  Multiplex networks are a representation of real-world complex systems as a
set of entities (i.e. nodes) connected via different types of connections (i.e.
layers). The observed connections in these networks may not be complete and the
link prediction task is about locating the missing links across layers. Here,
the main challenge is about collecting relevant evidence from different layers
to assist the link prediction task. It is known that co-membership in
communities increases the likelihood of connectivity between nodes. We discuss
that co-membership in the communities of the similar layers augments the chance
of connectivity. The layers are considered similar if they show significant
inter-layer community overlap. Moreover, we found that although the presence of
link is correlated in layers but the extent of this correlation is not the same
across different communities. Our proposed, ML-BNMTF, as a link prediction
method in multiplex networks, is devised based on these findings. ML-BNMTF
outperforms baseline methods specifically when the global link overlap is low.


  We study run and tumble particles on the one-dimensional lattice
$\mathbb{Z}$. We explicitly compute the Fourier-Laplace transform of the
position of the particle and as a consequence obtain explicit expressions for
the diffusion constant and the large deviation free energy function. We also do
the same computations in a corresponding continuum model. In the latter, when
adding an external field, we can explicitly compute the large deviation free
energy, and the deviation from the Einstein relation due to activity. Finally,
we generalize the model to the $d$-dimensional lattice $\mathbb{Z}^d$, with an
arbitrary finite set of velocities, and show that the large deviation free
energy for the position of the particle can be computed via the largest
eigenvalue of a matrix of Schr\"{o}dinger operator form, for which we can
derive an explicit variational formula via occupation time large deviations of
the velocity flip process.


  We present a detailed study on the magnetic order in the undoped mother
compound LaOFeAs of the recently discovered Fe-based superconductor
LaO$_{1-x}$F$_x$FeAs. In particular, we present local probe measurements of the
magnetic properties of LaOFeAs by means of $^{57}$Fe M\"ossbauer spectroscopy
and muon spin relaxation in zero external field along with magnetization and
resistivity studies. These experiments prove a commensurate static magnetic
order with a strongly reduced ordered moment of 0.25(5) $\mu_B$ at the iron
site below T_N = 138 K, well separated from a structural phase transition at
T_N = 156 K. The temperature dependence of the sublattice magnetization is
determined and compared to theory. Using a four-band spin density wave model
both, the size of the order parameter and the quick saturation below T_N are
reproduced.


  We consider the problem of clustering graph nodes over large-scale dynamic
graphs, such as citation networks, images and web networks, when graph updates
such as node/edge insertions/deletions are observed distributively. We propose
communication-efficient algorithms for two well-established communication
models namely the message passing and the blackboard models. Given a graph with
$n$ nodes that is observed at $s$ remote sites over time $[1,t]$, the two
proposed algorithms have communication costs $\tilde{O}(ns)$ and
$\tilde{O}(n+s)$ ($\tilde{O}$ hides a polylogarithmic factor), almost matching
their lower bounds, $\Omega(ns)$ and $\Omega(n+s)$, respectively, in the
message passing and the blackboard models. More importantly, we prove that at
each time point in $[1,t]$ our algorithms generate clustering quality nearly as
good as that of centralizing all updates up to that time and then applying a
standard centralized clustering algorithm. We conducted extensive experiments
on both synthetic and real-life datasets which confirmed the communication
efficiency of our approach over baseline algorithms while achieving comparable
clustering results.


  Recent developments of microscopic mechanical experiments allow the
manipulation of individual polymer molecules in two main ways: \textit{uniform}
stretching by external forces and \textit{non-uniform} stretching by external
fields. Many results can be thereby obtained for specific kinds of polymers and
specific geometries. In this work we describe the non-uniform stretching of a
single, non-branched polymer molecule by an external field (e.g. fluid in
uniform motion, or uniform electric field) by a universal physical framework
which leads to general conclusions on different types of polymers. We derive
analytical results both for the freely-jointed chain and the worm-like chain
models based on classical statistical mechanics. Moreover, we provide a Monte
Carlo numerical analysis of the mechanical properties of flexible and
semi-flexible polymers anchored at one end. The simulations confirm the
analytical achievements, and moreover allow to study the situations where the
theory can not provide explicit and useful results. In all cases we evaluate
the average conformation of the polymer and its fluctuation statistics as a
function of the chain length, bending rigidity and field strength.


  The promise of tabular generative models is to produce realistic synthetic
data that can be shared and safely used without dangerous leakage of
information from the training set. In evaluating these models, a variety of
methods have been proposed to measure the tendency to copy data from the
training dataset when generating a sample. However, these methods suffer from
either not considering data-copying from a privacy threat perspective, not
being motivated by recent results in the data-copying literature or being
difficult to make compatible with the high dimensional, mixed type nature of
tabular data. This paper proposes a new similarity metric and Membership
Inference Attack called Data Plagiarism Index (DPI) for tabular data. We show
that DPI evaluates a new intuitive definition of data-copying and characterizes
the corresponding privacy risk. We show that the data-copying identified by DPI
poses both privacy and fairness threats to common, high performing
architectures; underscoring the necessity for more sophisticated generative
modeling techniques to mitigate this issue.


  Annotations play a vital role in highlighting critical aspects of
visualizations, aiding in data externalization and exploration, collaborative
sensemaking, and visual storytelling. However, despite their widespread use, we
identified a lack of a design space for common practices for annotations. In
this paper, we evaluated over 1,800 static annotated charts to understand how
people annotate visualizations in practice. Through qualitative coding of these
diverse real-world annotated charts, we explored three primary aspects of
annotation usage patterns: analytic purposes for chart annotations (e.g.,
present, identify, summarize, or compare data features), mechanisms for chart
annotations (e.g., types and combinations of annotations used, frequency of
different annotation types across chart types, etc.), and the data source used
to generate the annotations. We then synthesized our findings into a design
space of annotations, highlighting key design choices for chart annotations. We
presented three case studies illustrating our design space as a practical
framework for chart annotations to enhance the communication of visualization
insights. All supplemental materials are available at
{https://shorturl.at/bAGM1}.


  The current fuel moisture content (FMC) subsystems in WRF-SFIRE and its
workflow system WRFx use a time-lag differential equation model with
assimilation of data from FMC sensors on Remote Automated Weather Stations
(RAWS) by the extended augmented Kalman filter. But the quality of the result
is constrained by the limitations of the model and of the Kalman filter. We
observe that the data flow in a system consisting of a model and the Kalman
filter can be interpreted to be the same as the data flow in a recurrent neural
network (RNN). Thus, instead of building more sophisticated models and data
assimilation methods, we want to train a RNN to approximate the dynamics of the
response of the FMC sensor to a time series of environmental data. Because
standard AI approaches did not converge to reasonable solutions, we pre-train
the RNN with special initial weights devised to turn it into a numerical solver
of the differential equation. We then allow the AI training machinery to
optimize the RNN weights to fit the data better. We illustrate the method on an
example of a time series of 10h-FMC from RAWS and weather data from the
Real-Time Mesoscale Analysis (RTMA).


  A seagull ({\it Larus crassirostris}) has a high ability to realize its safe,
accurate and smooth landing. We examined how a seagull controls its angle of
attack when landing on a specific target. First, we recorded the landing
behavior of an actual seagull by multiple video cameras and quantified the
flight trajectory and the angle of attack as time series data. Second, we
introduced a mathematical model that describes how a seagull controls its speed
by changing its angle of attack. Based on the numerical simulation combining
the mathematical model and empirical data, we succeeded in qualitatively
explaining the landing behavior of an actual seagull, which demonstrates that
the control the angle of attack is important for landing behavior.


  In recent years there has been a collective research effort to find new
formulations of reinforcement learning that are simultaneously more efficient
and more amenable to analysis. This paper concerns one approach that builds on
the linear programming (LP) formulation of optimal control of Manne. A primal
version is called logistic Q-learning, and a dual variant is convex Q-learning.
This paper focuses on the latter, while building bridges with the former. The
main contributions follow: (i) The dual of convex Q-learning is not precisely
Manne's LP or a version of logistic Q-learning, but has similar structure that
reveals the need for regularization to avoid over-fitting. (ii) A sufficient
condition is obtained for a bounded solution to the Q-learning LP. (iii)
Simulation studies reveal numerical challenges when addressing sampled-data
systems based on a continuous time model. The challenge is addressed using
state-dependent sampling. The theory is illustrated with applications to
examples from OpenAI gym. It is shown that convex Q-learning is successful in
cases where standard Q-learning diverges, such as the LQR problem.


  We are interested in geometric approximation by parameterization of
two-dimensional multiple-component shapes, in particular when the number of
components is a priori unknown. Starting a standard method based on successive
shape deformations with a one-component initial shape in order to approximate a
multiple-component target shape usually leads the deformation flow to make the
boundary evolve until it surrounds all the components of the target shape. This
classical phenomenon tends to create double points on the boundary of the
approximated shape. In order to improve the approximation of multiple-component
shapes (without any knowledge on the number of components in advance), we use
in this paper a piecewise B\'ezier parameterization and we consider two
procedures called intersecting control polygons detection and flip procedure.
The first one allows to prevent potential collisions between two parts of the
boundary of the approximated shape, and the second one permits to change its
topology by dividing a one-component shape into a two-component shape. For an
experimental purpose, we include these two processes in a basic geometrical
shape optimization algorithm and test it on the classical inverse obstacle
problem. This new approach allows to obtain a numerical approximation of the
unknown inclusion, detecting both the topology (i.e. the number of connected
components) and the shape of the obstacle. Several numerical simulations are
performed.


  We show theoretically that strong electron coupling to circularly polarized
photons in non-singly-connected nanostructures results in the appearance of an
artificial gauge field that changes the electron phase. The effect arises from
the breaking of time-reversal symmetry and is analogous to the well-known
Aharonov-Bohm phase effect. It can manifest itself in the oscillations of
conductance as a function of the intensity and frequency of the illumination.
The theory of the effect is elaborated for mesoscopic rings in both ballistic
and diffusive regimes.


