  It is known that inhomogeneous second-order macroscopic traffic models can
reproduce the phantom traffic jam phenomenon: whenever the sub-characteristic
condition is violated, uniform traffic flow is unstable, and small
perturbations grow into nonlinear traveling waves, called jamitons. In
contrast, what is essentially unstudied is the question: which jamiton
solutions are dynamically stable? To understand which stop-and-go traffic waves
can arise through the dynamics of the model, this question is critical. This
paper first presents a computational study demonstrating which types of
jamitons do arise dynamically, and which do not. Then, a procedure is presented
that characterizes the stability of jamitons. The study reveals that a critical
component of this analysis is the proper treatment of the perturbations to the
shocks, and of the neighborhood of the sonic points.


  Collective coordinates are frequently employed in path integrals to manage
divergences caused by fluctuations around saddle points that align with
classical symmetries. These coordinates parameterize a manifold of zero modes
and more broadly provide judicious coordinates on the space of fields. However,
changing from local coordinates around a saddle point to more global collective
coordinates is remarkably subtle. The main complication is that the mapping
from local coordinates to collective coordinates is generically multi-valued.
Consequently one is forced to either restrict the domain of path integral in a
delicate way, or otherwise correct for the multi-valuedness by dividing the
path integral by certain intersection numbers. We provide a careful treatment
of how to fix collective coordinates while accounting for these intersection
numbers, and then demonstrate the importance of the fix for free theories. We
also provide a detailed study of the fix for interacting theories and show that
the contributions of higher intersections to the path integral can be
non-perturbatively suppressed. Using a variety of examples ranging from
single-particle quantum mechanics to quantum field theory, we explain and
resolve various pitfalls in the implementation of collective coordinates.


  Detuned systems can spontaneously achieve a synchronous dynamics and display
robust quantum correlations in different local and global dissipation regimes.
Beyond the Markovian limit, information backflow from the environment becomes a
crucial mechanism whose interplay with spontaneous synchronization is unknown.
Considering a model of two coupled qubits, one of which interacts with a
dissipative environment, we show that non-Markovianity is highly detrimental
for the emergence of synchronization, for the latter can be delayed and
hindered because of the presence of information backflow. The results are
obtained considering both a master equation approach and a collision model
based on repeated interactions, which represents a very versatile tool to
tailor the desired kind of environment.


  The power graph $\mathcal{P}(G)$ of a finite group $G$ is the simple
undirected graph whose vertex set is $G$, in which two distinct vertices are
adjacent if one of them is an integral power of the other. For an integer
$n\geq 2$, let $C_n$ denote the cyclic group of order $n$ and let $r$ be the
number of distinct prime divisors of $n$. The minimum degree
$\delta(\mathcal{P}(C_n))$ of $\mathcal{P}(C_n)$ is known for $r\in\{1,2\}$,
see [18]. For $r\geq 3$, under certain conditions involving the prime divisors
of $n$, we identify at most $r-1$ vertices such that $\delta(\mathcal{P}(C_n))$
is equal to the degree of at least one of these vertices. If $r=3$ or if $n$ is
a product of distinct primes, we are able to identify two such vertices without
any condition on the prime divisors of $n$.


  Higher Spin Gravities are scarce, but covariant actions for them are even
scarcer. We construct covariant actions for contractions of Chiral Higher Spin
Gravity that represent higher spin extensions of self-dual Yang-Mills and
self-dual Gravity theories. The actions give examples of complete higher spin
theories both in flat and (anti)-de Sitter spaces that feature gauge and
gravitational interactions. The actions are based on a new description of
higher spin fields, whose origin can be traced to early works on twistor
theory. The new description simplifies the structure of interactions. In
particular, we find a covariant form of the minimal gravitational interaction
for higher spin fields both in flat and anti-de Sitter space, which resolves
some of the puzzles in the literature.


  A parametrization, given by the Euler angles, of Hermitian matrix generators
of even and odd-degenerate Clifford algebras is constructed by means of the
Kronecker product of a parametrized version of Pauli matrices and by the
identification of all possible anticommutation sets for a given algebra. The
internal parametrization of the matrix generators allows a straightforward
interpretation in terms of rotations, and in the absence of a similarity
transformation can be reduced to the canonical representations by an
appropriate choice of parameters. The parametric matrix generators of 2nd and
4th-order are linearly decomposed in terms of Pauli, Dirac, and 4th-order
Gell-Mann matrices establishing a direct correspondence between the bases. In
addition, and with the expectation for further applications in group theory, a
linear decomposition of GL(4) matrices on the basis of the parametric 4th-order
matrix generators and in terms of four-vector parameters is explored. By
establishing unitary conditions, a parametrization of two sub-groups of SU(4)
is achieved.


  These notes reflect the contents of three lectures given at the workshop of
the 14th International Conference on Representations of Algebras (ICRA XIV),
held in August 2010 in Tokyo. We first provide an introduction to quantum loop
algebras and their finite-dimensional representations. We explain in particular
Nakajima's geometric description of the irreducible q-characters in terms of
graded quiver varieties. We then present a recent attempt to understand the
tensor structure of the category of finite- dimensional representations by
means of cluster algebras.


  Red supergiants are massive evolved stars that contribute extensively to the
chemical enrichment of our Galaxy. It has been shown that convection in those
stars gives rise to large granules that cause surface inhomogeneities and shock
waves in the photosphere. The understanding of their dynamics is crucial to
unveil the unknown mass-loss mechanism, their chemical composition and stellar
parameters. We present a new generation of red supergiants simulations with a
more sophisticated opacity treatment done with 3D radiative- hydrodynamics
CO5BOLD. In the code, the coupled equations of compressible hydrodynamics and
non-local radiation transport are solved in the presence of a spherical
potential. The stellar core is replaced by a special spherical inner boundary
condition, where the gravitational potential is smoothed and the energy
production by fusion is mimicked by a simply producing heat corresponding to
the stellar luminosity. The post-processing radiative transfer code OPTIM3D is
used to extract spectroscopic and interferometric observables. We show that the
relaxation of the assumption of frequency-independent opacities shows a steeper
mean thermal gradient in the optical thin region that affect strongly the
atomic strengths and the spectral energy distribution. Moreover, the weaker
temperature fluctuations reduce the incertitude on the radius determination
with interferometry. We show that 1D models of red supergiants must include a
turbulent velocity calibrated on 3D simulations to obtain the effective surface
gravity that mimic the effect of turbulent pressure on the stellar atmosphere.
We provide an empirical calibration of the ad-hoc micro- and macroturbulence
parameters for 1D models using the 3D simulations: we find that there is not a
clear distinction between the different macroturbulent profiles needed in 1D
models to fit 3D synthetic lines.


  Adaptive optics (AO) systems have significantly improved astronomical imaging
capabilities over the last decade, and are revolutionizing the kinds of science
possible with 4-5m class ground-based telescopes. A thorough understanding of
AO system performance at the telescope can enable new frontiers of science as
observations push AO systems to their performance limits. We look at recent
advances with wave front reconstruction (WFR) on the Advanced Electro-Optical
System (AEOS) 3.6 m telescope to show how progress made in improving WFR can be
measured directly in improved science images. We describe how a "waffle mode"
wave front error (which is not sensed by a Fried geometry Shack-Hartmann wave
front sensor) affects the AO point-spread function (PSF). We model details of
AEOS AO to simulate a PSF which matches the actual AO PSF in the I-band, and
show that while the older observed AEOS PSF contained several times more waffle
error than expected, improved WFR techniques noticeably improve AEOS AO
performance. We estimate the impact of these improved WFRs on H-band imaging at
AEOS, chosen based on the optimization of the Lyot Project near-infrared
coronagraph at this bandpass.


  In cosmology, we would like to explain our observations and predict future
observations from theories of the entire universe. Such cosmological theories
make ontological assumptions of what entities exist and what their properties
and relationships are. One must also make epistemological assumptions or
metatheories of how one can test cosmological theories. Here I shall propose a
Bayesian analysis in which the likelihood of a complete theory is given by the
normalized measure it assigns to the observation used to test the theory. In
this context, a discussion is given of the trade-off between prior
probabilities and likelihoods, of the measure problem of cosmology, of the
death of Born's rule, of the Boltzmann brain problem, of whether there is a
better principle for prior probabilities than mathematical simplicity, and of
an Optimal Argument for the Existence of God.


  We argue that ultra-high energy cosmic rays emitted by galaxy clusters result
in electric currents in filaments of the large-scale structure that are
sufficient to generate magnetic fields in voids of the magnitude of ~1e-12 G
and the coherence length of up to tens of Mpc. These fields satisfy both the
lower and upper observational bounds on magnetic fields in voids without a need
of any primordial component.


  We develop a quasiclassical method based on the path integral formalism, to
study the influence of disorder on magnetooscillations of the density of states
and conductivity. The treatment is appropriate for electron systems in the
presence of a random potential with large correlation length or a random
magnetic field, which are characterisitic features of various 2D electronic
systems presently studied in experiment. In particular, we study the system of
composite fermions in the fractional quantum Hall effect device, which are
coupled to the Chern--Simons field and subject to a long--range random
potential.


  A spherical n-gon is a bordered surface homeomorphic to a closed disk, with n
distinguished boundary points called corners, equipped with a Riemannian metric
of constant curvature 1, except at the corners, and such that the boundary arcs
between the corners are geodesic. We discuss the problem of classification of
these polygons and enumerate them in the case that two angles at the corners
are not multiples of pi. The problem is equivalent to classification of some
second order linear differential equations with regular singularities, with
real parameters and unitary monodromy.


  Self-excited systems arise in numerous applications, such as biochemical
systems, fluid-structure interaction, and combustion. This paper analyzes a
discrete-time Lur'e system with a piecewise-linear saturation feedback
nonlinearity. The main result provides sufficient conditions under which the
Lur'e system is self-excited in the sense that its response is bounded and
nonconvergent.


