  This article proves the Riemann hypothesis, which states that all non-trivial
zeros of the zeta function have a real part equal to 1/2. We inspect in detail
the integral form of the (symmetrized) completed zeta function, which is a
product between the zeta and gamma functions. It is known that two integral
lines, expressing the completed zeta function, rotated from the real axis in
the opposite directions, can be shifted without affecting the completed zeta
function owing to the residue theorem. The completed zeta function is regular
in the region of the complex plane under consideration. For convenience in the
subsequent singularity analysis of the above integral, we first deform and
shift the integral contours. We then investigate the singularities of the
composite elements (caused by polynomial integrals in opposite directions),
which appear only in the case for which the distance between the contours and
the origin of the coordinates approaches zero. The real part of the zeros of
the zeta function is determined to be 1/2 along a symmetry line from the
singularity removal condition. (In the other points, the singularities are
adequately cancelled as a whole to lead to a finite value.)


  We propose a distributed control algorithm for a multi-agent network whose
agents deploy over a cluttered region in accordance with a time-varying
coverage density function while avoiding collisions with all obstacles they
encounter. Our algorithm is built on a two-level characterization of the
network. The first level treats the multi-agent network as a whole based on the
distribution of the locations of its agents over the spatial domain. In the
second level, the network is described in terms of the individual positions of
its agents. The aim of the multi-agent network is to attain a spatial
distribution that resembles that of a reference coverage density function
(high-level problem) by means of local (microscopic) interactions of its agents
(low-level problem). In addition, as the agents deploy, they must avoid
collisions with all the obstacles in the region at all times. Our approach
utilizes a modified version of Voronoi tessellations which are comprised of
what we refer to as Obstacle-Aware Voronoi Cells (OAVC) in order to enable
coverage control while ensuring obstacle avoidance. We consider two control
problems. The first problem which we refer to as the high-level coverage
control problem corresponds to an interpolation problem in the class of
Gaussian mixtures (no collision avoidance requirement), which we solve
analytically. The second problem which we refer to as the low-level coverage
control problem corresponds to a distributed control problem (collision
avoidance requirement is now enforced at all times) which is solved by
utilizing Lloyd's algorithm together with the modified Voronoi tessellation
(OAVC) and a time-varying coverage density function which corresponds to the
solution of the high-level coverage control problem. Finally, simulation
results for coverage in a cluttered environment are provided to demonstrate the
efficacy of the proposed approach.


  We show that the Higgs boson structure functions observable in the inclusive
process $e^-e^+ \to H + {\rm "anything"}$ may reveal the presence of anomalous
contributions corresponding to several types of new physics partners, Higgs
boson compositeness or invisible (dark) matter. This could be done without
making a difficult or even an impossible experimental analysis of the contents
of the "anything". We give illustrations showing how the shapes of the various
structure functions containing such typical new contributions may differ from
the standard prediction and allow their identification.


  In the seminal work by G. Eilenberger [Z. Phys. 214, 195 (1968)], the
quasiclassical expression for the free energy of spin-singlet superconductor
has been suggested. Starting from the Luttinger-Ward formulation we derive the
Eilenberger free energy and find its generalization for superconductor or
superfluid with spin-triplet correlations. Besides ordinary superconductors
with various scattering mechanisms, the obtained free energy functional can be
used for systems with spin-triplet pairing such as superfluid $^3$He and
superconducting systems with spatially-inhomogeneous exchange field or
spin-orbit coupling. Using this general result we derive the simplified
expression for the free energy in the diffusive limit in terms of the
momentum-averaged propagators.


  A feasibility study is presented for the search of the lightest top squark in
a compressed scenario, where its mass is approximately equal to the sum of the
masses of the top quark and the lightest neutralino. The study is performed in
the final state of two b-jets, one lepton, large missing energy, and two
high-$E_{\rm T}$ jets with large separation in pseudo-rapidity, in opposite
hemispheres, and with large dijet mass. The LHC could discover compressed top
squarks with mass up to approximately 340 GeV (390 GeV) with an integrated
luminosity of 1000 ifb (3000 ifb).


  After a short elementary introduction to the exact renormalization group for
the effective action, I discuss a particular truncation of the hierarchy of
flow equations that allows for the determination of the full momentum of the
$n$-point functions. Applications are then briefly presented, to critical O(N)
models, to Bose-Einstein condensation and to finite temperature field theory.


  Granular media (GM) present locomotor challenges for terrestrial and
extraterrestrial devices because they can flow and solidify in response to
localized intrusion of wheels, limbs, and bodies. While the development of
airplanes and submarines is aided by understanding of hydrodynamics,
fundamental theory does not yet exist to describe the complex interactions of
locomotors with GM. In this paper, we use experimental, computational, and
theoretical approaches to develop a terramechanics for bio-inspired locomotion
in granular environments. We use a fluidized bed to prepare GM with a desired
global packing fraction, and use empirical force measurements and the Discrete
Element Method (DEM) to elucidate interaction mechanics during
locomotion-relevant intrusions in GM such as vertical penetration and
horizontal drag. We develop a resistive force theory (RFT) to account for more
complex intrusions. We use these force models to understand the locomotor
performance of two bio-inspired robots moving on and within GM.


  Nonabelian Fradkin-Vasiliev cubic interactions for dual-graviton-like gauge
fields with gravity and themselves are constructed in anti-de Sitter spacetime.
The Young diagrams of gauge potentials have shapes of 'tall-hooks', i.e. two
columns the second of height one.
  The underlying nonabelian algebra is a Clifford algebra with the anti-de
Sitter signature. We also discuss the universal enveloping realization of
higher-spin algebras, showing that there is a one-parameter family of algebras
compatible with unitarity, which is reminiscent of 3d deformed oscillators.


  We study the spectral characteristics of spin current nano-oscillators based
on the Pt/[Co/Ni] magnetic multilayer with perpendicular magnetic anisotropy.
By varying the applied magnetic field and current, both localized and
propagating spin wave modes of the oscillation are achieved. At small fields,
we observe an abrupt onset of the modulation sidebands. We use micromagnetic
simulations to identify this state as a dynamical magnetic skyrmion stabilized
in the active device region by spin current injection, whose current-induced
dynamics is accompanied by the gyrotropic motion of the core due to the skew
deflection. Our results demonstrate a practical route for controllable skyrmion
manipulation by spin current in magnetic thin films.


  We have investigated the role of the quantum size effects in the evaluation
of the force caused by electromagnetic vacuum fluctuations between ultra-thin
films, using the dielectric tensor derived from the particle in a box model.
Comparison with the results obtained by adopting a continuum dielectric model
shows that, for film thicknesses of 1-10 nm, the electron confinement causes
changes in the force intensity with respect to the isotropic plasma model which
range from 40% to few percent depending upon the film electron density and the
film separation. The calculated force shows quantum size oscillations, which
can be significant for film separation distances of several nanometers. The
role of electron confinement in reducing the large distance Casimir force is
discussed.


  Optical photothermal microscopy is a powerful, emerging method that overcomes
the diffraction limit in infrared hyperspectral imaging by utilizing a visible
probe laser beam to detect local temperature-induced modulation at the visible
diffraction limit. However, the spectral range of this technique has been
limited by the tuning range of infrared sources, which is generally restricted
to the fingerprint window with commercially available quantum cascade lasers.
In this work, ultra-broadband synchrotron infrared radiation was used for
infrared photothermal imaging and spectroscopy, spanning the entire
mid-infrared range. Both optical- and fluorescence-detected photothermal
modalities were performed, demonstrating improved spectral range when compared
to optical photothermal microscopy using commercial sources and improved
spatial resolution when compared to synchrotron micro-spectroscopy
measurements. Following these initial validation studies, synchrotron
Fourier-transform optical photothermal infrared spectroscopy (FT-OPTIR) in
combination with synchrotron micro-spectroscopy measurements were used to
differentiate cells in mouse brain tissue sections.


  We deal here with three metastable systems: 1{\textdegree}- the dowser
texture, 2{\textdegree}- supertwistedcholesterics and 3{\textdegree}-
hypotwisted cholesterics. We outline remarkable properties of tropisms of the
dowser texture stemming from its low symmetry and we show that, using setups
called Dowsons Colliders, nematic monopoles can be nucleated, set into motion
and brought into collisions in the dowser texture. Subsequently we point out
that nucleation of dislocation loops occurs in cholesteric layers compressed or
dilated between cylindrical mica sheets. Under compression, three modes of
nucleation of dislocation loops have been identified: individual, serial and
continuous. The serial mode generates dislocation nets made of L circular loops
connected by C radial crossing into superloops. Similar superloops can also be
generated under dilation. We analyse the topology of superloops in terms of the
theory of knots and point out they can be reduced into the unknot by
Reidemeister moves. In other words, superloops are multiply folded loops that
can be continuously unfolded.


  The Relativistic Heavy Ion Collider at Brookhaven National Laboratory
provides polarized proton beams for the investigation of the nucleon spin
structure. For polarimetry, carbon-proton and proton-proton scattering is used
in the Coulomb nuclear interference region at small momentum transfer ($-t$).
Fast polarization measurements of each beam are carried out with carbon fiber
targets at several times during an accelerator store. A polarized hydrogen gas
jet target is needed for absolute normalization over multiple stores, while the
target polarization is constantly monitored in a Breit-Rabi polarimeter. In
2005, the jet polarimeter has been used with both RHIC beams. We present
results from the jet polarimeter including a detailed analysis of background
contributions to asymmetries and to the beam polarization.


  Multimodal models like GPT4o and Gemini Flash are exceptional at inference
and summarization tasks, which approach human-level in performance. However, we
find that these models underperform compared to humans when asked to do very
specific 'reading and estimation' tasks, particularly in the context of visual
charts in business decks. This paper evaluates the accuracy of GPT 4o and
Gemini Flash-1.5 in answering straightforward questions about data on labeled
charts (where data is clearly annotated on the graphs), and unlabeled charts
(where data is not clearly annotated and has to be inferred from the X and Y
axis). We conclude that these models aren't currently capable of reading a deck
accurately end-to-end if it contains any complex or unlabeled charts. Even if a
user created a deck of only labeled charts, the model would only be able to
read 7-8 out of 15 labeled charts perfectly end-to-end. For full list of slide
deck figures visit https://www.repromptai.com/chat_bcg


  It is recently shown that a split-step quantum walk possesses a chiral
symmetry, and that a certain well-defined index can be naturally assigned to
it. The index is a well-defined Fredholm index if and only if the associated
unitary time-evolution operator has spectral gaps at both $+1$ and $-1.$ In
this paper we extend the existing index formula for the Fredholm case to
encompass the non-Fredholm case (i.e., gapless case). We make use of a natural
extension of the Fredholm index to the non-Fredholm case, known as the Witten
index. The aim of this paper is to fully classify the Witten index of the
split-step quantum walk by employing the spectral shift function for a rank one
perturbation of a fourth order difference operator. It is also shown in this
paper that the Witten index can take half-integer values in the non-Fredholm
case.