  Communal violence in online forums has become extremely prevalent in South
Asia, where many communities of different cultures coexist and share resources.
These societies exhibit a phenomenon characterized by strong bonds within their
own groups and animosity towards others, leading to conflicts that frequently
escalate into violent confrontations. To address this issue, we have developed
the first comprehensive framework for the automatic detection of communal
violence markers in online Bangla content accompanying the largest collection
(13K raw sentences) of social media interactions that fall under the definition
of four major violence class and their 16 coarse expressions. Our workflow
introduces a 7-step expert annotation process incorporating insights from
social scientists, linguists, and psychologists. By presenting data statistics
and benchmarking performance using this dataset, we have determined that, aside
from the category of Non-communal violence, Religio-communal violence is
particularly pervasive in Bangla text. Moreover, we have substantiated the
effectiveness of fine-tuning language models in identifying violent comments by
conducting preliminary benchmarking on the state-of-the-art Bangla deep
learning model.


  It is a well-known fact that an exchangeable sequence has empirical
distributions that form a reverse-martingale. This paper is devoted to proof of
the converse statement. As a byproduct of the proof for the binary case, we
introduce and discuss the notion of two-coloring exchangeability.


  A recent paper by Harmut Traunm\"uller shows that the most adequate equation
to interpret the observations on magnitude and redshift from 892 type 1a
supernovae would be mu = 5 log[(1+z) ln(1+z)] + const. We discuss this result
which is exacly the one we have obtained few years ago when postulating a
relation between the speed of light and the expansion of the universe. We also
compare our analytical result to the conclusion of Marosi who studied 280
supernovae and gamma-ray bursts in the range 0.1014 < z < 8.1. The difference
between his results and ours is at worst of 0.3 %.


  Complex systems are characterized by multiple spatial and temporal scales. A
natural framework to capture their multiscale nature is that of multilayer
networks, where different layers represent distinct physical processes that
often regulate each other indirectly. We model these regulatory mechanisms
through triadic higher-order interactions between nodes and edges. In this
work, we focus on how the different timescales associated with each layer
impact their effective couplings in terms of their mutual information. We
unravel the general principles governing how such information propagates across
the multiscale structure, and apply them to study archetypal examples of
biological signaling networks and effective environmental dependencies in
stochastic processes. Our framework generalizes to any dynamics on multilayer
networks, paving the way for a deeper understanding of how the multiscale
nature of real-world systems shapes their information content and complexity.


  The paper provides a agent-based model, which describes distribution of
informative messages, containing links to informational resources in the
Internet. The results of modeling have been confirmed by studying a real
network of Twitter microblogs. The paper describes stages of building a
corporate system of monitoring network informational resources, the content of
which is determined by links in microblogs. The advantages of such approach are
set forth.


  Rashba nanowires in a magnetic field exhibit a helical regime when the
spin-orbit momentum is close to the Fermi momentum, k_F \approx k_{SO}. We show
that this regime is characterized by a strongly anisotropic electron spin
susceptibility, with an exponentially suppressed signal along one direction in
spin space, and that there are no low frequency spin fluctuations along this
direction. Since the spin response in the gapless regime k_F \not \approx
k_{SO} has a power law behavior in all three directions, spin measurements
provide a signature of the helical regime that complements spin-insensitive
conductance measurements.


  We develop a toy-model for the chemical evolution of the intracluster medium,
polluted by the galactic winds from elliptical galaxies. The model follows the
"galaxy formation history" of cluster galaxies, constrained by the observed
luminosity function.


  We show that a useful connection exists between spontaneous parametric
downconversion (SPDC) and sum frequency generation in nonlinear optical
waveguides with arbitrary scattering loss, while the same does not hold true
for SPDC and difference frequency generation. This result deepens the
relationship between quantum and classical second-order nonlinear optical
processes in waveguides, and identifies the most accurate characterization of
their quantum performance in the presence of loss based solely on classical
measurements.


  Strong changes in bulk properties, such as modulus and viscosity, are
observed near the glass transition temperature, T_{g}, of amorphous materials.
For more than a century, intense efforts have been made to define a microscopic
origin for these macroscopic changes in properties. Using transition state
theory, we delve into the atomic/molecular level picture of how microscopic
localized relaxations, or "cage rattles," translate to macroscopic structural
relaxations above T_{g}. Unit motion is broken down into two populations: (1)
simultaneous rearrangement occurs among a critical number of units, n_{\alpha},
which ranges from 1 to 4, allowing a systematic classification of glasses that
is compared to fragility; (2) near T_{g}, adjacent units provide additional
free volume for rearrangement, not simultaneously, but within the "primitive"
lifetime, {\tau}_{1}, of one unit rattling in its cage. Relaxation maps
illustrate how Johari-Goldstein \{beta} relaxations stem from the rattle of
n_{\alpha} units. We analyzed a wide variety of glassy materials, and materials
with glassy response, using literature data. Our four-parameter equation fits
"strong" and "weak" glasses over the entire range of temperatures and also
extends to other glassy systems, such as ion-transporting polymers and
ferroelectric relaxors. The role of activation entropy in boosting
preexponential factors to high "unphysical" apparent frequencies is discussed.


  Mobile manipulator platforms, like the Stretch RE1 robot, make the promise of
in-home robotic assistance feasible. For people with severe physical
limitations, like those with quadriplegia, the ability to tele-operate these
robots themselves means that they can perform physical tasks they cannot
otherwise do themselves, thereby increasing their level of independence. In
order for users with physical limitations to operate these robots, their
interfaces must be accessible and cater to the specific needs of all users. As
physical limitations vary amongst users, it is difficult to make a single
interface that will accommodate all users. Instead, such interfaces should be
customizable to each individual user. In this paper we explore the value of
customization of a browser-based interface for tele-operating the Stretch RE1
robot. More specifically, we evaluate the usability and effectiveness of a
customized interface in comparison to the default interface configurations from
prior work. We present a user study involving participants with motor
impairments (N=10) and without motor impairments, who could serve as a
caregiver, (N=13) that use the robot to perform mobile manipulation tasks in a
real kitchen environment. Our study demonstrates that no single interface
configuration satisfies all users' needs and preferences. Users perform better
when using the customized interface for navigation, but not for manipulation
due to higher complexity of learning to manipulate through the robot. All
participants are able to use the robot to complete all tasks and participants
with motor impairments believe that having the robot in their home would make
them more independent.


  Code completion is one of the killer features of Integrated Development
Environments (IDEs), and researchers have proposed different methods to improve
its accuracy. While these techniques are valuable to speed up code writing,
they are limited to recommendations related to the next few tokens a developer
is likely to type given the current context. In the best case, they can
recommend a few APIs that a developer is likely to use next. We present FeaRS,
a novel retrieval-based approach that, given the current code a developer is
writing in the IDE, can recommend the next complete method (i.e., signature and
method body) that the developer is likely to implement. To do this, FeaRS
exploits "implementation patterns" (i.e., groups of methods usually implemented
within the same task) learned by mining thousands of open source projects. We
instantiated our approach to the specific context of Android apps. A
large-scale empirical evaluation we performed across more than 20k apps shows
encouraging preliminary results, but also highlights future challenges to
overcome.


  We interpret the di-photon excess recently reported by the ATLAS and CMS
collaborations as a new resonance arising from the sgoldstino scalar, which is
the superpartner of the Goldstone mode of spontaneous supersymmetry breaking,
the goldstino. The sgoldstino is produced at the LHC via gluon fusion and
decays to photons, with interaction strengths proportional to the corresponding
gaugino masses over the supersymmetry breaking scale. Fitting the excess, while
evading bounds from searches in the di-jet, $Z\gamma$, $ZZ$ and $WW$ final
states, selects the supersymmetry breaking scale to be a few TeV, and
particular ranges for the gaugino masses. The two real scalars, corresponding
to the CP-even and CP-odd parts of the complex sgoldstino, both have narrow
widths, but their masses can be split of the order 10-30 GeV by electroweak
mixing corrections, which could account for the preference of a wider resonance
width in the current low-statistics data. In the parameter space under
consideration, tree-level $F$-term contributions to the Higgs mass arise, in
addition to the standard $D$-term contribution proportional to the $Z$-boson
mass, which can significantly enhance the tree level Higgs mass.


  Despite the large number of discoveries made recently by Fermi, the origins
of the so called unidentified gamma-ray sources remain unknown. The large
number of these sources suggests that among them there could be a population
that significantly contributes to the isotropic gamma-ray background and is
therefore crucial to understand their nature. The first step toward a complete
comprehension of the unidentified gamma-ray source population is to identify
those that can be associated with blazars, the most numerous class of
extragalactic sources in the gamma-ray sky. Recently, we discovered that
blazars can be recognized and separated from other extragalactic sources using
the infrared (IR) WISE satellite colors. The blazar population delineates a
remarkable and distinctive region of the IR color-color space, the WISE blazar
strip. In particular, the subregion delineated by the gamma-ray emitting
blazars is even narrower and we named it as the WISE Gamma-ray Strip (WGS). In
this paper we parametrize the WGS on the basis of a single parameter s that we
then use to determine if gamma-ray Active Galactic Nuclei of the uncertain type
(AGUs) detected by Fermi are consistent with the WGS and so can be considered
blazar candidates. We find that 54 AGUs out of a set 60 analyzed have IR colors
consistent with the WGS; only 6 AGUs are outliers. This result implies that a
very high percentage (i.e., in this sample about 90%) of the AGUs detected by
Fermi are indeed blazar candidates.


  Protein inference plays a vital role in the proteomics study. Two major
approaches could be used to handle the problem of protein inference; top-down
and bottom-up. This paper presents a framework for protein inference, which
uses hardware accelerated protein inference framework for handling the most
important step in a bottom-up approach, viz. peptide identification during the
assembling process. In our framework, identified peptides and their
probabilities are used to predict the most suitable reference protein cluster
for a given input amino acid sequence with the probability of identified
peptides. The framework is developed on an FPGA where hardware software
co-design techniques are used to accelerate the computationally intensive parts
of the protein inference process. In the paper we have measured, compared and
reported the time taken for the protein inference process in our framework
against a pure software implementation.


  Quantum cosmology is investigated in a de Sitter minisuperspace model with a
quantized scalar field non-minimally coupled to curvature. Quantum states of
the scalar field must satisfy the regularity condition, which requires that the
probability of field fluctuations should not increase with their amplitude. We
show that this condition imposes constraints on the allowed values of the
curvature coupling parameter $\xi$. This is a surprising result, since the
field dynamics depends only on the combination $m^2+\xi R$, where $m$ is the
field mass and $R = \mathrm{const}$ is the curvature, and does not depend on
$\xi$ separately.