  We present first results of $Z+4$ jet cross sections at the Tevatron $p\bar
p$ collider with heavy quark flavor identification. The $Z + 4$ jet channel is
of particular interest as a normalizer for the $W +4$ jet background to top
quark signals, as a background to a possible $t\to cZ$ flavor-changing
neutral-current (FCNC) decay signal, and as a background to missing-$p_T$
signals from gluino pairs. We also calculate the different heavy flavor
contributions to $W+4$ jet production. The MADGRAPH program is used to generate
all leading order subprocess helicity amplitudes. We present Monte Carlo
studies with separation and acceptance criteria suitable for the Tevatron
experimental analyses.


  A tree view or tree navigator is used to display hierarchical data organized
in the form of a tree. In a tree structure there are parent and child nodes.
The child nodes may further have descendants to n levels.
  There are many methods to make the navigation easy. Some of these are
expanding and collapsing branches, splitting the tree, displaying a parent node
in a separate tree, zooming branches, scrolling in various directions etc. It
is still a difficult exercise to handle large trees efficiently. The effort
still continues to manage large number of nodes with faster speed, greater
control, user friendliness and aesthetics.
  This article illustrates five inventions on tree navigators selected from US
patent database. Each of them tries to solve various problems relating to the
tree navigator in different ways. Each invention is also analyzed from a TRIZ
perspective.


  When doing data science, it's important to know what you're building. This
paper describes an idealized final product of a data science project, called a
Continuously Updated Data-Analysis System (CUDAS). The CUDAS concept
synthesizes ideas from a range of successful data science projects, such as
Nate Silver's FiveThirtyEight. A CUDAS can be built for any context, such as
the state of the economy, the state of the climate, and so on. To demonstrate,
we build two CUDAS systems. The first provides continuously-updated ratings for
soccer players, based on the newly developed Augmented Adjusted Plus-Minus
statistic. The second creates a large dataset of synthetic ecosystems, which is
used for agent-based modeling of infectious diseases.


  Recent modeling of the warm absorber in active galactic nuclei has proved the
usefulness of constant total (gas plus radiation) pressure models, which are
highly stratified in temperature and density. We explore the consistency of
those models when the typical variation of the flux from the central source is
taken into account. We perform a variability study of the warm absorber
response, based on timescales and our photoionization code TITAN. We show that
the ionization and recombination timescales are much shorter than the dynamical
timescale. Clouds very close to the central black hole will maintain their
equilibrium since the characteristic variability timescales of the nuclear
source are longer than cloud timescales. For more distant clouds, the density
structure has no time to vary, in response to the variations of the temperature
or ionization structure, and such clouds will show the departure from the
constant pressure equilibrium. We explore the impact of this departure on the
observed properties of the transmitted spectrum and soft X-ray variability: (i)
non uniform velocities, of the order of sound speed, appear due to pressure
gradients, up to typical values of 100 km/s. These velocities lead to the
broadening of lines. This broadening is usually observed and very difficult to
explain otherwise. (ii) Energy-dependent fractional variability amplitude in
soft X-ray range has a broader hump around ~ 1-2 keV, and (iv) the plot of the
equivalent hydrogen column density vs. ionization parameter is steeper than for
equilibrium clouds. The results have the character of a preliminary study and
should be supplemented in the future with full time-dependent radiation
transfer and dynamical computations.


  We analyze the ordering efficiency and the structure of disordered
configurations for the zero-temperature Glauber model on Watts-Strogatz
networks obtained by rewiring 2D regular square lattices. In the small-world
regime, the dynamics fails to reach the ordered state in the thermodynamic
limit. Due to interplay of the perturbed regular topology and the energy
neutral stochastic state transitions, the stationary state consists of two
intertwined domains, manifested as multi-clustered states on the original
lattice. Moreover, for intermediate rewiring probabilities, one finds an
additional source of disorder due to the low connectivity degree, which gives
rise to small isolated droplets of spins. We also examine the ordering process
in paradigmatic two-layer networks with heterogeneous rewiring probabilities.
Comparing the cases of a multiplex network and the corresponding network with
random inter-layer connectivity, we demonstrate that the character of the final
state qualitatively depends on the type of inter-layer connections.


  In the theory of zero-dimensional systems and their relation to
$C^*$-algebras, Poon (1990) introduced a class of closed sets. We call the
closed sets quasi-sections. Medynets (2006) introduced basic sets that are part
of quasi-sections in his study of aperiodic zero-dimensional systems and their
relation to Bratteli--Vershik models and $C^*$-algebras. Downarowicz and Karpel
(2019) introduced the notion of decisiveness in the theory of Bratteli--Vershik
models. We previously clarified that particular quasi-sections can be the
"bases" of the decisive Bratteli--Vershik models for zero-dimensional systems
with dense aperiodic orbits. We call them continuously decisive quasi-sections.
However, even the basic topological properties of quasi-sections and the basic
sets have not been studied systematically. This paper presents such a
systematic study. Some properties are defined, stated, and proved in the
general settings of compact Hausdorff topological dynamics. For example, if a
topological dynamical system has dense aperiodic orbits and no wandering
points, then every basic set is continuously decisive. If a zero-dimensional
system has dense aperiodic orbits, then there exists a minimal continuously
decisive basic set such that for every minimal set, there exists a unique
common point.


  The advent of smart power grid which plays a vital role in the upcoming smart
city era is accompanied with the implementation of a monitoring tool, called
state estimation. For the case of the unbalanced residential distribution grid,
the state estimating operation which is conducted at a regional scale is
considered as an application of the edge computing-based Internet of Things
(IoT). While the outcome of the state estimation is important to the subsequent
control activities, its accuracy heavily depends on the data integrity of the
information collected from the scattered measurement devices. This fact exposes
the vulnerability of the state estimation module under the effect of
data-driven attacks. Among these, false data injection attack (FDI) is
attracting much attention due to its capability to interfere with the normal
operation of the network without being detected. This paper presents an attack
design scheme based on a nonlinear physical-constraint model that is able to
produce an FDI attack with theoretically stealthy characteristic. To
demonstrate the effectiveness of the proposed design scheme, simulations with
the IEEE 13-node test feeder and the WSCC 9-bus system are conducted. The
experimental results indicate that not only the false positive rate of the bad
data detection mechanism is 100 per cent but the physical consequence of the
attack is severe. These results pose a serious challenge for operators in
maintaining the integrity of measurement data.


  The absence or presence of extremely wide binaries with a radio pulsar and an
optical counterpart imposes a strong constraint on the existence and magnitude
of kicks in supernova explosions. We search for such systems by comparing the
positions of radio pulsars which are not known to be in binaries with the
positions of visible stars, and find that the number of associations is
negligible. According to the performed population synthesis, this implies that
kicks must occur, with a lower limit of at least 10 to 20 km/s.


  Let $\Omega$ denote an algebra of sets and $\mu$ a $\sigma$-finite measure.
We then prove that the completion of $\Omega$ under the pseudometric $d(A,B)$ =
$\mu^{\ast}(A \triangle B)$ is $\sigma$-algebra isomorphic and isometric to the
Caratheodory Extension of $\Omega$ under the equivalence relation $\sim$.


  Critical parts of the definitions of standard serial and standard parallel
modes refer to stochastic independence. Standard serial models are defined by
stochastic independence and identical distributions of their processing times.
Processing times in the serial models are identical to the intercompletion time
statistics. Similarly, standard parallel models assume stochastically
independent and identical processing times. Their processing times are
equivalent to the statistic known as total completion times. Little is known
about what standard serial models can predict for the total completion time or
what standard parallel models can predict for the intercompletion times. Here
we demonstrate that standard serial models possess a tendency to predict a
positive dependence for the total completion times with that always being true
in the case of a single processing order. However, with mixtures of processing
orders, standard serial models may predict negative dependence of the total
completion times. Comparably, standard parallel models typically predict
neither independence of the intercompletion times nor identical distributions.
In fact, standard parallel models predict increasing intercompletion times as
the individual channels continue to finish. Nevertheless, dramatically
increasing hazard functions of the channels can defeat that tendency. And,
standard parallel models can predict intercompletion time independence but only
when individual channel distributions are exponential. Finally, we use these
and ancillary mathematical results to conclude that standard serial and
standard parallel models can never perfectly mimic one another. Therefore, our
findings set the stage for explicit model testing between these classes.


  This paper applies the Thomas decomposition technique to nonlinear control
systems, in particular to the study of the dependence of the system behavior on
parameters. Thomas' algorithm is a symbolic method which splits a given system
of nonlinear partial differential equations into a finite family of so-called
simple systems which are formally integrable and define a partition of the
solution set of the original differential system. Different simple systems of a
Thomas decomposition describe different structural behavior of the control
system in general. The paper gives an introduction to the Thomas decomposition
method and shows how notions such as invertibility, observability and flat
outputs can be studied. A Maple implementation of Thomas' algorithm is used to
illustrate the techniques on explicit examples.


  We exploit a recent computation of one graviton loop corrections to the
self-mass [1] to quantum-correct the field equation for a massless, conformally
coupled scalar on a de Sitter background. With the obvious choice for the
finite part of the $R^2 \phi^2$ counterterm, we find that neither plane wave
mode functions nor the response to a point source acquires large infrared
logarithms. However, we do find a decaying logarithmic correction to the mode
function and a short distance logarithmic running of the potential in addition
to the power-law effect inherited from flat space.


  In this paper we study the implications for conference program committees of
using single-blind reviewing, in which committee members are aware of the names
and affiliations of paper authors, versus double-blind reviewing, in which this
information is not visible to committee members. WSDM 2017, the 10th ACM
International ACM Conference on Web Search and Data Mining, performed a
controlled experiment in which each paper was reviewed by four committee
members. Two of these four reviewers were chosen from a pool of committee
members who had access to author information; the other two were chosen from a
disjoint pool who did not have access to this information. This information
asymmetry persisted through the process of bidding for papers, reviewing
papers, and entering scores. Reviewers in the single-blind condition typically
bid for 22% fewer papers, and preferentially bid for papers from top
institutions. Once papers were allocated to reviewers, single-blind reviewers
were significantly more likely than their double-blind counterparts to
recommend for acceptance papers from famous authors and top institutions. The
estimated odds multipliers are 1.63 for famous authors and 1.58 and 2.10 for
top universities and companies respectively, so the result is tangible. For
female authors, the associated odds multiplier of 0.78 is not statistically
significant in our study. However, a meta-analysis places this value in line
with that of other experiments, and in the context of this larger aggregate the
gender effect is also statistically significant.