  Alfv\'enic modes in the current quench (CQ) stage of the tokamak disruption
have been observed in experiments. In DIII-D the excitation of these modes is
associated with the presence of high-energy runaway electrons, and a strong
mode excitation is often associated with the failure of RE plateau formation.
In this work we present results of self-consistent kinetic-MHD simulations of
RE-driven compressional Alfv\'en eigenmodes (CAEs) in DIII-D disruption
scenarios, providing an explanation of the CQ modes. Simulation results reveal
that high energy trapped REs can have resonance with the Alfv\'en mode through
their precession motion, and the resonance frequency is proportional to the
energy of REs. The mode frequencies and their relationship with the RE energy
are consistent with experimental observation. The perturbed magnetic fields
from the modes can lead to spatial diffusion of runaway electrons including the
nonresonant passing ones, thus providing the theoretical basis for a potential
approach for runaway electron mitigation.


  Bayesian optimal design of experiments is a well-established approach to
planning experiments. Briefly, a probability distribution, known as a
statistical model, for the responses is assumed which is dependent on a vector
of unknown parameters. A utility function is then specified which gives the
gain in information for estimating the true value of the parameters using the
Bayesian posterior distribution. A Bayesian optimal design is given by
maximising the expectation of the utility with respect to the joint
distribution given by the statistical model and prior distribution for the true
parameter values. The approach takes account of the experimental aim via
specification of the utility and of all assumed sources of uncertainty via the
expected utility. However, it is predicated on the specification of the
statistical model. Recently, a new type of statistical inference, known as
Gibbs (or General Bayesian) inference, has been advanced. This is
Bayesian-like, in that uncertainty on unknown quantities is represented by a
posterior distribution, but does not necessarily rely on specification of a
statistical model. Thus the resulting inference should be less sensitive to
misspecification of the statistical model. The purpose of this paper is to
propose Gibbs optimal design: a framework for optimal design of experiments for
Gibbs inference. The concept behind the framework is introduced along with a
computational approach to find Gibbs optimal designs in practice. The framework
is demonstrated on exemplars including linear models, and experiments with
count and time-to-event responses.


  Active centres and hot spots of proteins have a paramount importance in
enzyme action, protein complex formation and drug design. Recently a number of
publications successfully applied the analysis of residue networks to predict
active centres in proteins. Most real-world networks show a number of
properties, such as small-worldness or scale-free degree distribution, which
are rather general features of networks, from molecules to society at large.
Using analogy I propose that existing findings and methodology already enable
us to detect active centres in cells, and can be expanded to social networks
and ecosystems. Members of these active centres are termed here as creative
elements of their respective networks, which may help them to survive
unprecedented, novel challenges, and play a key role in the development,
survival and evolvability of complex systems.


  This set of notes re-proves known results on weighted automata (over a field,
also known as multiplicity automata). The text offers a unified view on
theorems and proofs that have appeared in the literature over decades and were
written in different styles and contexts. None of the results reported here are
claimed to be new. The content centres around fundamentals of equivalence and
minimization, with an emphasis on algorithmic aspects. The presentation is
minimalistic. No attempt has been made to motivate the material. Weighted
automata are viewed from a linear-algebra angle. As a consequence, the proofs,
which are meant to be succinct, but complete and almost self-contained, rely
mainly on elementary linear algebra.


  We present a feasibility study of a simultaneous sub-percent extraction of
the weak charge and the weak radius of the ${}^{12}$C nucleus using
parity-violating electron scattering, based on a largely model-independent
assessment of the uncertainties. The corresponding measurement is considered to
be carried out at the future MESA facility in Mainz with $E_{\rm beam} = 155$
MeV. We find that a combination of a $0.3\%$ precise measurement of the
parity-violating asymmetry at forward angles with a $10\%$ measurement at
backward angles will allow to determine the weak charge and the weak radius of
${}^{12}$C with $0.4\%$ and $0.5\%$ precision, respectively. These values could
be improved to $0.3\%$ and $0.2\%$ for a $3\%$ backward measurement. This
experimental program will have impact on precision low-energy tests in the
electroweak sector and nuclear structure.


  Classifying human cognitive states from behavioral and physiological signals
is a challenging problem with important applications in robotics. The problem
is challenging due to the data variability among individual users, and sensor
artefacts. In this work, we propose an end-to-end framework for real-time
cognitive workload classification with mixture Hyper Long Short Term Memory
Networks, a novel variant of HyperNetworks. Evaluating the proposed approach on
an eye-gaze pattern dataset collected from simulated driving scenarios of
different cognitive demands, we show that the proposed framework outperforms
previous baseline methods and achieves 83.9\% precision and 87.8\% recall
during test. We also demonstrate the merit of our proposed architecture by
showing improved performance over other LSTM-based methods.


  Spinors are lightlike. How do they combine to make massive particles? We
visit the zoo of Lagrangian singularities, or caustics, in spacetime
projections from spin space- the phase space of lightlike, 8- spinor flows. We
find that the species living there are the elementary particles. Codimension
J=(1,2,3,4) phase singularities - vortex lines, sheets, tubes, and knots, are
classified by the Coxeter groups generated by multiplicity s reflections: "mass
scatterings" off the vacuum spinors, that keep chiral pairs of matter envelopes
confined to a timelike world tube, endowing a bispinor particle with mass.
Using the volume in spin space as the action, the particle masses emerge in
terms of the multiplicities, s: the number of null zigzags needed to close a
cycle of mass scatterings. These mass values (calculated to lowest order in the
vacuum intensity) are within a few percent of the observed masses for the
leptons (J=1) and hadrons (J=3) ; but are up to 25 percent off for the mesons
(J=2).


  This note is a survey of the enumerative geometry of rational curves on
Calabi-Yau threefolds, based on a talk given by the author at the May 1991
Workshop on Mirror Symmetry at MSRI. An earlier version appeared in "Essays on
Mirror Manifolds"; this version corrects typographical errors that appeared in
print, gives a brief update of related progress during the last two years in
the form of footnotes, and has more and updated references. (To appear in the
second edition of Essays on Mirror Manifolds.)


  There has been recently a growth of interest in developing the current
machine-readable Web towards the next generation of machine-understandable Web
- Semantic Web. The development of the Web to a global business was reasonably
fast, whereas Semantic Web development has taken time from a plan to be used as
the mainstream Web. It is also important to note that the use of Semantic Web
would only be successful in small technologies. However, the goal of Semantic
Web is to be used in big technologies and to be the mainstream Web. Some
challenges may impede make further progress of Semantic Web. In this review
paper, an overview of the current status and future needs of Semantic Web will
be presented. Specifically, the challenges and needs of Semantic Web in the
hope of shedding some light on the adoption or infusion of Semantic Web in the
future will be discussed. Then, a critical evaluation of these challenges and
needs will be presented. Semantic Web has a clear vision. It is moving, in line
with this vision, towards overcoming the challenges and usability in real world
applications.


  We describe a two-stage mechanism that fully implements the set of efficient
outcomes in two-agent environments with quasi-linear utilities. The mechanism
asks one agent to set prices for each outcome, and the other agent to make a
choice, paying the corresponding price: Price \& Choose. We extend our
implementation result in three main directions: an arbitrary number of players,
non-quasi linear utilities, and robustness to max-min behavior. Finally, we
discuss how to reduce the payoff inequality between players while still
achieving efficiency.


  In their fundamental work, B. Dubrovin and Y. Zhang, generalizing the
Virasoro equations for the genus 0 Gromov-Witten invariants, proved the
Virasoro equations for a descendent potential in genus 0 of an arbitrary
conformal Frobenius manifold. More recently, a remarkable system of partial
differential equations, called the open WDVV equations, appeared in the work of
A. Horev and J. P. Solomon. This system controls the genus 0 open Gromov-Witten
invariants. In our paper, for an arbitrary solution of the open WDVV equations,
satisfying a certain homogeneity condition, we construct a descendent potential
in genus 0 and prove an open analog of the Virasoro equations. We also present
conjectural open Virasoro equations in all genera and discuss some examples.


  Dropout and other feature noising schemes have shown promising results in
controlling over-fitting by artificially corrupting the training data. Though
extensive theoretical and empirical studies have been performed for generalized
linear models, little work has been done for support vector machines (SVMs),
one of the most successful approaches for supervised learning. This paper
presents dropout training for linear SVMs. To deal with the intractable
expectation of the non-smooth hinge loss under corrupting distributions, we
develop an iteratively re-weighted least square (IRLS) algorithm by exploring
data augmentation techniques. Our algorithm iteratively minimizes the
expectation of a re-weighted least square problem, where the re-weights have
closed-form solutions. The similar ideas are applied to develop a new IRLS
algorithm for the expected logistic loss under corrupting distributions. Our
algorithms offer insights on the connection and difference between the hinge
loss and logistic loss in dropout training. Empirical results on several real
datasets demonstrate the effectiveness of dropout training on significantly
boosting the classification accuracy of linear SVMs.


  We present the library Collier for the numerical evaluation of one-loop
scalar and tensor integrals in perturbative relativistic quantum field
theories. The code provides numerical results for arbitrary tensor and scalar
integrals for scattering processes in general quantum field theories. For
tensor integrals either the coefficients in a covariant decomposition or the
tensor components themselves are provided. Collier supports complex masses,
which are needed in calculations involving unstable particles. Ultraviolet and
infrared singularities are treated in dimensional regularization. For soft and
collinear singularities mass regularization is available as an alternative.


