  We elucidate the geometric background of function-theoretic properties for
the Gauss maps of several classes of immersed surfaces in three-dimensional
space forms, for example, minimal surfaces in Euclidean three-space, improper
affine spheres in the affine three-space, and constant mean curvature one
surfaces and flat surfaces in hyperbolic three-space. To achieve this purpose,
we prove an optimal curvature bound for a specified conformal metric on an open
Riemann surface and give some applications. We also provide unicity theorems
for the Gauss maps of these classes of surfaces.


  Conversational analysis systems are trained using noisy human labels and
often require heavy preprocessing during multi-modal feature extraction. Using
noisy labels in single-task learning increases the risk of over-fitting.
Auxiliary tasks could improve the performance of the primary task learning
during the same training -- this approach sits in the intersection of transfer
learning and multi-task learning (MTL). In this paper, we explore how the
preprocessed data used for feature engineering can be re-used as auxiliary
tasks, thereby promoting the productive use of data. Our main contributions
are: (1) the identification of sixteen beneficially auxiliary tasks, (2)
studying the method of distributing learning capacity between the primary and
auxiliary tasks, and (3) studying the relative supervision hierarchy between
the primary and auxiliary tasks. Extensive experiments on IEMOCAP and SEMAINE
data validate the improvements over single-task approaches, and suggest that it
may generalize across multiple primary tasks.


  'Flare Likelihood and Region Eruption Forecasting (FLARECAST)' is a Horizon
2020 project, which realized a technological platform for machine learning
algorithms, with the objective of providing the space weather community with a
prediction service for solar flares. This paper describes the FLARECAST service
and shows how the methods implemented in the platform allow both flare
prediction and a quantitative assessment of how the information contained in
the space data utilized in the analysis may impact the forecasting process.


  We study crossed $S$-matrices for braided $G$-crossed categories and reduce
their computation to a submatrix of the de-equivariantization. We study the
more general case of a category containing the symmetric category
$\mathrm{Rep}(A,z)$ with $A$ a finite cyclic group and $z\in A$ such that
$z^2=1$. We give two example of such categories, which enable us to recover the
Fourier matrix associated with the big family of unipotent characters of the
dihedral groups with automorphism as well as the Fourier matrix of the big
family of unipotent characters of the Ree group of type ${}^2F_4$.


  In this article, we study the location of the first nodal line and hot spots
under different boundary conditions on dumbbell-shaped domains. Apart from its
intrinsic interest, dumbbell domains are also geometrically contrasting to the
extensively studied convex domains. For dumbbells with Dirichlet boundary, we
investigate the location of the supremum level set of the first eigenfunction
and discuss the optimal positioning of obstacles. Considering the other end of
level sets, the nodal sets, we establish that the first nodal set of a Neumann
dumbbell (with sufficiently narrow connectors) lies within a neighborhood of
the connectors. The article demonstrates the utilization of the asymptotic
$L^2$-localization (or its absence, characterized by either Dirichlet or
Neumann boundaries) of dumbbell domains in tackling the aforementioned nodal
geometry problems.


  One of the main challenges that developers face when testing their systems
lies in engineering test cases that are good enough to reveal bugs. And while
our body of knowledge on software testing and automated test case generation is
already quite significant, in practice, developers are still the ones
responsible for engineering test cases manually. Therefore, understanding the
developers' thought- and decision-making processes while engineering test cases
is a fundamental step in making developers better at testing software. In this
paper, we observe 13 developers thinking-aloud while testing different
real-world open-source methods, and use these observations to explain how
developers engineer test cases. We then challenge and augment our main findings
by surveying 72 software developers on their testing practices. We discuss our
results from three different angles. First, we propose a general framework that
explains how developers reason about testing. Second, we propose and describe
in detail the three different overarching strategies that developers apply when
testing. Third, we compare and relate our observations with the existing body
of knowledge and propose future studies that would advance our knowledge on the
topic.


  We present a comprehensive theoretical treatment of the effect of
electron-phonon interactions in molecular transistors, including both quantal
and classical limits and we study both equilibrated and out of equilibrium
phonons. We present detailed results for conductance, noise and phonon
distribution in two regimes. One involves temperatures large as compared to the
rate of electronic transitions on and off the dot; in this limit our approach
yields classical rate equations, which are solved numerically for a wide range
of parameters. The other regime is that of low temperatures and weak
electron-phonon coupling where a perturbative approximation in the Keldysh
formulation can be applied. The interplay between the phonon-induced
renormalization of the density of states on the quantum dot and the
phonon-induced renormalization of the dot-lead coupling is found to be
important. Whether or not the phonons are able to equilibrate in a time rapid
compared to the transit time of an electron through the dot is found to affect
the conductance. Observable signatures of phonon equilibration are presented.
We also discuss the nature of the low-T to high-T crossover.


  Employing a recently proposed metamodeling for the nucleonic matter equation
of state we analyze neutron star global properties such as masses, radii,
momentum of inertia, and others. The impact of the uncertainty on empirical
parameters on these global properties is analyzed in a Bayesian statistical
approach. Physical constraints, such as causality and stability, are imposed on
the equation of state and different hypotheses for the direct Urca (dUrca)
process are investigated. In addition, only metamodels with maximum masses
above 2$M_\odot$ are selected. Our main results are the following: the equation
of state exhibits a universal behavior against the dUrca hypothesis under the
condition of charge neutrality and $\beta$-equilibrium; neutron stars, if
composed exclusively of nucleons and leptons, have a radius of 12.7$\pm$0.4~km
for masses ranging from 1 up to 2$M_\odot$; a small radius lower than 11~km is
very marginally compatible with our present knowledge of the nuclear empirical
parameters; and finally, the most important empirical parameters which are
still affected by large uncertainties and play an important role in determining
the radius of neutrons stars are the slope and curvature of the symmetry energy
($L_{sym}$ and $K_{sym}$) and, to a lower extent, the skewness parameters
($Q_{sat/sym}$).


  One-nucleon emission electron scattering experiments are studied with a model
that considers short--range correlations up to the first order in the number of
correlation lines. The proper normalization of the many-body wave functions
requires the evaluation of two- and three-point diagrams, the last ones usually
neglected in the literature. When all these diagrams are included the effects
of the short-range correlations are rather small. The results of our
calculations are compared with experimental data taken on $^{16}$O.


  Using N-body simulations, we have modeled the production and evolution of
diffuse, low surface brightness intracluster light (ICL) in three simulated
galaxy clusters. Using an observational definition of ICL to be luminosity at a
surface brightness mu_V>26.5 mag/sq.arcsec, we have found that the fraction of
cluster luminosity contained in ICL generally increases as clusters evolve,
although there are large deviations from this trend over short timescales,
including sustained periods of decreasing ICL luminosity. Most ICL luminosity
increases come in short, discrete events which are highly correlated with group
accretion events within the cluster. In evolved clusters we find that ~10-15%
of the clusters' luminosity is at ICL surface brightness. The morphological
structure of the ICL changes with time, evolving from a complex of filaments
and small-scale, relatively high surface brightness features early in a
cluster's history, to a more diffuse and amorphous cluster-scale ICL envelope
at later times. Finally, we also see a correlation between the evolution of ICL
at different surface brightnesses, including a time delay between the evolution
of faint and extremely faint surface brightness features which is traced to the
differing dynamical timescales in the group and cluster environment.


  Long-duration gamma-ray bursts (GRBs) and Type Ib/c Supernovae (SNe Ib/c) are
amongst nature's most magnificent explosions. While GRBs launch relativistic
jets, SNe Ib/c are core-collapse explosions whose progenitors have been
stripped of their hydrogen and helium envelopes. Yet for over a decade, one of
the key outstanding questions is which conditions lead to each kind of
explosion and death in massive stars. Determining the fates of massive stars is
not only a vibrant topic in itself, but also impacts using GRBs as star
formation indicators over distances of up to 13 billion light-years and for
mapping the chemical enrichment history of the universe. This article reviews a
number of comprehensive observational studies that probe the progenitor
environments, their metallicities and the explosion geometries of SN with and
without GRBs, as well as the emerging field of SN environmental studies.
Furthermore, it discusses SN 2008D/XRT 080109 that was discovered
serendipitously with the Swift satellite via its X-ray emission from shock
breakout, and that has generated great interest amongst both observers and
theorists while illustrating a novel technique for stellar forensics. The
article concludes with an outlook on how the most promising venues of research
- with the existing and upcoming innovative large-scale surveys such as the
Palomar Transient Factory and LSST - will shed new light on the diverse deaths
of massive stars.


  For nonlinear parabolic gradient systems of the form \[ u_t = -\nabla V(u) +
u_{xx} \,, \] where the spatial domain is the whole real line, the state
variable $u$ is multidimensional, and the potential function $V$ is coercive at
infinity, the following result is proved: for every critical point of $V$ which
is not a global minimum point, there exists a travelling front, either pushed
or pulled, invading this critical point at a speed which is not smaller than
its linear spreading speed. By contrast with previous existence results of the
same kind, no further assumption is made (neither that the invaded critical
point is a non-degenerate local minimum point, nor other assumptions ensuring
pushed invasion).


  A grazing bifurcation corresponds to the collision of a periodic orbit with a
switching manifold in a piecewise-smooth ODE system and often generates
complicated dynamics. The lowest order terms of the induced Poincare map
expanded about a regular grazing bifurcation constitute a Nordmark map. In this
paper we study a normal form of the Nordmark map in two dimensions with
additive Gaussian noise of amplitude, epsilson [e]. We show that this
particular noise formulation arises in a general setting and consider a
harmonically forced linear oscillator subject to compliant impacts to
illustrate the accuracy of the map. Numerically computed invariant densities of
the stochastic Nordmark map can take highly irregular forms, or, if there
exists an attracting period-n solution when e = 0, be well approximated by the
sum of n Gaussian densities centred about each point of the deterministic
solution, and scaled by 1/n, for sufficiently small e > 0. We explain the
irregular forms and calculate the covariance matrices associated with the
Gaussian approximations in terms of the parameters of the map. Close to the
grazing bifurcation the size of the invariant density may be proportional to
the square-root of e, as a consequence of a square-root singularity in the map.
Sequences of transitions between different dynamical regimes that occur as the
primary bifurcation parameter is varied have not been described previously.


  We study semi-dynamical systems associated to delay differential equations.
We give a simple criteria to obtain weak and strong persistence and provide
sufficient conditions to guarantee uniform persistence. Moreover, we show the
existence of non-trivial $T$-periodic solutions via topological degree
techniques. Finally, we prove that, in some sense, the conditions are also
necessary.


