub-surface processing. Based on two
different numerical models and taking Si as example material, we investigate
the spatio-temporal behavior of a pulse propagating through the material while
covering a broad range of parameters. The wavelength-dependence of material
processing depends on the different contributions of two- and tree-photon
absorption in combination with the Kerr effect which results in a particularly
sharp nonlinear peak at ~2100 nm. We could show that in silicon this makes
processing preferable close to this wavelength. The impact of the nonlinear
nonparaxial propagation effects on spatio-temporal beam structure is also
investigated. It could be shown that with increasing wavelength and large
focusing angles the aberrations at the focal spot can be reduced, and thereby
cleaner and more precise processing can be achieved. Finally, we could show
that the optimum energy transfer from the pulse to the material is within a
narrow window of pulse durations between 600 to 900 fs.


  Semi-Supervised Variational Autoencoders (SSVAEs) are widely used models for
data efficient learning. In this paper, we question the adequacy of the
standard design of sequence SSVAEs for the task of text classification as we
exhibit two sources of overcomplexity for which we provide simplifications.
These simplifications to SSVAEs preserve their theoretical soundness while
providing a number of practical advantages in the semi-supervised setup where
the result of training is a text classifier. These simplifications are the
removal of (i) the Kullback-Liebler divergence from its objective and (ii) the
fully unobserved latent variable from its probabilistic model. These changes
relieve users from choosing a prior for their latent variables, make the model
smaller and faster, and allow for a better flow of information into the latent
variables. We compare the simplified versions to standard SSVAEs on 4 text
classification tasks. On top of the above-mentioned simplification, experiments
show a speed-up of 26%, while keeping equivalent classification scores. The
code to reproduce our experiments is public.


  We provide estimates for weighted Fourier sums of integrable functions
defined on the sphere when the weights originate from a multiplier operator
acting on the space where the function belongs. That implies refined estimates
for weighted Fourier sums of integrable kernels on the sphere that satisfy an
abstract H\"{o}lder condition based on a parameterized family of multiplier
operators defining an approximate identity. This general estimation approach
includes an important class of multipliers operators, namely, that defined by
convolutions with zonal measures. The estimates are used to obtain decay rates
for the eigenvalues of positive integral operators on L^2(Sm) and generated by
a kernel satisfying the H\"{o}lder condition based on multiplier operators on
L^2(Sm).


  The ongoing trend to move industrial appliances from previously isolated
networks to the Internet requires fundamental changes in security to uphold
secure and safe operation. Consequently, to ensure end-to-end secure
communication and authentication, (i) traditional industrial protocols, e.g.,
Modbus, are retrofitted with TLS support, and (ii) modern protocols, e.g.,
MQTT, are directly designed to use TLS. To understand whether these changes
indeed lead to secure Industrial Internet of Things deployments, i.e., using
TLS-based protocols, which are configured according to security best practices,
we perform an Internet-wide security assessment of ten industrial protocols
covering the complete IPv4 address space.
  Our results show that both, retrofitted existing protocols and newly
developed secure alternatives, are barely noticeable in the wild. While we find
that new protocols have a higher TLS adoption rate than traditional protocols
(7.2% vs. 0.4%), the overall adoption of TLS is comparably low (6.5% of hosts).
Thus, most industrial deployments (934,736 hosts) are insecurely connected to
the Internet. Furthermore, we identify that 42% of hosts with TLS support
(26,665 hosts) show security deficits, e.g., missing access control. Finally,
we show that support in configuring systems securely, e.g., via configuration
templates, is promising to strengthen security.


  In this paper, we will introduce a new notion, that of $K$-Integral operator
frames in the set of all bounded linear operators noted $\mathcal{B}(H)$, where
$H$ is a separable Hilbert space. Also, we prove some results of integral
$K$-operator frame. Lastly we will establish some new properties for the
perturbation and stability for an integral $K$-operator frames for
$\mathcal{B}(H)$


  We are concerned with the numerical solution of a unified first order
hyperbolic formulation of continuum mechanics that originates from the work of
Godunov, Peshkov and Romenski (GPR model) and which is an extension of
nonlinear hyperelasticity that is able to describe simultaneously nonlinear
elasto-plastic solids at large strain, as well as viscous and ideal fluids. The
proposed governing PDE system also contains the effect of heat conduction and
can be shown to be symmetric and thermodynamically compatible.
  In this paper we extend the GPR model to the simulation of nonlinear dynamic
rupture processes and material fatigue effects, by adding a new scalar variable
to the governing PDE system. This extra parameter describes the material damage
and is governed by an advection-reaction equation, where the stiff and highly
nonlinear reaction mechanisms depend on the ratio of the local von Mises stress
to the yield stress of the material. The stiff reaction mechanisms are
integrated in time via an efficient exponential time integrator. Due to the
multiple space-time scales, the model is solved on space-time adaptive
Cartesian meshes using high order discontinuous Galerkin finite element schemes
with a posteriori subcell finite volume limiting.
  A key feature of our new model is the use of a twofold diffuse interface
approach that allows the cracks to form anywhere and at any time, independently
of the chosen computational grid, without requiring that the geometry of the
rupture fault be known a priori. We furthermore make use of a scalar volume
fraction function that indicates whether a given point is inside the solid or
outside, allowing the description of solids of arbitrarily complex shape.


  In this paper we present thorough experimental observation of the process of
shock wave transformation into a bulk strain solitary wave in a nonlinearly
elastic solid bar made of polystyrene. A theoretical model based on the
describing propagation of a plane elastic wave in a bar is developed with
account made for material nonlinearity and viscosity. Numerical modeling
performed on the base of the developed model with and without regard to
viscosity demonstrated formation of a long stable disturbance at proper account
made for viscoelastic properties of the bar material.