  We establish a representation of the joint moments of the characteristic
polynomial of a CUE random matrix and its derivative in terms of a solution of
the sigma-Painleve V equation. The derivation involves the analysis of a
formula for the joint moments in terms of a determinant of generalised Laguerre
polynomials using the Riemann-Hilbert method. We use this connection with the
sigma-Painleve V equation to derive explicit formulae for the joint moments and
to show that in the large-matrix limit the joint moments are related to a
solution of the sigma-Painleve III equation. Using the conformal block
expansion of the tau-functions associated with the sigma-Painleve V and the
sigma-Painleve III equations leads to general conjectures for the joint
moments.


  Initialization and readout of coupled quantum systems are essential
ingredients for the implementation of quantum algorithms. If the state of a
multi-qubit register can be read out in a single shot, this enables further key
resources such as quantum error correction and deterministic quantum
teleportation, as well as direct investigation of quantum correlations
(entanglement). While spins in solids are attractive candidates for scalable
quantum information processing, thus far single-shot detection has only been
achieved for isolated qubits. Here, we demonstrate preparation and measurement
of a multi-spin quantum register by implementing resonant optical excitation
techniques originally developed in atomic physics. We achieve high-fidelity
readout of the electronic spin associated with a single nitrogen-vacancy (NV)
centre in diamond at low temperature, and exploit this readout to project up to
three nearby nuclear spin qubits onto a well-defined state. Conversely, we can
distinguish the state of the nuclear spins in a single shot by mapping it onto
and subsequently measuring the electronic spin. Finally, we show compatibility
with qubit control by demonstrating initialization, coherent manipulation, and
single-shot readout in a single experiment on a two-qubit register, using
techniques suitable for extension to larger registers. These results pave the
way for the first test of Bell's inequalities on solid-state spins and the
implementation of measurement-based quantum information protocols.


  We present a new data-driven benchmark system to evaluate the performance of
new MCMC samplers. Taking inspiration from the COCO benchmark in optimization,
we view this task as having critical importance to machine learning and
statistics given the rate at which new samplers are proposed. The common
hand-crafted examples to test new samplers are unsatisfactory; we take a
meta-learning-like approach to generate benchmark examples from a large corpus
of data sets and models. Surrogates of posteriors found in real problems are
created using highly flexible density models including modern neural network
based approaches. We provide new insights into the real effective sample size
of various samplers per unit time and the estimation efficiency of the samplers
per sample. Additionally, we provide a meta-analysis to assess the predictive
utility of various MCMC diagnostics and perform a nonparametric regression to
combine them.


  The ground state of a microcavity polariton Bose-Einstein condensate is
determined by considering experimentally tunable parameters such as excitation
density, detuning, and ultraviolet cutoff. During a change in the ground state
of Bose-Einstein condensate from excitonic to photonic, which occurs as
increasing the excitation density, the origin of the binding force of
electron-hole pairs changes from Coulomb to photon-mediated interactions. The
change in the origin gives rise to the strongly bound pairs with a small
radius, like Frenkel excitons, in the photonic regime. The change in the ground
state can be a crossover or a first-order transition, depending on the
above-mentionsed parameters, and is outlined by a phase diagram. Our result
provides valuable information that can be used to build theoretical models for
each regime.


  As the key to sentiment analysis, sentiment composition considers the
classification of a constituent via classifications of its contained
sub-constituents and rules operated on them. Such compositionality has been
widely studied previously in the form of hierarchical trees including untagged
and sentiment ones, which are intrinsically suboptimal in our view. To address
this, we propose semantic tree, a new tree form capable of interpreting the
sentiment composition in a principled way. Semantic tree is a derivation of a
context-free grammar (CFG) describing the specific composition rules on
difference semantic roles, which is designed carefully following previous
linguistic conclusions. However, semantic tree is a latent variable since there
is no its annotation in regular datasets. Thus, in our method, it is
marginalized out via inside algorithm and learned to optimize the
classification performance. Quantitative and qualitative results demonstrate
that our method not only achieves better or competitive results compared to
baselines in the setting of regular and domain adaptation classification, and
also generates plausible tree explanations.


  We investigate the structural relaxation of a soft-sphere liquid quenched
isochorically ($\phi=0.7$) and instantaneously to different temperatures $T_f$
above and below the glass transition. For this, we combine extensive Brownian
dynamics simulations and theoretical calculations based on the non-equilibrium
self-consistent generalized Langevin equation (NE-SCGLE) theory. The response
of the liquid to a quench generally consists of a sub-linear increase of the
$\alpha$-relaxation time with system's age. Approaching the ideal
glass-transition temperature from above ($T_f>T^a$) sub-aging appears as a
transient process describing a broad equilibration crossover for quenches to
nearly arrested states. This allows us to empirically determine an
equilibration timescale $t^{eq}(T_f)$ that becomes increasingly longer as $T_f$
approaches $T^a$. For quenches inside the glass ($T_f\leq T^a$) the growth rate
of the structural relaxation time becomes progressively larger as $T_f$
decreases and, unlike the equilibration scenario, $\tau_{\alpha}$ remains
evolving within the whole observation time-window.These features are
consistently found in theory and simulations with remarkable semi-quantitative
agreement, and coincide with those revealed in the similar and complementary
exercise [Phys. Rev. {\bf 96}, 022608 (2017)] that considered a sequence of
quenches with fixed final temperature $T_f=0$ but increasing $\phi$ towards the
hard-sphere dynamical arrest volume fraction $\phi^a_{HS}=0.582$. The NE-SCGLE
analysis, however, unveils various fundamental aspects of the glass transition,
involving the abrupt passage from the ordinary equilibration scenario to the
persistent aging effects that are characteristic of glass-forming liquids. The
theory also explains that, within the time window of any experimental
observation, this can only be observed as a continuous crossover.


  We proposed a GAN-based method to generate a ship hull form. Unlike
mathematical hull forms that require geometrical parameters to generate ship
hull forms, the proposed method requires desirable ship performance parameters,
i.e., the drag coefficient and tonnage. The requirements of ship owners are
generally focused on the ship performance and not the geometry itself. Hence,
the proposed model is useful for obtaining the ship hull form based on an
owner's requirements. The GAN model was trained using a ship hull form dataset
generated using the generalized Wigley hull form. The proposed method was
evaluated through numerical experiments and successfully generated ship data
with small errors.


  Recently proposed models which learn to write computer programs from data use
either input/output examples or rich execution traces. Instead, we argue that a
novel alternative is to use a glass-box loss function, given as a program
itself that can be directly inspected. Glass-box optimization covers a wide
range of problems, from computing the greatest common divisor of two integers,
to learning-to-learn problems.
  In this paper, we present an intelligent search system which learns, given
the partial program and the glass-box problem, the probabilities over the space
of programs. We empirically demonstrate that our informed search procedure
leads to significant improvements compared to brute-force program search, both
in terms of accuracy and time. For our experiments we use rich context free
grammars inspired by number theory, text processing, and algebra. Our results
show that (i) performing 4 rounds of our framework typically solves about 70%
of the target problems, (ii) our framework can improve itself even in domain
agnostic scenarios, and (iii) it can solve problems that would be otherwise too
slow to solve with brute-force search.


  We report the first results from a deep Lya imaging program of local
starburst galaxies with the Advanced Camera for Surveys (ACS) of the Hubble
Space Telescope. The two observed galaxies ESO 350-IG038 and SBS 0335-052 have
luminosities similar to those of the Magellanic Clouds but differ in their
chemical composition. ESO 350-IG038 has an oxygen abundance of 1/8 solar,
whereas SBS 0335-052 is known to have one of the lowest abundances among blue
galaxies (~1/30). The ACS imaging reveals a complex Lya morphology, with
sometimes strong offsets between the emission of Lya and the location of
stellar light, ionized gas traced by Halpha, and the neutral gas. Overall, more
Lya photons escape from the more metal- and dust-rich galaxy ESO 350-IG038. The
absence of clear SBS 0335-052 Lya emission over all observed knots, whatever
their dust content or/and color indices, contradicts model expectations of a
lower escape fraction from dust-rich gas due to destruction of Lya photons by
dust grains. Rather, the results are in qualitative agreement with models
suggesting the kinematic properties of the gas as the dominant Lya escape
regulator. If the properties of the two observed galaxies are representative
for starburst galaxies in general, Lya will be difficult to interpret as a
star-formation indicator, in particular if based on Lya imaging at low spatial
resolution.


  We study heating and dissipation effects in granular nanosystems in the
regime of weak coupling between the grains. We focus on the cotunneling regime
and solve the heat-dissipation problem in an array of grains exactly. We show
that the power to heat ratio has a universal quantized value, which is
geometrically protected: it depends only on the number of grains.


  We calculate steady-state models of radiation-driven super-Eddington winds
and static expanded envelopes of neutron stars caused by high luminosities in
type I X-ray bursts. We use flux-limited diffusion to model the transition from
optically thick to optically thin, and include effects of general relativity,
allowing us to study the photospheric radius close to the star as the
hydrostatic atmosphere evolves into a wind. We find that the photospheric
radius evolves monotonically from static envelopes ($r_{\rm ph}\lesssim 50-70$
km) to winds ($r_{\rm ph}\approx 100-1000$ km). Photospheric radii of less than
$100$ km, as observed in most photospheric radius expansion bursts, can be
explained by static envelopes, but only in a narrow range of luminosity. In
most bursts, we would expect the luminosity to increase further, leading to a
wind with photospheric radius $\gtrsim 100$ km. In the contraction phase, the
expanded envelope solutions show that the photosphere is still $\approx 1$ km
above the surface when the effective temperature is only $3\%$ away from its
maximum value. This is a possible systematic uncertainty when interpreting the
measured Eddington fluxes from bursts at touchdown. We also discuss the
applicability of steady-state models to describe the dynamics of bursts. In
particular, we show that the sub to super-Eddington transition during the burst
rise is rapid enough that static models are not appropriate. Finally, we
analyze the strength of spectral shifts in our models. Expected shifts at the
photosphere are dominated by gravitational redshift, and are therefore
predicted to be less than a few percent.