  We calculate the combined angular distribution functions of the polarized
photons ($\gamma_1$ and $\gamma_2$) and electron ($e^-$) produced in the
cascade process $\bar{p}p\rightarrow$ $^3D_3\rightarrow$
$^3P_2+\gamma_1\rightarrow$
$(\psi+\gamma_2)+\gamma_1\rightarrow(e^++e^-)+\gamma_1+\gamma_2$, when the
colliding $\bar{p}$ and $p$ are unpolarized. Our results are independent of any
dynamical models and are expressed in terms of the spherical harmonics whose
coefficients are functions of the angular-momentum helicity amplitudes of the
individual processes. Once the joint angular distribution of ($\gamma_1$,
$\gamma_2$) and that of ($\gamma_2$, $e^-$) with the polarization of either one
of the two particles are measured, our results will enable one to determine the
relative magnitudes as well as the relative phases of all the angular-momentum
helicity amplitudes in the radiative decay processes $^3D_3\rightarrow$
$^3P_2+\gamma_1$ and $^3P_2\rightarrow\psi+\gamma_2$.


  Distributed Denial of Service flooding attacks are one of the biggest
challenges to the availability of online services today. These DDoS attacks
overwhelm the victim with huge volume of traffic and render it incapable of
performing normal communication or crashes it completely. If there are delays
in detecting the flooding attacks, nothing much can be done except to manually
disconnect the victim and fix the problem. With the rapid increase of DDoS
volume and frequency, the current DDoS detection technologies are challenged to
deal with huge attack volume in reasonable and affordable response time.
  In this paper, we propose HADEC, a Hadoop based Live DDoS Detection framework
to tackle efficient analysis of flooding attacks by harnessing MapReduce and
HDFS. We implemented a counter-based DDoS detection algorithm for four major
flooding attacks (TCP-SYN, HTTP GET, UDP and ICMP) in MapReduce, consisting of
map and reduce functions. We deployed a testbed to evaluate the performance of
HADEC framework for live DDoS detection. Based on the experiments we showed
that HADEC is capable of processing and detecting DDoS attacks in affordable
time.


  We provide a simple and natural solution to the problem of generating all
$2^n \cdot n!$ signed permutations of $[n] = \{1,2,\ldots,n\}$. Our solution
provides a pleasing generalization of the most famous ordering of permutations:
plain changes (Steinhaus-Johnson-Trotter algorithm). In plain changes, the $n!$
permutations of $[n]$ are ordered so that successive permutations differ by
swapping a pair of adjacent symbols, and the order is often visualized as a
weaving pattern involving $n$ ropes. Here we model a signed permutation using
$n$ ribbons with two distinct sides, and each successive configuration is
created by twisting (i.e., swapping and turning over) two neighboring ribbons
or a single ribbon. By greedily prioritizing $2$-twists of the largest symbol
before $1$-twists of the largest symbol, we create a signed version of plain
change's memorable zig-zag pattern. We provide a loopless algorithm (i.e.,
worst-case $\mathcal{O}(1)$-time per object) by extending the well-known
mixed-radix Gray code algorithm.


  Existing methods for dealing with knowledge updates differ greatly depending
on the underlying knowledge representation formalism. When Classical Logic is
used, updates are typically performed by manipulating the knowledge base on the
model-theoretic level. On the opposite side of the spectrum stand the semantics
for updating Answer-Set Programs that need to rely on rule syntax. Yet, a
unifying perspective that could embrace both these branches of research is of
great importance as it enables a deeper understanding of all involved methods
and principles and creates room for their cross-fertilisation, ripening and
further development.
  This paper bridges the seemingly irreconcilable approaches to updates. It
introduces a novel monotonic characterisation of rules, dubbed RE-models, and
shows it to be a more suitable semantic foundation for rule updates than
SE-models. Then it proposes a generic scheme for specifying semantic rule
update operators, based on the idea of viewing a program as the set of sets of
RE-models of its rules; updates are performed by introducing additional
interpretations - exceptions - to the sets of RE-models of rules in the
original program. The introduced scheme is used to define rule update operators
that are closely related to both classical update principles and traditional
approaches to rules updates, and serve as a basis for a solution to the
long-standing problem of state condensing, showing how they can be equivalently
defined as binary operators on some class of logic programs.
  Finally, the essence of these ideas is extracted to define an abstract
framework for exception-based update operators, viewing a knowledge base as the
set of sets of models of its elements, which can capture a wide range of both
model- and formula-based classical update operators, and thus serves as the
first firm formal ground connecting classical and rule updates.


  The spin Hall magnetoresistance (SMR) phenomenon includes the fundamental
physics of spin current, and originates from spin accumulation at an interface
owing to the spin Hall effect. Although bilayers are the simplest structure
exhibiting SMR, these exploit spin accumulation at only one side of a layer.
Herein, trilayers of CoFe2O4/Pt/CoFe2O4 were fabricated and their spin Hall
magnetoresistance was investigated. The trilayer structure featuring a thin Pt
layer exhibited an SMR ratio four times that of a CoFe2O4/Pt bilayer. Further,
the SMR ratio exhibited a dependence on Pt layer thickness that can be
attributed to interference of the spin accumulations at both sides. Herein,
several parameters such as spin diffusion length and mixing conductance were
derived using the theory of Chen et al.


  The virtual element method (VEM) allows discretization of the problem domain
with polygons in 2D. The polygons can have an arbitrary number of sides and can
be concave or convex. These features, among others, are attractive for meshing
complex geometries. VEM applied to linear elasticity problems is now well
established. Nonlinear problems involving plasticity and hyperelasticity have
also been explored by researchers using VEM. Clearly, techniques for extending
the method to nonlinear problems are attractive. In this work a novel first
order consistent virtual element method is applied within a static
co-rotational framework. To the author's knowledge this has not appeared before
in the literature with virtual elements. The formulation allows for large
displacements and large rotations in a small strain setting. For some problems
avoiding the complexity of finite strains, and alternative stress measures, is
warranted. Furthermore, small strain plasticity is easily incorporated. The
basic method, VEM specific implementation details for co-rotation, and
representative benchmark problems are illustrated. Consequently, this research
demonstrates that the co-rotational VEM formulation successfully solves certain
classes of nonlinear solid mechanics problems. The work concludes with a
discussion of results for the current formulation and future research
directions.


  Guarded Kleene Algebra with Tests (GKAT) is a fragment of Kleene Algebra with
Tests (KAT) that was recently introduced to reason efficiently about imperative
programs. In contrast to KAT, GKAT does not have an algebraic axiomatization,
but relies on an analogue of Salomaa's axiomatization of Kleene Algebra. In
this paper, we present an algebraic axiomatization and prove two completeness
results for a large fragment of GKAT consisting of skip-free programs.


  The recent WMAP data provide a rather restricted range of the Cold Dark
Matter (CDM) density $ \Omega_{CDM} h^2 $ of unprecedented accuracy. We combine
these new data along with data from BNL E821 experiment measuring $
{(g_{\mu}-2)}$, $ $the {$b\goes s \gamma$} branching ratio and the light Higgs
boson mass bound from LEP, to update our analysis of the allowed boundaries in
the parameter space of the Constrained Minimal Supersymmetric Standard Model
(CMSSM). The prospects of measuring Supersymmetry at LHC look like a very safe
bet, and the potential of discovering SUSY particles at a $ \sqrt{s} = 1.1
\mathrm{TeV} $ linear collider is enhanced considerably. The implications for
Dark Matter direct searches are also discussed.


  We define an $n$-gon to be any convex polygon with $n$ vertices. Let $V$
represent the set of vertices of the polygon. A proper $k$-coloring refers to a
function, $f$ : $V$ $\rightarrow$ $\{1, 2, 3, ... k\}$, such that for any two
vertices $u$ and $v$, if $f(u) = f(v)$, $u$ is not adjacent to $v$. The purpose
of this paper is to develop a recursive algorithm to compute the number of
proper $k$-colorings in an $n$-gon. The proposed algorithm can easily be solved
to obtain the explicit expression. This matches the explicit expression
obtained from the popular conventional solutions, which confirms the
correctness of the proposed algorithm. Often, for huge values of $n$ and $k$,
it becomes impractical to display the output numbers, which would consist of
thousands of digits. We report the answer modulo a certain number. In such
situations, the proposed algorithm is observed to run slightly faster than the
conventional recursive algorithm.


  In this paper we, first, present a class of charged rotating solutions in
four-dimensional Einstein-Maxwell-dilaton gravity with zero and Liouville-type
potentials. We find that these solutions can present a black hole/string with
two regular horizons, an extreme black hole or a naked singularity provided the
parameters of the solutions are chosen suitable. We also compute the conserved
and thermodynamic quantities, and show that they satisfy the first law of
thermodynamics. Second, we obtain the ($n+1$%)-dimensional rotating solutions
in Einstein-dilaton gravity with Liouville-type potential. We find that these
solutions can present black branes, naked singularities or spacetimes with
cosmological horizon if one chooses the parameters of the solutions correctly.
Again, we find that the thermodynamic quantities of these solutions satisfy the
first law of thermodynamics.


  Black phosphorus (BP) has recently emerged as a promising narrow band gap
layered semiconductor with optoelectronic properties that bridge the gap
between semi-metallic graphene and wide band gap transition metal
dichalcogenides such as MoS2. To date, BP field-effect transistors have
utilized a lateral geometry with in-plane transport dominating device
characteristics. In contrast, we present here a vertical field-effect
transistor geometry based on a graphene/BP van der Waals heterostructure. The
resulting device characteristics include high on-state current densities (>
1600 A/cm2) and current on/off ratios exceeding 800 at low temperature. Two
distinct charge transport mechanisms are identified, which are dominant for
different regimes of temperature and gate voltage. In particular, the Schottky
barrier between graphene and BP determines charge transport at high
temperatures and positive gate voltages, whereas tunneling dominates at low
temperatures and negative gate voltages. These results elucidate out-of-plane
electronic transport in BP, and thus have implications for the design and
operation of BP-based van der Waals heterostructures.