  We consider the energy of the filled quasiparticle's Fermi sea of a
macroscopic superconducting ring threaded by an hc/2e-vortex, when the material
of the ring is of an unconventional pairing symmetry. The energy relative to
the one for the hc/e-vortex configuration is finite, positive, and inversely
proportional to ring's inner radius. We argue that the existence of this energy
in unconventional superconductors removes the commonly assumed degeneracy
between the odd and the even vortices, with the loss of the concomitant hc/2e
periodicity in external magnetic field as a consequence. This macroscopic
quantum effect should be observable in nanosized unconventional superconductors
with a small phase stiffness, such as deeply underdoped YBCO with Tc < 5K.


  Noisy label learning aims to learn robust networks under the supervision of
noisy labels, which plays a critical role in deep learning. Existing work
either conducts sample selection or label correction to deal with noisy labels
during the model training process. In this paper, we design a simple yet
effective sample selection framework, termed Two-Stream Sample Distillation
(TSSD), for noisy label learning, which can extract more high-quality samples
with clean labels to improve the robustness of network training. Firstly, a
novel Parallel Sample Division (PSD) module is designed to generate a certain
training set with sufficient reliable positive and negative samples by jointly
considering the sample structure in feature space and the human prior in loss
space. Secondly, a novel Meta Sample Purification (MSP) module is further
designed to mine adequate semi-hard samples from the remaining uncertain
training set by learning a strong meta classifier with extra golden data. As a
result, more and more high-quality samples will be distilled from the noisy
training set to train networks robustly in every iteration. Extensive
experiments on four benchmark datasets, including CIFAR-10, CIFAR-100,
Tiny-ImageNet, and Clothing-1M, show that our method has achieved
state-of-the-art results over its competitors.


  The analysis of digitized historical manuscripts is typically addressed by
paleographic experts. Writer identification refers to the classification of
known writers while writer retrieval seeks to find the writer by means of image
similarity in a dataset of images. While automatic writer
identification/retrieval methods already provide promising results for many
historical document types, papyri data is very challenging due to the fiber
structures and severe artifacts. Thus, an important step for an improved writer
identification is the preprocessing and feature sampling process. We
investigate several methods and show that a good binarization is key to an
improved writer identification in papyri writings. We focus mainly on writer
retrieval using unsupervised feature methods based on traditional or
self-supervised-based methods. It is, however, also comparable to the state of
the art supervised deep learning-based method in the case of writer
classification/re-identification.


  We present CoVR, a novel robotic interface providing strong kinesthetic
feedback (100 N) in a room-scale VR arena. It consists of a physical column
mounted on a 2D Cartesian ceiling robot (XY displacements) with the capacity of
(1) resisting to body-scaled users' actions such as pushing or leaning; (2)
acting on the users by pulling or transporting them as well as (3) carrying
multiple potentially heavy objects (up to 80kg) that users can freely
manipulate or make interact with each other. We describe its implementation and
define a trajectory generation algorithm based on a novel user intention model
to support non-deterministic scenarios, where the users are free to interact
with any virtual object of interest with no regards to the scenarios' progress.
A technical evaluation and a user study demonstrate the feasibility and
usability of CoVR, as well as the relevance of whole-body interactions
involving strong forces, such as being pulled through or transported.


  Recently, we suggested that low-energy beta-beam neutrinos can be very useful
for the study of supernova neutrino interactions. In this paper, we examine the
use of a such experiment for the analysis of a supernova neutrino signal. Since
supernova neutrinos are oscillating, it is very likely that the terrestrial
spectrum of supernova neutrinos of a given flavor will not be the same as the
energy distribution with which these neutrinos were first emitted. We
demonstrate the efficacy of the proposed method for untangling multiple
neutrino spectra. This is an essential feature of any model aiming at gaining
information about the supernova mechanism, probing proto-neutron star physics,
and understanding supernova nucleosynthesis, such as the neutrino process and
the r-process. We also consider the efficacy of different experimental
approaches including measurements at multiple beam energies and detector
configurations.


  The discrepancy of a binary string refers to the maximum (absolute)
difference between the number of ones and the number of zeroes over all
possible substrings of the given binary string. We provide an investigation of
the discrepancy of known simple constructions of de Bruijn sequences.
Furthermore, we demonstrate constructions that attain the lower bound of
$\Theta(n)$ and a new construction that attains the previously known upper
bound of $\Theta(\frac{2^n}{\sqrt{n}})$. This extends the work of Cooper and
Heitsch~[\emph{Discrete Mathematics}, 310 (2010)].


  We consider the Activated Random Walk model in any dimension with any sleep
rate and jump distribution and ergodic initial state. We show that the
stabilization properties depend only on the average density of particles,
regardless of how they are initially located on the lattice.


  It is shown how the generating functional method of De Dominicis can be used
to solve the dynamics of the original version of the minority game (MG), in
which agents observe real as opposed to fake market histories. Here one again
finds exact closed equations for correlation and response functions, but now
these are defined in terms of two connected effective non-Markovian stochastic
processes: a single effective agent equation similar to that of the `fake'
history models, and a second effective equation for the overall market bid
itself (the latter is absent in `fake' history models). The result is an exact
theory, from which one can calculate from first principles both the persistent
observables in the MG and the distribution of history frequencies.


  Various convergence results for the Bergman kernel of the Hilbert space of
all polynomials in \C^{n} of total degree at most k, equipped with a weighted
norm, are obtained. The weight function is assumed to be C^{1,1}, i.e. it is
differentiable and all of its first partial derivatives are locally Lipshitz
continuous. The convergence is studied in the large k limit and is expressed in
terms of the global equilibrium potential associated to the weight function, as
well as in terms of the Monge-Ampere measure of the weight function itself on a
certain set. A setting of polynomials associated to a given Newton polytope,
scaled by k, is also considered. These results apply directly to the study of
the distribution of zeroes of random polynomials and of the eigenvalues of
random normal matrices.


  We use microscopic density functional theory to study filling transitions in
systems with long-ranged wall-fluid and short-ranged fluid-fluid forces
occurring in a right-angle wedge. By changing the strength of the wall-fluid
interaction we can induce both wetting and filling transitions over a wide
range of temperatures and study the order of these transitions. At low
temperatures we find that both wetting and filling transitions are first-order
in keeping with predictions of simple local effective Hamiltonian models.
However close to the bulk critical point the filling transition is observed to
be continuous even though the wetting transition remains first-order and the
wetting binding potential still exhibits a small activation barrier. The
critical singularities for adsorption for the continuous filling transitions
depend on whether retarded or non-retarded wall-fluid forces are present and
are in excellent agreement with predictions of effective Hamiltonian theory
even though the change in the order of the transition was not anticipated.


  This letter proposes a novel dual user selection scheme for uplink
transmission with multiple users, where a jamming user and a served user are
jointly selected to improve the secrecy performance. Specifically, the jamming
user transmits jamming signal with a certain rate, so that the base station
(BS) can decode the jamming signal before detecting the secret information
signal. By carefully selecting the jamming user and the served user, it makes
the eavesdropper decode the jamming signal with a low probability meanwhile the
BS can achieve a high receive signal-to-noise ratio (SNR). Therefore, the
uplink transmission achieves the dual secrecy improvement by jamming and
scheduling. It is shown that the proposed scheme can significantly improve the
security of the uplink transmission.


  Web request query strings (queries), which pass parameters to the referenced
resource, are always manipulated by attackers to retrieve sensitive data and
even take full control of victim web servers and web applications. However,
existing malicious query detection approaches in the current literature cannot
cope with changing web attacks with constant detection models. In this paper,
we propose AMODS, an adaptive system that periodically updates the detection
model to detect the latest unknown attacks. We also propose an adaptive
learning strategy, called SVM HYBRID, leveraged by our system to minimize
manual work. In the evaluation, an up-to-date detection model is trained on a
ten-day query dataset collected from an academic institute's web server logs.
Our system outperforms existing web attack detection methods, with an F-value
of 94.79% and FP rate of 0.09%. The total number of malicious queries obtained
by SVM HYBRID is 2.78 times that by the popular Support Vector Machine Adaptive
Learning (SVM AL) method. The malicious queries obtained can be used to update
the Web Application Firewall (WAF) signature library.


  Commonsense knowledge (CSK) about concepts and their properties is useful for
AI applications such as robust chatbots. Prior works like ConceptNet, TupleKB
and others compiled large CSK collections, but are restricted in their
expressiveness to subject-predicate-object (SPO) triples with simple concepts
for S and monolithic strings for P and O. Also, these projects have either
prioritized precision or recall, but hardly reconcile these complementary
goals. This paper presents a methodology, called Ascent, to automatically build
a large-scale knowledge base (KB) of CSK assertions, with advanced
expressiveness and both better precision and recall than prior works. Ascent
goes beyond triples by capturing composite concepts with subgroups and aspects,
and by refining assertions with semantic facets. The latter are important to
express temporal and spatial validity of assertions and further qualifiers.
Ascent combines open information extraction with judicious cleaning using
language models. Intrinsic evaluation shows the superior size and quality of
the Ascent KB, and an extrinsic evaluation for QA-support tasks underlines the
benefits of Ascent. A web interface, data and code can be found at
https://ascent.mpi-inf.mpg.de/.


  In \cite{BKN} the authors initiated a study of the representation theory of
classical Lie superalgebras via a cohomological approach. Detecting subalgebras
were constructed and a theory of support varieties was developed. The dimension
of a detecting subalgebra coincides with the defect of the Lie superalgebra and
the dimension of the support variety for a simple supermodule was conjectured
to equal the atypicality of the supermodule. In this paper the authors compute
the support varieties for Kac supermodules for Type I Lie superalgebras and the
simple supermodules for $\mathfrak{gl}(m|n)$. The latter result verifies our
earlier conjecture for $\mathfrak{gl}(m|n)$. In our investigation we also
delineate several of the major differences between Type I versus Type II
classical Lie superalgebras. Finally, the connection between atypicality,
defect and superdimension is made more precise by using the theory of support
varieties and representations of Clifford superalgebras.


  In this work, we consider tilings of the Hamming cube and look for metrics
which turn the tilings into a perfect code. We consider the family of metrics
which are determined by a weight and are compatible with the support of vectors
(TS-metrics). We determine which of the tilings with small tiles or high rank
can be a perfect code for some TS-metric and we characterize all such metrics.
Finally, we show some procedures to obtain new perfect codes (relatively to
TS-metrics) out of existing ones.