  This paper proposes a new parametric level set method for topology
optimization based on Deep Neural Network (DNN). In this method, the fully
connected deep neural network is incorporated into the conventional level set
methods to construct an effective approach for structural topology
optimization. The implicit function of level set is described by fully
connected deep neural networks. A DNN-based level set optimization method is
proposed, where the Hamilton-Jacobi partial differential equations (PDEs) are
transformed into parametrized ordinary differential equations (ODEs). The
zero-level set of implicit function is updated through updating the weights and
biases of networks. The parametrized reinitialization is applied periodically
to prevent the implicit function from being too steep or too flat in the
vicinity of its zero-level set. The proposed method is implemented in the
framework of minimum compliance, which is a well-known benchmark for topology
optimization. In practice, designers desire to have multiple design options,
where they can choose a better conceptual design base on their design
experience. One of the major advantages of DNN-based level set method is its
ability to generate diverse and competitive designs with different network
architectures. Several numerical examples are presented to verify the
effectiveness of the proposed DNN-based level set method.


  We examine the utility of implicit user behavioral signals captured using
low-cost, off-the-shelf devices for anonymous gender and emotion recognition. A
user study designed to examine male and female sensitivity to facial emotions
confirms that females recognize (especially negative) emotions quicker and more
accurately than men, mirroring prior findings. Implicit viewer responses in the
form of EEG brain signals and eye movements are then examined for existence of
(a) emotion and gender-specific patterns from event-related potentials (ERPs)
and fixation distributions and (b) emotion and gender discriminability.
Experiments reveal that (i) Gender and emotion-specific differences are
observable from ERPs, (ii) multiple similarities exist between explicit
responses gathered from users and their implicit behavioral signals, and (iii)
Significantly above-chance ($\approx$70%) gender recognition is achievable on
comparing emotion-specific EEG responses-- gender differences are encoded best
for anger and disgust. Also, fairly modest valence (positive vs negative
emotion) recognition is achieved with EEG and eye-based features.


  Accurately measuring the Hubble parameter is vital for understanding the
expansion history and properties of the universe. In this paper, we propose a
new method that supplements the covariance between redshift pairs to improve
the reconstruction of the Hubble parameter using the OHD dataset. Our approach
utilizes a cosmological model-independent radial basis function neural network
(RBFNN) to describe the Hubble parameter as a function of redshift effectively.
Our experiments show that this method results in a reconstructed Hubble
parameter of $H_0 = 67.1\pm9.7~\mathrm{km~s^{-1}~Mpc^{-1}}$ , which is more
noise-resistant and fits better with the $\Lambda$CDM model at high redshifts.
Providing the covariance between redshift pairs in subsequent observations will
significantly improve the reliability and accuracy of Hubble parametric data
reconstruction. Future applications of this method could help overcome the
limitations of previous methods and lead to new advances in our understanding
of the universe.


  Low-capacitance Josephson junction systems as well as coupled quantum dots,
in a parameter range where single charges can be controlled, provide physical
realizations of quantum bits, discussed in connection with quantum computing.
The necessary manipulation of the quantum states can be controlled by applied
gate voltages. In addition, the state of the system has to be read out. Here we
suggest to measure the quantum state by coupling a single-electron transistor
to the q-bit. As long as no transport voltage is applied, the transistor
influences the quantum dynamics of the q-bit only weakly. We have analyzed the
time evolution of the density matrix of the transistor and q-bit when a voltage
is turned on. For values of the capacitances and temperatures which can be
realized by modern nano-techniques the process constitutes a quantum
measurement process.


  We present spectroscopic observations of the black-hole binary V4641
Sagittarii, obtained between 4th July 2004 and 28th March 2005, which cover the
minor outburst of the star in early July 2004 and quiescence variations on 19
nights scattered over six months. During the outburst, the star peaked
approximately 3 magnitudes brighter than usual, and our spectra were dominated
by broad hydrogen, helium and iron emission lines. The very first spectra
showed P Cygni profiles, which disappeared within a few hours, indicating rapid
changes in matter ejection. The H-alpha line had multiple components, one being
a broad blue-shifted wing exceeding 5000 km/s. During a simultaneously observed
10-min photometric flare-up, the equivalent width of the H-alpha line
temporarily decreased, implying that it was a flare of the continuum. The
overall spectral appearance was similar to that observed in the 1999 September
active phase, which suggests that similar mass-ejection processes were
associated with both eruptions. In quiescence, the spectra were those of the
early-type secondary star showing its orbital motion around the primary. By
measuring cross-correlation radial velocities, we give an improved set of
spectroscopic elements. Whereas we measure the same velocity amplitude
(K_2=211.3+/-1.0 km/s), within errors, as Orosz et al. (2001), our
centre-of-mass velocity (v_gamma=72.7+/-3.3 km/s) differs significantly from
the previously published value (107.4+/-m2.9 km/s). However, we find evidence
that the difference is caused by a systematic error in data reduction in the
previous study, rather than by gravitational effects of an invisible third
component.


  We study the crossed Andreev effects in two-dimensional
conductor/superconductor hybrid systems under a perpendicular magnetic field.
Both a graphene/superconductor hybrid system and an electron gas/superconductor
one are considered. It is shown that an exclusive crossed Andreev reflection,
with other Andreev reflections being completely suppressed, is obtained in a
high magnetic field because of the chiral edge states in the quantum Hall
regime. Importantly, the exclusive crossed Andreev reflection not only holds
for a wide range of system parameters, e.g., the size of system, the width of
central superconductor, and the quality of coupling between the graphene and
the superconductor, but also is very robust against disorder. When the applied
bias is within the superconductor gap, a robust Cooper-pair splitting process
with high-efficiency can be realized in this system.


  Based on the thermal phase structure of pure SU(2) quantum Yang-Mills theory,
we describe the electron at rest as an extended particle, a so-called blob of
radius $r_0$ which is comparable to the Bohr radius $a_0$. This blob is of
vanishing pressure and traps an electric-magnetic dually interpreted BPS
monopole within its bulk at a temperature of $T_0=7.95$ keV. Utilizing a
spherical mirror-charge construction, we approximate the blob's charge at a
value of the electromagnetic fine-structure constant $\alpha$ of
$\alpha^{-1}\sim 134$ for soft external probes. It is shown that the blob does
not exhibit an electric dipole or quadrupole moment. We also calculate the
mixing angle $\theta_{\rm W}\sim 30^{\circ}$ belonging to the deconfining
phases of two SU(2) gauge theories of very distinct Yang-Mills scales
($\Lambda_{\rm e}=3.6 $ keV and $\Lambda_{\rm CMB}\sim 10^{-4} $eV) which
establish the blob's stable bulk thermodynamics. The core radius of the
monopole is about 1 % of $r_0$.


  As well as several different kinds of periodically ordered ferroic phases,
there are now recognized several different examples of ferroic glassiness,
although not always described as such and in material fields of study that have
mostly been developed separately. In this chapter an attempt is made to
indicate common conceptual origins and features, observed or anticipated.
Throughout, this aim is pursued through the use of simple models, in an attempt
to determine probable fundamental origins within a larger picture of greater
complication, and analogies between systems in different areas, both
experimental and theoretical, in the light of significant progress in spin
glass understanding.


  The ability to manipulate the refractive index is a fundamental principle
underlying numerous photonic devices. Various techniques exist to modify the
refractive index across diverse materials, making performance comparison far
from straightforward. In evaluating these methods, power consumption emerges as
a key performance characteristic, alongside bandwidth and footprint. Here I
undertake a comprehensive comparison of the energy and power requirements for
the most well-known index change schemes. The findings reveal that while the
energy per volume for index change remains within the same order of magnitude
across different techniques and materials, the power consumption required to
achieve switching, 100% modulation, or 100% frequency conversion can differ
significantly, spanning many orders of magnitude. As it turns out, the material
used has less influence on power reduction than the specific resonant or
traveling wave scheme employed to enhance the interaction time between light
and matter. Though this work is not intended to serve as a design guide, it
does establish the limitations and trade-offs involved in index modulation,
thus providing valuable insights for photonics practitioners.


  We measure and analyze galaxy clustering and the dependence on luminosity,
color, age, stellar mass and specific star formation rate using Baryon
Oscillation Spectroscopic Survey (BOSS) galaxies at $0.48<z<0.62$. We fit the
monopole and quadrupole moments of the two-point correlation function (2PCF)
and its projection on scales of $0.1$ -- $60.2h^{-1}$Mpc, after having split
the catalog in a variety of ways. We find that the clustering dependence is
consistent with previous well-established results showing the broad trends
expected: For example, that brighter, redder, older, more massive and quenched
galaxies are more strongly clustered. We also investigate the dependence on
additional parameters previously derived from stellar population synthesis
model fits to the spectra. We find that galaxy clustering depends on look-back
formation time at a low level, while it has little dependence on metallicity.
To understand the physics behind these trends, we fit the clustering with a
simulation-based emulator to simultaneously model cosmology and galaxy bias
using a Halo Occupation Distribution framework. After marginalizing parameters
determining the background cosmology, galaxy bias, and a scaling parameter to
decouple halo velocity field, we find that the growth rate of large scale
structure as determined by the redshift-space distortions is consistent with
previous analysis using the full sample, and we do not find evidence that
cosmological constraints depend systematically on galaxy selection. This
demonstrates that cosmological inference using small scale clustering
measurements is robust to changes in the catalog selection.