  Using $\mathcal{N}=4$ supersymmetric Yang-Mills theory we recover important
aspects of the near-extremal thermodynamics of AdS$_5$ black holes including
both the outer and the inner horizons with their corresponding entropy and
energy. This $\mathcal{N}=4$ supersymmetric Yang-Mills theory approach to black
hole thermodynamics leads to an effective CFT$_2$ interpretation similar to the
work by Callan and Maldacena. We corroborate this effective CFT$_2$ by
implementing a particular near-horizon limit that geometrizes the Virasoro
algebras as asymptotic symmetries. Using the effective CFT$_2$ picture, we
discuss aspects of the Hawking radiation rate for a region of the near-extremal
AdS$_5$ black hole quantum evolution.


  We investigate the advantages of extracting the degree of entanglement in
bipartite systems directly from tomograms, as it is the latter that are readily
obtained from experiments. This would provide a superior alternative to the
standard procedure of assessing the extent of entanglement between subsystems
after employing the machinery of state reconstruction from the tomogram. The
latter is both cumbersome and involves statistical methods, while a direct
inference about entanglement from the tomogram circumvents these limitations.
In an earlier paper, we had identified a procedure to obtain a bipartite
entanglement indicator directly from tomograms. To assess the efficacy of this
indicator, we now carry out a detailed investigation using two nonlinear
bipartite models by comparing this tomographic indicator with standard markers
of entanglement such as the subsystem linear entropy and the subsystem von
Neumann entropy and also with a commonly-used indicator obtained from inverse
participation ratios. The two model systems selected for this purpose are a
multilevel atom interacting with a radiation field, and a double-well
Bose-Einstein condensate. The role played by the specific initial states of
these two systems in the performance of the tomographic indicator is also
examined. Further, the efficiency of the tomographic entanglement indicator
during the dynamical evolution of the system is assessed from a time-series
analysis of the difference between this indicator and the subsystem von Neumann
entropy.


  We study the dynamical evolution of star clusters on eccentric orbits using a
semi-analytical approach. In particular we adapt and extend the equations of
EMACSS code, introduced by Gieles et al. (2014), to work with eccentric orbits.
We follow the evolution of star clusters in terms of mass, half-mass radius,
core radius, Jacobi radius and the total energy over their dissolution time.
Moreover, we compare the results of our semi-analytical models against $N$-body
computations of clusters with various initial half-mass radius, number of stars
and orbital eccentricity to cover both tidally filling and under-filling
systems. The evolution profiles of clusters obtained by our semi-analytical
approach closely follow those of $N$-body simulations in different evolutionary
phases of star clusters, from pre-collapse to post-collapse. Given that the
average runtime of our semi-analytical models is significantly less than that
of $N$-body models, our approach makes it feasible to study the evolution of
large samples of globular clusters on eccentric orbits.


  We consider special cases of the two tree degree sequences problem. We show
that if two tree degree sequences do not have common leaves then they always
have edge-disjoint caterpillar realizations. By using a probabilistic method,
we prove that two tree degree sequences always have edge-disjoint realizations
if each vertex is a leaf in at least one of the trees. This theorem can be
extended to more trees: we show that the edge packing problem is in P for an
arbitrary number of tree sequences with the property that each vertex is a
non-leaf in at most one of the trees.
  We also consider the following variant of the degree matrix problem: given
two degree sequences $D_1$ and $D_2$ such that $D_2$ is a tree degree sequence,
decide if there exists edge-disjoint realizations of $D_1$ and $D_2$ where the
realization of $D_2$ is not necessarily a tree. We show that this problem is
already $\NP$-complete.
  Counting, or just estimating the number of distinct realizations of degree
sequences is challenging in general. We show that efficient approximations for
the number of solutions as well as an almost uniform sampler exist for two tree
degree sequences if each vertex is a leaf in at least one of the trees.


  We propose and analyze a novel approach to construct structure preserving
approximations for the Poisson-Nernst-Planck equations, focusing on the
positivity preserving and mass conservation properties. The strategy consists
of a standard time marching step with a projection (or correction) step to
satisfy the desired physical constraints (positivity and mass conservation).
Based on the $L^2$ projection, we construct a second order Crank-Nicolson type
finite difference scheme, which is linear (exclude the very efficient $L^2$
projection part), positivity preserving and mass conserving. Rigorous error
estimates in $L^2$ norm are established, which are both second order accurate
in space and time. The other choice of projection, e.g. $H^1$ projection, is
discussed.
  Numerical examples are presented to verify the theoretical results and
demonstrate the efficiency of the proposed method.


  Gene expression is a complex and quantitative trait that is influenced by
both genetic and non-genetic regulators including environmental factors.
Evaluating the contribution of environment to gene expression regulation and
identifying which genes are more likely to be influenced by environmental
factors are important for understanding human complex traits. We hypothesize
that by living together as couples, there can be commonly co-regulated genes
that may reflect the shared living environment (e.g., diet, indoor air
pollutants, behavioral lifestyle). The lymphoblastoid cell lines (LCLs) derived
from unrelated couples of African ancestry (YRI, Yoruba people from Ibadan,
Nigeria) from the International HapMap Project provided a unique model for us
to characterize gene expression pattern in couples by comparing gene expression
levels between husbands and wives. Strikingly, 778 genes were found to show
much smaller variances in couples than random pairs of individuals at a false
discovery rate (FDR) of 5%. Since genetic variation between unrelated family
members in a general population is expected to be the same assuming a
random-mating society, non-genetic factors (e.g., epigenetic systems) are more
likely to be the mediators for the observed transcriptional similarity in
couples. We thus evaluated the contribution of modified cytosines to those
genes showing transcriptional similarity in couples as well as the
relationships these CpG sites with other gene regulatory elements, such as
transcription factor binding sites (TFBS). Our findings suggested that
transcriptional similarity in couples likely reflected shared common
environment partially mediated through cytosine modifications.


  Manual maintenance and repair of cracks in concrete structures are often
unsustainable because of associated labor, capital and environmental damage.
Introduction of microfibers and superabsorbent polymers is a material solution
to restrict crack propagation and enhance self-healing efficiency. Therefore,
the study proposes a combination of polypropylene(PP) fibers and superabsorbent
polymers (SAP) which would facilitate autonomous healing and recover original
mechanical and durability properties of mortar. Mechanical strength, sorptivity
and water penetration of healed mortars were compared to that of undamaged
mortar at same age to estimate recovery of original properties while crack
sealing was investigated by means of optical microscopy. Experimental results
show mortar with combination of PP fibers and SAP showed full recovery of
mechanical strength after healing while recovery in durability up to 90% was
recorded. Microscopic images show that average crack-sealing ratio of 85% could
be achieved under moist condition by combination of SAP and PP fibers while
sealing under drier air curing condition is also significantly higher than
reference samples with only fibers. Crack width up to 330{\mu}m has been found
to be completely sealed by carbonate crystals. Furthermore, mortar with SAP and
PP fibers retain about 70% of their original 28-day strength after three cycles
of loading while reference mortar samples were found to retain only about
40-50% of their original strength. Effective crack sealing and high recovery of
original properties in mortars with SAP and fibers suggest that this material
combination would reduce the need for environmentally damaging and expensive
repairs during the service life.


  Consider the $S_n$-action on $\mathbb{R}^n$ given by permuting coordinates.
This paper addresses the following problem: compute $\max_{v,H} |H\cap S_nv|$
as $H\subset\mathbb{R}^n$ ranges over all hyperplanes through the origin and
$v\in\mathbb{R}^n$ ranges over all vectors with distinct coordinates that are
not contained in the hyperplane $\sum x_i=0$. We conjecture that for $n\geq3$,
the answer is $(n-1)!$ for odd $n$, and $n(n-2)!$ for even $n$. We prove that
if $p$ is the largest prime with $p\leq n$, then $\max_{v,H} |H\cap S_nv|\leq
\frac{n!}{p}$. In particular, this proves the conjecture when $n$ or $n-1$ is
prime.


  Taking matrix as a synonym for a numerical function on the Cartesian product
of two (in general, infinite) sets, a simple purely algebraic "reciprocity
property" says that the set of rows spans a finite-dim space iff the set of
columns does so. Similar topological reciprocity properties serve to define
strongly compact and weakly compact matrices, featured in the well-known basic
facts about almost periodic functions and about compact operators. Some
properties, especially for the weak compact case, are investigated, such as the
connection with the matrix having a Fubini-like property for general means.
These are applied to prove possibility of extension to the entire semigroup of
bounded densely defined semigroups of operators in a Banach space with weak
continuity properties.


  Conflicting values of the hypertriton lifetime $\tau({}_\Lambda^3\mathrm{H})$
were derived in relativistic heavy ion (RHI) collision experiments over the
last decade. A very recent ALICE Collaboration measurement is the only
experiment where the reported $\tau({}_\Lambda^3\mathrm{H})$ comes sufficiently
close to the free-$\Lambda$ lifetime $\tau_\Lambda$,as expected naively for a
very weakly bound $\Lambda$ in ${}_\Lambda^3\mathrm{H}$. We revisited
theoretically this ${}_\Lambda^3\mathrm{H}$ lifetime puzzle, using
${}_\Lambda^3\mathrm{H}$ and ${}^3\mathrm{He}$ wave functions computed within
the abinitio no-core shell model employing interactions derived from chiral
effective field theory to calculate the two-body decay rate
$\Gamma({}_\Lambda^3\mathrm{H}\to{}^3\mathrm{He}+\pi^-)$. We found significant
but opposing contributions arising from $\Sigma NN$ admixtures in
${}_\Lambda^3\mathrm{H}$ and from $\pi^- -{}^3\mathrm{He}$ final-state
interaction. To derive $\tau({}_\Lambda^3\mathrm{H})$, we evaluated the
inclusive $\pi^-$ decay rate $\Gamma_{\pi^-}({}_\Lambda^3\mathrm{H})$ by using
the measured branching ratio
$\Gamma({}_\Lambda^3\mathrm{H}\to{}^3\mathrm{He}+\pi^-)/\Gamma_{\pi^-}({}_\Lambda^3\mathrm{H})$
and added the $\pi^0$ contributions through the $\Delta I = \frac{1}{2}$ rule.
The resulting $\tau({}_\Lambda^3\mathrm{H})$ varies strongly with the rather
poorly known $\Lambda$ separation energy
$E_{\mathrm{sep}}({}_\Lambda^3\mathrm{H})$ and it is thus possible to associate
each one of the distinct RHI $\tau({}_\Lambda^3\mathrm{H})$ measurements with
its own underlying value of $E_{\mathrm{sep}}({}_\Lambda^3\mathrm{H})$.