  Graph convolutional neural network (GCN) has effectively boosted the
multi-label image recognition task by introducing label dependencies based on
statistical label co-occurrence of data. However, in previous methods, label
correlation is computed based on statistical information of data and therefore
the same for all samples, and this makes graph inference on labels insufficient
to handle huge variations among numerous image instances. In this paper, we
propose an instance-aware graph convolutional neural network (IA-GCN) framework
for multi-label classification. As a whole, two fused branches of sub-networks
are involved in the framework: a global branch modeling the whole image and a
region-based branch exploring dependencies among regions of interests (ROIs).
For label diffusion of instance-awareness in graph convolution, rather than
using the statistical label correlation alone, an image-dependent label
correlation matrix (LCM), fusing both the statistical LCM and an individual one
of each image instance, is constructed for graph inference on labels to inject
adaptive information of label-awareness into the learned features of the model.
Specifically, the individual LCM of each image is obtained by mining the label
dependencies based on the scores of labels about detected ROIs. In this
process, considering the contribution differences of ROIs to multi-label
classification, variational inference is introduced to learn adaptive scaling
factors for those ROIs by considering their complex distribution. Finally,
extensive experiments on MS-COCO and VOC datasets show that our proposed
approach outperforms existing state-of-the-art methods.


  We investigate hypothesis testing in nonparametric additive models estimated
using simplified smooth backfitting (Huang and Yu, Journal of Computational and
Graphical Statistics, \textbf{28(2)}, 386--400, 2019). Simplified smooth
backfitting achieves oracle properties under regularity conditions and provides
closed-form expressions of the estimators that are useful for deriving
asymptotic properties. We develop a generalized likelihood ratio (GLR) and a
loss function (LF) based testing framework for inference. Under the null
hypothesis, both the GLR and LF tests have asymptotically rescaled chi-squared
distributions, and both exhibit the Wilks phenomenon, which means the scaling
constants and degrees of freedom are independent of nuisance parameters. These
tests are asymptotically optimal in terms of rates of convergence for
nonparametric hypothesis testing. Additionally, the bandwidths that are
well-suited for model estimation may be useful for testing. We show that in
additive models, the LF test is asymptotically more powerful than the GLR test.
We use simulations to demonstrate the Wilks phenomenon and the power of these
proposed GLR and LF tests, and a real example to illustrate their usefulness.


  Within Einstein-Hilbert gravity, higher derivatives and a scalar field as
representative of matter different versions of tensorlike quantities are
discussed.The concepts of improvement and superpotential help to understand the
details of their construction and meaning. On this basis it is claimed that the
higher derivatives which are necessary for defining higher orders in
perturbation theory donot ruin the physical content of the model.


  Nucleosynthesis beyond Fe poses additional challenges not encountered when
studying astrophysical processes involving light nuclei. Generally higher
temperatures and nuclear level densities lead to stronger contributions of
transitions on excited target states. This may prevent cross section
measurements to determine stellar reaction rates and theory contributions
remain important. Furthermore, measurements often are not feasible in the
astrophysically relevant energy range. Sensitivity analysis allows not only to
determine the contributing nuclear properties but also is a handy tool for
experimentalists to interpret the impact of their data on predicted cross
sections and rates. It can also speed up future input variation studies of
nucleosynthesis by simplifying an intermediate step in the full calculation
sequence. Large-scale predictions of sensitivities and ground-state
contributions to the stellar rates are presented, allowing an estimate of how
well rates can be directly constrained by experiment. The reactions
185W(n,gamma) and 186W(gamma,n) are discussed as application examples. Studies
of uncertainties in abundances predicted in nucleosynthesis simulations rely on
the knowledge of reaction rate errors. An improved treatment of uncertainty
analysis is presented as well as a recipe for combining experimental data and
theory to arrive at a new reaction rate and its uncertainty. As an example, it
is applied to neutron capture rates for the s-process, leading to larger
uncertainties than previously assumed.


  Zinc sulfide is a wide bandgap semiconductor which crystallizes in either the
wurtzite modification (a-ZnS), the zincblende modification (b-ZnS) or as one of
several similar tetrahedrally coordinated polytypes. In this work, we report a
photoluminescence study of different samples of isotopically pure b-ZnS
crystals, and crystals with the natural isotopic abundances, at 15 and 77 K.
The derivatives of the free and bound exciton energies on isotopic mass have
been obtained. They allow us to estimate the contribution of the zinc and
sulfur vibrations to the bandgap renormalization energy by electron-phonon
interaction. A two-oscillator model based on the zinc and sulfur
renormalization energies has been used to account for the temperature
dependence of the bandgap energy in ZnS. The results are compared with those
found for other tetrahedrally coordinated semiconductors.


  Let $G$ be a connected graph with vertex set
$V(G)=\{v_{1},v_{2},...,v_{n}\}$. The distance matrix $D(G)=(d_{ij})_{n\times
n}$ is the matrix indexed by the vertices of $G,$ where $d_{ij}$ denotes the
distance between the vertices $v_{i}$ and $v_{j}$. Suppose that
$\lambda_{1}(D)\geq\lambda_{2}(D)\geq\cdots\geq\lambda_{n}(D)$ are the distance
spectrum of $G$. The graph $G$ is said to be determined by its $D$-spectrum if
with respect to the distance matrix $D(G)$, any graph having the same spectrum
as $G$ is isomorphic to $G$. In this paper, we give the distance characteristic
polynomial of some graphs with small diameter, and also prove that these graphs
are determined by their $D$-spectra.


  Learning has propelled the cutting edge of performance in robotic control to
new heights, allowing robots to operate with high performance in conditions
that were previously unimaginable. The majority of the work, however, assumes
that the unknown parts are static or slowly changing. This limits them to
static or slowly changing environments. However, in the real world, a robot may
experience various unknown conditions. This paper presents a method to extend
an existing single mode GP-based safe learning controller to learn an
increasing number of non-linear models for the robot dynamics. We show that
this approach enables a robot to re-use past experience from a large number of
previously visited operating conditions, and to safely adapt when a new and
distinct operating condition is encountered. This allows the robot to achieve
safety and high performance in an large number of operating conditions that do
not have to be specified ahead of time. Our approach runs independently from
the controller, imposing no additional computation time on the control loop
regardless of the number of previous operating conditions considered. We
demonstrate the effectiveness of our approach in experiment on a 900\,kg ground
robot with both physical and artificial changes to its dynamics. All of our
experiments are conducted using vision for localization.


  Earth is constantly struck by radiation coming from the interstellar medium.
The very low energy end of the spectrum is shielded by the geomagnetic field
but charged particles with energies higher than the geomagnetic cutoff will
penetrate the atmosphere and are likely to interact, giving rise to secondary
particles. Some astrophysical events, such as gamma ray bursts and supernovae,
when happening at short distances, may affect the planet's biosphere due to the
temporary enhanced radiation flux. Muons are abundantly produced by high energy
cosmic rays in the Earth's atmosphere. These particles, due to their low cross
section, are able to penetrate deep underground and underwater, with the
possibility of affecting biological niches normally considered shielded from
radiation. We investigate the interaction of muons produced by high energy
cosmic rays on Earth's atmosphere using the Geant4 toolkit. We analyze
penetration power in water and crust and also the interaction effects within
bacteria-like material according to particle type and energy, and notice the
possibility of off-track damage due to secondary particles.


  The quality of the inverse approach in electroencephalography (EEG) source
analysis is - among other things - depending on the accuracy of the forward
modeling approach, i.e., the simulation of the electric potential for a known
dipole source in the brain. Here, we use multilayer sphere modeling scenarios
to investigate the performance of three different finite element method (FEM)
based EEG forward approaches - subtraction, Venant and partial integration - in
the presence of tissue conductivity anisotropy in the source space. In our
studies, the effect of anisotropy on the potential is related to model errors
when ignoring anisotropy and to numerical errors, convergence behavior and
computational speed of the different FEM approaches. Three different source
space anisotropy models that best represent adult, child and premature baby
volume conduction scenarios, are used. Major findings of the study include (1)
source space conductivity anisotropy has a significant effect on electric
potential computation: The effect increases with increasing anisotropy ratio;
(2) with numerical errors far below anisotropy effects, all three FEM
approaches are able to model source space anisotropy accordingly, with the
Venant approach offering the best compromise between accuracy and computational
speed; (3) FE meshes have to be fine enough in the subdomain between the source
and the sensors that capture its main activity. We conclude that, especially
for the analysis of cortical development, but also for more general
applications using EEG source analysis techniques, source space conductivity
anisotropy should be modeled and the FEM Venant approach is an appropriate
method.


  We study a Stackelberg game between one attacker and one defender in a
configurable environment. The defender picks a specific environment
configuration. The attacker observes the configuration and attacks via
Reinforcement Learning (RL trained against the observed environment). The
defender's goal is to find the environment with minimum achievable reward for
the attacker. We apply Evolutionary Diversity Optimization (EDO) to generate
diverse population of environments for training. Environments with clearly high
rewards are killed off and replaced by new offsprings to avoid wasting training
time. Diversity not only improves training quality but also fits well with our
RL scenario: RL agents tend to improve gradually, so a slightly worse
environment earlier on may become better later. We demonstrate the
effectiveness of our approach by focusing on a specific application, Active
Directory (AD). AD is the default security management system for Windows domain
networks. AD environment describes an attack graph, where nodes represent
computers/accounts/etc., and edges represent accesses. The attacker aims to
find the best attack path to reach the highest-privilege node. The defender can
change the graph by removing a limited number of edges (revoke accesses). Our
approach generates better defensive plans than the existing approach and scales
better.


  We describe derivations and automorphisms of infinite tensor products of
matrix algebras. Using this description we show that for a
countable--dimensional locally matrix algebra $A$ over a field $\mathbb{F}$ the
dimension of the Lie algebra of outer derivations of $A$ and the order of the
group of outer automorphisms of $A$ are both equal to
$|\mathbb{F}|^{\aleph_0},$ where $|\mathbb{F}|$ is the cardinality of the field
$\mathbb{F}.$


  In the present work, we calculate the conductance through a single quantum
dot weakly coupled to metallic contacts. We use the spin-1/2 Anderson model to
describe the quantum dot, while considering a finite Coulomb repulsion. We
solve the interacting system using the non-crossing-approximation (NCA) and the
one-crossing approximation (OCA). We obtain the linear response conductance as
a function of temperature and energy position of the localized level. From the
comparison of both approximations we extract the role of the vertex
corrections, which are introduced in the OCA calculations and neglected in the
NCA scheme. As a function of the energy position, we observe that the diagrams
omitted within NCA are really important for appropriately describing transport
phenomena in Kondo systems as well as in the mixed valence regime. On the other
hand, as a function of temperature, the corrections introduced by OCA partly
recover the universal scaling properties known from numerical approaches such
as the Numerical Renormalization Group(NRG).