  We study the minimal bigraded free resolution of an ideal with three
generators of the same bidegree, contained in the bihomogeneous maximal ideal $
\langle s,t\rangle \cap \langle u,v \rangle$ of the bigraded ring K[s,t;u,v].
Our analysis involves tools from algebraic geometry (Segre-Veronese varieties),
classical commutative algebra (Buchsbaum-Eisenbud criteria for exactness,
Hilbert-Burch theorem), and homological algebra (Koszul homology, spectral
sequences). We treat in detail the case in which the bidegree is (1,n). We
connect our work to a conjecture of Fr\"oberg-Lundqvist on bigraded Hilbert
functions, and close with a number of open problems.


  Cellular barcoding is a significant, recently developed, biotechnology tool
that enables the familial identification of progeny of individual cells in
vivo. Most existing approaches rely on ex vivo viral transduction of cells with
barcodes, followed by adoptive transfer into an animal, which works well for
some systems, but precludes barcoding cells in their native environment, such
as those inside solid tissues. With a view to overcoming this limitation, we
propose a new design for a genetic barcoding construct based on the Cre Lox
system that induces randomly created stable barcodes in cells in situ by
exploiting inherent sequence distance constraints during site-specific
recombination. Leveraging this previously unused feature, we identify the
cassette with maximal code diversity. This proves to be orders of magnitude
higher than what is attainable with previously considered Cre Lox barcoding
approaches and is well suited for its intended applications as it exceeds the
number of lymphocytes or hematopoietic progenitor cells in mice. Moreover, it
can be built using established technology.


  We investigate in detail the initial susceptibility, magnetization curves,
and microstructure of ferrofluids in various concentration and particle dipole
moment ranges by means of molecular dynamics simulations. We use the Ewald
summation for the long-range dipolar interactions, take explicitly into account
the translational and rotational degrees of freedom, coupled to a Langevin
thermostat. When the dipolar interaction energy is comparable with the thermal
energy, the simulation results on the magnetization properties agree with the
theoretical predictions very well. For stronger dipolar couplings, however, we
find systematic deviations from the theoretical curves. We analyze in detail
the observed microstructure of the fluids under different conditions. The
formation of clusters is found to enhance the magnetization at weak fields and
thus leads to a larger initial susceptibility. The influence of the particle
aggregation is isolated by studying ferro-solids, which consist of magnetic
dipoles frozen in at random locations but which are free to rotate. Due to the
artificial suppression of clusters in ferro-solids the observed susceptibility
is considerably lowered when compared to ferrofluids.


  The triggering mechanism(s) and critical condition(s) of solar flares are
still not completely clarified, although various studies have attempted to
elucidate them. We have also proposed a theoretical flare-trigger model based
on MHD simulations Kusano et al. 2012, in which two types of small-scale bipole
field, the so-called Opposite Polarity (OP) and Reversed Shear (RS) types of
field, can trigger flares. In this study, we evaluated the applicability of our
flare-trigger model to observation of 32 flares that were observed by the Solar
Dynamics Observatory (SDO), by focusing on geometrical structures. We
classified the events into six types, including the OP and RS types, based on
photospheric magnetic field configuration, presence of precursor brightenings,
and shape of the initial flare ribbons. As a result, we found that
approximately 30% of the flares were consistent with our flare-trigger model,
and the number of RS type triggered flares is larger than that of the OP type.
We found none of the sampled events contradicts our flare model, although we
cannot clearly determine the trigger mechanism of 70% of the flares in this
study. We carefully investigated the applicability of our flare-trigger model
and the possibility that other models can explain the other 70% of the events.
Consequently, we concluded that our flare-trigger model has certainly proposed
important conditions for flare-triggering.


  We give an algebraic and a geometric criterion for the existence of
$G$-connections on $\mathbb{P}^{1}$ with prescribed irregular type with equal
slope at $\infty$ (isoclinic) and with regular singularity of prescribed
residue at $0$. The algebraic criterion is in terms of an irreducible module of
the rational Cherednik algebra, and the geometric criterion is in terms of
affine Springer fibers. We use these criteria to give complete solutions to the
isoclinic Deligne-Simpson problem for classical groups, and for arbitrary $G$
when the slope at $\infty$ has Coxeter number as the denominator. Among our
solutions, we classify the cohomologically rigid connections, and obtain new
cases in types $B,C$ and $F_4$.


  Exchanged interactions in recently observed helical structure in LiCu2O2 is
probed by inelastic neutron scattering. The main conlusions of Refs. [1,2] are
confirmed: nn interactions in single chains are ferromagnetic and frustrated by
nnn antiferromagnetic ones. However, in apparent disagreement with Refs. [1,2]
double-chain interactions are found to be of the same order of magnitude as the
single-chain ones, and thus involved in the frustration mechanism.
  [1] Drechsler et al., cond-mat/0411418. [2] A. Gippius et al. Phys. Rev. B 70
(2004), R01426; cond-mat/0312576.