  We discuss the validity of replacing the complicated three-body confinement
operator of the Y string junction type by three kinds of approximation which
are numerically much simpler to handle: a one-body operator with the junction
point at the centre of mass, a two-body operator corresponding to half the
perimeter of the triangle formed by the three particles, and the average of
both. Two different approaches for testing the quality of the approximations
are proposed: a geometrical treatment based on the comparison of the potential
energy strengths for the various inter quark distances, and a dynamical
treatment based on the comparison of the corresponding effective string
tensions using a hyperspherical approach. Both procedures give very similar
results. It is shown how to simulate the genuine string junction operator by
the approximations proposed above. Exact three-body calculations are presented
in order to compare quantitatively the various approximations and to confirm
our analysis.


  In the $2$-reachability problem we are given a directed graph $G$ and we wish
to determine if there are two (edge or vertex) disjoint paths from $u$ to $v$,
for a given pair of vertices $u$ and $v$. In this paper, we present an
algorithm that computes $2$-reachability information for all pairs of vertices
in $\mathcal{O}(n^{\omega}\log n)$ time, where $n$ is the number of vertices
and $\omega$ is the matrix multiplication exponent. Hence, we show that the
running time of all-pairs $2$-reachability is only within a $\log$ factor of
transitive closure.
  Moreover, our algorithm produces a witness (i.e., a separating edge or a
separating vertex) for all pair of vertices where $2$-reachability does not
hold. By processing these witnesses, we can compute all the edge- and
vertex-dominator trees of $G$ in $\mathcal{O}(n^2)$ additional time, which in
turn enables us to answer various connectivity queries in $\mathcal{O}(1)$
time. For instance, we can test in constant time if there is a path from $u$ to
$v$ avoiding an edge $e$, for any pair of query vertices $u$ and $v$, and any
query edge $e$, or if there is a path from $u$ to $v$ avoiding a vertex $w$,
for any query vertices $u$, $v$, and $w$.


  We give a new proof for the existence of rotationally symmetric steady and
expanding gradient Ricci solitons in dimension $n+1$, $2\le n\le 4$, with
metric $g=\frac{da^2}{h(a^2)}+a^2d\,\sigma$ for some function $h$ where
$d\sigma$ is the standard metric on the unit sphere $S^n$ in $\mathbb{R}^n$.
More precisely for any $\lambda\ge 0$, $2\le n\le 4$ and $\mu_1\in\mathbb{R}$,
we prove the existence of unique solution $h\in C^2((0,\infty))\cap
C^1([0,\infty))$ for the equation
$2r^2h(r)h_{rr}(r)=(n-1)h(r)(h(r)-1)+rh_r(r)(rh_r(r)-\lambda r-(n-1))$,
$h(r)>0$, in $(0,\infty)$ satisfying $h(0)=1$, $h_r(0)=\mu_1$. We also prove
the existence of unique analytic solution of the about equation on $[0,\infty)$
for any $\lambda\ge 0$, $n\ge 2$ and $\mu_1\in\mathbb{R}$. Moreover we will
prove the asymptotic behaviour of the solution $h$ for any $n\ge 2$,
$\lambda\ge 0$ and $\mu_1\in\mathbb{R}\setminus\{0\}$.


  We present results for a numerical study of the ghost propagator in Coulomb
gauge whereby lattice results for the spatial gluon propagator are used as
input to solving the ghost Dyson-Schwinger equation. We show that in order to
solve completely, the ghost equation must be supplemented by a boundary
condition (the value of the inverse ghost propagator dressing function at zero
momentum) which determines if the solution is critical (zero value for the
boundary condition) or subcritical (finite value). The various solutions
exhibit a characteristic behavior where all curves follow the same (critical)
solution when going from high to low momenta until `forced' to freeze out in
the infrared to the value of the boundary condition. The boundary condition can
be interpreted in terms of the Gribov gauge-fixing ambiguity; we also
demonstrate that this is not connected to the renormalization. Further, the
connection to the temporal gluon propagator and the infrared slavery picture of
confinement is discussed.


  We compute the complete O(alpha^2) QED corrections to the electron energy
spectrum in unpolarized muon decay, including the full dependence on the
electron mass. Our calculation reduces the theoretical uncertainty on the
electron energy spectrum well below 10^{-4}, the precision anticipated by the
TWIST experiment at TRIUMF, which is currently performing this measurement. For
this calculation, we extend techniques we have recently developed for
performing next-to-next-to-leading order computations to handle the decay
spectra of massive particles. Such an extension enables further applications to
precision predictions for b, t, and Higgs differential decay rates.


  Recently, X-ray microscopy (XRM) and light-sheet fluorescence microscopy
(LSFM) have emerged as two pivotal imaging tools in preclinical research on
bone remodeling diseases, offering micrometer-level resolution. Integrating
these complementary modalities provides a holistic view of bone
microstructures, facilitating function-oriented volume analysis across
different disease cycles. However, registering such independently acquired
large-scale volumes is extremely challenging under real and reference-free
scenarios. This paper presents a fast two-stage pipeline for volume
registration of XRM and LSFM. The first stage extracts the surface features and
employs two successive point cloud-based methods for coarse alignment. The
second stage fine-tunes the initial alignment using a modified
cross-correlation method, ensuring precise volumetric registration. Moreover,
we propose residual similarity as a novel metric to assess the alignment of two
complementary modalities. The results imply robust gradual improvement across
the stages. In the end, all correlating microstructures, particularly lacunae
in XRM and bone cells in LSFM, are precisely matched, enabling new insights
into bone diseases like osteoporosis which are a substantial burden in aging
societies.


  We build up a class of N=2 supersymmetric non-linear $\sigma$-models in an
N=1 superspace based on the Atiyah-Ward space-time of (2+2)-signature metric.
We also discuss the gauging of isometries of the associated hyper-K\"ahlerian
target spaces and present the resulting gauge-covariant supersymmetric action
functional.


  We reinterpret $W'$, $Z'$ and Higgs searches at the LHC in terms of a model
with nonuniversal $V'$ couplings to fermions in order to gauge how well these
searches can be applied outside the (simplified) scenarios for which they were
optimized. In particular, we consider bounds from $V'$ searches in final states
$\tau \tau$, $e\nu$, $ll$ and $t b$, and discuss the impact of width effects.
We then show that decays of the type $V' \rightarrow V h$ yield additional
bounds on the heavy vector masses and, in the case of a discovery, provide an
important probe of the heavy sector. Finally, we match the low energy limit of
the model to an effective theory and compare the bounds on the resulting
dimension-6 operators with the direct searches discussed in this paper.


  Theories with massive gravitons are interesting for a variety of physical
applications, ranging from cosmological phenomena to holographic modeling of
condensed matter systems. To date, they have been formulated as effective field
theories with a cutoff proportional to a positive power of the graviton mass
m_g and much smaller than that of the massless theory (M_P ~ 10^19 GeV in the
case of general relativity). In this paper we present an ultraviolet completion
for massive gravity valid up to a high energy scale independent of the graviton
mass. The construction is based on the existence of a preferred time foliation
combined with spontaneous condensation of vector fields. The perturbations of
these fields are massive and below their mass the theory reduces to a model of
Lorentz violating massive gravity. The latter theory possesses instantaneous
modes whose consistent quantization we discuss in detail. We briefly study some
modifications to gravitational phenomenology at low-energies. The homogeneous
cosmological solutions are the same as in the standard cosmology. The
gravitational potential of point sources agrees with the Newtonian one at
distances small with respect to m_g^(-1). Interestingly, it becomes repulsive
at larger distances.


  Understanding the Higgs potential at large field values corresponding to
scales in the range above $10^{10}{\rm GeV}$ is important for questions of
vacuum stability, particularly in the early universe where survival of the
Higgs vacuum can be an issue. In this paper we show that the Higgs potential
can be derived in away which is independent of the choice of conformal frame
for the spacetime metric. Questions about vacuum stability can therefore be
answered unambiguously. We show that frame independence leads to new relations
between the beta functions of the theory and we give improved limits on the
allowed values of the Higgs curvature coupling for stability.


  We study the vibrational modes of Skyrmions with baryon numbers one through
eight in the standard Skyrme model. The vibrational modes are found in the
harmonic approximation around the classical soliton solution and the real parts
of the frequencies of the modes are extracted. We further classify the
vibrational modes into representations of the symmetries possessed by the
Skyrmion solutions. We find that there are approximately 7B low-lying modes for
a Skyrmion with baryon number B, in addition to an infinite continuum of
scattering modes. This result suggests that the instanton moduli space, which
is 8B-dimensional, does not accurately describe the deformation space of
Skyrmions as previously conjectured.


  Typical stars in the Milky Way galaxy have velocities of hundreds of
kilometres per second and experience gravitational accelerations of $\sim
10^{-10}$ m s$^{-2}$, resulting in velocity changes of a few centimetres per
second over a decade. Measurements of these accelerations would permit direct
tests of the applicability of Newtonian dynamics on kiloparsec length scales
and could reveal significant small scale inhomogeneities within the galaxy, as
well increasing the sensitivity of measurements of the overall mass
distribution of the galaxy. Noting that a reasonable extrapolation of progress
in exoplanet hunting spectrographs suggests that centimetre per second level
precision will be attainable in the coming decade(s), we explore the
possibilities such measurements would create. We consider possible confounding
effects, including apparent accelerations induced by stellar motion and reflex
velocities from planetary systems, along with possible strategies for their
mitigation. If these issues can be satisfactorily addressed it will be possible
to use high precision measurements of changing stellar velocities to perform a
"blind search" for dark matter, make direct tests of theories of non-Newtonian
gravitational dynamics, detect local inhomogeneities in the dark matter
density, and greatly improve measurements of the overall properties of the
galaxy.


  We propose and analyze a one-dimensional multi-species cross-diffusion system
with non-zero-flux boundary conditions on a moving domain, motivated by the
mod- eling of a Physical Vapor Deposition process. Using the boundedness by
entropy method, we prove the existence of a global weak solution to the
obtained system. In addition, existence of a solution to an optimal control
problem defined on the fluxes is established under the assumption that the
solution to the considered cross-diffusion system is unique. Lastly, we prove
that in the case when the imposed external fluxes are constant and positive and
the entropy density is defined as a classical logarithmic entropy, the
concentrations of the dif- ferent species converge in the long-time limit to
constant profiles at a rate inversely proportional to time. These theoretical
results are illustrated by numerical tests.