  We analyze doping dependent spectral intensities and Fermi surface maps
obtained recently in Nd$_{2-x}$Ce$_x$CuO$_{4\pm\delta}$ (NCCO) via high
resolution ARPES measurements, and show that the behavior of this
electron-doped compound can be understood as the closing of a Mott (pseudo)
gap, leading to a quantum critical point just above optimal doping. The doping
dependence of the effective Hubbard $U$ adduced by comparing theoretical and
experimental spectra is in resonable accord with various estimates and a simple
screening calculation.


  Let $(\mathcal{H}_k, \mathcal{H}_{\ell})$ be a pair of Hilbert function
spaces with kernels $k, \ell$. In a 2005 paper, Shimorin showed that a certain
factorization condition on $(k, \ell)$ yields a commutant lifting theorem for
multipliers $\mathcal{H}_k\to\mathcal{H}_{\ell}$, thus unifying and extending
previous results due to Ball-Trent-Vinnikov and Volberg-Treil. Our main result
is a strong converse to Shimorin's theorem for a large class of holomorphic
pairs $(k, \ell),$ which leads to a full characterization of the complete Pick
property for such pairs. We also present a short alternative proof of
sufficiency for Shimorin's condition. Finally, we establish necessary
conditions for abstract pairs $(k, \ell)$ to satisfy the complete Pick
property, further generalizing Shimorin's work with proofs that are new even in
the single-kernel case $k=\ell.$ Our approach differs from Shimorin's in that
we do not work with the Nevanlinna-Pick problem directly; instead, we are able
to extract vital information for $(k, \ell)$ through Carath\'eodory-Fej\'er
interpolation.


  In this paper we derive the analogue of Lebesque-Radon Nikody theorem with
respect to fermionic p-adic invariant measures on Zp


  We show that a compact n-polyhedron PL embeds in a product of n trees if and
only if it collapses onto an (n-1)-polyhedron. If the n-polyhedron is
contractible and n\ne 3 (or n=3 and the Andrews-Curtis Conjecture holds), the
product of trees may be assumed to collapse onto the image of the embedding.
  In contrast, there exists a 2-dimensional compact absolute retract X such
that X\times I^k does not embed in any product of 2+k dendrites for each k.


  Using the coalescence model based on the phase-space distribution of nucleons
from an extended blast-wave model that includes the space-momentum correlation
of high momentum nucleons, we study the transverse momentum spectra and
elliptic flows of deuteron and helium-3 in Pb+Pb collisions at the energy
$\sqrt{s_{NN}}=2.76$ TeV. We find that the measured elliptic flows of deuteron
can be satisfactorily described if nucleons of large transverse momenta are
more spread in space when their momenta are more aligned along the reaction
plane.


  This is the Proceedings of the 2nd OMNeT++ Community Summit, which was held
at IBM Research - Zurich, Switzerland on September 3-4, 2015.


  The performance of continuous aperture array (CAPA)-based wireless
communications is analyzed in an uplink scenario. An analytical framework is
proposed to characterize uplink CAPA-based transmission using electromagnetic
field theories. On this basis, new expressions are derived for the channel
capacity in a single-user scenario and the sum-rate capacity in a multiuser
scenario, along with the capacity-achieving decoding schemes. These findings
are proved to differ greatly from those established for conventional spatially
discrete (SPD) arrays. Numerical results are provided to demonstrate that CAPA
offers significant capacity gains compared to the SPD array.


  Lyapunov exponents describe the asymptotic behavior of the singular values of
large products of random matrices. A direct computation of these exponents is
however often infeasible. By establishing a link between Lyapunov exponents and
an information theoretic tool called entropy accumulation theorem we derive an
upper and a lower bound for the maximal and minimal Lyapunov exponent,
respectively. The bounds assume independence of the random matrices, are
analytical, and are tight in the commutative case as well as in other
scenarios. They can be expressed in terms of an optimization problem that only
involves single matrices rather than large products. The upper bound for the
maximal Lyapunov exponent can be evaluated efficiently via the theory of convex
optimization.


  Data on jet production in deep inelastic e^+ p scattering are presented.
  The results are compared with pQCD calculations. At low Q^2 no consistent
description of the data over all the phase space is available yet. At high Q^2
(>150 GeV^2) the data are well described by pQCD in NLO.


  We report the discovery of five bright strong gravitationally lensed galaxies
at $3 < z < 4$: COOLJ0101$+$2055 ($z = 3.459$), COOLJ0104$-$0757 ($z = 3.480$),
COOLJ0145$+$1018 ($z = 3.310$), COOLJ0516$-$2208 ($z = 3.549$), and
COOLJ1356$+$0339 ($z = 3.753$). These galaxies have magnitudes of $r_{\rm AB},
z_{\rm AB} < 21.81$ mag and are lensed by galaxy clusters at $0.26 < z < 1$.
This sample nearly doubles the number of known bright lensed galaxies with
extended arcs at $3 < z < 4$. We characterize the lensed galaxies using
ground-based grz/giy imaging and optical spectroscopy. We report model-based
magnitudes and derive stellar masses, dust content, and star-formation rates
via stellar population synthesis modeling. Building lens models based on
ground-based imaging, we estimate source magnifications in the range $\sim$29
to $\sim$180. Combining these analyses, we derive demagnified stellar masses in
the range $\rm log_{10}(M_{*}/M_{\odot}) \sim 9.69 - 10.75$ and star formation
rates in the youngest age bin ranging from $\rm log_{10}(SFR/(M_{\odot}\cdot
yr^{-1})) \sim 0.39 - 1.46$, placing the sample galaxies on the massive end of
the star-forming main sequence in this redshift interval. In addition, three of
the five galaxies have strong Ly$\alpha$ emissions, offering unique
opportunities to study Ly$\alpha$ emitters at high redshift in future work.


  The M/EEG inverse problem is ill-posed. Thus additional hypotheses are needed
to constrain the solution space. In this work, we consider that brain activity
which generates an M/EEG signal is a connected cortical region. We study the
case when only one region is active at once. We show that even in this simple
case several configurations can explain the data. As opposed to methods based
on convex optimization which are forced to select one possible solution, we
propose an approach which is able to find several "good" candidates - regions
which are different in term of their sizes and/or positions but fit the data
with similar accuracy.


  Regulatory compliance is a well-studied area, including research on how to
model, check, analyse, enact, and verify compliance of software. However, while
the theoretical body of knowledge is vast, empirical evidence on challenges
with regulatory compliance, as faced by industrial practitioners particularly
in the Software Engineering domain, is still lacking. In this paper, we report
on an industrial case study which aims at providing insights into common
practices and challenges with checking and analysing regulatory compliance, and
we discuss our insights in direct relation to the state of reported evidence.
Our study is performed at Ericsson AB, a large telecommunications company,
which must comply to both locally and internationally governing regulatory
entities and standards such as GDPR. The main contributions of this work are
empirical evidence on challenges experienced by Ericsson that complement the
existing body of knowledge on regulatory compliance.


  In this paper we present the concept of description of random processes in
complex systems with the discrete time. It involves the description of kinetics
of discrete processes by means of the chain of finite-difference non-Markov
equations for time correlation functions (TCF). We have introduced the dynamic
(time dependent) information Shannon entropy $S_i(t)$ where i=0,1,2,3,... as an
information measure of stochastic dynamics of time correlation $(i=0)$ and time
memory (i=1,2,3,...). The set of functions $S_i(t)$ constitute the quantitative
measure of time correlation disorder $(i=0)$ and time memory disorder
(i=1,2,3,...) in complex system. Harnessing the infinite set of orthogonal
dynamic random variables on a basis of Gram-Shmidt orthogonalization procedure
tends to creation of infinite chain of finite-difference non-Markov kinetic
equations for discrete TCF and memory function.The solution of the equations
above thereof brings to the recurrence relations between the TCF and MF of
senior and junior orders. The results obtained offer considerable scope for
attack on stochastic dynamics of discrete random processes in a complex
systems. Application of this technique on the analysis of stochastic dynamics
of RR-intervals from human ECG's shows convincing evidence for a non-Markovian
phenomemena associated with a peculiarities in short and long-range scaling.
This method may be of use in distinguishing healthy from pathologic data sets
based in differences in these non-Markovian properties.


  User-based KNN recommender systems (UserKNN) utilize the rating data of a
target user's k nearest neighbors in the recommendation process. This, however,
increases the privacy risk of the neighbors since their rating data might be
exposed to other users or malicious parties. To reduce this risk, existing work
applies differential privacy by adding randomness to the neighbors' ratings,
which reduces the accuracy of UserKNN. In this work, we introduce ReuseKNN, a
novel differentially-private KNN-based recommender system. The main idea is to
identify small but highly reusable neighborhoods so that (i) only a minimal set
of users requires protection with differential privacy, and (ii) most users do
not need to be protected with differential privacy, since they are only rarely
exploited as neighbors. In our experiments on five diverse datasets, we make
two key observations: Firstly, ReuseKNN requires significantly smaller
neighborhoods, and thus, fewer neighbors need to be protected with differential
privacy compared to traditional UserKNN. Secondly, despite the small
neighborhoods, ReuseKNN outperforms UserKNN and a fully differentially private
approach in terms of accuracy. Overall, ReuseKNN leads to significantly less
privacy risk for users than in the case of UserKNN.


  Due to cancer's complex nature and variable response to therapy, precision
oncology informed by omics sequence analysis has become the current standard of
care. However, the amount of data produced for each patients makes it difficult
to quickly identify the best treatment regimen. Moreover, limited data
availability has hindered computational methods' abilities to learn patterns
associated with effective drug-cell line pairs. In this work, we propose the
use of contrastive learning to improve learned drug and cell line
representations by preserving relationship structures associated with drug
mechanism of action and cell line cancer types. In addition to achieving
enhanced performance relative to a state-of-the-art method, we find that
classifiers using our learned representations exhibit a more balances reliance
on drug- and cell line-derived features when making predictions. This
facilitates more personalized drug prioritizations that are informed by signals
related to drug resistance.