  We describe our plan to develop a large-scale cluster system with a peak
speed of 14.3Tflops for lattice QCD at the Center for Computational Sciences,
University of Tsukuba, as a successor to the current 0.6Tflops CP-PACS
computer. The system consist of 2560 nodes connected by a 16x16x10
three-dimensional hyper crossbar network. Each node has a single low-voltage
2.8GHz Xeon processor and 2GBytes of memory with 6.4GBytes/sec bandwidth, and
160 GBytes of disk in RAID1 mode. The network link in each of the three
directions is made of dual Gigabit Ethernet with the peak throughput of
250MByte/sec. Hence each node has an aggregate network bandwidth of
750MByte/sec. The system will run under Linux and SCore, and an extension of
the PM driver is developed for the network. The system will be developed
jointly with Hitachi Limited. The installation is scheduled in the first
quarter of Japanese Fiscal 2006 (April-June 2006) and the start of operation is
expected in July 2006.


  Quantum computing has gained considerable attention, especially after the
arrival of the Noisy Intermediate-Scale Quantum (NISQ) era. Quantum processors
and cloud services have been made world-wide increasingly available.
Unfortunately, programs on existing quantum processors are often executed in
series, and the workload could be heavy to the processor. Typically, one has to
wait for hours or even longer to obtain the result of a single quantum program
on public quantum cloud due to long queue time. In fact, as the scale grows,
the qubit utilization rate of the serial execution mode will further diminish,
causing the waste of quantum resources. In this paper, to our best knowledge
for the first time, the Quantum Program Scheduling Problem (QPSP) is formulated
and introduced to improve the utility efficiency of quantum resources.
Specifically, a quantum program scheduling method concerning the circuit width,
number of measurement shots, and submission time of quantum programs is
proposed to reduce the execution latency. We conduct extensive experiments on a
simulated Qiskit noise model, as well as on the Xiaohong (from QuantumCTek)
superconducting quantum processor. Numerical results show the effectiveness in
both QPU time and turnaround time.


  Weak-temperature-gradient influences from the tropics and quasigeostrophic
influences from the extratropics plausibly constrain the subtropical-mean
static stability in terrestrial atmospheres. Because mean descent acting on
this static stability is a leading-order term in the thermodynamic balance, a
state-invariant static stability would impose constraints on the Hadley cells,
which this paper explores in simulations of varying planetary rotation rate. If
downdraft-averaged effective heating (the sum of diabatic heating and eddy heat
flux convergence) too is invariant, so must be vertical velocity -- an "omega
governor." In that case, the Hadley circulation overturning strength and
downdraft width must scale identically -- the cell can strengthen only by
widening or weaken only by narrowing. Simulations in two idealized, dry GCMs
with a wide range of planetary rotation rates exhibit nearly unchanging
downdraft-averaged static stability, effective heating, and vertical velocity,
as well as nearly identical scalings of the Hadley cell downdraft width and
strength. In one, eddy stresses set this scaling directly (the Rossby number
remains small); in the other, eddy stress and bulk Rossby number changes
compensate to yield the same, ({\sim}\Omega^{-1/3}) scaling. The consistency of
this power law for cell width and strength variations may indicate a common
driver, and we speculate that Ekman pumping could be the mechanism responsible
for this behavior. Extending to moist atmospheres, in an idealized aquaplanet
GCM the subtropical static stability is also insensitive to rotation rate but
the effective heating and vertical velocity are not.


  Morphology and its stability are essential features to address
physicochemical properties of metallic nanoparticles. By means of Molecular
Dynamics based simulations we show a complex dependence on the size and
material of common structural mechanisms taking place in mono-metallic
nanoparticles at icosahedral magic sizes. We show that the well known Lipscomb
s Diamond Square Diamond mechanisms, single step screw dislocation motions of
the whole cluster, take place only below a given size which is material
dependent. Above that size, layer by layer dislocations and/or surface peeling
are likely to happen, leading to low symmetry defected motifs. The material
dependence of this critical size is similar to the crossover sizes among
structural motifs, based on the ration between the bulk modulus and atomic
cohesive energy.


  We describe the design of a new polarization sensitive receiver, SPT-3G, for
the 10-meter South Pole Telescope (SPT). The SPT-3G receiver will deliver a
factor of ~20 improvement in mapping speed over the current receiver, SPTpol.
The sensitivity of the SPT-3G receiver will enable the advance from statistical
detection of B-mode polarization anisotropy power to high signal-to-noise
measurements of the individual modes, i.e., maps. This will lead to precise
(~0.06 eV) constraints on the sum of neutrino masses with the potential to
directly address the neutrino mass hierarchy. It will allow a separation of the
lensing and inflationary B-mode power spectra, improving constraints on the
amplitude and shape of the primordial signal, either through SPT-3G data alone
or in combination with BICEP-2/KECK, which is observing the same area of sky.
The measurement of small-scale temperature anisotropy will provide new
constraints on the epoch of reionization. Additional science from the SPT-3G
survey will be significantly enhanced by the synergy with the ongoing optical
Dark Energy Survey (DES), including: a 1% constraint on the bias of optical
tracers of large-scale structure, a measurement of the differential Doppler
signal from pairs of galaxy clusters that will test General Relativity on ~200
Mpc scales, and improved cosmological constraints from the abundance of
clusters of galaxies.


  We propose a novel network initialization method using Perlin noise for
training image classification networks with a limited amount of data. Our main
idea is to initialize the network parameters by solving an artificial noise
classification problem, where the aim is to classify Perlin noise samples into
their noise categories. Specifically, the proposed method consists of two
steps. First, it generates Perlin noise samples with category labels defined
based on noise complexity. Second, it solves a classification problem, in which
network parameters are optimized to classify the generated noise samples. This
method produces a reasonable set of initial weights (filters) for image
classification. To the best of our knowledge, this is the first work to
initialize networks by solving an artificial optimization problem without using
any real-world images. Our experiments show that the proposed method
outperforms conventional initialization methods on four image classification
datasets.


  We report new estimates of the time delays in the quadruple gravitationally
lensed quasar PG1115+080, obtained from the monitoring data in filter R with
the 1.5-m telescope at the Maidanak Mountain (Uzbekistan, Central Asia) in
2004-2006. The time delays are 16.4 days between images C and B, and 12 days
between C and A1+A2, with image C being leading for both pairs. The only known
estimates of the time delays in PG1115 are those based on observations by
Schechter et al. (1997) -- 23.7 and 9.4 days between images C and B, C and
A1+A2, respectively, as calculated by Schechter et al., and 25 and 13.3 days as
revised by Barkana (1997) for the same image components with the use of another
method. The new values of time delays in PG 1115+080 may be expected to provide
larger estimates of the Hubble constant thus decreasing a diversity between the
H_0 estimates taken from gravitationally lensed quasars and with other methods.


  Due to limited budgets allocated for road maintenance projects in various
countries, road management departments face difficulties in making scientific
maintenance decisions. This paper aims to provide road management departments
with more scientific decision tools and evidence. The framework proposed in
this paper mainly has the following four innovative points: 1) Predicting
pavement performance deterioration levels of road sections as decision basis
rather than accurately predicting specific indicator values; 2) Determining
maintenance route priorities based on multiple factors; 3) Making maintenance
plan decisions by establishing deep reinforcement learning models to formulate
predictive strategies based on past maintenance performance evaluations, while
considering both technical and management indicators; 4) Determining repair
section priorities according to actual and suggested repair effects. By
resolving these four issues, the framework can make intelligent decisions
regarding optimal maintenance plans and sections, taking into account limited
funds and historical maintenance management experiences.


  We calculate the homotopy type of the Brown-Comenetz dual $I_2$ of the
K(2)-local sphere at the prime 3 and show that there is a twisting by a
non-trivial element $P$ in the exotic part of the Picard group. We give a
complete characterization of $P$ as well. The main technique is to give a
sequence of calculations of the homotopy groups of elements of the Picard group
after smashing with the Smith-Toda complex V(1).


  Cubic SrTiO$_{3}$ becomes tetragonal below 105 K. The antiferrodistortive
(AFD) distortion leads to clockwise and counter-clockwise rotation of adjacent
TiO$_{6}$ octahedra. This insulator becomes a metal upon the introduction of
extremely low concentration of n-type dopants. However, signatures of the
structural phase transition in charge conduction have remained elusive.
Employing the Montgomery technique, we succeed in resolving the anisotropy of
charge conductivity induced by the AFD transition, in the presence of different
types of dopants. We find that the slight lattice distortion ($<6 \times
10^{-4}$) gives rise to a twenty percent anisotropy in charge conductivity, in
agreement with the expectations of band calculations. Application of uniaxial
strain amplifies the detectable anisotropy by disfavoring one of the three
possible tetragonal domains. In contrast with all other known anisotropic Fermi
liquids, the anisotropy has opposite signs for elastic and inelastic
scattering. Increasing the concentration of dopants leads to a drastic shift in
the temperature of the AFD transition either upward or downward. The latter
result puts strong constraints on any hypothetical role played by the AFD soft
mode in the formation of Cooper pairs and the emergence of superconductivity in
SrTiO$_3$.


  Crystallization often proceeds through successive stages that lead to a
gradual increase in organization. Using molecular simulation, we determine the
nucleation pathway for solid solutions of copper and gold. We identify a new
nucleation mechanism (liquid$\to$$L1_2$~precursor$\to$solid solution),
involving a chemically ordered intermediate that is more organized than the end
product. This nucleation pathway arises from the low formation energy of $L1_2$
clusters which, in turn, promote crystal nucleation. We also show that this
mechanism is composition-dependent since the high formation energy of other
ordered phases precludes them from acting as precursors.


  We consider the numerical integration of the matrix Hill's equation.
Parametric resonances can appear and this property is of great interest in many
different physical applications. Usually, the Hill's equations originate from a
Hamiltonian function and the fundamental matrix solution is a symplectic
matrix. This is a very important property to be preserved by the numerical
integrators. In this work we present new sixth-and eighth-order symplectic
exponential integrators that are tailored to the Hill's equation. The methods
are based on an efficient symplectic approximation to the exponential of high
dimensional coupled autonomous harmonic oscillators and yield accurate results
for oscillatory problems at a low computational cost. Several numerical
examples illustrate the performance of the new methods.