  The remarkable finding of this work is the linear correlation between the
critical temperature of superconducting (SC) transition, Tc, and the
room-temperature half-width of angular correlation of positron annihila- tion
phonons (ACPAP), Go/2, in the series of powder samples of high-Tc YBCO(123)
ceramic superconductors (SCs) with various deficiency of oxygen content. This
correlation points to the existence of fundamental physical parameter of
materials in all-temperature range,which is the crucial one for their
insulator-metal-superconductor (IMSC) transition. We attribute this
key-parameter to the rapid increase and then the steady (due to the minimal
mechanical relaxation rate) lattice compressive deformation - the sudden and
stable jump in work-hardening of crystals). The traces of this compression may
be observed by different methods over a wide range of te- mperatures and used
for the forecast of the parameters of technological interest for the new SCs.


  Previous studies have revealed that artificial intelligence (AI) systems are
vulnerable to adversarial attacks. Among them, model extraction attacks fool
the target model by generating adversarial examples on a substitute model. The
core of such an attack is training a substitute model as similar to the target
model as possible, where the simulation process can be categorized in a
data-dependent and data-free manner. Compared with the data-dependent method,
the data-free one has been proven to be more practical in the real world since
it trains the substitute model with synthesized data. However, the distribution
of these fake data lacks diversity and cannot detect the decision boundary of
the target model well, resulting in the dissatisfactory simulation effect.
Besides, these data-free techniques need a vast number of queries to train the
substitute model, increasing the time and computing consumption and the risk of
exposure. To solve the aforementioned problems, in this paper, we propose a
novel data-free model extraction method named SCME (Self-Contrastive Model
Extraction), which considers both the inter- and intra-class diversity in
synthesizing fake data. In addition, SCME introduces the Mixup operation to
augment the fake data, which can explore the target model's decision boundary
effectively and improve the simulating capacity. Extensive experiments show
that the proposed method can yield diversified fake data. Moreover, our method
has shown superiority in many different attack settings under the query-limited
scenario, especially for untargeted attacks, the SCME outperforms SOTA methods
by 11.43\% on average for five baseline datasets.


  We develop a geometric theory for difference equations with a given group of
automorphisms. To solve this problem we extend the class of difference fields
to the class of absolutely flat simple difference rings called pseudofields. We
prove the Nullstellensatz over pseudofields and investigate geometric
properties of pseudovarieties.


  Recently the existence of a random critical line in two dimensional Dirac
fermions is confirmed. In this paper, we focus on its scaling properties,
especially in the critical region. We treat Dirac fermions in two dimensions
with two types of randomness, a random site (RS) model and a random hopping
(RH) model. The RS model belongs to the usual orthogonal class and all states
are localized. For the RH model, there is an additional symmetry expressed by
${\{}{\cal H},{\gamma}{\}}=0$. Therefore, although all non-zero energy states
localize, the localization length diverges at the zero energy. In the weak
localization region, the generalized Ohm's law in fractional dimensions,
$d^{*}(<2)$, has been observed for the RH model.


  Calculations using staggered quarks augmented with a root of the fermion
determinant to reduce doubling give a qualitatively incorrect behavior in the
small quark mass region. Attempts to circumvent this problem for the continuum
limit involve an unproven combination of unphysical states, a loss of
unitarity, and a rather peculiar non-commutation of limits.


  We study a class of statistical inverse problems with non-linear pointwise
operators motivated by concrete statistical applications. A two-step procedure
is proposed, where the first step smoothes the data and inverts the
non-linearity. This reduces the initial non-linear problem to a linear inverse
problem with deterministic noise, which is then solved in a second step. The
noise reduction step is based on wavelet thresholding and is shown to be
minimax optimal (up to logarithmic factors) in a pointwise function-dependent
sense. Our analysis is based on a modified notion of H\"older smoothness scales
that are natural in this setting.


  We aim to construct a system that captures real-world facial images through
the front camera on a laptop. The system is capable of processing/recognizing
the captured image and predict a result in real-time. In this system, we
exploit the power of deep learning technique to learn a facial emotion
recognition (FER) model based on a set of labeled facial images. Finally,
experiments are conducted to evaluate our model using largely used public
database.


  We present for the first time a master formula for
$\varepsilon'/\varepsilon$, the ratio probing direct CP violation in $K \to
\pi\pi$ decays, valid in any theory beyond the Standard Model (BSM). The
formula makes use of hadronic matrix elements of BSM operators calculated
recently in the Dual QCD approach and the ones of the SM operators from lattice
QCD. We emphasize the large impact of several scalar and tensor BSM operators
in the context of the emerging $\varepsilon'/\varepsilon$ anomaly. We have
implemented the results in the open source code flavio.


  We report the storage and retrieval of single photons, via a quantum memory,
in the optical phonons of room-temperature bulk diamond. The THz-bandwidth
heralded photons are generated by spontaneous parametric downconversion and
mapped to phonons via a Raman transition, stored for a variable delay, and
released on demand. The second-order correlation of the memory output is
$g^{(2)}(0) = 0.65 \pm 0.07$, demonstrating preservation of non-classical
photon statistics throughout storage and retrieval. The memory is low-noise,
high-speed and broadly tunable; it therefore promises to be a versatile
light-matter interface for local quantum processing applications.


  In this paper we give a complete description of the horofunction boundary of
the infinite dimensional real hyperbolic space, and characterise its Busemann
points.


  In this paper, we focus on the hitting times of a stochastic epidemic model
presented by \cite{Gray}. Under the help of the auxiliary stopping times, we
investigate the asymptotic limits of the hitting times by the variations of
calculus and the large deviation inequalities when the noise is sufficiently
small. It can be shown that the relative position between the initial state and
the hitting state determines the scope of the hitting times greatly.