  This paper describes an experimental search for GUT magnetic monopoles in the
MACRO experiment using the nuclear track subdetector CR39. After discussing the
working principle, the charge resolution and the calibration of the detector,
the experimental procedure for searching for magnetic monopoles is described.
Since no candidates were found, the upper flux limits obtained by the MACRO
CR39 used as a "stand alone detector" for magnetic monopoles of different
magnetic charges are presented.


  In this paper, we obtain several structural results for the value function
associated to a mean-field optimal control problem of Bolza type in the space
of measures. After establishing the sensitivity relations bridging between the
costates of the maximum principle and metric superdifferentials of the value
function, we investigate semiconcavity properties of this latter with respect
to both variables. We then characterise optimal trajectories using set-valued
feedback mappings defined in terms of suitable directional derivatives of the
value function.


  This article presents a quick view on the development of mechatronic products
and how the techniques of Design Thinking, Concurrent Engineering and Agilism
can be integrated to address this development. Design Thinking is employed in
the early stages in order to better explore creativity, whereas Concurrent
Engineering and Agilism are applied during the development of the product, in
order to deal with emerging requirements, typical of the development of complex
products.


  In this paper we study the moduli spaces $Simp^m_n$ of degree $n+1$ morphisms
$ \mathbb{A}^1_{K} \to \mathbb{A}^1_{K}$ with "ramification length $<m$" over
an algebraically closed field $K$. For each $m$, the moduli space $Simp^m_n$ is
a Zariski open subset of the space of degree $n+1$ polynomials over $K$ up to
$Aut (\mathbb{A}^1_{K})$. It is, in a way, orthogonal to the many papers about
polynomials with prescribed zeroes -- here we are prescribing, instead, the
ramification data. Exploiting the topological properties of the poset that
encodes the ramification behaviour, we use a sheaf-theoretic argument to
compute $H^*(Simp^m_n(\mathbb{C}); \mathbb{Q})$ as well as the \'etale
cohomology $H^*_{et}({Simp^m_n}_{/K}; \mathbb{Q}_{\ell})$ for $char K=0$ or
$char K> n+1$. As a by-product we obtain that $H^*(Simp^m_n(\mathbb{C});
\mathbb{Q})$ is independent of $n$, thus implying rational cohomological
stability. When $char K>0$ our methods compute $H^*_{et}(Simp^m_n;
\mathbb{Q}_{\ell})$ provided $char K>n+1$ and show that the \'etale cohomology
groups in positive characteristics do not stabilize.


  Superconducting quantum computing architectures comprise resonators and
qubits that experience energy loss due to two-level systems (TLS) in bulk and
interfacial dielectrics. Understanding these losses is critical to improving
performance in superconducting circuits. In this work, we present a method for
quantifying the TLS losses of different bulk and interfacial dielectrics
present in superconducting coplanar waveguide (CPW) resonators. By combining
statistical characterization of sets of specifically designed CPW resonators on
isotropically etched silicon substrates with detailed electromagnetic modeling,
we determine the separate loss contributions from individual material
interfaces and bulk dielectrics. This technique for analyzing interfacial TLS
losses can be used to guide targeted improvements to qubits, resonators, and
their superconducting fabrication processes.


  The curvature dimension condition CD(K,N), pioneered by Sturm and
Lott--Villani, is a synthetic notion of having curvature bounded below and
dimension bounded above, in the non-smooth setting. This condition implies a
suitable generalization of the Brunn--Minkowski inequality, denoted by BM(K,N).
In this paper, we address the converse implication in the setting of weighted
Riemannian manifolds, proving that BM(K,N) is in fact equivalent to CD(K,N).
Our result allows to characterize the curvature dimension condition without
using neither the optimal transport nor the differential structure of the
manifold.


  In this paper we present a computation of the thermally generated
acceleration of the Cassini probe during its solar conjunction experiment,
obtained from a model of the spacecraft. We build a thermal model of the
vehicle and perform a Monte Carlo simulation to find a thermal acceleration
with a main component of $(3.01 \pm 0.33) \times 10^{-9} {\rm m/s^2}$. This
result is in close agreement with the estimates of this effect performed
through Doppler data analysis.


  Out-of-distribution (OOD) generalization in the graph domain is challenging
due to complex distribution shifts and a lack of environmental contexts. Recent
methods attempt to enhance graph OOD generalization by generating flat
environments. However, such flat environments come with inherent limitations to
capture more complex data distributions. Considering the DrugOOD dataset, which
contains diverse training environments (e.g., scaffold, size, etc.), flat
contexts cannot sufficiently address its high heterogeneity. Thus, a new
challenge is posed to generate more semantically enriched environments to
enhance graph invariant learning for handling distribution shifts. In this
paper, we propose a novel approach to generate hierarchical semantic
environments for each graph. Firstly, given an input graph, we explicitly
extract variant subgraphs from the input graph to generate proxy predictions on
local environments. Then, stochastic attention mechanisms are employed to
re-extract the subgraphs for regenerating global environments in a hierarchical
manner. In addition, we introduce a new learning objective that guides our
model to learn the diversity of environments within the same hierarchy while
maintaining consistency across different hierarchies. This approach enables our
model to consider the relationships between environments and facilitates robust
graph invariant learning. Extensive experiments on real-world graph data have
demonstrated the effectiveness of our framework. Particularly, in the
challenging dataset DrugOOD, our method achieves up to 1.29% and 2.83%
improvement over the best baselines on IC50 and EC50 prediction tasks,
respectively.


  We study the two-dimensional topology of the galactic distribution when
projected onto two-dimensional spherical shells. Using the latest Horizon Run 4
simulation data, we construct the genus of the two-dimensional field and
consider how this statistic is affected by late-time nonlinear effects --
principally gravitational collapse and redshift space distortion (RSD). We also
consider systematic and numerical artifacts such as shot noise, galaxy bias,
and finite pixel effects. We model the systematics using a Hermite polynomial
expansion and perform a comprehensive analysis of known effects on the
two-dimensional genus, with a view toward using the statistic for cosmological
parameter estimation. We find that the finite pixel effect is dominated by an
amplitude drop and can be made less than $1\%$ by adopting pixels smaller than
$1/3$ of the angular smoothing length. Nonlinear gravitational evolution
introduces time-dependent coefficients of the zeroth, first, and second Hermite
polynomials, but the genus amplitude changes by less than $1\%$ between $z=1$
and $z=0$ for smoothing scales $R_{\rm G} > 9 {\rm Mpc/h}$. Non-zero terms are
measured up to third order in the Hermite polynomial expansion when studying
RSD. Differences in shapes of the genus curves in real and redshift space are
small when we adopt thick redshift shells, but the amplitude change remains a
significant $\sim {\cal O}(10\%)$ effect. The combined effects of galaxy
biasing and shot noise produce systematic effects up to the second Hermite
polynomial. It is shown that, when sampling, the use of galaxy mass cuts
significantly reduces the effect of shot noise relative to random sampling.


  The monogamy of entanglement is one of the basic quantum mechanical features,
which says that when two partners Alice and Bob are more entangled then either
of them has to be less entangled with the third party. Here we qualitatively
present the converse monogamy of entanglement: given a tripartite pure system
and when Alice and Bob are weakly entangled, then either of them is generally
strongly entangled with the third party. Our result leads to the classification
of tripartite pure states based on bipartite reduced density operators, which
is a novel and effective way to this long-standing problem compared to the
means by stochastic local operations and classical communications. We also
systematically indicate the structure of the classified states and generate
them.


  It is shown that the set of 4-period orbits in outer billiard with piecewise
smooth convex boundary has an empty interior, provided that no four corners of
the boundary form a parallelogram.


  There are currently two optical interferometry recombiners that can provide
spectral resolutions better than 10000, AMBER/VLTI operating in the H-K bands,
and VEGA/CHARA, recently commissioned, operating in the visible. These
instruments are well suited to study the wind activity of the brightest AB
supergiants in our vicinity, in lines such as H$\alpha$ or BrGamma. We present
here the first observations of this kind, performed on Rigel (B8Ia) and Deneb
(A2Ia). Rigel was monitored by AMBER in two campaigns, in 2006-2007 and
2009-2010, and observed in 2009 by VEGA; whereas Deneb was monitored in
2008-2009 by VEGA. The extension of the Halpha and BrGamma line forming regions
were accurately measured and compared with CMFGEN models of both stars.
Moreover, clear signs of activity were observed in the differential visibility
and phases. These pioneer observations are still limited, but show the path for
a better understanding of the spatial structure and temporal evolution of
localized ejections using optical interferometry.


  We discuss recent results in neutrino astronomy and their implications for
the cosmic-ray acceleration in relativistic outflows, such as in Active
Galactic Nuclei (AGN) jets, Gamma-Ray Bursts (GRBs), and Tidal Disruption
Events (TDEs). We especially focus on challenges at the interface to particle
acceleration which can be inferred from the multi-messenger context, such as
the paradigm that the sources power the Ultra-High-Energy Cosmic Rays (UHECRs).
We demonstrate that both AGN blazars (in the context of neutrino observations)
and GRBs (as UHECR sources in the context of neutrino-non-observations) point
towards acceleration spectra harder than $E^{-2}$, or relatively high minimal
cosmic-ray injection energies, to meet the respective energy budget
requirements. We furthermore speculate that neutrino flares in blazars may be
related to super-Eddington accretion flares, or that GRBs are powered by
significantly higher kinetic energies than typically assumed in electromagnetic
models. For internal shock models, the UHECR paradigm for GRBs can only be
maintained in the light of neutrino stacking limits in multi-zone models. While
relativistic outflows in TDEs have become recently interesting per se and
models for the neutrino emission from jetted TDEs exist, a direct connection
between TDE jets pointing in our direction and astrophysical neutrinos has not
been identified yet.


  The Common Core Ontologies (CCO) are designed as a mid-level ontology suite
that extends the Basic Formal Ontology. CCO has since been increasingly adopted
by a broad group of users and applications and is proposed as the first
standard mid-level ontology. Despite these successes, documentation of the
contents and design patterns of the CCO has been comparatively minimal. This
paper is a step toward providing enhanced documentation for the mid-level
ontology suite through a discussion of the contents of the eleven ontologies
that collectively comprise the Common Core Ontology suite.


  We give estimates for the probability that a chordal, radial or two-sided
radial SLE$_\kappa$ curve retreats far from its terminal point after coming
close to it, for $\kappa \leq 4$. The estimates are uniform over all initial
segments of the curve, and are sharp up to a universal constant.