  A simple method is proposed to prepare conveniently the effective pure state
|00...0><0...00| with any number of qubits in a quantum ensemble. The
preparation is based on the temporal averaging (Knill, Chuang, and Laflamme,
Phys.Rev.A 57, 3348(1998)). The quantum circuit to prepare the effective pure
state is designed in a unified and systematical form and is explicitly
decomposed completely into a product of a series of one-qubit quantum gates and
the two-qubit diagonal quantum gates. The preparation could be programmed and
implemented conveniently on an NMR quantum computer.


  J. Kigami has laid the foundations of what is now known as analysis on
fractals, by allowing the construction of an operator of the same nature of the
Laplacian, defined locally, on graphs having a fractal character. The
Sierpinski gasket stands out of the best known example. It has, since then,
been taken up, developed and popularized by R. S. Strichartz.
  The Laplacian is obtained through a weak formulation, obtained by means of
Dirichlet forms, built by induction on a sequence of graphs that converges
towards the considered domain. It is these Dirichlet forms that enable one to
obtain energy forms on this domain.
  Yet, things are not that simple. If, for domains like the Sierpinski gasket,
the Laplacian is obtained in a quite natural way, one must bear in mind that
Dirichlet forms solely depend on the topology of the domain, and not of its
geometry. Which means that, if one aims at building a Laplacian on a fractal
domain, the topology of which is the same as, for instance, a line segment, one
has to find a way of taking account a very specific geometry. We came across
that problem in our work on the graph of the Weierstrass function The solution
was thus to consider energy forms more sophisticated than classical ones, by
means of normalization constants that could, not only bear the topology, but,
also, the very specific geometry of, from now on, we will call W-curves.
  We presently aim at investigating the links between energy forms and
geometry. We have chosen to consider fractal curves, specifically, the
Sierpi\'nski arrowhead curve, the limit of which is the Sierpi\'nski gasket.
Does one obtain the same Laplacian as for the triangle ? The question appears
as worth to be investigated.


  We prove that the stress tensor, tau^{ab}, of a molecular system with
arbitrary, short-range interactions can be point-wisely expressed as the
functional derivative of the partition function with respect to the local
deformation tensor. In this approach the set of components of tau^{ab} has a
simple interpretation as the set of Lagrangian multipliers which need to be
introduced to enforce the conditions relating point particle displacements to
the body local deformation tensor. The question of the non-uniqueness of the
formula for tau^{ab} is discussed.


  Arabic is a widely-spoken language with a rich and long history spanning more
than fourteen centuries. Yet existing Arabic corpora largely focus on the
modern period or lack sufficient diachronic information. We develop a
large-scale, historical corpus of Arabic of about 1 billion words from diverse
periods of time. We clean this corpus, process it with a morphological
analyzer, and enhance it by detecting parallel passages and automatically
dating undated texts. We demonstrate its utility with selected case-studies in
which we show its application to the digital humanities.


  We report a record high superconducting transition temperature ($T_{\rm c}$)
up to 23.6 K under high pressure in the elemental metal Ti, one of the top ten
most abundant elements in Earth's crust. The $T_{\rm c}$ increases
monotonically from 2.3 K at 40.3 GPa to 23.6 K at 144.9 GPa, which surpasses
all known records from elemental metals reported so far. With further
compression, a robust $T_{\rm c}$ of ~23 K is observed between 144.9 and 183
GPa in the $\delta$-Ti phase. The pressure-dependent $T_{\rm c}$ can be well
described by the conventional electron-phonon coupling (EPC) mechanism. Density
Functional Theory calculations show the Fermi nesting and the phonon softening
of optical branches at the $\gamma$-Ti to $\delta$-Ti phase transition pressure
enhance EPC, which results in the record high $T_{\rm c}$. We attribute the
robust superconductivity in $\delta$-Ti to the apparent robustness of its
strong EPC against lattice compression. These results provide new insight into
exploring new high-$T_{\rm c}$ elemental metals and Ti-based superconducting
alloys.


  We present a dequantization procedure based on a variational approach whereby
quantum fluctuations latent in the quantum momentum are suppressed. This is
done by adding generic local deformations to the quantum momentum operator
which give rise to a deformed kinetic term quantifying the amount of
``fuzzyness'' caused by such fluctuations. Considered as a functional of such
deformations, the deformed kinetic term is shown to possess a unique minimum
which is seen to be the classical kinetic energy. Furthermore, we show that
extremization of the associated deformed action functional introduces an
essential nonlinearity to the resulting field equations which are seen to be
the classical Hamilton-Jacobi and continuity equations. Thus, a variational
procedure determines the particular deformation that has the effect of
suppressing the quantum fluctuations, resulting in dequantization of the
system.


  The cross section of the process $e^{+} e^{-} \rightarrow K^{+} K^{-}$ is
measured at a number of center-of-mass energies $\sqrt{s}$ from 2.00 to 3.08
GeV with the BESIII detector at the Beijing Electron Positron Collider
(BEPCII). The results provide the best precision achieved so far. A resonant
structure around 2.2 GeV is observed in the cross section line shape. A
Breit-Wigner fit yields a mass of $M=2239.2 \pm 7.1 \pm 11.3$~and a width of
$\Gamma=139.8\pm12.3\pm20.6$ MeV, where the first uncertainties are statistical
and the second ones are systematic. In addition, the time-like electromagnetic
form factor of the kaon is determined at the individual center-of-mass energy
points.


  In this paper, we give a new lower bound for the eigenvalues of the Dirac
operator on a compact spin manifold. This estimate is motivated by the fact
that in its limiting case a skew-symmetric tensor (see Equation \eqref{eq:16})
appears that can be identified geometrically with the O'Neill tensor of a
Riemannian flow, carrying a transversal parallel spinor. The Heisenberg group
which is a fibration over the torus is an example of this case. Sasakian
manifolds are also considered as particular examples of Riemannian flows.
Finally, we characterize the 3-dimensional case by a solution of the Dirac
equation


  In this work, we present a new paradigm, called 4D-StOP, to tackle the task
of 4D Panoptic LiDAR Segmentation. 4D-StOP first generates spatio-temporal
proposals using voting-based center predictions, where each point in the 4D
volume votes for a corresponding center. These tracklet proposals are further
aggregated using learned geometric features. The tracklet aggregation method
effectively generates a video-level 4D scene representation over the entire
space-time volume. This is in contrast to existing end-to-end trainable
state-of-the-art approaches which use spatio-temporal embeddings that are
represented by Gaussian probability distributions. Our voting-based tracklet
generation method followed by geometric feature-based aggregation generates
significantly improved panoptic LiDAR segmentation quality when compared to
modeling the entire 4D volume using Gaussian probability distributions. 4D-StOP
achieves a new state-of-the-art when applied to the SemanticKITTI test dataset
with a score of 63.9 LSTQ, which is a large (+7%) improvement compared to
current best-performing end-to-end trainable methods. The code and pre-trained
models are available at: https://github.com/LarsKreuzberg/4D-StOP.


  The general form of the solutions of the Kac--Bernstein functional equation
$$ f(x+y)g(x-y)=f(x)f(y)g(x)g(-y), \ x, y\in X, $$ on an arbitrary Abelian
group $X$ in the class of positive functions is obtained. We also study the
solutions of this equation in the class of complex-valued functions that do not
vanish and satisfy the Hermitian condition.


  The large interest in chiral magnetic structures for realization of nanoscale
magnetic storage or logic devices has necessitated methods which can quantify
magnetic interactions at the atomic scale. To overcome the limitations of the
typically used current-based sensing of atomic-scale exchange interactions, a
force-based detection scheme is highly advantageous. Here, we quantify the
atomic-scale exchange force field between a ferromagnetic tip and a cycloidal
spin spiral using our developed combination of current and exchange force
detection. Compared to the surprisingly weak spin polarization, the exchange
force field is more sensitive to atomic-scale variations in the magnetization.
First-principles calculations reveal that the measured atomic-scale variations
in the exchange force originate from different contributions of direct and
indirect (Zener) type exchange mechanisms, depending on the chemical tip
termination. Our work opens the perspective of quantifying different exchange
mechanisms of chiral magnetic structures with atomic-scale precision using 3D
magnetic exchange force field measurements.


  Let $K$ be a convex body in $\mathbb{R}^n$ (i.e., a compact convex set with
nonempty interior). Given a point $p$ in the interior of $K$, a hyperplane $h$
passing through $p$ is called barycentric if $p$ is the barycenter of $K \cap
h$. In 1961, Gr\"{u}nbaum raised the question whether, for every $K$, there
exists an interior point $p$ through which there are at least $n+1$ distinct
barycentric hyperplanes. Two years later, this was seemingly resolved
affirmatively by showing that this is the case if $p=p_0$ is the point of
maximal depth in $K$. However, while working on a related question, we noticed
that one of the auxiliary claims in the proof is incorrect. Here, we provide a
counterexample; this re-opens Gr\"unbaum's question. It follows from known
results that for $n \geq 2$, there are always at least three distinct
barycentric cuts through the point $p_0 \in K$ of maximal depth. Using tools
related to Morse theory we are able to improve this bound: four distinct
barycentric cuts through $p_0$ are guaranteed if $n \geq 3$.


  IGR J18483-0311 is a supergiant fast X-ray transient whose compact object is
located in a wide (18.5 d) and eccentric (e~0.4) orbit, which shows sporadic
outbursts that reach X-ray luminosities of ~1e36 erg/s. We investigated the
timing properties of IGR J18483-0311 and studied the spectra during bright
outbursts by fitting physical models based on thermal and bulk Comptonization
processes for accreting compact objects. We analysed archival INTEGRAL data
collected in the period 2003-2010, focusing on the observations with IGR
J18483-0311 in outburst. We searched for pulsations in the INTEGRAL light
curves of each outburst. We took advantage of the broadband observing
capability of INTEGRAL for the spectral analysis. We observed 15 outbursts,
seven of which we report here for the first time. This data analysis almost
doubles the statistics of flares of this binary system detected by INTEGRAL. A
refined timing analysis did not reveal a significant periodicity in the
INTEGRAL observation where a ~21s pulsation was previously detected. Neither
did we find evidence for pulsations in the X-ray light curve of an archival
XMM-Newton observation of IGR J18483-0311. In the light of these results the
nature of the compact object in IGR J18483-0311 is unclear. The broadband X-ray
spectrum of IGR J18483-0311 in outburst is well fitted by a thermal and bulk
Comptonization model of blackbody seed photons by the infalling material in the
accretion column of a neutron star. We also obtained a new measurement of the
orbital period using the Swift/BAT light curve.