  This is an English translation from the Latin original of Leonhard Euler's
``Solutio facilior problematis Diophantei circa triangulum, in quo rectae ex
angulis latera opposita bisecantes rationaliter exprimantur''. In this paper,
Euler proves that there exist triangles with integer length sides such that the
length of the bisectors of the sides to the opposite angles are integer valued,
and he gives a general method for making a certain class of such triangles.


  The intrinsic transverse momentum distribution of partons in the nucleon can
be used to explain a large amount of high-$p_T$ hadron and photon production
data in high-energy nucleon-nucleon collisions at energies $\sqrt{s} \approx
20$ to 1800 GeV. However, proton-nucleus experiments at energies $\approx 30$
GeV show an extra enhancement (Cronin effect) in the yield of photons and
mesons compared to a simple extrapolation of the proton-proton data. This
enhancement is due to the effect of the dense hadronic matter encountered by
the projectile proton in the nuclear environment. We discuss the origin and the
properties of the nuclear enhancement.


  In representation theory, the problem of classifying pairs of matrices up to
simultaneous similarity is used as a measure of complexity; classification
problems containing it are called wild problems, and the other are referred to
as tame.


  Using our ingeniously designed new filter systems, we investigate the
multiple stellar populations of the RGB and AGB in the GC M5. Our results are
the following. (1) Our cn_jwl index accurately traces the nitrogen abundances
in M5, while other color indices fail to do so. (2) We find bimodal CN
distributions both in the RGB and the AGB sequences, with the number ratios
between the CN-weak (CN-w) and the CN-strong (CN-s) of n(CN-w):n(CN-s) =
29:71(+/- 2) and 21:79(+/- 7), respectively. (3) We also find the bimodal
photometric [N/Fe] distribution for M5 RGB stars. (4) Our cn_jwl-[O/Fe] and
cn_jwl-[Na/Fe] relations show the clear discontinuities between the two RGB
populations. (5) Although small, the RGB bump of the CN-s is slightly brighter,
0.07 +/- 0.04 mag. If real, the difference in the helium abundance becomes
\dy\=0.028$\pm$0.016, in the sense that the CN-s is more helium enhanced. (6)
Very similar radial but different spatial distributions with comparable center
positions are found for the two RGB populations. The CN-s RGB and AGB stars are
more elongated along the NW-SE direction. (7) The CN-s population shows a
substantial net projected rotation, while that of the CN-w population is nil.
(8) Our results confirm the deficiency of the CN-w AGB stars previously noted
by others. We show that it is most likely due to the stochastic truncation in
the outer part of the cluster. Finally, we discuss the formation scenario of
M5.


  Search processes in the natural world are often punctuated by home returns
that reset the position of foraging animals, birds, and insects. Many
theoretical, numerical, and experimental studies have now demonstrated that
this strategy can drastically facilitate search, which could explain its
prevalence. To further facilitate search, foragers also work as a group:
modifying their surroundings in highly sophisticated ways e.g., by leaving
chemical scent trails that imprint the memory of previous excursions. Here, we
design a controlled experiment to show that the benefit coming from such
``environmental memory'' is significant even for a single, non-intelligent,
searcher that is limited to simple physical interactions with its surroundings.
To this end, we employ a self-propelled bristle robot that moves randomly
within an arena filled with obstacles that the robot can push around. To mimic
home returns, we reset the bristle robot's position at constant time intervals.
We show that trails created by the robot give rise to a form of environmental
memory that facilitates search by increasing the effective diffusion
coefficient. Numerical simulations, and theoretical estimates, designed to
capture the essential physics of the experiment support our conclusions and
indicate that these are not limited to the particular system studied herein.


  We establish finite convergence of circumcentered-reflection method (CRM) for
the case of intersection of two closed convex cones in a real Hilbert space. We
apply this result to prove the finite convergence for two polyhedral sets in
R^n.


  The discovery of the primordial B-mode polarisation by the BICEP2 experiment
indicates inflation with a relatively high energy scale. Taking this indication
into account, we propose consistent scenarios to account for the observed
baryon and dark matter densities in gravity and gauge mediated supersymmetry
breaking models. The baryon asymmetry is explained by the Afflck-Dine
mechanism, which requires relatively low reheating temperature to avoid a
sizable baryonic isocurvature perturbation. The low reheating temperature then
requires non-thermal production of dark matter to account for the correct relic
density of dark matter. Our scenarios can account for the observations of
baryon and dark matter density in gravity and gauge mediation and predict some
parameters, including the mass of dark matter.


  A crucial test of any cosmological model is the distribution of distant
objects such as quasars. Because of well defined selection criteria quasars
found by a ultraviolet excess (UVX) survey are ideal candidates for testing the
model out to a redshift of z = 2.2. The static cosmology proposed by Crawford
(1993) is used to analyse a recent quasar survey (BOYLE et al MNRAS 227, 717
1990). It is shown that the distribution of number of quasars from the survey
as a function of redshift is in excellent agreement with the predictions of the
model. A V/V_m test on 351 confirmed quasars with defined redshifts has a mean
value of 0.568\pm 0.015 with the discrepancy being most likely due to
incompleteness of the catalogue at low redshifts. For the redshift range $1.5 <
z < 2.2$ where the accuracy of the cosmological model is critical V/V_m was
0.51 \pm 0.02. A well defined quasar luminosity function is derived that has a
peak at M_B = -21.16 mag and is well fitted by a Gaussian distribution in
absolute magnitude with a standard deviation of 1.52 magnitudes.


  A design principle is suggested to overcome obstacles that prevent positive
net energy output in nuclear fusion devices based on electrostatically
accelerated ions. Since Coulomb scattering cross-section dwarfs that of nuclear
fusion, the focus is on re-capturing energy of elastically scattered ions
before the energy is lost to heat. Device configuration to achieve efficient
energy re-capturing is proposed and a favorable estimate of net energy gain is
obtained.