  The structure of the pentaquark state uudd-sbar is studied in the chiral
SU(3) quark model as well as in the extended chiral SU(3) quark model, in which
the vector meson exchanges are included. Four configurations of JP=1/2- and
four of JP=1/2+ are considered. The results show that the isospin T=0 state is
always the lowest one for both JP=1/2- and JP=1/2+ cases in various models. But
the theoretical value of the lowest one is still about 200-300 MeV higher than
the experimental mass of $\Theta$. It seems that a dynamical calculation should
be done for the further study.


  With 95% of Internet traffic now encrypted, an effective approach to
classifying this traffic is crucial for network security and management. This
paper introduces ECHO -- a novel optimization process for ML/DL-based encrypted
traffic classification. ECHO targets both classification time and memory
utilization and incorporates two innovative techniques.
  The first component, HO (Hyperparameter Optimization of binnings), aims at
creating efficient traffic representations. While previous research often uses
representations that map packet sizes and packet arrival times to fixed-sized
bins, we show that non-uniform binnings are significantly more efficient. These
non-uniform binnings are derived by employing a hyperparameter optimization
algorithm in the training stage. HO significantly improves accuracy given a
required representation size, or, equivalently, achieves comparable accuracy
using smaller representations.
  Then, we introduce EC (Early Classification of traffic), which enables faster
classification using a cascade of classifiers adapted for different exit times,
where classification is based on the level of confidence. EC reduces the
average classification latency by up to 90\%. Remarkably, this method not only
maintains classification accuracy but also, in certain cases, improves it.
  Using three publicly available datasets, we demonstrate that the combined
method, Early Classification with Hyperparameter Optimization (ECHO), leads to
a significant improvement in classification efficiency.


  We address the problem of recognizing emotion cause in conversations, define
two novel sub-tasks of this problem, and provide a corresponding dialogue-level
dataset, along with strong Transformer-based baselines. The dataset is
available at https://github.com/declare-lab/RECCON.
  Introduction: Recognizing the cause behind emotions in text is a fundamental
yet under-explored area of research in NLP. Advances in this area hold the
potential to improve interpretability and performance in affect-based models.
Identifying emotion causes at the utterance level in conversations is
particularly challenging due to the intermingling dynamics among the
interlocutors.
  Method: We introduce the task of Recognizing Emotion Cause in CONversations
with an accompanying dataset named RECCON, containing over 1,000 dialogues and
10,000 utterance cause-effect pairs. Furthermore, we define different cause
types based on the source of the causes, and establish strong Transformer-based
baselines to address two different sub-tasks on this dataset: causal span
extraction and causal emotion entailment.
  Result: Our Transformer-based baselines, which leverage contextual
pre-trained embeddings, such as RoBERTa, outperform the state-of-the-art
emotion cause extraction approaches
  Conclusion: We introduce a new task highly relevant for (explainable)
emotion-aware artificial intelligence: recognizing emotion cause in
conversations, provide a new highly challenging publicly available
dialogue-level dataset for this task, and give strong baseline results on this
dataset.


  Data science has been satisfactorily used to discover social issues in
several parts of the world. However, there is a lack of governmental open data
to discover those issues in countries such as Iraq. This situation arises the
following questions: how to apply data science principles to discover social
issues despite the lack of open data in Iraq? How to use the available data to
make predictions in places without data? Our contribution is the application of
data science to open non-governmental big data from the Global Database of
Events, Language, and Tone (GDELT) to discover particular violence-related
social issues in Iraq. Specifically we applied the K-Nearest Neighbors, N\"aive
Bayes, Decision Trees, and Logistic Regression classification algorithms to
discover the following issues: refugees, humanitarian aid, violent protests,
fights with artillery and tanks, and mass killings. The best results were
obtained with the Decision Trees algorithm to discover areas with refugee
crises and artillery fights. The accuracy for these two events is 0.7629. The
precision to discover the locations of refugee crises is 0.76, the recall is
0.76, and the F1-score is 0.76. Also, our approach discovers the locations of
artillery fights with a precision of 0.74, a recall of 0.75, and a F1-score of
0.75.


  Degeneration of modules is usually defined geometrically, but due to results
of Zwara and Riedtmann we can also define it in terms of exact sequences. This
definition also works over fields that are not algebraically closed. Let $k$ be
a field, $K$ a finite extension of $k$ and $\Lambda$ a $k$-algebra. Then any
$K\otimes_k\Lambda$-module is also a $\Lambda$-module. We study how the
isomorphism classes, degeneration and hom-order differ depending on which
algebra we are working over.


  The BES data on the $J/\psi \to \eta K^{*0}\bar{K}^{*0}$ reaction show a
clear enhancement in the $K^{*0}\bar{K}^{*0}$ mass distribution close to the
threshold of this channel. Such an enhancement is usually a signature of a L=0
resonance around threshold, which in this case would correspond to an $h_1$
state with quantum numbers $I^G(J^{PC})=0^-(1^{+-})$. A state around $1800\
\text{MeV}$ results from the interaction of the $K^* \bar{K}^*$ using the local
hidden gauge approach. We show that the peak observed in $J/\psi \to \eta
K^{*0}\bar{K}^{*0}$ naturally comes from the creation of this $h_1$ state with
mass and width around $1830\ \text{MeV}$ and $110\ \text{MeV}$, respectively. A
second analysis, model independent, corroborates the first result, confirming
the relationship of the enhancement in the invariant mass spectrum with the
$h_1$ resonance.


  Inference with modern Large Language Models (LLMs) is expensive and
time-consuming, and speculative sampling has proven to be an effective
solution. Most speculative sampling methods such as EAGLE use a static draft
tree, implicitly assuming that the acceptance rate of draft tokens depends only
on their position. Interestingly, we found that the acceptance rate of draft
tokens is also context-dependent. In this paper, building upon EAGLE, we
propose EAGLE-2, which introduces a new technique of context-aware dynamic
draft tree into drafting modeling. This improvement leverages the fact that the
draft model of EAGLE is well-calibrated: the confidence scores from the draft
model approximate acceptance rates with small errors. We conducted extensive
evaluations on three series of LLMs and six tasks, with EAGLE-2 achieving
speedup ratios 3.05x-4.26x, which is 20%-40% faster than EAGLE-1. EAGLE-2 also
ensures that the distribution of the generated text remains unchanged, making
it a lossless acceleration algorithm.


  We prove that a spacelike spherical symmetric constant mean curvature (SSCMC)
surface and a general spacelike constant mean curvature (CMC) surface with
certain boundary condition at the future null-infinity in Schwarzschild
spacetime are asymptotically hyperbolic in the sense of Wang \cite{Wang2001}
and Chru\'sciel-Herzlich \cite{ChruscielHerzlich} respectively. Near the future
null-infinity ($s=0$), we derive that the boundary data of spacelike CMC
surfaces can be expressed as those on $\mathbb{S}^{2}$ up to three order and
obtain a compatibility condition for fourth order derivatives near $s=0$. We
also show that if the trace free part of the second fundamental forms
$\mathring A$ of this spacelike CMC surface decay fast enough then the
restriction of its associate function $P$ (for definition, see \eqref{defofp} )
on the null-infinity must be a first eigenfunction of the Laplace on
$\mathbb{S}^2$ or constant. In particular in Minkowski spacetime, a uniqueness
result and constructions of spacelike CMC surfaces near $s=0$ are proved. Also,
we show that the inner boundary of certain spacelike CMC surfaces are totally
geodesic.


  In this paper, I calculate the large $N$ limit of marginal $O(N)$ models with
non-polynomial potentials in arbitrary odd dimensions $d$. This results in a
new class of interacting pure conformal field theories (CFTs) in $d=3+4n$ for
any $n \in \mathbb{Z}_+$. Similarly, in $d=3+4n$ I calculate the thermal
entropy for all couplings on $R^{2+4n} \times S^1$ for $n=0,1,2,3$. In 2+1
dimensions I find the strong-to-weak coupling ratio of the thermal entropy to
be 4/5, matching recent results, and further extend this analysis to higher odd
dimensions. Next, I calculated the vacuum entanglement entropy
$s^d_{\text{EE}}$ on $S^{d-2}$ for all couplings in arbitrary odd $d$ in the
large N limit. I find the vacuum entanglement entropy on $S^{d-2}$ to be not
only solvable but also constant for all couplings $\lambda$. Thus, in the large
$N$ limit, the vacuum entanglement entropy on $S^{d-2}$ for odd $d$ is constant
for all $\lambda$, in contrast to the thermal entropy which is shown to also be
monotonically decreasing with $\lambda$ in $d=3+4n$.


  It is observed that hypervelocity space dust, which is continuously
bombarding the Earth, creates immense momentum flows in the atmosphere. Some of
this fast space dust inevitably will interact with the atmospheric system,
transferring energy and moving particles around, with various possible
consequences. This paper examines, with supporting estimates, the possibility
that through collisions, the Earth-grazing component of space dust can
facilitate planetary escape of atmospheric particles, whether they be the atoms
and molecules forming the atmosphere or bigger sized particles. As one
interesting outcome, floating in the Earth's atmosphere are a variety of
particles containing the telltale signs of Earth's organic story, including
microbial life and life essential molecules. This paper will assess the ability
for this space dust collision mechanism to propel some of these biological
constituents into space.


  This paper discusses a few main topics in Number Theory, such as the
M\"{o}bius function and its generalization, leading up to the derivation of
neat power series for the prime counting function, $\pi(x)$, and the
prime-power counting function, $J(x)$. Among its main findings, we can cite the
extremely useful inversion formula for Dirichlet series (given $F_a(s)$, we
know $a(n)$, which implies the Riemann hypothesis, and enabled the creation of
a formula for $\pi(x)$ in the first place), and the realization that sums of
divisors and the M\"{o}bius function are particular cases of a more general
concept. From this result, one concludes that it's not necessary to resort to
the zeros of the analytic continuation of the zeta function to obtain $\pi(x)$.


  We investigate the discrimination of pure-mixed (quantum filtering) and
mixed-mixed states and compare their optimal success probability with the one
for discriminating other pairs of pure states superposed by the vectors
included in the mixed states. We prove that under the equal-fidelity condition,
the pure-pure state discrimination scheme is superior to the pure-mixed
(mixed-mixed) one. With respect to quantum filtering, the coherence exists only
in one pure state and is detrimental to the state discrimination for lower
dimensional systems; while it is the opposite for the mixed-mixed case with
symmetrically distributed coherence. Making an extension to
infinite-dimensional systems, we find that the coherence which is detrimental
to state discrimination may become helpful and vice versa.