  GD-1 is a long, thin, Milky Way star stream that has readily visible density
variations along its length. We quantify the locations, sizes and statistical
significance of the density structure, i.e. gaps, using a set of scaled
filters. The shapes of the filters are based on the gaps that develop in
simulations of dark matter sub-halos crossing a star stream. The high Galactic
latitude 8.4 kpc long segment of GD-1 that we examine has 8+/-3 gaps of 99%
significance or greater, with the error estimated on the basis of tests of the
gap-filtering technique. The cumulative distribution of gaps more than 3 times
the width of the stream is in good agreement with predictions for dark matter
sub-halo encounters with cold star streams. The number of gaps narrower than 3
times the width of the GD-1 stream falls well below the cold stream prediction
which is taken into account for the gap creation rate integrated over all
sizes. Simple warm stream simulations scaled to GD-1 show that the falloff in
gaps is expected for sub-halos below a mass of 10^6 M_sun. The GD-1 gaps
requires 100 sub-halos >10^6 M_sun within 30 kpc, the apocenter of GD-1 orbit.
These results are consistent with LCDM sub-halo predictions but further
improvements in stream signal-to-noise and gap modeling will be welcome.


  Traveling wave solutions to Kawahara equation (KE), transmission line (TL),
and Korteweg-de Vries (KdV) equation are found by using an elliptic function
method which is more general than the $\mathrm{tanh}$-method. The method works
by assuming that a polynomial ansatz satisfies a Weierstrass equation, and has
two advantages: first, it reduces the number of terms in the ansatz by an order
of two, and second, it uses Weierstrass functions which satisfy an elliptic
equation for the dependent variable instead of the hyperbolic tangent functions
which only satisfy the Riccati equation with constant coefficients.
  When the polynomial ansatz in the traveling wave variable is of first order,
the equation reduces to the KdV equation with only a cubic dispersion term,
while for the KE which includes a fifth order dispersion term the polynomial
ansatz must necessary be of quadratic type.
  By solving the elliptic equation with coefficients that depend on the
boundary conditions, velocity of the traveling waves, nonlinear strength, and
dispersion coefficients, in the case of KdV equation we find the well-known
solitary waves (solitons) for zero boundary conditions, as well as wave-trains
of cnoidal waves for nonzero boundary conditions. Both solutions are either
compressive (bright) or rarefactive (dark), and either propagate to the left or
right with arbitrary velocity.


  This paper is concerned with the study of a geometric flow whose law involves
a singular integral operator. This operator is used to define a non-local mean
curvature of a set. Moreover the associated flow appears in two important
applications: dislocation dynamics and phase field theory for fractional
reaction-diffusion equations. It is defined by using the level set method. The
main results of this paper are: on one hand, the proper level set formulation
of the geometric flow; on the other hand, stability and comparison results for
the geometric equation associated with the flow.


  In any geometrically nonlinear, isotropic and quadratic Cosserat micropolar
extended continuum model formulated in the deformation gradient field $F =
\nabla\varphi : \Omega \to GL^+(n)$ and the microrotation field $R: \Omega \to
SO(n)$, the shear-stretch energy is necessarily of the form
  $$W_{\mu,\mu_c}(R;F) = \mu\, \| sym(R^T F - 1) \|^2 + \mu_c\, \| skew(R^T F -
1) \|^2 .$$
  We aim at the derivation of closed form expressions for the minimizers of
$W(R;F)$ in $SO(3)$, i.e., for the set of optimal Cosserat microrotations in
dimension $n = 3$, as a function of $F \in GL^+(n)$. In a previous contribution
(Part I), we have first shown that, for all $n \geq 2$, the full range of
weights $\mu > 0$ and $\mu_c \geq 0$ can be reduced to either a classical or a
non-classical limit case. We have then derived the associated closed form
expressions for the optimal planar rotations in $SO(2)$ and proved their global
optimality. In the present contribution (Part II), we characterize the
non-classical optimal rotations in dimension n = 3. After a lift of the
minimization problem to the unit quaternions, the Euler-Lagrange equations can
be symbolically solved by the computer algebra system Mathematica. Among the
symbolic expressions for the critical points, we single out two candidates
$rpolar^{\pm}_{\mu,\mu_c}(F) \in SO(3)$ which we analyze and for which we can
computationally validate their global optimality by Monte Carlo statistical
sampling of $SO(3)$. Geometrically, our proposed optimal Cosserat rotations
$rpolar^{\pm}_{\mu,\mu_c}(F)$ act in the "plane of maximal strain" and our
previously obtained explicit formulae for planar optimal Cosserat rotations in
$SO(2)$ reveal themselves as a simple special case. Further, we derive the
associated reduced energy levels of the Cosserat shear--stretch energy and
criteria for the existence of non-classical optimal rotations.


  We prove excision in entire and periodic cyclic cohomology and construct a
Chern-Connes character for Fredholm modules over a C*-algebra without
summability restrictions, taking values in a variant of Connes's entire cyclic
cohomology.
  Before these results can be obtained, we have to sort out some fundamental
questions about the class of algebras on which to define entire cyclic
cohomology. The right domain of definition for entire cyclic cohomology is the
category of complete bornological algebras. For these algebras, we define a
bivariant cohomology theory, called analytic cyclic cohomology, that contains
Connes's entire cyclic cohomology as a special case.
  The definition of analytic cyclic cohomology is based on the Cuntz-Quillen
approach to cyclic cohomology theories using tensor algebras and X-complexes.
The appropriate completion of the tensor algebra that yields analytic cyclic
cohomology can be understood using an appropriate notion of analytic
nilpotence.
  In addition, we develop the elementary theory of analytic cyclic cohomology
(smooth homotopy invariance, stability, Chern character in K-theory).


  We compute ground state fidelity of the one-dimensional Bose-Hubbard model at
unit filling factor. To this aim, we apply the DMRG algorithm to systems with
open and periodic boundary conditions. We find that fidelity differs
significantly in the two cases and study its scaling properties in the quantum
critical regime.


  We review some applications of relativistic shells that are relevant in the
context of quantum gravity/quantum cosmology. Using a recently developed
approach, the stationary states of this general relativistic system can be
determined in the semiclassical approximation. We suggest that this technique
might be of phenomenological relevance in the context of the brane-world
scenario and we draw a picture of the general set-up and of the possible
developments.


  Exploratory visual data analysis tools empower data analysts to efficiently
and intuitively explore data insights throughout the entire analysis cycle.
However, the gap between common programmatic analysis (e.g., within
computational notebooks) and exploratory visual analysis leads to a disjointed
and inefficient data analysis experience. To bridge this gap, we developed
PyGWalker, a Python library that offers on-the-fly assistance for exploratory
visual data analysis. It features a lightweight and intuitive GUI with a shelf
builder modality. Its loosely coupled architecture supports multiple
computational environments to accommodate varying data sizes. Since its release
in February 2023, PyGWalker has gained much attention, with 612k downloads on
PyPI and over 10.5k stars on GitHub as of June 2024. This demonstrates its
value to the data science and visualization community, with researchers and
developers integrating it into their own applications and studies.


  In the past few years, convolutional neural networks (CNNs) have achieved
impressive results in computer vision tasks, which however mainly focus on
photos with natural scene content. Besides, non-sensor derived images such as
illustrations, data visualizations, figures, etc. are typically used to convey
complex information or to explore large datasets. However, this kind of images
has received little attention in computer vision. CNNs and similar techniques
use large volumes of training data. Currently, many document analysis systems
are trained in part on scene images due to the lack of large datasets of
educational image data. In this paper, we address this issue and present
SlideImages, a dataset for the task of classifying educational illustrations.
SlideImages contains training data collected from various sources, e.g.,
Wikimedia Commons and the AI2D dataset, and test data collected from
educational slides. We have reserved all the actual educational images as a
test dataset in order to ensure that the approaches using this dataset
generalize well to new educational images, and potentially other domains.
Furthermore, we present a baseline system using a standard deep neural
architecture and discuss dealing with the challenge of limited training data.


  There is a recent surge of interest in the behavior of active particles that
can at the same time align their direction of movement and synchronize their
oscillations, known as swarmalators. While theoretical and numerical models of
such systems are now abundant, no real-life examples have been shown to date.
We present an experimental investigation of the collective motion of the
nematode Turbatrix aceti that self-propel by body undulation. We discover that
these nematodes can synchronize their body oscillations, forming striking
traveling metachronal waves, which produces strong fluid flows. We uncover that
the location and strength of this collective state can be controlled through
the shape of the confining structure; in our case the contact angle of a
droplet. This opens a way for producing controlled work such as on-demand flows
or displacement of objects. We illustrate this by showing that the force
generated by this state is sufficient to change the physics of evaporation of
fluid droplets, by counteracting the surface-tension force, which allow us to
estimate its strength. The relatively large size and ease of culture make
Turbatrix aceti a promising model organism for experimental investigation of
swarming and oscillating active matter capable of producing controllable work.


  Thermal noise arising from mechanical dissipation in oxide coatings is a
major limitation to many precision measurement systems, including optical
frequency standards, high resolution optical spectroscopy and interferometric
gravity wave detectors. Presented here are measurements of dissipation as a
function of temperature between 7 K and 290 K in ion-beam sputtered Ta2O5 doped
with TiO2, showing a loss peak at 20 K. Analysis of the peak provides the first
evidence of the source of dissipation in doped Ta2O5 coatings, leading to
possibilities for the reduction of thermal noise effects.


  We report a 3 dB increase in the nonlinear threshold of a 64*0.5Gbaud 16-QAM
continuous-nonlinear-spectrum modulated signal by nonlinear multiplexing with
QPSK modulated multi-solitons, showing the first ever fully nonlinear-spectrum
modulated system in the highly nonlinear regime.