  One of the three testaments in favor of the big bang theory is the prediction
of the primordial elemental abundances in the big-bang nucleosynthesis (BBN).
The Standard BBN is a parameter-free theory due to the precise knowledge of the
baryon-to-photon ratio of the Universe obtained from studies of the
anisotropies of cosmic microwave background radiation. Although the computed
abundances of light elements during primordial nucleosynthesis and those
determined from observations are in good agreement throughout a range of nine
orders of magnitude, there is still a disparity of $^7$Li abundance
overestimated by a factor of $\sim 2.5$ when calculated theoretically. The
number of light neutrino flavors, the neutron lifetime and the baryon-to-photon
ratio in addition to the astrophysical nuclear reaction rates determine the
primordial abundances. We previously looked into the impact of updating
baryon-to-photon ratio and neutron lifetime and changing quite a few reaction
rates on the yields of light element abundances in BBN. In this work,
calculations are performed using new reaction rates for
$^3$H(p,$\gamma$)$^4$He, $^6$Li(p,$\gamma$)$^7$Be, $^7$Be(p,$\gamma$)$^8$B,
$^{13}$N(p,$\gamma$)$^{14}$O, $^7$Li(n,$\gamma$)$^8$Li and
$^{11}$B(n,$\gamma$)$^{12}$B along with the latest measured value of neutron
lifetime. We observe from theoretical calculations that these changes result in
improvement by causing further reduction in the abundance of $^7$Li than
calculated earlier.


  This article presents a review of the finite element method (FEM) model based
on the $H$ formulation of Maxwell's equations used to calculate AC losses in
high temperature superconductor (HTS) tapes, cables and windings for different
applications. This model, which uses the components of the magnetic field as
state variables, has been gaining a great popularity and has been in use in
tens of research groups around the world. This contribution first reviews the
equations on which the model is based and their implementation in finite
element method programs for different cases, such 2D longitudinal and
axis-symmetric geometries, 3D geometries. Modeling strategies to tackle large
number of HTS tapes, such as multi-scale and homogenization methods, are also
introduced. Then, the second part of the article reviews the applications for
which the $H$ formulations has been used to calculate AC losses, ranging from
individual tapes, to complex cables and large magnet windings. Afterwards, a
section is dedicated to the discussion of the $H$ formulation in terms of
computational efficiency and easiness of implementation. Its pros and cons are
listed. Finally, the last section draws the main conclusions.


  Parton distributions contain factorizable final state interaction effects
originating from the fast-moving struck quark interacting with the target
spectators in deeply inelastic scattering. We show that these interactions give
rise to gauge invariance of the transverse momentum-dependent parton
distributions. As compared to previous analyses, our study demonstrates the
existence of extra scaling contributions from transverse components of the
gauge potential at the light-cone infinity. They form a transverse gauge link
which is indispensable for restoration of the gauge invariance of parton
distributions in the light-cone gauge where the gauge potential does not vanish
asymptotically. Our finding helps to explain a number of features observed in a
model calculation of structure functions in the light-cone gauge.


  We construct a smooth and projective surface over an arbitrary number field
that is a counterexample to the Hasse principle but has the infinite etale
Brauer-Manin set. We also construct a surface with a unique rational point and
the infinite etale Brauer-Manin set. The key new ingredient is the arithmetic
of singular projective curves.


  Single document summarization generates summary by extracting the
representative sentences from the document. In this paper, we presented a novel
technique for summarization of domain-specific text from a single web document
that uses statistical and linguistic analysis on the text in a reference corpus
and the web document. The proposed summarizer uses the combinational function
of Sentence Weight (SW) and Subject Weight (SuW) to determine the rank of a
sentence, where SW is the function of number of terms (t_n) and number of words
(w_n) in a sentence, and term frequency (t_f) in the corpus and SuW is the
function of t_n and w_n in a subject, and t_f in the corpus. 30 percent of the
ranked sentences are considered to be the summary of the web document. We
generated three web document summaries using our technique and compared each of
them with the summaries developed manually from 16 different human subjects.
Results showed that 68 percent of the summaries produced by our approach
satisfy the manual summaries.


  Explaining the behaviour of intelligent systems will get increasingly and
perhaps intractably challenging as models grow in size and complexity. We may
not be able to expect an explanation for every prediction made by a brain-scale
model, nor can we expect explanations to remain objective or apolitical. Our
functionalist understanding of these models is of less advantage than we might
assume. Models precede explanations, and can be useful even when both model and
explanation are incorrect. Explainability may never win the race against
complexity, but this is less problematic than it seems.


  One of the challenges in affect recognition is accurate estimation of the
emotion intensity level. This research proposes development of an affect
intensity estimation model based on a weighted sum of classification confidence
levels, displacement of feature points and speed of feature point motion. The
parameters of the model were calculated from data captured using multiple
modalities such as face, body posture, hand movement and speech. A preliminary
study was conducted to compare the accuracy of the model with the annotated
intensity levels. An emotion intensity scale ranging from 0 to 1 along the
arousal dimension in the emotion space was used. Results indicated speech and
hand modality significantly contributed in improving accuracy in emotion
intensity estimation using the proposed model.