  In engineering crystal plasticity inelastic mechanisms correspond to
tensorial zero-energy valleys in the space of macroscopic strains. The flat
nature of such valleys is in contradiction with the fact that plastic slips,
mimicking lattice-invariant shears, are inherently discrete. A reconciliation
has recently been achieved in the mesoscopic tensorial model (MTM) of crystal
plasticity, which introduces periodically modulated energy valleys while also
capturing in a geometrically exact way the crystallographically-specific
aspects of plastic slips. In this paper, we extend the MTM framework, which in
its original form had the appearance of a discretized nonlinear elasticity
theory, by explicitly introducing the concept of plastic deformation. The
ensuing model contains a novel matrix-valued spin variable, representing the
quantized plastic distortion, whose rate-independent evolution can be described
by a discrete (quasi-)automaton. The proposed reformulation of the MTM leads to
a considerable computational speedup associated with the use of a robust and
efficient hybrid Gauss-Newton--Cauchy energy minimization algorithm. To
illustrate the effectiveness of the new approach, we present a detailed
case-study focusing on the aspects of crystal plasticity that are beyond reach
for the classical continuum theory. Thus, we provide compelling evidence that
the re-formulated MTM is fully adequate to deal with the intermittency of
plastic response under quasi-static loading. In particular, our numerical
experiments show that the statistics of dislocational avalanches, associated
with plastic yield in 2D square crystals, exhibits a power-law tail with a
critical exponent matching the value predicted by general theoretical
considerations and also independently observed in discrete-dislocation-dynamics
(DDD) simulations.


  Let (W,S) be a crystallographic Coxeter group (this includes all finite and
affine Weyl groups), and J a subset of S. Let $W^J$ denote the set of minimal
coset representatives modulo the parabolic subgroup $W_J$. For w in $W^J$, let
$f^{w,J}_{i}$ denote the number of elements of length i below w in Bruhat order
on $W^J$ (notation simplified to $f^{w}_{i}$ in the case when J=S). We show
that $f^{w,J}_{i}$ is less than or equal to $f^{w,J}_{j}$ when i < j and j is
less than or equal to the length of w minus i.
  Furthermore, we express when an initial and final interval of the f's is
symmetric around the middle in terms of Kazhdan-Lusztig polynomials.
  It is also shown that if W is finite then the sequence of f's cannot grow too
rapidly. Som result mirroring our first result are obtaind, again in the finite
case.
  The proofs rely for the most part on properties of the cohomology of
Kac-Moody Schubert varieties.


  Numerical integration and function approximation on compact Riemannian
manifolds based on eigenfunctions of the Laplace-Beltrami operator have been
widely studied in the recent literature. The standard example in numerical
experiments is the Euclidean sphere. Here, we derive numerically feasible
expressions for the approximation schemes on the Grassmannian manifold, and we
present the associated numerical experiments on the Grassmannian. Indeed, our
experiments illustrate and match the corresponding theoretical results in the
literature.


  We explore non-redundant aperture masking to derive the size and shape of the
ALBA synchrotron light source at optical wavelengths using synchrotron
radiation interferometry. We show that non-redundant masks are required due to
phase fluctuations arising within the experimental set-up. We also show, using
closure phase, that the phase fluctuations are factorizable into element-based
errors. We employ multiple masks, including 2, 3, 5, and 6 hole configurations.
We develop a process for self-calibration of the element-based amplitudes
(square root of flux through the aperture), which corrects for non-uniform
illumination over the mask, in order to derive visibility coherences and
phases, from which the source size and shape can be derived. We explore the
optimal procedures to obtain the most reliable results with the 5-hole mask,
based on the temporal scatter in measured coherences and closure phases. We
find that the closure phases are very stable, and close to zero (within $2^o$).
Through uv-modeling, we consider the noise properties of the experiment and
conclude that our visibility measurements per frame are likely accurate to an
rms scatter of $\sim 1\%$.


  Evidence on the effectiveness of retraining U.S. unemployed workers primarily
comes from evaluations of training programs, which represent one narrow avenue
for skill acquisition. We use high-quality records from Ohio and a matching
method to estimate the effects of retraining, broadly defined as enrollment in
postsecondary institutions. Our simple method bridges two strands of the
dynamic treatment effect literature that estimate the
treatment-now-versus-later and treatment-versus-no-treatment effects. We find
that enrollees experience earnings gains of six percent three to four years
after enrolling, after depressed earnings during the first two years. The
earnings effects are driven by industry-switchers, particularly to healthcare.


  We report on optical reflectivity experiments performed on Cd3As2 over a
broad range of photon energies and magnetic fields. The observed response
clearly indicates the presence of 3D massless charge carriers. The specific
cyclotron resonance absorption in the quantum limit implies that we are probing
massless Kane electrons rather than symmetry-protected 3D Dirac particles. The
latter may appear at a smaller energy scale and are not directly observed in
our infrared experiments.


  Several aspects of complex-valued potentials generating a real and positive
spectrum are discussed. In particular, we construct complex-valued potentials
whose corresponding Schr\"odinger eigenvalue problem can be solved
analytically.


  Fast discrimination between quantum states of superconducting artificial
atoms is an important ingredient for quantum information processing. In circuit
quantum electrodynamics, increasing the signal field amplitude in the readout
resonator, dispersively coupled to the artificial atom, improves the
signal-to-noise ratio and increases the measurement strength. Here we employ
this effect over two orders of magnitude in readout power, made possible by the
unique combination of a dimer Josephson junction array amplifier with a large
dynamic range, and the fact that the readout of our granular aluminum fluxonium
artificial atom remained quantum-non-demolition (QND) at relatively large
photon numbers in the readout resonator, up to $\overline{n} = 110$. Using
Bayesian inference, this allows us to detect quantum jumps faster than the
readout resonator response time $2/\kappa$, where $\kappa$ is the bandwidth of
the readout resonator.


  These lectures are intended to provide the theoretical basis of describing
high-energy particle collisions at a level appropriate to graduate students in
experimental high energy physics. They are supposed to be familiar with quantum
electrodynamics, the concept of Feynman rules, Feynman graphs and computation
of the cross section in quantum field theory.


  A great deal of effort has been spent measuring topological features of the
Internet. However, it was recently argued that sampling based on taking paths
or traceroutes through the network from a small number of sources introduces a
fundamental bias in the observed degree distribution. We examine this bias
analytically and experimentally. For Erdos-Renyi random graphs with mean degree
c, we show analytically that traceroute sampling gives an observed degree
distribution P(k) ~ 1/k for k < c, even though the underlying degree
distribution is Poisson. For graphs whose degree distributions have power-law
tails P(k) ~ k^-alpha, traceroute sampling from a small number of sources can
significantly underestimate the value of \alpha when the graph has a large
excess (i.e., many more edges than vertices). We find that in order to obtain a
good estimate of alpha it is necessary to use a number of sources which grows
linearly in the average degree of the underlying graph. Based on these
observations we comment on the accuracy of the published values of alpha for
the Internet.


  Many experiments have confirmed the spectral hardening at a few hundred GV of
cosmic-ray (CR) nuclei spectra, and three general different origins have been
proposed: the primary source acceleration, the propagation, and the
superposition of different kinds of sources. The AMS-02 CR nuclei spectra of
He, C, N, O, Ne, Mg, Si, and B (which including B and its dominating parents
species) are collected to study the necessity of employing a break in diffusion
coefficient and independent breaks in primary source injection spectra to
reproduce the spectral hardening at a few hundred GV. For comparison, three
different schemes are introduced to do the global fitting. The fitting results
show that both the break in diffusion coefficient and the independent breaks in
primary source injection spectra are needed, which are corresponding to the
spatial dependent propagation and the superposition of different kinds of
sources, respectively. Consequently, the nuclei spectral hardening in a few
hundred GV should have hybrid origins. Moreover, the CR spectral indices of He
and Ne show large deviations to other species in low-rigidity region, which
indicates their different CR origins.


  Vision-language models such as CLIP have boosted the performance of
open-vocabulary object detection, where the detector is trained on base
categories but required to detect novel categories. Existing methods leverage
CLIP's strong zero-shot recognition ability to align object-level embeddings
with textual embeddings of categories. However, we observe that using CLIP for
object-level alignment results in overfitting to base categories, i.e., novel
categories most similar to base categories have particularly poor performance
as they are recognized as similar base categories. In this paper, we first
identify that the loss of critical fine-grained local image semantics hinders
existing methods from attaining strong base-to-novel generalization. Then, we
propose Early Dense Alignment (EDA) to bridge the gap between generalizable
local semantics and object-level prediction. In EDA, we use object-level
supervision to learn the dense-level rather than object-level alignment to
maintain the local fine-grained semantics. Extensive experiments demonstrate
our superior performance to competing approaches under the same strict setting
and without using external training resources, i.e., improving the +8.4% novel
box AP50 on COCO and +3.9% rare mask AP on LVIS.


  Models of black hole accretion disks are reviewed, with an emphasis on the
theory of hard X-ray production. The following models are considered: i)
standard, ii) super-critical, iii) two-temperature, and iv) disk+corona. New
developments have recently been made in hydrodynamical models of accretion and
in phenomenological radiative models fitting the observed X-ray spectra.
Attempts to unify the two approaches are only partly successful.


  Using the Insight-HXMT observations of GRS 1915+105 when it exhibits low
frequency quasi-periodic oscillations (QPOs), we measure the evolution of the
QPO frequency along with disk inner radius and mass accretion rate. We find a
tight positive correlation between the QPO frequency and mass accretion rate.
Our results extend the finding of previous work with AstroSat to a larger range
of accretion rate with independent instruments and observations. Treating the
QPO frequency of GRS 1915+105 as the relativistic dynamic frequency of a
truncated disk, we are able to confirm the high spin nature of the black hole
in GRS 1915+105. We also address the potential of our finding to test general
relativity in the future.