  Contribution of the strong CP angle, $\bar\theta$, to the Wilson Coefficients
of electron and muon electric dipole moment (EDM) operators are discussed.
Previously, $\bar\theta$ contribution to the electron EDM operator was
calculated by Choi and Hong. However, the effect of CP-violating three meson
coupling was missing there. We include this missing contribution for the first
time in the literature, and reevaluate the Wilson coefficients of the lepton
EDM operator. We obtain $d_e = - (2.2-8.6) \times 10^{-28} \bar\theta$ e-cm
which is 15 - 70 % of the result obtained in Choi and Hong. We also estimated
the muon EDM as $d_\mu = - (0.5-1.8) \times 10^{-25} \bar\theta$ e-cm. Using
$|\bar\theta| \lesssim 10^{-10}$ suggested by the neutron EDM measurements, we
obtain $|d_e| \lesssim 8.6 \times 10^{-38}$ e-cm and $|d_\mu| \lesssim 1.8
\times 10^{-35}$ e-cm. The $\bar\theta$ contribution to the muon EDM is much
below the sensitivities of the current and near future experiments. Our result
shows that the $\bar\theta$ contribution to $d_{e,\mu}$ can be larger than the
CKM contributions by many orders of magnitude.


  Hypercontractive inequalities are a useful tool in dealing with extremal
questions in the geometry of high-dimensional discrete and continuous spaces.
In this survey we trace a few connections between different manifestations of
hypercontractivity, and also present some relatively recent applications of
these techniques in computer science.


  We explore the effects of noncommuting applied fields on the ground-state
ordering of the quasi-one-dimensional spin-1/2 XY-like antiferromagnet Cs2CoCl4
using single-crystal neutron diffraction. In zero field interchain couplings
cause long-range order below T_N=217(5) mK with chains ordered
antiferromagnetically along their length and moments confined to the (b,c)
plane. Magnetic fields applied at an angle to the XY planes are found to
initially stabilize the order by promoting a spin-flop phase with an increased
perpendicular antiferromagnetic moment. In higher fields the antiferromagnetic
order becomes unstable and a transition occurs to a phase with no long-range
order in the (b,c) plane, proposed to be a spin liquid phase that arises when
the quantum fluctuations induced by the noncommuting field become strong enough
to overcome ordering tendencies. Magnetization measurements confirm that
saturation occurs at much higher fields and that the proposed spin-liquid state
exists in the region 2.10 < H_SL < 2.52 T || a. The observed phase diagram is
discussed in terms of known results on XY-like chains in coexisting
longitudinal and transverse fields.


  In the framework of the coagulation scenario, kilometre-sized planetesimals
form by subsequent collisions of pre-planetesimals of sizes from centimetre to
hundreds of metres. Pre-planetesimals are fluffy, porous dust aggregates, which
are inhomogeneous owing to their collisional history. Planetesimal growth can
be prevented by catastrophic disruption in pre-planetesimal collisions above
the destruction velocity threshold. We develop an inhomogeneity model based on
the density distribution of dust aggregates, which is assumed to be a Gaussian
distribution with a well-defined standard deviation. As a second input
parameter, we consider the typical size of an inhomogeneous clump. These input
parameters are easily accessible by laboratory experiments. For the simulation
of the dust aggregates, we utilise a smoothed particle hydrodynamics (SPH) code
with extensions for modelling porous solid bodies. The porosity model was
previously calibrated for the simulation of silica dust, which commonly serves
as an analogue for pre-planetesimal material. The inhomogeneity is imposed as
an initial condition on the SPH particle distribution. We carry out collisions
of centimetre-sized dust aggregates of intermediate porosity. We vary the
standard deviation of the inhomogeneous distribution at fixed typical clump
size. The collision outcome is categorised according to the four-population
model. We show that inhomogeneous pre-planetesimals are more prone to
destruction than homogeneous aggregates. Even slight inhomogeneities can lower
the threshold for catastrophic disruption. For a fixed collision velocity, the
sizes of the fragments decrease with increasing inhomogeneity.
Pre-planetesimals with an active collisional history tend to be weaker. This is
a possible obstacle to collisional growth and needs to be taken into account in
future studies of the coagulation scenario.


  We present a new systematic method of constructing rational mappings as
ergordic transformations with nonuniform invariant measures on the unit
interval [0,1]. As a result, we obtain a two-parameter family of rational
mappings that have a special property in that their invariant measures can be
explicitly written in terms of algebraic functions of parameters and a
dynamical variable. Furthermore, it is shown here that this family is the most
generalized class of rational mappings possessing the property of exactly
solvable chaos on the unit interval, including the Ulam=Neumann map y=4x(1-x).
Based on the present method, we can produce a series of rational mappings
resembling the asymmetric shape of the experimentally obtained first return
maps of the Beloussof-Zhabotinski chemical reaction, and we can match some
rational functions with other experimentally obtained first return maps in a
systematic manner.


  We consider N=2 and N=4 supersymmetric gauge theories in two-dimensions,
coupled to matter multiplets. In analogy with the N=2 case also in the N=4 case
one can introduce Fayet-Iliopoulos terms.The associated three-parameters have
the meaning of momentum-map levels in a HyperK\"ahler quotient construction.
Differently from the N=2 case, however, the N=4 has a single phase
corresponding to an effective $\sigma$-model. There is no Landau-Ginzburg
phase. The main possible application of our N=4 model is to an effective
Lagrangian construction of a $\sigma$-model on ALE-manifolds. We discuss the A
and B topological twists of these models clarifying some issues not yet
discussed in the literature, in particular the identification of the
topological systems emerging from the twist. Applying our results to the case
of ALE-manifolds we indicate how one can use the topologically twisted theories
to study the K\"ahler class and complex structure deformations of these
gravitational instantons.


  Internet of Things (IoT) has become the buzzword for the development of Smart
City and its applications. In this context, development of supporting software
forms the core part of the IoT infrastructure. A Middleware sits in between the
IoT devices and interacts between them to exchange data among the components of
the automated architecture. The Middleware services include hand shaking, data
transfer and security among its core set of functionalities. It also includes
cross-cutting functional services such as authentication, logging and caching.
A software that can run these Middleware services requires a careful choice of
a good software modelling technique. Aspect-Oriented Programming (AOP) is a
software development methodology that can be used to independently encapsulate
the core and cross-cutting functionalities of the Middleware services of the
IoT infrastructure. In this paper, an attempt has been made using a simulation
environment to independently model the two orthogonal functionalities of the
Middleware with the focus to improve its modularity. Further, a quantitative
measurement of the core design property of cohesion has been done to infer on
the improvement in the reusability of the modules encapsulated in the
Middleware of IoT. Based on the measurement, it was found that the modularity
and reusability of functionalities in the Middleware software has improved in
the AspectJ version compared to its equivalent Java version.


  Due to their intrinsic brightness, supernovae make excellent cosmological
probes. We describe the SEAM method for obtaining distances to Type IIP
supernovae (SNe IIP) and present a distance to SN 1999em for which a Cepheid
distance exists. Our models give results consistent with the Cepheid distance,
even though we have not attempted to tune the underlying hydrodynamical model,
we have simply chosen the best fits. This is in contradistinction to the
expanding photosphere method (EPM) which yields a distance to SN 1999em that is
50% smaller than the Cepheid distance. We emphasize the differences between
SEAM and EPM. We show that the dilution factors used in the EPM analysis were
systematically too small at later epochs. We also show that the EPM blackbody
assumption is suspect.
  Since SNe IIP are visible to redshifts as high as z less than about 6, with
the JWST, SEAM may be a valuable probe of the early universe.


  I discuss particle content of the Ising field theory (the scaling limit of
the Ising model in a magnetic field), in particular the evolution of its mass
spectrum under the change of the scaling parameter. I consider both real and
pure imaginary magnetic field. Here I address the high-temperature regime,
where the spectrum of stable particles is relatively simple (there are from one
to three particles, depending on the parameter). My goal is to understand
analytic continuations of the masses to the domain of the parameter where they
no longer exist as the stable particles. I use the natural tool -- the $2\to 2$
elastic scattering amplitude, with its poles associated with the stable
particles, virtual and resonance states in a standard manner. Concentrating
attention on the "real" poles (those corresponding to stable and virtual
states) I propose a scenario on how the pattern of the poles evolves from the
integrable point $T=T_c,\ H\neq 0$ to the free particle point $T>T_c,\ H=0$,
and then, along the pure imaginary $H$, to the Yang-Lee critical point.
Waypoints along this evolution path are located using TFFSA data. I also
speculate about likely behavior of some of the resonance poles.


  Microscopic signatures of nuclear ground-state shape phase transitions in Nd
isotopes are studied using excitation spectra and collective wave functions
obtained by diagonalization of a five-dimensional Hamiltonian for quadrupole
vibrational and rotational degrees of freedom, with parameters determined by
constrained self-consistent relativistic mean-field calculations for triaxial
shapes. As a function of the physical control parameter -- the number of
nucleons, energy gaps between the ground state and the excited vibrational
states with zero angular momentum, isomer shifts, and monopole transition
strengths, exhibit sharp discontinuities at neutron number N=90, characteristic
of a first-order quantum phase transition.


  Bayesian On-line Changepoint Detection is extended to on-line model selection
and non-stationary spatio-temporal processes. We propose spatially structured
Vector Autoregressions (VARs) for modelling the process between changepoints
(CPs) and give an upper bound on the approximation error of such models. The
resulting algorithm performs prediction, model selection and CP detection
on-line. Its time complexity is linear and its space complexity constant, and
thus it is two orders of magnitudes faster than its closest competitor. In
addition, it outperforms the state of the art for multivariate data.