  A remarkable self-duality of the "guiding-center" structure function s(q) of
particles in a partially-filled 2D Landau level is used to express the
long-wavelength collective excitation energy of fractional quantum Hall fluids
in terms of a shear modulus. A bound on the small-q behavior of s(q) is given.


  A novel method is proposed here to precisely model the multi-dimensional
features of QCD multi-jet events in hadron collisions. The method relies on the
schematization of high-pT QCD processes as 2->2 reactions made complex by
sub-leading effects. The construction of libraries of hemispheres from
experimental data and the definition of a suitable nearest-neighbor-based
association map allow for the generation of artificial events that reproduce
with surprising accuracy the kinematics of the QCD component of original data,
while remaining insensitive to small signal contaminations. The method is
succinctly described and its performance is tested in the case of the search
for the hh->bbbb process at the LHC.


  We apply quantum trajectory techniques to analyze a realistic set-up of a
superconducting qubit coupled to a heat bath formed by a resistor, a system
that yields explicit expressions of the relevant transition rates to be used in
the analysis. We discuss the main characteristics of the jump trajectories and
relate them to the expected outcomes ("clicks") of a fluorescence measurement
using the resistor as a nanocalorimeter. As the main practical outcome we
present a model that predicts the time-domain response of a realistic
calorimeter subject to single microwave photons, incorporating the intrinsic
noise due to the fundamental thermal fluctuations of the absorber and finite
bandwidth of a thermometer.


  The mathematical theory of rigidity of body-bar and body-hinge frameworks
provides a useful tool for analyzing the rigidity and flexibility of many
articulated structures appearing in engineering, robotics and biochemistry. In
this paper we develop a symmetric extension of this theory which permits a
rigidity analysis of body-bar and body-hinge structures with point group
symmetries. The infinitesimal rigidity of body-bar frameworks can naturally be
formulated in the language of the exterior (or Grassmann) algebra. Using this
algebraic formulation, we derive symmetry-adapted rigidity matrices to analyze
the infinitesimal rigidity of body-bar frameworks with Abelian point group
symmetries in an arbitrary dimension. In particular, from the patterns of these
new matrices, we derive combinatorial characterizations of infinitesimally
rigid body-bar frameworks which are generic with respect to a point group of
the form $\mathbb{Z}/2\mathbb{Z}\times \dots \times \mathbb{Z}/2\mathbb{Z}$.
Our characterizations are given in terms of packings of bases of signed-graphic
matroids on quotient graphs. Finally, we also extend our methods and results to
body-hinge frameworks with Abelian point group symmetries in an arbitrary
dimension. As special cases of these results, we obtain combinatorial
characterizations of infinitesimally rigid body-hinge frameworks with
$\mathcal{C}_2$ or $\mathcal{D}_2$ symmetry - the most common symmetry groups
found in proteins.


  Deformable Parts Models and Convolutional Networks each have achieved notable
performance in object detection. Yet these two approaches find their strengths
in complementary areas: DPMs are well-versed in object composition, modeling
fine-grained spatial relationships between parts; likewise, ConvNets are adept
at producing powerful image features, having been discriminatively trained
directly on the pixels. In this paper, we propose a new model that combines
these two approaches, obtaining the advantages of each. We train this model
using a new structured loss function that considers all bounding boxes within
an image, rather than isolated object instances. This enables the non-maximal
suppression (NMS) operation, previously treated as a separate post-processing
stage, to be integrated into the model. This allows for discriminative training
of our combined Convnet + DPM + NMS model in end-to-end fashion. We evaluate
our system on PASCAL VOC 2007 and 2011 datasets, achieving competitive results
on both benchmarks.


  Feshbach resonances - namely resonances between an unbound two-body state
(atomic state) and a bound (molecular) state, differing in magnetic moment -
are a unique tool to tune the interaction properties of ultracold atoms. Here
we show that the spin-changing interactions, coherently coupling the atomic and
molecular state, can act as a novel mechanism to stabilize an insulating phase
- the Feshbach insulator - for bosons in an optical lattice close to a narrow
Feshbach resonance. Making use of quantum Monte Carlo simulations and
mean-field theory, we show that the Feshbach insulator appears around the
resonance, preventing the system from collapsing when the effective atomic
scattering length becomes negative. On the atomic side of the resonance, the
transition from condensate to Feshbach insulator has a characteristic
first-order nature, due to the simultaneous loss of coherence in the atomic and
molecular components. These features appear clearly in the ground-state phase
diagram of e.g. $^{87}$Rb around its 414 G resonance, and they are therefore
directly amenable to experimental observation.


  We summarize our findings about laterally periodic convection structures in
binary mixtures in the Rayleigh-Benard system for positive Soret effect.
Stationary roll, square, and crossroll solutions and their stability are
determined with a multimode Galerkin expansion. The oscillatory competition of
squares and rolls in the form of crossroll oscillations is reviewed. They
undergo a subharmonic bifurcation cascade where the oscillation period grows in
integer steps as a consequence of an entrainment process.


  Exponential lepton flavor mass-ratio phenomenology with an extreme value
problem for the neutrinos predicts small Quasi-Degenerate (QD) neutrino masses,
m =(0.14-0.30)eV at 99% CL, and small solar-atmospheric oscillation hierarchy
parameter, compatible with neutrino mass and oscillation data. An attempt is
made to discover the physical meaning of the exponential exp5 which emerges as
an empirical parameter in that description. Accurate relations between the data
value of the fine structure constant and integer 5 are observed starting with a
bare value exp(-5). This value as a physical constant unifies dimensionless low
energy gauge and Higgs-scalar coupling constants of the lepton
electroweak-theory-sector and QD-neutrino mass ratios in conformity with
duality and hierarchy rules in the discussed phenomenology of lepton flavor
physics.


  We propose a regression-based approach to removing implicit biases in
representations. On tasks where the protected attribute is observed, the method
is statistically more efficient than known approaches. Further, we show that
this approach leads to debiased representations that satisfy a first order
approximation of conditional parity. Finally, we demonstrate the efficacy of
the proposed approach by reducing racial bias in recidivism risk scores.


  We theoretically study chaos synchronization of two lasers which are
delay-coupled via an active or a passive relay. While the lasers are
synchronized, their dynamics is identical to a single laser with delayed
feedback for a passive relay and identical to two delay-coupled lasers for an
active relay. Depending on the coupling parameters the system exhibits
bubbling, i.e., noise-induced desynchronization, or on-off intermittency. We
associate the desynchronization dynamics in the coherence collapse and low
frequency fluctuation regimes with the transverse instability of some of the
compound cavity's antimodes. Finally, we demonstrate how, by using an active
relay, bubbling can be suppressed.


  We review the predictions of the quark model for the doubly-heavy tetraquarks
$QQ\bar q\bar q$. The possibility of resonances near the $BB^*$ threshold in
addition to a deeply bound state is discussed.


  We report the discovery of a nearby, old, halo white dwarf candidate from the
Sloan Digital Sky Survey. SDSS J110217.48+411315.4 has a proper motion of 1.75
arcsec/year and redder optical colors than all other known featureless (type
DC) white dwarfs. We present SDSS imaging and spectroscopy of this object,
along with near-infrared photometry obtained at the United Kingdom Infra-Red
Telescope. Fitting its photometry with up-to-date model atmospheres, we find
that its overall spectral energy distribution is fit reasonably well with a
pure hydrogen composition and T_eff~3800 K (assuming log g=8). That temperature
and gravity would place this white dwarf at 35 pc from the Sun with a
tangential velocity of 290 km/s and space velocities consistent with halo
membership; furthermore, its combined main sequence and white dwarf cooling age
would be ~11 Gyr. However, if this object is a massive white dwarf, it could be
a younger object with a thick disk origin. Whatever its origin, the optical
colors of this object are redder than predicted by any current pure hydrogen,
pure helium or mixed hydrogen-helium atmospheric model, indicating that there
remain problems in our understanding of the complicated physics of the dense
atmospheres of cool white dwarfs.


  We briefly recall the history of the Nijenhuis torsion of (1,1)-tensors on
manifolds and of the lesser-known Haantjes torsion. We then show how the
Haantjes manifolds of Magri and the symplectic-Haantjes structures of Tempesta
and Tondo generalize the classical approach to integrable systems in the
bi-hamiltonian and symplectic-Nijenhuis formalisms, the sequence of powers of
the recursion operator being replaced by a family of commuting Haantjes
operators.


  Online temporal action segmentation shows a strong potential to facilitate
many HRI tasks where extended human action sequences must be tracked and
understood in real time. Traditional action segmentation approaches, however,
operate in an offline two stage approach, relying on computationally expensive
video wide features for segmentation, rendering them unsuitable for online HRI
applications. In order to facilitate online action segmentation on a stream of
incoming video data, we introduce two methods for improved training and
inference of backbone action recognition models, allowing them to be deployed
directly for online frame level classification. Firstly, we introduce surround
dense sampling whilst training to facilitate training vs. inference clip
matching and improve segment boundary predictions. Secondly, we introduce an
Online Temporally Aware Label Cleaning (O-TALC) strategy to explicitly reduce
oversegmentation during online inference. As our methods are backbone
invariant, they can be deployed with computationally efficient spatio-temporal
action recognition models capable of operating in real time with a small
segmentation latency. We show our method outperforms similar online action
segmentation work as well as matches the performance of many offline models
with access to full temporal resolution when operating on challenging
fine-grained datasets.


  adaptNMT is an open-source application that offers a streamlined approach to
the development and deployment of Recurrent Neural Networks and Transformer
models. This application is built upon the widely-adopted OpenNMT ecosystem,
and is particularly useful for new entrants to the field, as it simplifies the
setup of the development environment and creation of train, validation, and
test splits. The application offers a graphing feature that illustrates the
progress of model training, and employs SentencePiece for creating subword
segmentation models. Furthermore, the application provides an intuitive user
interface that facilitates hyperparameter customization. Notably, a
single-click model development approach has been implemented, and models
developed by adaptNMT can be evaluated using a range of metrics. To encourage
eco-friendly research, adaptNMT incorporates a green report that flags the
power consumption and kgCO${_2}$ emissions generated during model development.
The application is freely available.