  The transit of primordial black holes through a white dwarf causes localized
heating around the trajectory of the black hole through dynamical friction. For
sufficiently massive black holes, this heat can initiate runaway thermonuclear
fusion causing the white dwarf to explode as a supernova. The shape of the
observed distribution of white dwarfs with masses up to $1.25 M_{\odot}$ rules
out primordial black holes with masses $\sim 10^{19}$ gm - $10^{20}$ gm as a
dominant constituent of the local dark matter density. Black holes with masses
as large as $10^{24}$ gm will be excluded if recent observations by the NuStar
collaboration of a population of white dwarfs near the galactic center are
confirmed. Black holes in the mass range $10^{20}$ gm - $10^{22}$ gm are also
constrained by the observed supernova rate, though these bounds are subject to
astrophysical uncertainties. These bounds can be further strengthened through
measurements of white dwarf binaries in gravitational wave observatories. The
mechanism proposed in this paper can constrain a variety of other dark matter
scenarios such as Q balls, annihilation/collision of large composite states of
dark matter and models of dark matter where the accretion of dark matter leads
to the formation of compact cores within the star. White dwarfs, with their
astronomical lifetimes and sizes, can thus act as large space-time volume
detectors enabling a unique probe of the properties of dark matter, especially
of dark matter candidates that have low number density. This mechanism also
raises the intriguing possibility that a class of supernova may be triggered
through rare events induced by dark matter rather than the conventional
mechanism of accreting white dwarfs that explode upon reaching the
Chandrasekhar mass.


  The detection and characterization of exoplanets have made huge progresses
since the first discoveries in the late nineties. In particular, the
independent measurement of the mass and radius of planets, by combining the
transit and radial-velociy techniques, allowed exploring their density and
hence, their internal structure. With CoRoT (2007-2012), the pioneering CNES
space-based mission in this investigation, about thirty new planets were
characterized. CoRoT has enhanced the diversity of giant exoplanets and
discovered the first telluric exoplanet. Following CoRoT, the NASA Kepler
mission has extended our knowledge to small-size planets, multiple systems and
planets orbiting binaries. Exploring these new worlds will continue with the
NASA/TESS (2017) and ESA/PLATO (2024) missions.


  The declared aim of Marvel Fusion is the realization of a reactor based on
the aneutronic fusion of proton and boron-11 nuclei in the near future, making
use of latest-day laser technology and nano-structured materials. The aim of
the preprint quoted above is to demonstrate the feasibility of fusion energy
gain from the irradiation of an initially uncompressed target consisting of an
array of nano-wires, by a femto-second laser. This proposal is in apparent
contrast to text-book wisdom, which postulates - even for the fast-ignitor
concept, and a DT fuel mix - a target density about 1000 times that of solid
state. The novel, optimistic predictions of Ruhl and Korn are based, however,
not on rigorous estimates, but only on parametric dependencies, extrapolated
far beyond their conventional limits of validity. The authors invoke the
effects of self-arising magnetic fields to result in additional magnetic
confinement, but we show their model to contain intrinsic contradictions. The
conclusion from out note is that ultra-fast, high power lasers can be of use to
inertial fusion energy production only, if the intrinsic time-scale for fusion
reactions can be brought down to a level more commensurate with the Laser pulse
length. Involving magnetic fields does not change this basic limitation, as the
Alfv\'en time will be similar to the kinetic disintegration time. Given that
the fusion energy gain as function of particle energy has a maximum (for DT at
about 170 keV) overheating will not be helpful so that the required enhancement
of the fusion reaction rate can only be achieved by strong pre-compression of
the target.


  The viscosity-radius relationship for semi-dilute polymer solutions is
derived using scaling arguments. The viscosity temperature and the temperature
radius relationships are combined using the transitive equality relationship.
The viscosity-radius relationship is determined to be . The reduced viscosity
observed with both increasing temperature and increasing shear rate then
results from a reduction in coil radius.


  In this paper we study the splitting of separatrices phenomenon which arises
when one considers a Hamiltonian System of one degree of freedom with a fast
periodic or quasiperiodic and meromorphic in the state variables perturbation.
The obtained results are different from the previous ones in the literature,
which mainly assume algebraic or trigonometric polynomial dependence on the
state variables. As a model, we consider the pendulum equation with several
meromorphic perturbations and we show the sensitivity of the size of the
splitting on the width of the analyticity strip of the perturbation with
respect to the state variables. We show that the size of the splitting is
exponentially small if the strip of analyticity is wide enough. Furthermore, we
see that the splitting grows as the width of the analyticity strip shrinks,
even becoming non-exponentially small for very narrow strips. Our results
prevent from using polynomial truncations of the meromorphic perturbation to
compute the size of the splitting of separatrices.


  We propose a novel learning paradigm, Self-Imitation via Reduction (SIR), for
solving compositional reinforcement learning problems. SIR is based on two core
ideas: task reduction and self-imitation. Task reduction tackles a
hard-to-solve task by actively reducing it to an easier task whose solution is
known by the RL agent. Once the original hard task is successfully solved by
task reduction, the agent naturally obtains a self-generated solution
trajectory to imitate. By continuously collecting and imitating such
demonstrations, the agent is able to progressively expand the solved subspace
in the entire task space. Experiment results show that SIR can significantly
accelerate and improve learning on a variety of challenging sparse-reward
continuous-control problems with compositional structures. Code and videos are
available at https://sites.google.com/view/sir-compositional.


  In some newly discovered materials the ratio of phonon to electron energies
is no longer small. We have investigated the basement of the recently proposed
gauge-invariant self-consistent method and found conditions of its
applicability.