  In this paper, we present a theoretical framework for understanding the
Extremely Correlated Fermi Liquid (ECFL) phenomenon within the $U=\infty$
Hubbard model. Our approach involves deriving equations of motion for the
single-particle Green's function $G$ and its associated self-energy $\Sigma$,
which involves the product of the bosonic correlation function comprising both
density ($D_N$) and spin ($D_S$) correlations with $G$. By solving these
equations self-consistently, we explore the behavior of $G$, $D_N$, and $D_S$
as functions of frequency, temperature, and hole concentration. Our results
reveal distinct coherent and incoherent Fermi liquid regimes characterized by
the presence or absence of quasiparticle excitations. Additionally, we analyze
the intrinsic dc resistivity $\rho(T)$, observing a crossover from $T^2$ to
linear behavior with increasing temperature. Our findings delineate Fermi
liquid, quantum incoherent, and `classical' regimes in strongly correlated
systems, emphasizing the importance of quantum diffusive local charge and spin
fluctuations.


  A set of high-resolution optical spectra of RCrB acquired before, during, and
after its 1995-1996 decline is discussed. All of the components reported from
earlier declines are seen. This novel dataset provides new information on these
components including several aspects not previously seen in declines of RCrB
and other RCBs. In the latter category is the discovery that the decline's
onset is marked by distortions of absorption lines of high-excitation lines,
and quickly followed by emission in these and in low excitation lines. This
'photospheric trigger' implies that dust causing the decline is formed close to
the star. These emission lines fade quickly. After 1995 November 2, low
excitation narrow (FWHM ~12 km s-1) emission lines remain. These appear to be a
permanent feature, slightly blue-shifted from the systemic velocity, and
unaffected by the decline except for a late and slight decrease of flux at
minimum light. The location of the warm, dense gas providing these lines is
uncertain. Absorption lines unaffected by overlying sharp emission are greatly
broadened, weakened, and red-shifted at the faintest magnitudes when scattered
light from the star is a greater contributor than direct light transmitted
through the fresh soot cloud. A few broad lines are seen at and near minimum
light with approxiamately constant flux: prominent among these are the He I
triplet series, Na I D, and [N II] lines. These lines are blue-shifted by about
30 km s(-1) relative to the systemic velocity with no change in velocity over
the several months for whicht he lines were seen. It is suggested that these
lines, especially the He I lines, arise from an accretion disk around an unseen
compact companion, which may be a low-mass white dwarf. If so, R CrB is similar
to the unusual post-AGB star 89 Her.


  Vehicle-to-everything (V2X) communication techniques enable the collaboration
between vehicles and many other entities in the neighboring environment, which
could fundamentally improve the perception system for autonomous driving.
However, the lack of a public dataset significantly restricts the research
progress of collaborative perception. To fill this gap, we present V2X-Sim, a
comprehensive simulated multi-agent perception dataset for V2X-aided autonomous
driving. V2X-Sim provides: (1) \hl{multi-agent} sensor recordings from the
road-side unit (RSU) and multiple vehicles that enable collaborative
perception, (2) multi-modality sensor streams that facilitate multi-modality
perception, and (3) diverse ground truths that support various perception
tasks. Meanwhile, we build an open-source testbed and provide a benchmark for
the state-of-the-art collaborative perception algorithms on three tasks,
including detection, tracking and segmentation. V2X-Sim seeks to stimulate
collaborative perception research for autonomous driving before realistic
datasets become widely available. Our dataset and code are available at
\url{https://ai4ce.github.io/V2X-Sim/}.


  With the aim to study the relationship between protein sequences and their
native structures, we adopt vectorial representations for both sequence and
structure. The structural representation is based on the Principal Eigenvector
of the fold's contact matrix (PE). As recently shown, the latter encodes
sufficient information for reconstructing the whole contact matrix. The
sequence is represented through a Hydrophobicity Profile (HP), using a
generalized hydrophobicity scale that we obtain from the principal eigenvector
of a residue-residue interaction matrix and denote it as interactivity scale.
Using this novel scale, we define the optimal HP of a protein fold, and
predict, by means of stability arguments, that it is strongly correlated with
the PE of the fold's contact matrix. This prediction is confirmed through an
evolutionary analysis, which shows that the PE correlates with the HP of each
individual sequence adopting the same fold and, even more strongly, with the
average HP of this set of sequences. Thus, protein sequences evolve in such a
way that their average HP is close to the optimal one, implying that neutral
evolution can be viewed as a kind of motion in sequence space around the
optimal HP. Our results indicate that the correlation coefficient between
N-dimensional vectors constitutes a natural metric in the vectorial space in
which we represent both protein sequences and protein structures, which we call
Vectorial Protein Space. In this way, we define a unified framework for
sequence to sequence, sequence to structure, and structure to structure
alignments. We show that the interactivity scale is nearly optimal both for the
comparison of sequences with sequences and sequences with structures.


  Hydrogen ($\delta$2H) and oxygen ($\delta$18O) isotopes of water extracted
from speleothem fluid inclusions are important proxies used for paleoclimate
reconstruction. In our study we use a cavity ring-down laser spectroscopy
system for analysis and modified the approach of Affolter et al. (2014) for
sample extraction. The method is based on crushing of small sub-gram speleothem
samples in a heated and continuously water-vapour purged extraction line. The
following points were identified:
  Injection of reference water shows a precision (1$\sigma$) of 0.4-0.5 permil
for $\delta$18O values and 1.1-1.9 permil for $\delta$2H values for water
amounts of 0.1-0.5 $\mu$l, which improves with increasing water amount to
0.1-0.3 permil and 0.2-0.7 permil, respectively, above 1 $\mu$l. The accuracy
of measurements of water injections and water-filled glass capillaries crushed
in the system is better than 0.08 permil for $\delta$18O and 0.3 permil for
$\delta$2H values. The reproducibility (1$\sigma$) based on replicate analysis
of speleothem fluid inclusion samples with water amounts > 0.2 $\mu$l is 0.5
permil for $\delta$18O and 1.2 permil for $\delta$2H values, respectively.
Isotopic differences between the water vapour background of the extraction
system and the fluid inclusions have no significant impact on the measured
fluid inclusion isotope values if they are within 10 permil for $\delta$18O and
50 permil for $\delta$2H values of the background. Tests of potential
adsorption effects with inclusion free spar calcite confirm that the isotope
values are unaffected by adsorption for water contents of about 1 $\mu$l (fluid
inclusion) water per g of carbonate or above.
  Fluid inclusion analysis on three different modern to late Holocene
speleothems from caves in northwest Germany resulted ...


  We present here findings for C18O depletion in eight starless cores in
Taurus: TMC-2, L1498, L1512, L1489, L1517B, L1521E, L1495A-S, and L1544. We
compare observations of the C18O J=2-1 transition taken with the ALMA prototype
receiver on the Heinrich Hertz Submillimeter Telescope to results of radiative
transfer modeling using RATRAN. We use temperature and density profiles
calculated from dust continuum radiative transfer models to model the C18O
emission. We present modeling of three cores, TMC-2, L1489, and L1495A-S, which
have not been modeled before and compare our results for the five cores with
published models. We find that all of the cores but one, L1521E, are
substantially depleted. We also find that varying the temperature profiles of
these model cores has a discernable effect, and varying the central density has
an even larger effect. We find no trends with depletion radius or depletion
fraction with the density or temperature of these cores, suggesting that the
physical structure alone is insufficient to fully constrain evolutionary state.
We are able to place tighter constraints on the radius at which C18O is
depleted than the absolute fraction of depletion. As the timeline of chemical
depletion depends sensitively on the fraction of depletion, this difficulty in
constraining depletion fraction makes comparison with other timescales, such as
the free-fall timescale, very difficult. Keywords: Stars:Formation --
ISM:abundances-- ISM:clouds -- Individual Objects: TMC-2, L1498, L1512, L1489,
L1517B, L1521E, L1495A-S, L1544


  For some $k \in \mathbb{Z}_{\geq 0}\cup \infty$, we call a linear forest
$k$-bounded if each of its components has at most $k$ edges. We will say a
$(k,\ell)$-bounded linear forest decomposition of a graph $G$ is a partition of
$E(G)$ into the edge sets of two linear forests $F_k,F_\ell$ where $F_k$ is
$k$-bounded and $F_\ell$ is $\ell$-bounded. We show that the problem of
deciding whether a given graph has such a decomposition is NP-complete if both
$k$ and $\ell$ are at least $2$, NP-complete if $k\geq 9$ and $\ell =1$, and is
in P for $(k,\ell)=(2,1)$. Before this, the only known NP-complete cases were
the $(2,2)$ and $(3,3)$ cases. Our hardness result answers a question of
Bermond et al. from 1984. We also show that planar graphs of girth at least
nine decompose into a linear forest and a matching, which in particular is
stronger than $3$-edge-colouring such graphs.


  A {\em $(d,h)$-decomposition} of a graph $G$ is an order pair $(D,H)$ such
that $H$ is a subgraph of $G$ where $H$ has the maximum degree at most $h$ and
$D$ is an acyclic orientation of $G-E(H)$ of maximum out-degree at most $d$. A
graph $G$ is {\em $(d, h)$-decomposable} if $G$ has a $(d,h)$-decomposition.
Let $G$ be a graph embeddable in a surface of nonnegative characteristic. In
this paper, we prove the following results. (1) If $G$ has no chord $5$-cycles
or no chord $6$-cycles or no chord $7$-cycles and no adjacent $4$-cycles, then
$G$ is $(3,1)$-decomposable, which generalizes the results of Chen, Zhu and
Wang [Comput. Math. Appl, 56 (2008) 2073--2078] and the results of Zhang
[Comment. Math. Univ. Carolin, 54(3) (2013) 339--344]. (2) If $G$ has no
$i$-cycles nor $j$-cycles for any subset $\{i,j\}\subseteq \{3,4,6\}$ is
$(2,1)$-decomposable, which generalizes the results of Dong and Xu [Discrete
Math. Alg. and Appl., 1(2) (2009), 291--297].


  We construct an infinite family $\{ C_{n,k}\}_{k=1}^{\infty}$ of corks of
Mazur type satisfying $2n\leq \mathrm{sc}^{\mathrm{sp}}(C_{n,k})\leq
O(n^{3/2})$ for any positive integer $n$. Furthermore, using these corks, we
construct an infinite family $\{(W_{n,k},W'_{n,k})\}_{k=1}^{\infty}$ of exotic
pairs of $4$-manifolds with boundary whose special shadow-complexities satisfy
the above inequalities. We also discuss exotic pairs with small
shadow-complexity.