  We describe several improvements to algorithms for the rigorous computation
of the endomorphism ring of the Jacobian of a curve defined over a number
field.


  The key task of physical simulation is to solve partial differential
equations (PDEs) on discretized domains, which is known to be costly. In
particular, high-fidelity solutions are much more expensive than low-fidelity
ones. To reduce the cost, we consider novel Gaussian process (GP) models that
leverage simulation examples of different fidelities to predict
high-dimensional PDE solution outputs. Existing GP methods are either not
scalable to high-dimensional outputs or lack effective strategies to integrate
multi-fidelity examples. To address these issues, we propose Multi-Fidelity
High-Order Gaussian Process (MFHoGP) that can capture complex correlations both
between the outputs and between the fidelities to enhance solution estimation,
and scale to large numbers of outputs. Based on a novel nonlinear
coregionalization model, MFHoGP propagates bases throughout fidelities to fuse
information, and places a deep matrix GP prior over the basis weights to
capture the (nonlinear) relationships across the fidelities. To improve
inference efficiency and quality, we use bases decomposition to largely reduce
the model parameters, and layer-wise matrix Gaussian posteriors to capture the
posterior dependency and to simplify the computation. Our stochastic
variational learning algorithm successfully handles millions of outputs without
extra sparse approximations. We show the advantages of our method in several
typical applications.


  Alternating-time temporal logic (ATL) allows to specify requirements on
abilities that different agents should (or should not) possess in a multi-agent
system. However, model checking ATL specifications in realistic systems is
computationally hard. In particular, if the agents have imperfect information
about the global state of the system, the complexity ranges from Delta2P to
undecidable, depending on the syntactic and semantic details. The problem is
also hard in practice, as evidenced by several recent attempts to tackle it. On
the other hand, model checking of alternating epistemic mu-calculus can have a
distinctly lower computational complexity.
  In this work, we look at the idea of approximating the former problem by the
verification of its "naive" translations to the latter. In other words, we look
at what happens when one uses the (incorrect) fixpoint algorithm to verify
formulae of ATL with imperfect information.


  We report a complete analysis of the formal oxidation state of Co in NaxCoO2,
in the interval 0.31<x<0.67. Iodometric titration and thermoelectric power
confirm that a direct relationship between the Na content and the amount of Co
3 + cannot be established in this system. Creation of a significant amount of
oxygen vacancies accompanies Na-ion deintercalation, keeping the formal Co
valence at 3.45 + for x<0.45. To the light of new thermoelectric power data
which reveals important differences between the hydrated (superconducting) and
non-hydrated (non-superconducting) samples, we propose here that water plays an
important chemical role beyond that of a spacer between the CoO2 layers.


  We prove that the degree-one vortex solution is the unique minimizer for the
Ginzburg--Landau functional for gradient fields (that is, the Aviles--Giga
model) in the unit ball $B^N$ in dimension $N \geq 4$ and with respect to its
boundary value. A similar result is also proved for $\mathbb{S}^N$-valued maps
in the theory of micromagnetics. Two methods are presented. The first method is
an extension of the analogous technique previously used to treat the
unconstrained Ginzburg--Landau functional in dimension $N \geq 7$. The second
method uses a symmetrization procedure for gradient fields such that the
$L^2$-norm is invariant while the $L^p$-norm, $2 < p < \infty$, and the
$H^1$-norm are lowered.


  A \textit{distinguishing partition} of a group $X$ with automorphism group
${aut}(X)$ is a partition of $X$ that is fixed by no nontrivial element of
${aut}(X)$. In the event that $X$ is a complete multipartite graph with its
automorphism group, the existence of a distinguishing partition is equivalent
to the existence of an asymmetric hypergraph with prescribed edge sizes. An
asymptotic result is proven on the existence of a distinguishing partition when
$X$ is a complete multipartite graph with $m_1$ parts of size $n_1$ and $m_2$
parts of size $n_2$ for small $n_1$, $m_2$ and large $m_1$, $n_2$. A key tool
in making the estimate is counting the number of trees of particular classes.


  The CALICE collaboration develops prototypes for highly granular calorimeters
for detectors at a future linear electron positron collider. The highly
granular electromagnetic calorimeter prototype was tested in particle beams. We
present the study of the interactions of hadrons in this prototype.


  We calculate the cross-section for the diffractive exclusive process gamma*_L
(Q_1^2) gamma*_L(Q_2^2) -> rho^0_L rho^0_L, in view of its study in the future
high energy e+e- linear collider. The Born order approximation of the amplitude
is completely calculable in the hard region Q_1, Q_2 >> Lambda_QCD. The
resulting cross-section is large enough for this process to be measurable with
foreseen luminosity and energy, for Q_1 and Q_2 in the range of a few GeV.


  Positronium is the simplest bound state, built of an electron and a positron.
Studies of positronium in vacuum and its decays in medium tell us about Quantum
Electrodynamics, QED, and about the structure of matter and biological
processes of living organisms at the nanoscale, respectively. Spectroscopic
measurements constrain our understanding of QED bound state theory. Searches
for rare decays and measurements of the effect of gravitation on positronium
are used to look for new physics phenomena. In biological materials positronium
decays are sensitive to the inter- and intra-molecular structure and to the
metabolism of living organisms ranging from single cells to human beings. This
leads to new ideas of positronium imaging in medicine using the fact that
during positron emission tomography (PET) as much as 40% of positron
annihilation occurs through the production of positronium atoms inside the
patient's body. A new generation of the high sensitivity and multi-photon
total-body PET systems opens perspectives for clinical applications of
positronium as a biomarker of tissue pathology and the degree of tissue
oxidation.


  The details of reheating energy scale $\rho_{reh}$ is largely uncertain
today, independent of inflation models. This would induce uncertainty in
predicting primordial spectrum. Such uncertainty could be very large,
especially for spectra with large running $n_S$. We find that for some
inflation models with a large $d\ln n_S(k)/d\ln k$, $\rho_{reh}$ could be
highly restricted by current CMB observations.


  We construct a Banach space satisfying that the nearest point map (also
called proximity mapping or metric projection) onto any compact and convex
subset is continuous but not uniformly continuous. The space we construct is
locally uniformly convex, which ensures the continuity of all these nearest
point maps. Moreover, we prove that every infinite-dimensional separable Banach
space is arbitrarily close (in the Banach-Mazur distance) to one satisfying the
above conditions.


  A nanochannel subjected to both a potential and concentration gradient has an
asymmetric current-voltage, I-V, response with three primary characteristics:
the Ohmic conductance, G, the current at zero voltage, I(v=0), and the voltage
at zero current, V(I=0). To date, there is no known self-consistent theory for
these characteristics subject to an arbitrary concentration gradient. Here, we
present simple expressions for each of these characteristics that have been
derived self-consistently. Our findings provide insights into the underlying
physics of nanofluidics systems used for water desalination and energy
harvesting.


  In a room with five cosmologists there there may easily be ten theories of
cosmogenesis. Cosmogenesis is a popular topic for speculation because it is
philosophically deep and because such speculations are unlikely to be proven
wrong in the near future. The scenario we present here was intended mainly as a
pedagogical illustration or toy model, but it turns out to possibly have a more
serious and interesting result - a rationale for the spatial flatness of the
Universe. Our basic assumptions are that the cosmological scale factor obeys
the standard Friedman equation of general relativistic cosmology and that the
equation is dominated by a cosmological constant term and a curvature term; the
dynamics of the Universe is then (approximately) the same as that of a tipping
pencil. The scale factor cannot remain at an unstable initial value of zero and
must increase (i.e. the Universe must come into existence) according to the
uncertainty principle, that is due to quantum fluctuations; in other words we
propose in a precise but limited context an answer to Heidegger's famous
question "Why is there something rather than nothing." The mechanism is the
same as that whereby an idealized pencil balanced on its point cannot remain so
and must tip over. If it is moreover assumed that the Universe expands at the
minimum asymptotic rate consistent with the uncertainty principle then the
result is spatial flatness.


  Fuchsian equations provide a way of constructing large classes of spacetimes
whose singularities can be described in detail. In some of the applications of
this technique only the analytic case could be handled up to now. This paper
develops a method of removing the undesirable hypothesis of analyticity. This
is applied to the specific case of the Gowdy spacetimes in order to show that
analogues of the results known in the analytic case hold in the smooth case. As
far as possible the likely strengths and weaknesses of the method as applied to
more general problems are displayed.


  This paper intends to give a mathematical explanation for results on the
zeta-function of some families of varieties recently obtained in the context of
Mirror Symmetry. In doing so, we obtain concrete and explicit examples for some
results recently used in algorithms to count points on smooth hypersurfaces in
P^n. In particular, we extend the monomial-motive correspondence of Kadir and
Yui and we give explicit solutions to the p-adic Picard-Fuchs equation
associated with monomial deformations of Fermat hypersurfaces. As a by-product
we obtain Poincare Duality for the Rigid cohomology of certain singular affine
varieties.


  The stochastic dissipative Schrodinger equation is derived for an open
quantum system consisting of a sub-system able to exchange energy with a
thermal reservoir. The resultant evolution of the wave function also gives the
evolution of the density matrix, which is an explicit, stochastic form of the
Lindblad master equation. A quantum fluctuation-dissipation theorem is also
derived. The time correlation function is discussed.


  Multicast communication plays a crucial role in Mobile Adhoc Networks
(MANETs). MANETs provide low cost, self configuring devices for multimedia data
communication in military battlefield scenarios, disaster and public safety
networks (PSN). Multicast communication improves the network performance in
terms of bandwidth consumption, battery power and routing overhead as compared
to unicast for same volume of data communication. In recent past, a number of
multicast routing protocols (MRPs) have been proposed that tried to resolve
issues and challenges in MRP. Multicast based group communication demands
dynamic construction of efficient and reliable route for multimedia data
communication during high node mobility, contention, routing and channel
overhead. This paper gives an insight into the merits and demerits of the
currently known research techniques and provides a better environment to make
reliable MRP. It presents a ample study of various Quality of Service (QoS)
techniques and existing enhancement in mesh based MRPs. Mesh topology based
MRPs are classified according to their enhancement in routing mechanism and QoS
modification on On-Demand Multicast Routing Protocol (ODMRP) protocol to
improve performance metrics. This paper covers the most recent, robust and
reliable QoS and Mesh based MRPs, classified based on their operational
features, with their advantages and limitations, and provides comparison of
their performance parameters.