  There is growing evidence that the Galactic Center Excess identified in the
$\textit{Fermi}$-LAT gamma-ray data arises from a population of faint
astrophysical sources. We provide compelling supporting evidence by showing
that the morphology of the excess traces the stellar over-density of the
Galactic bulge. By adopting a template of the bulge stars obtained from a
triaxial 3D fit to the diffuse near-infrared emission, we show that it is
detected at high significance. The significance deteriorates when either the
position or the orientation of the template is artificially shifted, supporting
the correlation of the gamma-ray data with the Galactic bulge. In deriving
these results, we have used more sophisticated templates at low-latitudes for
the $\textit{Fermi}$ bubbles compared to previous work and the
three-dimensional Inverse Compton (IC) maps recently released by the ${\tt
GALPROP}$ team. Our results provide strong constraints on Millisecond Pulsar
(MSP) formation scenarios proposed to explain the excess. We find that an
$\textit{admixture formation}$ scenario, in which some of the relevant binaries
are $\textit{primordial}$ and the rest are formed $\textit{dynamically}$, is
preferred over a primordial-only formation scenario at $7.6\sigma$ confidence
level. Our detailed morphological analysis also disfavors models of the
disrupted globular clusters scenario that predict a spherically symmetric
distribution of MSPs in the Galactic bulge. For the first time, we report
evidence of a high energy tail in the nuclear bulge spectrum that could be the
result of IC emission from electrons and positrons injected by a population of
MSPs and star formation activity from the same site.


  Let R be a commutative ring with 1. We prove that every homogeneous
polynomial f(x_0,x_1,x_2) in R[x_0,x_1,x_2] up to degree 5 admits a linear
Pfaffian R-representation. We believe that conceptually we give the shortest
self-contained proof possible: we exhibit explicitly such a representation. In
this sense, we generalize (up to degree 5) a result due to A. Beauville about
the existence of Pfaffian representations for any smooth plane curve of any
degree.


  This paper considers three aspects of Massive MIMO (multiple-input
multiple-output) communication networks that have received little attention in
previous works, but are important to understand when designing and implementing
this promising wireless technology. First, we analyze how bursty data traffic
behaviors affect the system. Using a probabilistic model for intermittent user
activity, we show that the spectral efficiency (SE) scales gracefully with
reduced user activity. Then, we make an analytic comparison between synchronous
and asynchronous pilot signaling, and prove that the choice between these has
no impact on the SE. Finally, we provide an analytical and numerical study of
the SE achieved with random network deployment.


  This paper presents an algorithm to compute the value of the inverse Laplace
transforms of rational functions with poles on arrangements of hyperplanes. As
an application, we present an efficient computation of the partition function
for classical root systems.


  We consider a colored version of the SYK model, that is we distinguish the
$D$ vector fermionic fields involved in the interaction by a color. We obtain
the full $1/N$ series of both the quenched and annealed free energies of the
model and show that at leading order the two are identical. The results can be
used to study systematically the $1/N$ corrections to this leading order
behavior.


  The increasing volume of space objects in Earth's orbit presents a
significant challenge for Space Situational Awareness (SSA). And in particular,
accurate orbit prediction is crucial to anticipate the position and velocity of
space objects, for collision avoidance and space debris mitigation. When
performing Orbit Prediction (OP), it is necessary to consider the impact of
non-conservative forces, such as atmospheric drag and gravitational
perturbations, that contribute to uncertainty around the future position of
spacecraft and space debris alike. Conventional propagator methods like the
SGP4 inadequately account for these forces, while numerical propagators are
able to model the forces at a high computational cost. To address these
limitations, we propose an orbit prediction algorithm utilizing machine
learning. This algorithm forecasts state vectors on a spacecraft using past
positions and environmental variables like atmospheric density from external
sources. The orbital data used in the paper is gathered from precision
ephemeris data from the International Laser Ranging Service (ILRS), for the
period of almost a year. We show how the use of machine learning and
time-series techniques can produce low positioning errors at a very low
computational cost, thus significantly improving SSA capabilities by providing
faster and reliable orbit determination for an ever increasing number of space
objects.


  Information Technology (IT) significantly impacts the environment throughout
its life cycle. Most enterprises have not paid enough attention to this until
recently. IT's environmental impact can be significantly reduced by behavioral
changes, as well as technology changes. Given the relative energy and materials
inefficiency of most IT infrastructures today, many green IT initiatives can be
easily tackled at no incremental cost. The Green Grid - a non-profit trade
organization of IT professionals is such an initiative, formed to initiate the
issues of power and cooling in data centers, scattered world-wide. The Green
Grid seeks to define best practices for optimizing the efficient consumption of
power at IT equipment and facility levels, as well as the manner in which
cooling is delivered at these levels hence, providing promising attitude in
bringing down the environmental hazards, as well as proceeding to the new era
of green computing. In this paper we review the various analytical aspects of
The Green Grid upon the data centers and found green facts.


  We study the stochastic Multi-Armed Bandit (MAB) problem with random delays
in the feedback received by the algorithm. We consider two settings: the
reward-dependent delay setting, where realized delays may depend on the
stochastic rewards, and the reward-independent delay setting. Our main
contribution is algorithms that achieve near-optimal regret in each of the
settings, with an additional additive dependence on the quantiles of the delay
distribution. Our results do not make any assumptions on the delay
distributions: in particular, we do not assume they come from any parametric
family of distributions and allow for unbounded support and expectation; we
further allow for infinite delays where the algorithm might occasionally not
observe any feedback.