  Despite the popularity of Shapley Values in explaining neural text
classification models, computing them is prohibitive for large pretrained
models due to a large number of model evaluations. In practice, Shapley Values
are often estimated with a small number of stochastic model evaluations.
However, we show that the estimated Shapley Values are sensitive to random seed
choices -- the top-ranked features often have little overlap across different
seeds, especially on examples with longer input texts. This can only be
mitigated by aggregating thousands of model evaluations, which on the other
hand, induces substantial computational overheads. To mitigate the trade-off
between stability and efficiency, we develop an amortized model that directly
predicts each input feature's Shapley Value without additional model
evaluations. It is trained on a set of examples whose Shapley Values are
estimated from a large number of model evaluations to ensure stability.
Experimental results on two text classification datasets demonstrate that our
amortized model estimates Shapley Values accurately with up to 60 times speedup
compared to traditional methods. Furthermore, the estimated values are stable
as the inference is deterministic. We release our code at
https://github.com/yangalan123/Amortized-Interpretability.


  We discuss both theoretically and experimentally elementary two-photon
polarization entanglement localization after break of entanglement caused by
linear coupling of environmental photon with one of the system photons. The
localization of entanglement is based on simple polarization measurement of the
surrounding photon after the coupling. We demonstrate that non-zero
entanglement can be localized back irrespectively to the distinguishability of
coupled photons. Further, it can be increased by local single-copy polarization
filters up to an amount violating Bell inequalities. The present technique
allows to restore entanglement in that cases, when the entanglement
distillation does not produce any entanglement out of the coupling.


  We propose a doubly subordinated Levy process, NDIG, to model the time series
properties of the cryptocurrency bitcoin. NDIG captures the skew and fat-tailed
properties of bitcoin prices and gives rise to an arbitrage free, option
pricing model. In this framework we derive two bitcoin volatility measures. The
first combines NDIG option pricing with the Cboe VIX model to compute an
implied volatility; the second uses the volatility of the unit time increment
of the NDIG model. Both are compared to a volatility based upon historical
standard deviation. With appropriate linear scaling, the NDIG process perfectly
captures observed, in-sample, volatility.


  Using the brick wall regularization of 't Hooft, the entropy of non-extreme
and extreme black holes is investigated in a general static, spherically
symmetric spacetime. We classify the singularity in the entropy by introducing
a {\it new} index $\delta $ with respect to the brick wall cut-off $\epsilon $.
The leading contribution to entropy for non-extreme case $(\delta \neq 0)$ is
shown to satisfy the area law with quadratic divergence with respect to the
invariant cut-off $\epsilon_{{\rm inv}}$ while the extreme case $(\delta =0)$
exhibits logarithmic divergence or constant value with respect to $\epsilon $.
The general formula is applied to Reissner-Nordstr\"{o}m, dilaton and
brane-world black holes and we obtain consistent results.


  We construct the thermodynamics of energy magnetization in the presence of
gravitomagnetic field. We show that the free energy must be modified to account
for the modification of the energy current operator in the presence of a
confining potential. The explicit expression of the energy magnetization is
derived for a periodic system, and the Streda formula for the thermal Hall
conductivity is rigorously established. We demonstrate our theory of the energy
magnetization and the Streda formula in a Chern insulator.


  Following the recent ideas of Dryzek, Kato, Mu\~noz and Singleton \cite{R1}
(henceforth we call this paper as R1), that the composite system consisting of
an electron along with its screened electric field and within the sphere of
influence, the trapped magnetic field of white dwarf can behave like a boson,
we have argued that such an exotic transition (bosonization) of electronic
component in strongly magnetized neutron star matter in $\beta$-equilibrium can
make the existence of magnetars physically viable.


  Americans are increasingly relying on crowdfunding to pay for the costs of
healthcare. In medical crowdfunding, online platforms allow individuals to
appeal to social networks to request donations for health and medical needs.
Users are often told that success depends on how they organize and share their
campaigns to increase social network engagement. However, experts have
cautioned that MCF could exacerbate health and social disparities by amplifying
the choices and biases of the crowd and leveraging these to determine who has
access to financial support for healthcare. To date, research on potential axes
of disparity in MCF, and their impacts on fundraising outcomes, has been
limited. This paper presents an exploratory cross-sectional study of a
randomized sample of 637 MCF campaigns on the popular platform Gofundme, for
which the race, gender, age, and relationships of campaigners and campaign
recipients were categorized alongside campaign characteristics and outcomes.
Our analyses examine race, gender, and age disparities in MCF use, and tests
how these are associated with differential campaign outcomes. The results show
systemic disparities in MCF use and outcomes: non-white users are
under-represented. There is significant evidence of an additional digital care
labor burden on women organizers of campaigns, and marginalized race and gender
groups are associated with poorer fundraising outcomes. Outcomes are only
minimally associated with campaign characteristics under users' control, such
as photos, videos, and updates. These results corroborate widespread concerns
how technology fuels health inequities, and about how crowdfunding may be
creating an unequal and biased marketplace for those seeking financial support
to access healthcare. Further research and better data access are needed to
explore these dynamics more deeply and inform policy for this largely
unregulated industry.


  Accurately simulating real world object dynamics is essential for various
applications such as robotics, engineering, graphics, and design. To better
capture complex real dynamics such as contact and friction, learned simulators
based on graph networks have recently shown great promise. However, applying
these learned simulators to real scenes comes with two major challenges: first,
scaling learned simulators to handle the complexity of real world scenes which
can involve hundreds of objects each with complicated 3D shapes, and second,
handling inputs from perception rather than 3D state information. Here we
introduce a method which substantially reduces the memory required to run
graph-based learned simulators. Based on this memory-efficient simulation
model, we then present a perceptual interface in the form of editable NeRFs
which can convert real-world scenes into a structured representation that can
be processed by graph network simulator. We show that our method uses
substantially less memory than previous graph-based simulators while retaining
their accuracy, and that the simulators learned in synthetic environments can
be applied to real world scenes captured from multiple camera angles. This
paves the way for expanding the application of learned simulators to settings
where only perceptual information is available at inference time.


  False vacuum decay, a quantum mechanical first-order phase transition in
scalar field theories, is an important phenomenon in early universe cosmology.
Recently, real-time semi-classical techniques based on ensembles of lattice
simulations were applied to the problem of false vacuum decay. In this context,
or any other lattice simulation, the effective potential experienced by
long-wavelength modes is not the same as the bare potential. To make
quantitative predictions using the real-time semi-classical techniques, it is
therefore necessary to understand the redefinition of model parameters and the
corresponding deformation of the vacuum state, as well as stochastic
contributions that require modeling of unresolved subgrid modes. In this work,
we focus on the former corrections and compute the expected modification of the
true and false vacuum effective mass, which manifests as a modified dispersion
relationship for linear fluctuations about the vacuum. We compare these
theoretical predictions to numerical simulations and find excellent agreement.
Motivated by this, we use the effective masses to fix the shape of a
parameterized effective potential, and explore the modeling uncertainty
associated with non-linear corrections. We compute the decay rates in both the
Euclidean and real-time formalisms, finding qualitative agreement in the
dependence on the UV cutoff. These calculations further demonstrate that a
quantitative understanding of the rates requires additional corrections.


  Let $G$ be a connected reductive group defined over a finite field
$\mathbb{F}_q$ of characteristic $p$, with Deligne--Lusztig dual $G^\ast$. We
show that, over $\overline{\mathbb{Z}}[1/pM]$ where $M$ is the product of all
bad primes for $G$, the endomorphism ring of a Gelfand--Graev representation of
$G(\mathbb{F}_q)$ is isomorphic to the Grothendieck ring of the category of
finite-dimensional $\overline{\mathbb{F}}_q$-representations of
$G^\ast(\mathbb{F}_q)$.


  This paper presents a novel approach to the digital signing of electronic
documents through the use of a camera-based interaction system, single-finger
tracking for sign recognition, and multi commands executing hand gestures. The
proposed solution, referred to as "Air Signature," involves writing the
signature in front of the camera, rather than relying on traditional methods
such as mouse drawing or physically signing on paper and showing it to a web
camera. The goal is to develop a state-of-the-art method for detecting and
tracking gestures and objects in real-time. The proposed methods include
applying existing gesture recognition and object tracking systems, improving
accuracy through smoothing and line drawing, and maintaining continuity during
fast finger movements. An evaluation of the fingertip detection, sketching, and
overall signing process is performed to assess the effectiveness of the
proposed solution. The secondary objective of this research is to develop a
model that can effectively recognize the unique signature of a user. This type
of signature can be verified by neural cores that analyze the movement, speed,
and stroke pixels of the signing in real time. The neural cores use machine
learning algorithms to match air signatures to the individual's stored
signatures, providing a secure and efficient method of verification. Our
proposed System does not require sensors or any hardware other than the camera.


  Anticipating future actions based on spatiotemporal observations is essential
in video understanding and predictive computer vision. Moreover, a model
capable of anticipating the future has important applications, it can benefit
precautionary systems to react before an event occurs. However, unlike in the
action recognition task, future information is inaccessible at observation time
-- a model cannot directly map the video frames to the target action to solve
the anticipation task. Instead, the temporal inference is required to associate
the relevant evidence with possible future actions. Consequently, existing
solutions based on the action recognition models are only suboptimal. Recently,
researchers proposed extending the observation window to capture longer
pre-action profiles from past moments and leveraging attention to retrieve the
subtle evidence to improve the anticipation predictions. However, existing
attention designs typically use frame inputs as the query which is suboptimal,
as a video frame only weakly connects to the future action. To this end, we
propose an inductive attention model, dubbed IAM, which leverages the current
prediction priors as the query to infer future action and can efficiently
process the long video content. Furthermore, our method considers the
uncertainty of the future via the many-to-many association in the attention
design. As a result, IAM consistently outperforms the state-of-the-art
anticipation models on multiple large-scale egocentric video datasets while
using significantly fewer model parameters.


  We demonstrate a spin-wave-based time-multiplexed Ising Machine (SWIM),
implemented using a 5 $\mu$m thick Yttrium Iron Garnet (YIG) film and
off-the-shelf microwave components. The artificial Ising spins consist of
34--68 ns long 3.125 GHz spinwave RF pulses with their phase binarized using a
phase-sensitive microwave amplifier. Thanks to the very low spinwave group
velocity, the 7 mm long YIG waveguide can host an 8-spin MAX-CUT problem and
solve it in less than 4 $\mu$s while consuming only 7 $\mu$J. Using a real-time
oscilloscope, we follow the temporal evolution of each spin as the SWIM
minimizes its energy and find both uniform and domain-propagation-like
switching of the spin state. The SWIM has the potential for substantial further
miniaturization, scalability, speed, and reduced power consumption, and may
become a versatile platform for commercially feasible optimization problem
solvers with high performance.