  Auto-encoder is a special kind of neural network based on reconstruction.
De-noising auto-encoder (DAE) is an improved auto-encoder which is robust to
the input by corrupting the original data first and then reconstructing the
original input by minimizing the reconstruction error function. And contractive
auto-encoder (CAE) is another kind of improved auto-encoder to learn robust
feature by introducing the Frobenius norm of the Jacobean matrix of the learned
feature with respect to the original input. In this paper, we combine
de-noising auto-encoder and contractive auto- encoder, and propose another
improved auto-encoder, contractive de-noising auto- encoder (CDAE), which is
robust to both the original input and the learned feature. We stack CDAE to
extract more abstract features and apply SVM for classification. The experiment
result on benchmark dataset MNIST shows that our proposed CDAE performed better
than both DAE and CAE, proving the effective of our method.


  Machine learning systems are often trained using data collected from
historical decisions. If past decisions were biased, then automated systems
that learn from historical data will also be biased. We propose a black-box
approach to identify and remove biased training data. Machine learning models
trained on such debiased data (a subset of the original training data) have low
individual discrimination, often 0%. These models also have greater accuracy
and lower statistical disparity than models trained on the full historical
data. We evaluated our methodology in experiments using 6 real-world datasets.
Our approach outperformed seven previous approaches in terms of individual
discrimination and accuracy.


  We consider seven-vertex two-dimensional integrable statistical model. With
the help of intertwining vector method we construct its counterpart integrable
model of SOS type. More general models of both types are constructed by means
of fusion procedure. For SOS models we calculate the Boltzmann weights in terms
of terminating hypergeometric series ${}_{9} F_8.$ Then using the similarity
transformation for $R$-operators we construct a new family of vertex models
containing the 11-vertex model as the simplest representative. For this new set
of models the vertex-SOS correspondence is constructed: we find the
intertwining vectors, show that they do not depend on spectral parameter and
the SOS statistical weights are similar to those obtained from the 7-vertex
model.


  Like other experimental techniques, X-ray Photon Correlation Spectroscopy is
subject to various kinds of noise. Random and correlated fluctuations and
heterogeneities can be present in a two-time correlation function and obscure
the information about the intrinsic dynamics of a sample. Simultaneously
addressing the disparate origins of noise in the experimental data is
challenging. We propose a computational approach for improving the
signal-to-noise ratio in two-time correlation functions that is based on
Convolutional Neural Network Encoder-Decoder (CNN-ED) models. Such models
extract features from an image via convolutional layers, project them to a low
dimensional space and then reconstruct a clean image from this reduced
representation via transposed convolutional layers. Not only are ED models a
general tool for random noise removal, but their application to low
signal-to-noise data can enhance the data quantitative usage since they are
able to learn the functional form of the signal. We demonstrate that the CNN-ED
models trained on real-world experimental data help to effectively extract
equilibrium dynamics parameters from two-time correlation functions, containing
statistical noise and dynamic heterogeneities. Strategies for optimizing the
models performance and their applicability limits are discussed.


  We consider the Cauchy problem for the defocusing modified Korteweg-de Vries
(mKdV) equation with finite density type initial data. With the
$\bar{\partial}$ generalization of the nonlinear steepest descent method of
Deift and Zhou, we extrapolate the leading order approximation to the solution
of mKdV for large time in the solitonic space-time region $|x/t+4|<2$, and we
give bounds for the error which decay as $t\rightarrow\infty$ for a general
class of initial data whose difference from the non-vanishing background
possesses a fixed number of finite moments. Our results provide a verification
of the soliton resolution conjecture and asymptotic stability of $N$-soliton
solutions for mKdV equation with finite density type initial data.


  We propose a type of elastic metamaterial comprising fluid-solid composite
inclusions which can possess negative shear modulus and negative mass density
over a large frequency region. Such a solid metamaterial has a unique elastic
property that only transverse waves can propagate with a negative dispersion
while longitudinal waves are forbidden. This leads to many interesting
phenomena such as negative refraction, which is demonstrated by using a wedge
sample, and a significant amount of mode conversion from transverse waves to
longitudinal waves that cannot occur on the interface of two natural solids.


  High-mobility wireless communications have been receiving a lot attentions.
In this paper, we consider the highmobility uplink transmission from a
high-speed terminal (HST) to a base station (BS). We propose two transmit
diversity schemes for high-mobility massive communications with angle domain
Doppler compensation. In the first scheme, we propose the idea of block-wise
angle domain Doppler compensation, such that the uplink equivalent channel
would exhibit the feature of nearly perfect independent block fading. The
signal space diversity encoding technique is then exploited to achieve transmit
diversity. In the second scheme, the multiple parallel beamformers with Doppler
compensation are exclusively occupied to transmit multiple orthogonal
space-time block coding (OSTBC) data streams. Both analysis and numerical
results verify that both the proposed schemes can achieve transmit diversity
and outperform the conventional scheme.


  Supersymmetric unification in warped space provides new possibilities for
model building. I argue that the picture of warped supersymmetric unification
arises naturally through the AdS/CFT correspondence from the assumption that
supersymmetry is dynamically broken at a scale about (10 - 100) TeV, and
present several fully realistic theories in this framework. In the minimal
model, the bulk SU(5) gauge group is broken at the Planck brane by boundary
conditions, while supersymmetry is broken at the TeV brane. The theory
preserves the successes of conventional supersymmetric unification, and yet
physics at accessible energies has a drastic departure from that of the
conventional scenario. There are also several variations of the minimal model
giving distinct phenomenologies. These theories can provide a basis for
phenomenological studies of dynamical supersymmetry breaking at low energies.


  We study two-player multi-weighted reachability games played on a finite
directed graph, where an agent, called P1, has several quantitative
reachability objectives that he wants to optimize against an antagonistic
environment, called P2. In this setting, we ask what cost profiles P1 can
ensure regardless of the opponent's behavior. Cost profiles are compared thanks
to: (i) a lexicographic order that ensures the unicity of an upper value and
(ii) a componentwise order for which we consider the Pareto frontier. We
synthesize (i) lexico-optimal strategies and (ii) Pareto-optimal strategies.
The strategies are obtained thanks to a fixpoint algorithm which also computes
the upper value in polynomial time and the Pareto frontier in exponential time.
Finally, the constrained existence problem is proved in P for the lexicographic
order and PSPACE-complete for the componentwise order.


  This paper deals with the Keller--Segel system with signal-dependent
sensitivity \begin{equation*} u_t=\Delta u - \nabla \cdot (u \chi(v)\nabla v),
\quad v_t=\Delta v + u - v, \quad x\in\Omega,\ t>0, \end{equation*} where
$\Omega$ is a bounded domain in $\mathbb{R}^n$, $n\geq 2$; $\chi$ is a function
satisfying $\chi(s)\leq K(a+s)^{-k}$ for some $k\geq 1$ and $a\geq 0$. In the
case that $k=1$, Fujie (J. Math. Anal. Appl.; 2015; 424; 675--684) established
global existence of bounded solutions under the condition
$K<\sqrt{\frac{2}{n}}$. On the other hand, when $k>1$, Winkler (Math. Nachr.;
2010; 283; 1664--1673) asserted global existence of bounded solutions for
arbitrary $K>0$. However, there is a gap in the proof. Recently, Fujie tried
modifying the proof; nevertheless it also has a gap. It seems to be difficult
to show global existence of bounded solutions for arbitrary $K>0$. Moreover,
the condition for $K$ when $k>1$ cannot connect to the condition when $k=1$.
The purpose of the present paper is to obtain global existence and boundedness
under more natural and proper condition for $\chi$ and to build a mathematical
bridge between the cases $k=1$ and $k>1$.


  There is growing interest in the possible link between the growth of
supermassive black holes and the effect of feedback from them on galaxy growth.
There are three areas of significant uncertainty: (i) the physics of the
feedback; (ii) the prevalence and effectiveness of feedback; (iii) the link
between the growth of black holes and their hosts. The 2QZ optical QSO survey
indicates that luminous QSOs are relatively short-lived, and it has recently
been shown that the observed bolometric luminosity density from all AGN and its
evolution can be reproduced if black holes grew coevally with their galaxies,
implying but not requiring a causal link between galaxy growth and black hole
growth. At low redshifts there is some evidence that black hole and galaxy
growth are starting to decouple.


  The Internet of Things (IoT) has witnessed unprecedented growth, resulting in
a massive influx of diverse network traffic from interconnected devices.
Effectively classifying this network traffic is crucial for optimizing resource
allocation, enhancing security measures, and ensuring efficient network
management in IoT systems. Deep learning has emerged as a powerful technique
for network traffic classification due to its ability to automatically learn
complex patterns and representations from raw data. This survey paper aims to
provide a comprehensive overview of the existing deep learning approaches
employed in network traffic classification specifically tailored for IoT
environments. By systematically analyzing and categorizing the latest research
contributions in this domain, we explore the strengths and limitations of
various deep learning models in handling the unique challenges posed by IoT
network traffic. Through this survey, we aim to offer researchers and
practitioners valuable insights, identify research gaps, and provide directions
for future research to further enhance the effectiveness and efficiency of deep
learning-based network traffic classification in IoT.


  We study the multi-armed bandit (MAB) problem where the agent receives a
vectorial feedback that encodes many possibly competing objectives to be
optimized. The goal of the agent is to find a policy, which can optimize these
objectives simultaneously in a fair way. This multi-objective online
optimization problem is formalized by using the Generalized Gini Index (GGI)
aggregation function. We propose an online gradient descent algorithm which
exploits the convexity of the GGI aggregation function, and controls the
exploration in a careful way achieving a distribution-free regret
$\tilde{\bigO} (T^{-1/2} )$ with high probability. We test our algorithm on
synthetic data as well as on an electric battery control problem where the goal
is to trade off the use of the different cells of a battery in order to balance
their respective degradation rates.


  Original definition of the pseudogap [11,12] allowes to connect it
conceptually with a topological insulator. It concerns the multiband
superconductivity background with variable chemical potential position.


  We present a reduction of the termination problem for a Turing machine (in
the simplified form of the Post correspondence problem) to the problem of
determining whether a continuous-time Markov chain presented as a set of Kappa
graph-rewriting rules has an equilibrium. It follows that the problem of
whether a computable CTMC is dissipative (ie does not have an equilibrium) is
undecidable.