  Many of the new high energy sources discovered both by INTEGRAL/IBIS and
Swift/BAT have been characterised thanks to extensive, multi-band follow-up
campaigns, but there are still objects whose nature remains to be asserted. In
this paper we investigate the true nature of three high energy sources, IGR
J12134-6015, IGR J16058-7253 and Swift J2037.2+4151, employing multiwavelength
data from the NIR to the X-rays. Through Gaia and ESO-VLT measurements and
through Swift/XRT X-ray spectral analysis, we re-evaluate the classification
for IGR J12134-6015, arguing that the source is a Galactic object and in
particular a Cataclysmic Variable. We were able to confirm, thanks to NuSTAR
observations, that the hard X-ray emission detected by INTEGRAL/IBIS and
Swift/BAT from IGR J16058-7253 is coming from two Seyfert 2 galaxies which are
both counterparts for this source. Through optical and X-ray spectral analysis
of Swift J2037.2+4151 we find that this source is likely part of the rare and
peculiar class of Symbiotic X-ray binaries and displays flux and spectral
variability as well as interesting spectral features, such as a blending of
several emission lines around the iron line complex.


  We provide the syntax and semantics of the cat language, a domain specific
language to describe consistency properties of parallel/distributed programs.
The language is implemented in the herd7 too
(http://diy.inria.fr/doc/herd.html)l.


  We study the transport of excitations on a V-shaped network of three coupled
two-level systems that are subjected to an environment that induces incoherent
hopping between the nodes. Two of the nodes are coupled to a source while the
third node is coupled to a drain. A common feature of these networks is the
existence of a dark-state that blocks the transport to the drain. Here we
propose a means to avoid this state by a suitable choice of initial
correlations, induced by a source that is common to both coupled nodes.


  In this work we explore the boundary of the jacobian of a singular curve in
the compactified picard group. We formulate a functor that helps to determine
this boundary and show that this functor is representable. We try to dertermine
the points on the boundary.


  Atoms and molecules are important conceptual entities we invented to
understand the physical world around us. The key to their usefulness lies in
the organization of nuclear and electronic degrees of freedom into a single
dynamical variable whose time evolution we can better imagine. The use of such
effective variables in place of the true microscopic variables is possible
because of the separation between nuclear/electronic and atomic/molecular time
scales. Where separation of time scales occurs, identification of analogous
objects in financial markets can help advance our understanding of their
dynamics. To detect separated time scales and identify their associated
effective degrees of freedom in financial markets, we devised a two-stage
statistical clustering scheme to analyze the price movements of stocks in
several equity markets. Through this two-time-scale clustering analysis, we
discovered a hierarchy of levels of self-organization in real financial
markets. We call these statistically robust self-organized dynamical structures
financial atoms, financial molecules, and financial supermolecules. In general,
the detailed compositions of these dynamical structures cannot be deduced based
on raw financial intuition alone, and must be explained in terms of the
underlying portfolios, and investment strategies of market players. More
interestingly, we find that major market events such as the Chinese Correction
and the Subprime Crisis leave many tell-tale signs within the correlational
structures of financial molecules.


  The concept of {\it active gravitational mass}, its definition and its
relation with the sources of a gravitational field, was clearly established by
Tolman in 1934. On the contrary, and surprisingly in our opinion, the concept
of {\it proper mass} has remained obscure in General relativity. We compare a
new definition to an apparent more obvious one and discuss how each choice
modifies the ratio of active to proper gravitational mass.


  Considering systems of self-propelled polar particles with nematic
interactions ("rods"), we compare the continuum equations describing the
evolution of polar and nematic order parameters, derived either from
Smoluchowski or Boltzmann equations. Our main goal is to understand the
discrepancies between the continuum equations obtained so far in both
frameworks. We first show that in the simple case of point-like particles with
only alignment interactions, the continuum equations obtained have the same
structure in both cases. We further study, in the Smoluchowski framework, the
case where an interaction force is added on top of the aligning torque. This
clarifies the origin of the additional terms obtained in previous works. Our
observations lead us to emphasize the need for a more involved closure scheme
than the standard normal form of the distribution when dealing with active
systems.


  We have studied the light hadron spectrum and decay constants for quenched
QCD at beta=6.2 on a 24^3x48 lattice. We compare the results obtained using a
nearest-neighbour O(a)-improved ("clover") fermion action with those obtained
using the standard Wilson fermion action on the same gauge configurations. For
pseudoscalar meson masses in the range 330-800 MeV, we find no significant
difference between the results for the two actions. The scales obtained from
the string tension and mesonic sector are consistent, but higher than those
derived from baryon masses. The ratio of the pseudoscalar decay constant to the
vector meson mass is roughly independent of quark mass as observed
experimentally.


  Using density-functional theory with the hybrid functional B3LYP, we
investigate the electronic properties of polymers with diketo-pyrrolo-pyrrole
(DPP) unit. We note that some of the polymers studied have LUCO energy similar
to the C70-PCBM, or even lower, making them promising candidates for electron
transport in organic photovoltaic devices. The homopolymer of DPP is predicted
to have a band gap around 1.2 eV and shows a good dispersion of the conduction
band.


  The paper revisits recently revealed regimes of the "nonconventional
synchronization" in systems of coupled bi-stable Van der Pol oscillators. These
regimes are characterized by periodic (or quasiperiodic) almost complete energy
exchanges between the coupled oscillators. In the paper it is demonstrated that
such responses correspond to synchronization of the modulation amplitudes
between symmetric and antisymmetric modes of the system, with persistent phase
drift. This observation substantially simplifies the treatment, reduces the
dynamics to simple phase cylinder and allows to reveal a rich set of global and
local bifurcations of limit cycles and tori in the system. Among other
findings, one encounters an unexpected regime of nonstationary asymmetric
synchronization.


  This study introduces a novel estimation method for the entries and structure
of a matrix $A$ in the linear factor model $\textbf{X} = A\textbf{Z} +
\textbf{E}$. This is applied to an observable vector $\textbf{X} \in
\mathbb{R}^d$ with $\textbf{Z} \in \mathbb{R}^K$, a vector composed of
independently regularly varying random variables, and independent lighter tail
noise $\textbf{E} \in \mathbb{R}^d$. This leads to max-linear models treated in
classical multivariate extreme value theory. The spectral of the limit
distribution is subsequently discrete and completely characterised by the
matrix $A$. Every max-stable random vector with discrete spectral measure can
be written as a max-linear model. Each row of the matrix $A$ is supposed to be
both scaled and sparse. Additionally, the value of $K$ is not known a priori.
The problem of identifying the matrix $A$ from its matrix of pairwise extremal
correlation is addressed. In the presence of pure variables, which are elements
of $\textbf{X}$ linked, through $A$, to a single latent factor, the matrix $A$
can be reconstructed from the extremal correlation matrix. Our proofs of
identifiability are constructive and pave the way for our innovative estimation
for determining the number of factors $K$ and the matrix $A$ from $n$ weakly
dependent observations on $\textbf{X}$. We apply the suggested method to weekly
maxima rainfall and wildfires to illustrate its applicability.


  Image keypoints and descriptors play a crucial role in many visual
measurement tasks. In recent years, deep neural networks have been widely used
to improve the performance of keypoint and descriptor extraction. However, the
conventional convolution operations do not provide the geometric invariance
required for the descriptor. To address this issue, we propose the Sparse
Deformable Descriptor Head (SDDH), which learns the deformable positions of
supporting features for each keypoint and constructs deformable descriptors.
Furthermore, SDDH extracts descriptors at sparse keypoints instead of a dense
descriptor map, which enables efficient extraction of descriptors with strong
expressiveness. In addition, we relax the neural reprojection error (NRE) loss
from dense to sparse to train the extracted sparse descriptors. Experimental
results show that the proposed network is both efficient and powerful in
various visual measurement tasks, including image matching, 3D reconstruction,
and visual relocalization.


  Private Computation (PC), recently introduced by Sun and Jafar, is a
generalization of Private Information Retrieval (PIR) in which a user wishes to
privately compute an arbitrary function of data stored across several servers.
We construct a PC scheme which accounts for server collusion, coded data, and
non-linear functions. For data replicated over several possibly colluding
servers, our scheme computes arbitrary functions of the data with rate equal to
the asymptotic capacity of PIR for this setup. For systematically encoded data
stored over colluding servers, we privately compute arbitrary functions of the
columns of the data matrix and calculate the rate explicitly for polynomial
functions. The scheme is a generalization of previously studied star-product
PIR schemes.


  Image pre-processing in the frequency domain has traditionally played a vital
role in computer vision and was even part of the standard pipeline in the early
days of deep learning. However, with the advent of large datasets, many
practitioners concluded that this was unnecessary due to the belief that these
priors can be learned from the data itself. Frequency aliasing is a phenomenon
that may occur when sub-sampling any signal, such as an image or feature map,
causing distortion in the sub-sampled output. We show that we can mitigate this
effect by placing non-trainable blur filters and using smooth activation
functions at key locations, particularly where networks lack the capacity to
learn them. These simple architectural changes lead to substantial improvements
in out-of-distribution generalization on both image classification under
natural corruptions on ImageNet-C [10] and few-shot learning on Meta-Dataset
[17], without introducing additional trainable parameters and using the default
hyper-parameters of open source codebases.


  In this paper, the new information system development methodology will be
proposed. This methodology will enable the whole data model to be built and
adjusted at the run time, without rebuilding the application. This will make
the user much more powerful and independent on the manufacturer of the system.
It will also cut the price and shorten the development time of the information
systems dramatically, because common business logic will not have to be
implemented for each individual table and the major part of the user interface
will be generated automatically.