  I present an overview of observational studies of quasars of all types, with
particular emphasis on X-ray observational studies. The presentation is based
on the most popularly accepted unified picture of quasars - collectively
referred to as AGN (active galactic nuclei) in this review. Characteristics of
X-ray spectra and X-ray variability obtained from various X-ray satellites over
the last 5 decades have been presented and discussed. The contribution of AGN
in understanding the cosmic X-ray background is discussed very briefly. Attempt
has been made to provide up-to-date information; however, this is a vast
subject and this presentation is not intended to be comprehensive.


  Let $\psi$ be a Parceval wavelet in $L^2 (\R)$ with the space of negative
dilates $V(\psi)$. The intersection of the dilates $V(\psi)$ is the zero space.
In other words, we have \begin{align*}
  \bigcap_{n\in\Z} D^n \overline{\textrm{span}}\{D^{\textrm{-}m} T^\ell \psi
\mid m\geq 0, m,\ell\in\Z\}=\{0\}. \end{align*}


  Human respiration rate (HRR) is an important physiological metric for
diagnosing a variety of health conditions from stress levels to heart
conditions. Estimation of HRR is well-studied in controlled terrestrial
environments, yet robotic estimation of HRR as an indicator of diver stress in
underwater for underwater human robot interaction (UHRI) scenarios is to our
knowledge unexplored. We introduce a novel system for robotic estimation of HRR
from underwater visual data by utilizing bubbles from exhalation cycles in
scuba diving to time respiration rate. We introduce a fuzzy labeling system
that utilizes audio information to label a diverse dataset of diver breathing
data on which we compare four different methods for characterizing the presence
of bubbles in images. Ultimately we show that our method is effective at
estimating HRR by comparing the respiration rate output with human analysts.


  Ensembles of geophysical models improve projection accuracy and express
uncertainties. We develop a novel data-driven ensembling strategy for combining
geophysical models using Bayesian Neural Networks, which infers
spatiotemporally varying model weights and bias while accounting for
heteroscedastic uncertainties in the observations. This produces more accurate
and uncertainty-aware projections without sacrificing interpretability. Applied
to the prediction of total column ozone from an ensemble of 15
chemistry-climate models, we find that the Bayesian neural network ensemble
(BayNNE) outperforms existing ensembling methods, achieving a 49.4% reduction
in RMSE for temporal extrapolation, and a 67.4% reduction in RMSE for polar
data voids, compared to a weighted mean. Uncertainty is also
well-characterized, with 90.6% of the data points in our extrapolation
validation dataset lying within 2 standard deviations and 98.5% within 3
standard deviations.


  We demonstrate that a supersymmetric theory twisted on a K\"ahler four
manifold $M=\Sigma_1 \times \Sigma_2 ,$ where $\Sigma_{1,2}$ are 2D Riemann
surfaces, possesses a "left-moving" conformal stress tensor on $\Sigma_1$
($\Sigma_2$) in the BRST cohomology. The central charge of the Virasoro algebra
has a purely geometric origin and is proportional to the Euler characteristic
of the $\Sigma_2$ ($\Sigma_1$) surface. This structure is shown to be invariant
under renormalization group. We also give a representation of the algebra
$W_{1+\infty}$ in terms of a free chiral supermultiplet.


  In prevalent cohort studies with follow-up, the time-to-event outcome is
subject to left truncation leading to selection bias. For estimation of the
distribution of time-to-event, conventional methods adjusting for left
truncation tend to rely on the (quasi-)independence assumption that the
truncation time and the event time are "independent" on the observed region.
This assumption is violated when there is dependence between the truncation
time and the event time possibly induced by measured covariates. Inverse
probability of truncation weighting leveraging covariate information can be
used in this case, but it is sensitive to misspecification of the truncation
model. In this work, we apply the semiparametric theory to find the efficient
influence curve of an expected (arbitrarily transformed) survival time in the
presence of covariate-induced dependent left truncation. We then use it to
construct estimators that are shown to enjoy double-robustness properties. Our
work represents the first attempt to construct doubly robust estimators in the
presence of left truncation, which does not fall under the established
framework of coarsened data where doubly robust approaches are developed. We
provide technical conditions for the asymptotic properties that appear to not
have been carefully examined in the literature for time-to-event data, and
study the estimators via extensive simulation. We apply the estimators to two
data sets from practice, with different right-censoring patterns.


  We report a high precision measurement of the transverse single spin
asymmetry $A_N$ at the center of mass energy $\sqrt{s}=200$ GeV in elastic
proton-proton scattering by the STAR experiment at RHIC. The $A_N$ was measured
in the four-momentum transfer squared $t$ range $0.003 \leqslant |t| \leqslant
0.035$ $\GeVcSq$, the region of a significant interference between the
electromagnetic and hadronic scattering amplitudes. The measured values of
$A_N$ and its $t$-dependence are consistent with a vanishing hadronic spin-flip
amplitude, thus providing strong constraints on the ratio of the single
spin-flip to the non-flip amplitudes. Since the hadronic amplitude is dominated
by the Pomeron amplitude at this $\sqrt{s}$, we conclude that this measurement
addresses the question about the presence of a hadronic spin flip due to the
Pomeron exchange in polarized proton-proton elastic scattering.


  Representation of the elastic scattering amplitude in the form of the path
integral is obtained using the stationary Schroedinger equation. A few methods
of evaluation of path integrals for large coupling constants are formulated.
The methods are based on the uncertainty correlation. The scattering lengths
and cross sections are calculated for the right angled and singular potentials
and the Yukawa potential. The comparison with exact results is made.


  The aim of this paper is to study a concentration-compactness principle for
homogeneous fractional Sobolev space $\mathcal{D}^{s,2} (\mathbb{R}^N)$ for
$0<s<\min\{1,N/2\}.$ As an application we establish Palais-Smale compactness
for the Lagrangian associated to the fractional scalar field equation
$(-\Delta)^{s} u = f(x,u)$ for $0<s<1.$ Moreover, using an analytic framework
based on $\mathcal{D}^{s,2}(\mathbb{R}^N),$ we obtain the existence of ground
state solutions for a wide class of nonlinearities in the critical growth
range.


  The onset of thermal convection in a uniformly rotating and horizontally
isotropic bi-disperse porous medium, taking into account the Vadasz term, is
investigated. Via linear instability analysis, it has been proven that the
Vadasz term allows the onset of convection via an oscillatory state but does
not affect convection via a stationary motion.


  We investigate the relevance of the conformal method by investigating
stability issues for the Einstein-Lichnerowicz conformal constraint system in a
nonlinear scalar-field setting. We prove the stability of the system with
respect to arbitrary perturbations of generic focusing physics data on closed
locally conformally flat manifolds, in any dimension. We also show that our
stability result is sharp by constructing explicit instability examples when
its assumptions are not satisfied. Our results apply to a more general class of
constraint-like systems.


  It is argued that electron density dynamic's response to phonons at the
Brillouin zone boundary is the key factor in the superconductivity mechanism of
MgB2 as well as of all superconducting compounds leading to a real space
electron-hole pairing characterized by CP symmetry (Charge and Parity
symmetries) that enables a unified description of superconductivity
phenomenon.First principle calculation of the electron density difference is
determined by subtracting the electron density of the crystal distorted by
longitudinal acoustical phonons at the Brillouin zone boundary from that of the
perfect crystal.The origin of this electron density dynamic's response to this
kind of distortion that leads to in real space electron hole pairing
caracterized by CP symmetry is discussed in terms of local polarizabilities and
delocalized transfer of charge caused by phonon-distortion driven dynamical
change of orbital hybridization. This approach also provides clear and quick
guidelines in the search for a new superconductors.


  This paper summarizes the recent state of the art of the following topics
presented at the FQMT'04 conference: Quantum, mesoscopic and (partly) classical
thermodynamics; Quantum limits to the second law of thermodynamics; Quantum
measurement; Quantum decoherence and dephasing; Mesoscopic and
nano-electro-mechanical systems; Classical molecular motors, ratchet systems
and rectified motion; Quantum Brownian motion and Quantum motors; Physics of
quantum computing; and Relevant experiments from the nanoscale to the
macroscale. To all these subjects an introduction is given and the recent
literature is broadly overviewed. The paper contains some 450 references in
total.


  We propose and investigate an "interface-flattening" transformation, hinging
upon Transformation Optics (T.O.) techniques, to facilitate the rigorous
analysis of electromagnetic (EM) fields radiated by sources embedded in tilted,
cylindrically-layered geophysical media. Our method addresses the major
challenge in such problems of appropriately approximating the domain boundaries
in the computational model while, in a full-wave manner, predicting the effects
of tilting in the layers. When incorporated into standard pseudo-analytical
algorithms, moreover, the proposed method is quite robust, as it is not limited
by absorption, anisotropy, and/or eccentering profile of the cylindrical
geophysical formations, nor is it limited by the radiation frequency. These
attributes of the proposed method are in contrast to past analysis methods for
tilted-layer media that often place limitations on the source and medium
characteristics. Through analytical derivations as well as a preliminary
numerical investigation, we analyze and discuss the method's strengths and
limitations.


  Rejoinder to ``The 2005 Neyman Lecture: Dynamic Indeterminism in Science''
[arXiv:0808.0620]


  For the proposed duality relating a family of N=4 superconformal coset models
to a certain supersymmetric higher spin theory on AdS_3, the asymptotic
symmetry algebra of the bulk description is determined. It is shown that,
depending on the choice of the boundary charges, one may obtain either the
linear or the non-linear superconformal algebra on the boundary. We compare the
non-linear version of the asymptotic symmetry algebra with the non-linear coset
algebra and find non-trivial agreement in the 't Hooft limit, thus giving
strong support for the proposed duality. As a by-product of our analysis we
also show that the W_infinity symmetry of the coset theory is broken under the
exactly marginal perturbation that preserves the N=4 superconformal algebra.


  Resonance states of a two-electron quantum dot are studied using a
variational expansion with both real basis-set functions and complex scaling
methods. The two-electron entanglement (linear entropy) is calculated as a
function of the electron repulsion at both sides of the critical value, where
the ground (bound) state becomes a resonance (unbound) state. The linear
entropy and fidelity and double orthogonality functions are compared as methods
for the determination of the real part of the energy of a resonance. The
complex linear entropy of a resonance state is introduced using complex scaling
formalism.