  Given access to a single long trajectory generated by an unknown irreducible
Markov chain $M$, we simulate an $\alpha$-lazy version of $M$ which is ergodic.
This enables us to generalize recent results on estimation and identity testing
that were stated for ergodic Markov chains in a way that allows fully empirical
inference. In particular, our approach shows that the pseudo spectral gap
introduced by Paulin [2015] and defined for ergodic Markov chains may be given
a meaning already in the case of irreducible but possibly periodic Markov
chains.


  Colloidal systems offer unique opportunities for the study of phase formation
and structure since their characteristic length scales are accessible to
visible light. As a model system the two dimensional assembly of colloidal
magnetic and non-magnetic particles dispersed in a ferrofluid (FF) matrix is
studied by transmission optical microscopy. We present a method to
statistically evaluate images with thousands of particles and map phases by
extraction of local variables. Different lattice structures and long-range
connected branching chains are observed, when tuning the effective magnetic
interaction and varying particle ratios.


  We present formulas for the (raw and central) moments and absolute moments of
the normal distribution. We note that these results are not new, yet many
textbooks miss out on at least some of them. Hence, we believe that it is
worthwhile to collect these formulas and their derivations in these notes.


  Despite the rapid rise in social engineering attacks, not all employees are
as compliant with information security policies (ISPs) to the extent that
organisations expect them to be. ISP non-compliance is caused by a variety of
psychological motivation. This study investigates the effect of psychological
contract breach (PCB) of employees on ISP compliance intention (ICI) by
dividing them into intrinsic and extrinsic motivation using the theory of
planned behaviour (TPB) and the general deterrence theory (GDT). Data analysis
from UK employees (\textit{n=206}) showed that the higher the PCB, the lower
the ICI. The study also found that PCBs significantly reduced intrinsic
motivation (attitude and perceived fairness) for ICI, whereas PCBs did not
moderate the relationship between extrinsic motivation (sanction severity and
sanctions certainty) and ICI. As a result, this study successfully addresses
the risks of PCBs in the field of IS security and proposes effective solutions
for employees with high PCBs.


  We present Monte Carlo and Langevin micromagnetic calculations to investigate
thermal switching of single-domain ferromagnetic particles. For the Monte Carlo
study we place particular emphasis on the probability that the magnetization
does not switch by time t. We find that this quantity has different behaviors
in different regimes of applied field, temperature, and system size, and we
explain this in terms of different reversal mechanisms that dominate in the
different regimes. In the micromagnetic study of an array of Ni pillars, we
show that the reversal mode is an outside-in mode starting at the perimeter of
the array of pillars.


  We study non-equilibrium dynamics of integrable and non-integrable closed
quantum systems whose unitary evolution is interrupted with stochastic resets,
characterized by a reset rate $r$, that project the system to its initial
state. We show that the steady state density matrix of a non-integrable system,
averaged over the reset distribution, retains its off-diagonal elements for any
finite $r$. Consequently a generic observable $\hat O$, whose expectation value
receives contribution from these off-diagonal elements, never thermalizes under
such dynamics for any finite $r$. We demonstrate this phenomenon by exact
numerical studies of experimentally realizable models of ultracold bosonic
atoms in a tilted optical lattice. For integrable Dirac-like fermionic models
driven periodically between such resets, the reset-averaged steady state is
found to be described by a family of generalized Gibbs ensembles (GGE s)
characterized by $r$. We also study the spread of particle density of a
non-interacting one-dimensional fermionic chain, starting from an initial state
where all fermions occupy the left half of the sample, while the right half is
empty. When driven by resetting dynamics, the density profile approaches at
long times to a nonequilibrium stationary profile that we compute exactly. We
suggest concrete experiments that can possibly test our theory.


  While the general principles of high-energy neutrino detection have been
understood for many years, the deep, remote geographical locations of suitable
detector sites have challenged the ingenuity of experimentalists, who have
confronted unusual deployment, calibration, and robustness issues. Two high
energy neutrino programs are now operating (Baikal and AMANDA), with the
expectation of ushering in an era of multi-messenger astronomy, and two
Mediterranean programs have made impressive progress. The detectors are
optimized to detect neutrinos with energies of the order of 1-10 TeV, although
they are capable of detecting neutrinos with energies of tens of MeV to greater
than PeV. This paper outlines the interdisciplinary scientific agenda, which
span the fields of astronomy, particle physics, and cosmic ray physics, and
describes ongoing worldwide experimental programs to realize these goals.


  We propose a fast and non-destructive spectroscopic method for single
molecular ions that implements quantum logic schemes between an atomic ion and
the molecular ion of interest. Our proposal relies on a hybrid coherent
manipulation of the two-ion system, using optical or magnetic forces depending
on the types of molecular levels to be addressed (Zeeman, rotational,
vibrational or electronic degrees of freedom). The method is especially suited
for the non-destructive precision spectroscopy of single molecular ions, and
sets a starting point for new hybrid quantum computation schemes that combine
molecular and atomic ions, covering the measurement and entangling steps.


  We verify the critical case $p=p_0(n)$ of Strauss' conjecture (1981)
concerning the blow-up of solutions to semilinear wave equations with variable
coefficients in $\mathbf{R}^n$, where $n\geq 2$. The perturbations of Laplace
operator are assumed to be smooth and decay exponentially fast at infinity. We
also obtain a sharp lifespan upper bound for solutions with compactly supported
data when $p=p_0(n)$. The unified approach to blow-up problems in all
dimensions combines several classical ideas in order to generalize and simplify
the method of Zhou(2007) and Zhou and Han (2014): exponential "eigenfunctions"
of the Laplacian are used to construct the test function $\phi_q$ for linear
wave equation with variable coefficients and John's method of iterations (1979)
is augmented with the "slicing method" of Agemi, Kurokawa and Takamura (2000)
for lower bounds in the critical case.


  Depth estimation from a single image represents a very exciting challenge in
computer vision. While other image-based depth sensing techniques leverage on
the geometry between different viewpoints (e.g., stereo or structure from
motion), the lack of these cues within a single image renders ill-posed the
monocular depth estimation task. For inference, state-of-the-art
encoder-decoder architectures for monocular depth estimation rely on effective
feature representations learned at training time. For unsupervised training of
these models, geometry has been effectively exploited by suitable images
warping losses computed from views acquired by a stereo rig or a moving camera.
In this paper, we make a further step forward showing that learning semantic
information from images enables to improve effectively monocular depth
estimation as well. In particular, by leveraging on semantically labeled images
together with unsupervised signals gained by geometry through an image warping
loss, we propose a deep learning approach aimed at joint semantic segmentation
and depth estimation. Our overall learning framework is semi-supervised, as we
deploy groundtruth data only in the semantic domain. At training time, our
network learns a common feature representation for both tasks and a novel
cross-task loss function is proposed. The experimental findings show how,
jointly tackling depth prediction and semantic segmentation, allows to improve
depth estimation accuracy. In particular, on the KITTI dataset our network
outperforms state-of-the-art methods for monocular depth estimation.


  The ratio of non-synonymous to synonymous substitutions
$\omega(=d_{N}/d_{S})$ has been widely used as a measure of adaptive evolution
in protein coding genes. Omega can be defined in terms of population genetics
parameters as the fixation ratio of selected vs. neutral mutants. Here it is
argued that approaches based on the infinite sites model are not appropriate to
define $\omega$ for single codon locations. Simple models of amino acid
substitution with reversible mutation and selection are analysed, and used to
define $\omega$ under several evolutionary scenarios. In most practical cases
$\omega<1$ when selection is constant throughout time. However, it is shown
that when the pattern of selection on amino acids changes, for example after an
environment shift, a temporary burst of adaptive evolution ($\omega\gg1$) can
be observed. The fixation probability of a novel mutant under frequency
dependent selection is calculated, and it is used to show why $\omega>1$ can be
sometimes expected for single locations at equilibrium. An example with
influenza data is discussed.


  We report on calculations of the formation energies of several [100] and
[110] oriented step structures on biaxially stressed Si and Ge (001) surfaces.
It is shown that a novel rebonded [100] oriented single-height step is strongly
stabilized by compressive strain compared to most well-known step structures.
We propose that the side walls of ``hut''-shaped quantum dots observed in
recent experiments on SiGe/Si films are made up of these steps. Our
calculations provide an explanation for the nucleationless growth of shallow
mounds, with steps along the [100] and [110] directions in low- and high-misfit
films, respectively, and for the stability of the (105) facets under
compressive strain.


  The relationships between reversible Carnot cycles, the absence of perpetual
motion machines and the existence of a non-decreasing, globally unique entropy
function forms the starting point of many textbook presentations of the
foundations of thermodynamics. However, the thermal fluctuation phenomena
associated with statistical mechanics has been argued to restrict the domain of
validity of this basis of the second law of thermodynamics. Here we demonstrate
that fluctuation phenomena can be incorporated into the traditional
presentation, extending, rather than restricting, the domain of validity of the
phenomenologically motivated second law. Consistency conditions lead to
constraints upon the possible spectrum of thermal fluctuations. In a special
case this uniquely selects the Gibbs canonical distribution and more generally
incorporates the Tsallis distributions. No particular model of microscopic
dynamics need be assumed.


  Transport properties of the complex oxide LaAlO3/SrTiO3 interface are
investigated under high magnetic field (55T). By rotating the sample with
respect to the magnetic field, the two-dimensional nature of charge transport
is clearly established. Small oscillations of the agnetoresistance with altered
periodicity are observed when plotted versus inverse magnetic field. We
attribute this effect to Rashba spin-orbit coupling which remains consistent
with large negative magnetoresistance when the field is parallel to the sample
plane. A large inconsistency between the carrier density extracted from
Shubnikov-de Haas analysis and from the Hall effect is explained by the
contribution to transport of at least two bands with different mobility.