  Given sets X and Y of positive integers and a permutation sigma = sigma_1,
sigma_2, ..., sigma_n in S_n, an X,Y-descent of sigma is a descent pair sigma_i
> sigma_{i+1} whose "top" sigma_i is in X and whose "bottom" sigma_{i+1} is in
Y. We give two formulas for the number P_{n,s}^{X,Y} of sigma in S_n with s
X,Y-descents. P_{n,s}^{X,Y} is also shown to be a hit number of a certain
Ferrers board. This work generalizes results of Kitaev and Remmel on counting
descent pairs whose top (or bottom) is equal to 0 mod k.


  For more than half a century, the Hough transform is ever-expanding for new
frontiers. Thousands of research papers and numerous applications have evolved
over the decades. Carrying out an all-inclusive survey is hardly possible and
enormously space-demanding. What we care about here is emphasizing some of the
most crucial milestones of the transform. We describe its variations
elaborating on the basic ones such as the line and circle Hough transforms. The
high demand for storage and computation time is clarified with different
solution approaches. Since most uses of the transform take place on binary
images, we have been concerned with the work done directly on gray or color
images. The myriad applications of the standard transform and its variations
have been classified highlighting the up-to-date and the unconventional ones.
Due to its merits such as noise-immunity and expandability, the transform has
an excellent history, and a bright future as well.


  We use a sample of radio-loud active galactic nuclei (AGNs) with measured
black hole masses to explore the jet formation mechanisms in these sources.
Based on the K\"{o}nigl's inhomogeneous jet model, the jet parameters, such as
the bulk motion Lorentz factor, magnetic field strength, and electron density
in the jet, can be estimated with the very long-baseline interferometry and
X-ray data. We find a significant correlation between black hole mass and the
bulk Lorentz factor of the jet components for this sample, while no significant
correlation is present between the bulk Lorentz factor and the Eddington ratio.
The massive black holes will be spun up through accretion, as the black holes
acquire mass and angular momentum simultaneously through accretion. Recent
investigation indeed suggested that most supermassive black holes in elliptical
galaxies have on average higher spins than the black holes in spiral galaxies,
where random, small accretion episodes (e.g., tidally disrupted stars,
accretion of molecular clouds) might have played a more important role. If this
is true, the correlation between black hole mass and the bulk Lorentz factor of
the jet components found in this work implies that the motion velocity of the
jet components is probably governed by the black hole spin. No correlation is
found between the magnetic field strength at $10R_{\rm S}$ ($R_{\rm S}=2GM/c^2$
is the Schwarzschild radius) in the jets and the bulk Lorentz factor of the jet
components for this sample. This is consistent with the black hole spin
scenario, i.e., the faster moving jets are magnetically accelerated by the
magnetic fields threading the horizon of more rapidly rotating black holes. The
results imply that the Blandford-Znajek (BZ) mechanism may dominate over the
Blandford-Payne (BP) mechanism for the jet acceleration at least in these
radio-loud AGNs.


  In this paper, we focus on fine-grained recognition of vehicles mainly in
traffic surveillance applications. We propose an approach that is orthogonal to
recent advancements in fine-grained recognition (automatic part discovery and
bilinear pooling). In addition, in contrast to other methods focused on
fine-grained recognition of vehicles, we do not limit ourselves to a
frontal/rear viewpoint, but allow the vehicles to be seen from any viewpoint.
Our approach is based on 3-D bounding boxes built around the vehicles. The
bounding box can be automatically constructed from traffic surveillance data.
For scenarios where it is not possible to use precise construction, we propose
a method for an estimation of the 3-D bounding box. The 3-D bounding box is
used to normalize the image viewpoint by "unpacking" the image into a plane. We
also propose to randomly alter the color of the image and add a rectangle with
random noise to a random position in the image during the training of
convolutional neural networks (CNNs). We have collected a large fine-grained
vehicle data set BoxCars116k, with 116k images of vehicles from various
viewpoints taken by numerous surveillance cameras. We performed a number of
experiments, which show that our proposed method significantly improves CNN
classification accuracy (the accuracy is increased by up to 12% points and the
error is reduced by up to 50% compared with CNNs without the proposed
modifications). We also show that our method outperforms the state-of-the-art
methods for fine-grained recognition.


  The data revolution experienced in recent times has thrown up new challenges
and opportunities for businesses of all sizes in diverse industries. Big data
analytics is already at the forefront of innovations to help make meaningful
business decisions from the abundance of raw data available today. Business
intelligence and analytics has become a huge trend in todays IT world as
companies of all sizes are looking to improve their business processes and
scale up using data driven solutions. This paper aims to demonstrate the data
analytical process of deriving business intelligence via the historical data of
a fictional bike share company seeking to find innovative ways to convert their
casual riders to annual paying registered members. The dataset used is freely
available as Chicago Divvy Bicycle Sharing Data on Kaggle. The authors used the
RTidyverse library in RStudio to analyse the data and followed the six data
analysis steps of ask, prepare, process, analyse, share, and act to recommend
some actionable approaches the company could adopt to convert casual riders to
paying annual members. The findings from this research serve as a valuable case
example, of a real world deployment of BIA technologies in the industry, and a
demonstration of the data analysis cycle for data practitioners, researchers,
and other potential users.


  We present an abstract functional analytic formulation of the celebrated
$\dive$-$\curl$ lemma found by F.~Murat and L.~Tartar. The viewpoint in this
note relies on sequences for operators in Hilbert spaces. Hence, we draw the
functional analytic relation of the div-curl lemma to differential forms and
other sequences such as the $\Grad\grad$-sequence discovered recently by
D.~Pauly and W.~Zulehner in connection with the biharmonic operator.