  We present a detailed derivation of the electromagnetic force density and
pressure in linear dielectric media according to the so-called Microscopic
Amp\`ere formulation, which considers the classical dipolar sources in matter
along with the hidden momentum contribution. It is seen that, among the other
formulations existing in the literature, our proposal is the only one
simultaneously compatible with the experimental works reported to date and with
the absence of magnetic monopoles in nature. A new radiation pressure equation
for non-magnetic dielectrics under oblique illumination from p-polarized beams
is also derived.


  We discuss $Z$ mediated flavour changing neutral currents within a model
where the hierarchical quark and lepton masses are explained via a fourth
vector-like family, together with a scalar sector consisting of two Higgs
doublets augmented by a gauge singlet scalar field that spontaneously breaks an
extra global $U(1)^{\prime}$ symmetry. The $Z$ mediated flavor violating
interactions arise from the mixings between the SM fermions and the vector-like
fermions, where the mixing is discussed in an analytic approximation and also
exactly numerically. We first discuss charged lepton flavor violating (CLFV)
$\tau \rightarrow \mu \gamma, \tau \rightarrow 3\mu$ and $Z \rightarrow \mu
\tau$ decays and find that they cannot significantly constrain the masses of
charged vector-like leptons. However, the $790 \text{GeV}$ mass bound arising
from collider searches on vector-like lepton doublets can set further
constraints on the model parameter space. We also consider rare $t \rightarrow
c Z$ decays as well as unitarity violation in the CKM mixing in order to
constrain the quark sector of the model under consideration.


  We provide exact analytical solutions for the problem of time-optimal
transfer of coherence from one spin polarization to a three-fold coherence in a
trilinear Ising chain with a fixed energy available and subject to local
controls with a non negligible time cost. The time of transfer is optimal and
consistent with a previous numerical result obtained assuming instantaneous
local controls.


  Fragmentation of the planetesimals is found to play a role whose importance
is greater than previously believed and depends on the average characteristic
size of the primordial planetesimals but not on their mass distribution. In the
small size range the mass spectrum is strongly modified with the formation of a
small bodies tail but, on the other hand, the growth of the most massive
objects is significantly slowed down. The formation of planetary embryos much
more massive than the rest of the swarm is delayed; nevertheless the time-scale
problem for the growth of the outer planets is not revived.


  We present a fast numerical algorithm for large scale zero-sum stochastic
games with perfect information, which combines policy iteration and algebraic
multigrid methods. This algorithm can be applied either to a true finite state
space zero-sum two player game or to the discretization of an Isaacs equation.
We present numerical tests on discretizations of Isaacs equations or
variational inequalities. We also present a full multi-level policy iteration,
similar to FMG, which allows to improve substantially the computation time for
solving some variational inequalities.


  We establish a central limit theorem and prove a moderate deviation principle
for stochastic scalar conservation laws. Due to the lack of viscous term, this
is done in the framework of kinetic solution. The weak convergence method and
doubling variables method play a key role.


  We investigate the contact process on four different types of scale-free
inhomogeneous random graphs evolving according to a stationary dynamics, where
each potential edge is updated with a rate depending on the strength of the
adjacent vertices. Depending on the type of graph, the tail exponent of the
degree distribution and the updating rate, we find parameter regimes of fast
and slow extinction and in the latter case identify metastable exponents that
undergo first order phase transitions.


  We report on the non-adiabatic offset of the initial electron momentum
distribution in the plane of polarization upon single ionization of argon by
strong field tunneling and show how to experimentally control the degree of
non-adiabaticity. Two-color counter- and co-rotating fields (390 and 780 nm)
are compared to show that the non-adiabatic offset strongly depends on the
temporal evolution of the laser electric field. We introduce a simple method
for the direct access to the non-adiabatic offset using two-color counter- and
co-rotating fields. Further, for a single-color circularly polarized field at
780 nm we show that the radius of the experimentally observed donut-like
distribution increases for increasing momentum in the light propagation
direction. Our observed initial momentum offsets are well reproduced by the
strong-field approximation (SFA). A mechanistic picture is introduced that
links the measured non-adiabatic offset to the magnetic quantum number of
virtually populated intermediate states.


  We investigate the Majorana physics and its effect on the electron transport
in the non-topological superconductor(NS)-topological superconductor(TS) double
junctions of a ring geometry. We find that, depending on the ratio between the
lengths of two topologically different regions and the localization lengths of
the Majorana fermions formed between them, two completely different transport
mechanisms are working: perfect crossed Andreev reflection (CAR) for the short
NS region and perfect normal Andreev reflection for the short TS region. The
difference is explained in terms of the topologically distinct properties of
subgap states in the NS-TS double junction system, which have not been revealed
so far. The exotic dependence of the CAR process on the magnetic flux threading
the ring is uncovered and can be used to detect the Majorana fermions.


  Weak localization corrections to conductivity of ferromagnetic systems are
studied theoretically in the case when spin-orbit interaction plays a
significant role. Two cases are analyzed in detail: (i) the case when the
spin-orbit interaction is due to scattering from impurities, and (ii) the case
when the spin-orbit interaction results from reduced dimensionality of the
system and is of the Bychkov-Rashba type. Results of the analysis show that the
localization corrections to conductivity of ferromagnetic metals lead to a
negative magnetoresistance -- also in the presence of the spin-orbit
scattering. Positive magnetoresistance due to weak antilocalization, typical of
nonmagnetic systems, does not occur in ferromagnetic systems. In the case of
two-dimensional ferromagnets, the quantum corrections depend on the
magnetization orientation with respect to the plane of the system.


  We use some of the recently released observational data to test the viability
of two classes of minimally coupled scalar field models of quintessence with
exponential potentials for which exact solutions of the Einstein equations are
known. These models are very sturdy, depending on only one parameter - the
Hubble constant. To compare predictions of our models with observations we
concentrate on the following data: the power spectrum of the CMBR anisotropy as
measured by WMAP, the publicly available data on type Ia supernovae, and the
parameters of large scale structure determined by the 2-degree Field Galaxy
Redshift Survey (2dFGRS). We use the WMAP data on the age of the universe and
the Hubble constant to fix the free parameters in our models. We then show that
the predictions of our models are consistent with the observed positions and
relative heights of the first 3 peaks in the CMB power spectrum, with the
energy density of dark energy as deduced from observations of distant type Ia
supernovae, and with parameters of the large scale structure as determined by
2dFGRS, in particular with the average density of dark matter. Our models are
also consistent with the results of the Sloan Digital Sky Survey (SDSS).
Moreover, we investigate the evolution of matter density perturbations in our
quintessential models, solve exactly the evolution equation for the density
perturbations, and obtain an analytical expression for the growth index $f$. We
verify that the approximate relation f ~ Omega_M^(alpha) also holds in our
models.


  We present for the first time a complex network approach to the study of the
electrical properties of single protein devices. In particular, we consider an
electronic nanobiosensor based on a G-protein coupled receptor. By adopting a
coarse grain description, the protein is modeled as a complex network of
elementary impedances. The positions of the alpha-carbon atoms of each amino
acid are taken as the nodes of the network. The amino acids are assumed to
interact electrically among them. Consequently, a link is drawn between any
pair of nodes neighboring in space within a given distance and an elementary
impedance is associated with each link. The value of this impedance can be
related to the physical and chemical properties of the amino acid pair and to
their relative distance. Accordingly, the conformational changes of the
receptor induced by the capture of the ligand, are translated into a variation
of its electrical properties. Stochastic fluctuations in the value of the
elementary impedances of the network, which mimic different physical effects,
have also been considered. Preliminary results concerning the impedance
spectrum of the network and its fluctuations are presented and discussed for
different values of the model parameters.


  Surface plasma waves (SPWs) are usually discussed in the context of a metal
in contact with a dielectric. However, they can also exist between two metals.
In this work we study these bimetallic waves. We find that their dispersion
curve always cuts the light line, which allows direct optical coupling without
surface grating structures. We propose practical schemes to excite them and the
excitation efficiency is estimated. We also show that these waves can be much
less lossy than conventional SPWs and their losses can be systematically
controlled, a highly desirable attribute in applications. Conducting metal
oxides are apt for experimental studies.


  We study the effects of unparticle physics on the cosmic ray photon and
$e^\pm$, including on the pair production (PP) and elastic scattering (ES) of
cosmic ray photon off various background radiations, and on the inverse Compton
scattering of cosmic ray $e^\pm$ with cosmic radiations. We compute the
spin-averaged amplitudes squared of three processes and find that the advent of
unparticle will never significantly change the interactions of cosmic ray
photon and $e^\pm$ with various background radiations, although the available
papers show that ES which occurs in the tree-level through unparticle exchanges
will easily surpass PP in the approximate parameter regions.


  Behavior Trees (BTs) are becoming a popular tool to model the behaviors of
autonomous agents in the computer game and the robotics industry. One of the
key advantages of BTs lies in their composability, where complex behaviors can
be built by composing simpler ones. The parallel composition is the one with
the highest potential since the complexity of composing pre-existing behaviors
in parallel is much lower than the one needed using classical control
architectures as finite state machines. However, the parallel composition is
rarely used due to the underlying concurrency problems that are similar to the
ones faced in concurrent programming. In this paper, we define two
synchronization techniques to tackle the concurrency problems in BTs
compositions and we show how to exploit them to improve behavior
predictability. Also, we introduce measures to assess execution performance,
and we show how design choices can affect them. To illustrate the proposed
framework, we provide a set of experiments using the R1 robot and we gather
statistically-significant data.


  We present a preliminary analysis of the heavy-heavy spectrum and heavy-light
decay constants in full QCD, using a tadpole-improved SW quark action and an
RG-improved gauge action on a 16^3 x 32 lattice with four sea quark masses
corresponding to m_pi/m_rho = 0.8, 0.75, 0.7, 0.6 and a^-1 = 1.3 GeV. We focus
particularly on the effect of sea quarks on these observables.


  We study the thermal structure and evolution of magnetars as cooling neutron
stars with a phenomenological heat source in an internal layer. We focus on the
effect of magnetized (B > 10^{14} G) non-accreted and accreted outermost
envelopes composed of different elements, from iron to hydrogen or helium. We
discuss a combined effect of thermal conduction and neutrino emission in the
outer neutron star crust and calculate the cooling of magnetars with a dipole
magnetic field for various locations of the heat layer, heat rates and magnetic
field strengths. Combined effects of strong magnetic fields and light-element
composition simplify the interpretation of magnetars in our model: these
effects allow one to interpret observations assuming less extreme (therefore,
more realistic) heating. Massive magnetars, with fast neutrino cooling in their
cores, can have higher thermal surface luminosity.