  Dealing with multi-objective problems by using generation methods has some
interesting advantages since it provides the decision-maker with the complete
information about the set of non-dominated points (Pareto front) and a clear
overview of the problem. However, providing many solutions to the
decision-maker might also be overwhelming. As an alternative approach,
presenting a representative set of solutions of the Pareto front may be
advantageous. Choosing such a representative set is by itself also a
multi-objective problem that must consider the number of solutions to present,
the uniformity, and/or the coverage of the representation, to guarantee its
quality. This paper proposes three algorithms for the representation problem
for multi-objective integer linear programming problems with two or more
objective functions, each one of them dealing with each dimension of the
problem (cardinality, coverage, and uniformity). Such algorithms are all based
on the $\epsilon$-constraint approach. In addition, the paper also presents
strategies to overcome poor estimations of the Pareto front bounds. The
algorithms were tested on the ability to efficiently generate the whole Pareto
front or its representation. The uniformity and cardinality algorithms proved
to be very efficient both in binary and integer problems, being amongst the
best in the literature. Both coverage and uniformity algorithms provide good
quality representations on their targeted objective, while the cardinality
algorithm appears to be the most flexible, privileging uniformity for lower
cardinality representations and coverage on higher cardinality.


  Searching for new particles beyond the standard model is crucial for
understanding several fundamental conundrums in physics and astrophysics.
Amongst them, axions or similar hypothetical pseudoscalar bosons would mediate
electron-nucleon interactions. While previous experiments set stringent upper
bounds of this interaction strength with force range over $20 ~\mu$m,
experimental searching at shorter force range remains elusive. We develop a
method that utilizes a near-surface Nitrogen-vacancy center as a quantum sensor
to explore such interaction. New constraints for axion-mediated
electron-nucleon coupling, $g_s^Ng_p^e$, have been set for the force range $0.1
$--$23~\mu$m. The obtained upper bound of the interaction at $20~\mu$m,
$g_s^Ng_p^e < 6.24\times10^{-15}$, is two orders of magnitude more stringent
than that set by earlier experiments. Our method can be further extended to
investigate other spin-dependent interactions and opens the door for the
single-spin quantum sensor to explore new physics beyond the standard model.


  We argue that tetragonal CuO (T-CuO) has the potential to finally settle
long-standing modelling issues for cuprate physics. We compare the one-hole
quasiparticle (qp) dispersion of T-CuO to that of cuprates, in the framework of
the strongly-correlated ($U_{dd}\rightarrow \infty$) limit of the three-band
Emery model. Unlike in CuO$_2$, magnetic frustration in T-CuO breaks the $C_4$
rotational symmetry and leads to strong deviations from the Zhang-Rice singlet
picture in parts of the reciprocal space. Our results are consistent with
angle-resolved photoemission spectroscopy data but in sharp contradiction to
those of a one-band model previously suggested for them. These differences
identify T-CuO as an ideal material to test a variety of scenarios proposed for
explaining cuprate phenomenology.


  As e-commerce expands, delivering real-time personalized recommendations from
vast catalogs poses a critical challenge for retail platforms. Maximizing
revenue requires careful consideration of both individual customer
characteristics and available item features to optimize assortments over time.
In this paper, we consider the dynamic assortment problem with dual contexts --
user and item features. In high-dimensional scenarios, the quadratic growth of
dimensions complicates computation and estimation. To tackle this challenge, we
introduce a new low-rank dynamic assortment model to transform this problem
into a manageable scale. Then we propose an efficient algorithm that estimates
the intrinsic subspaces and utilizes the upper confidence bound approach to
address the exploration-exploitation trade-off in online decision making.
Theoretically, we establish a regret bound of $\tilde{O}((d_1+d_2)r\sqrt{T})$,
where $d_1, d_2$ represent the dimensions of the user and item features
respectively, $r$ is the rank of the parameter matrix, and $T$ denotes the time
horizon. This bound represents a substantial improvement over prior literature,
made possible by leveraging the low-rank structure. Extensive simulations and
an application to the Expedia hotel recommendation dataset further demonstrate
the advantages of our proposed method.


  The Large Binocular Telescope Interferometer (LBTI) is a versatile instrument
designed for high-angular resolution and high-contrast infrared imaging (1.5-13
microns). In this paper, we focus on the mid-infrared (8-13 microns) nulling
mode and present its theory of operation, data reduction, and on-sky
performance as of the end of the commissioning phase in March 2015. With an
interferometric baseline of 14.4 meters, the LBTI nuller is specifically tuned
to resolve the habitable zone of nearby main-sequence stars, where warm
exozodiacal dust emission peaks. Measuring the exozodi luminosity function of
nearby main-sequence stars is a key milestone to prepare for future exoEarth
direct imaging instruments. Thanks to recent progress in wavefront control and
phase stabilization, as well as in data reduction techniques, the LBTI
demonstrated in February 2015 a calibrated null accuracy of 0.05% over a
three-hour long observing sequence on the bright nearby A3V star beta Leo. This
is equivalent to an exozodiacal disk density of 15 to 30 zodi for a Sun-like
star located at 10pc, depending on the adopted disk model. This result sets a
new record for high-contrast mid-infrared interferometric imaging and opens a
new window on the study of planetary systems.


  This paper develops a model for the bid and ask prices of a European type
asset by formulating a stochastic control problem. The state process is
governed by a modified geometric Brownian motion whose drift and diffusion
coefficients depend on a Markov chain. A Girsanov theorem for Markov chains is
implemented for the change of coefficients, including the diffusion coefficient
which cannot be changed by the usual Girsanov theorem for Brownian motion. The
price of a European type asset is then determined using an Esscher transform
and a system of partial differential equations. A dynamic programming principle
and a maximum/minimum principle associated with the stochastic control problem
are then derived to model bid and ask prices. These prices are not quotes of
traders or market makers but represent estimates in our model on which
reasonable quantities could be traded.


  We consider a scheduling problem where a cloud service provider has multiple
units of a resource available over time. Selfish clients submit jobs, each with
an arrival time, deadline, length, and value. The service provider's goal is to
implement a truthful online mechanism for scheduling jobs so as to maximize the
social welfare of the schedule. Recent work shows that under a stochastic
assumption on job arrivals, there is a single-parameter family of mechanisms
that achieves near-optimal social welfare. We show that given any such family
of near-optimal online mechanisms, there exists an online mechanism that in the
worst case performs nearly as well as the best of the given mechanisms. Our
mechanism is truthful whenever the mechanisms in the given family are truthful
and prompt, and achieves optimal (within constant factors) regret.
  We model the problem of competing against a family of online scheduling
mechanisms as one of learning from expert advice. A primary challenge is that
any scheduling decisions we make affect not only the payoff at the current
step, but also the resource availability and payoffs in future steps.
Furthermore, switching from one algorithm (a.k.a. expert) to another in an
online fashion is challenging both because it requires synchronization with the
state of the latter algorithm as well as because it affects the incentive
structure of the algorithms. We further show how to adapt our algorithm to a
non-clairvoyant setting where job lengths are unknown until jobs are run to
completion. Once again, in this setting, we obtain truthfulness along with
asymptotically optimal regret (within poly-logarithmic factors).


  Let R be a commutative ring with identity. In this paper, we introduce and
investigate the second ideal intersection graph SII(R) of R with vertices are
non-zero proper ideals of R and two distinct vertices I and J are adjacent if
and only if $I \cap J$ is a second ideal of R.


  We present extinction curves that include data down to far ultraviolet
wavelengths (FUV; 1050 - 1200 A) for nine Galactic sight lines. The FUV
extinction was measured using data from the Far Ultraviolet Spectroscopic
Explorer. The sight lines were chosen for their unusual extinction properties
in the infrared through the ultraviolet; that they probe a wide range of dust
environments is evidenced by the large spread in their measured ratios of
total-to-selective extinction, R_V = 2.43 - 3.81. We find that extrapolation of
the Fitzpatrick & Massa relationship from the ultraviolet appears to be a good
predictor of the FUV extinction behavior. We find that predictions of the FUV
extinction based upon the Cardelli, Clayton & Mathis (CCM) dependence on R_V
give mixed results. For the seven extinction curves well represented by CCM in
the infrared through ultraviolet, the FUV extinction is well predicted in three
sight lines, over-predicted in two sight lines, and under-predicted in 2 sight
lines. A Maximum Entropy Method analysis using a simple three component grain
model shows that seven of the nine sight lines in the study require a larger
fraction of grain materials to be in dust when FUV extinction is included in
the models. Most of the added grain material is in the form of small (radii <
200 A) grains.


  These are the proceedings of the Second Workshop on GRAPH Inspection and
Traversal Engineering (GRAPHITE 2013), which took place on March 24, 2013 in
Rome, Italy, as a satellite event of the 16th European Joint Conferences on
Theory and Practice of Software (ETAPS 2013).
  The topic of the GRAPHITE workshop is graph analysis in all its forms in
computer science. Graphs are used to represent data in many application areas,
and they are subjected to various computational algorithms in order to acquire
the desired information. These graph algorithms tend to have common
characteristics, such as duplicate detection to guarantee their termination,
independent of their application domain. Over the past few years, it has been
shown that the scalability of such algorithms can be dramatically improved by
using, e.g., external memory, by exploiting parallel architectures, such as
clusters, multi-core CPUs, and graphics processing units, and by using
heuristics to guide the search. Novel techniques to further scale graph search
algorithms, and new applications of graph search are within the scope of this
workshop.
  Another topic of interest of the event is more related to the structural
properties of graphs: which kind of graph characteristics are relevant for a
particular application area, and how can these be measured? Finally, any novel
way of using graphs for a particular application area is on topic.
  The goal of this event is to gather scientists from different communities,
such as model checking, artificial intelligence planning, game playing, and
algorithm engineering, who do research on graph search algorithms, such that
awareness of each others' work is increased.


  Although the modern shell-model picture of atomic nuclei is built from
single-particle orbits with good total angular momentum $j$, leading to $j$-$j$
coupling, phenomenological models suggested decades ago that for $0p$-shell
nuclides a simpler picture can be realized via coupling of total spin $S$ and
total orbital angular momentum $L$. I revisit this idea with large-basis,
no-core shell model (NCSM) calculations using modern \textit{ab initio}
two-body interactions, and dissect the resulting wavefunctions into their
component $L$- and $S$-components. Remarkably, there is broad agreement with
calculations using the phenomenological Cohen-Kurath forces, despite a gap of
nearly fifty years and six orders of magnitude in basis dimensions. I suggest
$L$-$S$ may be a useful tool for analyzing \textit{ab initio} wavefunctions of
light nuclei, for example in the case of rotational bands.