  Currently, robotics is one of the fastest growing areas not only in the
industrial sector but also in the consumer and service sectors. Several areas
benefit from the technological advancement of robotics, especially the
industrial area those benefits from gains in productivity and quality. However,
to supply this growing demand it is necessary for the newly graduated
professionals to have a deeper understanding of how to design and control a
robotic manipulator. It is logical that in order to obtain this more in-depth
knowledge of robotics, it is necessary to have an experience with a real
robotic manipulator, since the practice is a much more efficient way of
learning than theory. However, it is known that a robotic arm is not a cheap
investment, and its maintenance is not cheap either. Therefore, many
educational institutions are not able to provide this type of experience to
their students. With this in mind, and through the use of Unity 3D, which is a
game development software, a robotic arm simulator has been developed to
correlate classroom theory with what actually happens in practice. The robotic
manipulators implemented on this simulator can be controlled by both inverse
kinematics (which is the industry standard) and direct kinematics.


  In decision-making, maxitive functions are used for worst-case and best-case
evaluations. Maxitivity gives rise to a rich structure that is well-studied in
the context of the pointwise order. In this article, we investigate maxitivity
with respect to general preorders and provide a representation theorem for such
functionals. The results are illustrated for different stochastic orders in the
literature, including the usual stochastic order, the increasing convex/concave
order, and the dispersive order.


  Fractures are ubiquitous in the subsurface and strongly affect flow and
deformation. The physical shape of the fractures, they are long and thin
objects, puts strong limitations on how the effect of this dynamics can be
incorporated into standard reservoir simulation tools. This paper reports the
development of an open-source software framework, termed PorePy, which is aimed
at simulation of flow and transport in three-dimensional fractured reservoirs,
as well as deformation of the reservoir due to shearing along fracture and
fault planes. Starting from a description of fractures as polygons embedded in
a 3D domain, PorePy provides semi-automatic gridding to construct a
discrete-fracture-matrix model, which forms the basis for subsequent
simulations. PorePy allows for flow and transport in all lower-dimensional
objects, including planes (2D) representing fractures, and lines (1D) and
points (0D), representing fracture intersections. Interaction between processes
in neighboring domains of different dimension is implemented as a sequence of
couplings of objects one dimension apart. This readily allows for handling of
complex fracture geometries compared to capabilities of existing software. In
addition to flow and transport, PorePy provides models for rock mechanics,
poro-elasticity and coupling with fracture deformation models. The software is
fully open, and can serve as a framework for transparency and reproducibility
of simulations. We describe the design principles of PorePy from a user
perspective, with focus on possibilities within gridding, covered physical
processes and available discretizations. The power of the framework is
illustrated with two sets of simulations; involving respectively coupled flow
and transport in a fractured porous medium, and low-pressure stimulation of a
geothermal reservoir.


  The review is devoted to the Radcliffe Wave recently discovered by Alves et
al. from the analysis of molecular clouds. These authors singled out a narrow
chain of molecular clouds, elongated almost in one line, located at an
inclination of about 30$^o$ to the galactic axis y. The Radcliffe Wave itself
describes damped vertical oscillations of molecular clouds with a maximum
oscillation amplitude of about 160 pc and a characteristic wavelength of about
2.5 kpc. To date, the presence of the Radcliffe Wave has been confirmed in the
vertical distribution of a) interstellar dust, b) sources of maser radiation
and radio stars, which are very young stars and protostars closely associated
with molecular clouds, c) low-mass stars of the T Tau type, d) more massive OB
stars and e) young open clusters of stars. The Radcliffe Wave is also traced in
the vertical velocities of young stars. Most of the considered results of the
analysis of the vertical velocities of various young stars show that the
oscillations of the vertical positions and vertical velocities of stars in the
Radcliffe Wave occur synchronously. The nature of the Radcliffe Wave is
completely unclear. The majority of researchers associate its occurrence with
the assumption of an external gravitational impact on the galactic disk of a
striker such as a dwarf satellite galaxy of the Milky Way.


  This paper explains the method used in the segmentation challenge (Task 1) in
the International Skin Imaging Collaboration's (ISIC) Skin Lesion Analysis
Towards Melanoma Detection challenge held in 2018. We have trained a U-Net
network to perform the segmentation. The key elements for the training were
first to adjust the loss function to incorporate unbalanced proportion of
background and second to perform post-processing operation to adjust the
contour of the prediction.


  This paper presents a closed-form expression for the integral kernels
associated with the derivatives of the Ornstein-Uhlenbeck semigroup $e^{tL}$.
Our approach is to expand the Mehler kernel into Hermite polynomials and
applying the powers $L^N$ of the Ornstein-Uhlenbeck operator to it, where we
exploit the fact that the Hermite polynomials are eigenfunctions for $L$. As an
application we give an alternative proof of the kernel estimates by Portal
[2014], making all relevant quantities explicit.


  During the formation of large galaxies, thermal instability leads to the
formation of a population of cool fragments embedded within a background of
tenuous hot gas. The hot gas attains a quasi-hydrostatic equilibrium. Although
the cool clouds are pressure confined by the hot gas, they fall into the
galactic potential, and their motion is subject to drag from the hot gas. The
release of gravitational energy due to the infall of the cool clouds is first
converted into their kinetic energy, and is subsequently dissipated as heat.
The cool clouds therefore represent a potentially significant energy source for
the background hot gas, depending upon the ratio of thermal energy deposited
within the clouds versus the hot gas. In this paper, we show that most of
dissipated energy is deposited in the tenuous hot halo gas, providing a source
of internal energy to replenish losses in the hot gas through bremsstrahlung
emission and conduction into the cool clouds. The heating from the motion of
the cool clouds allows the multi-phase structure of the interstellar medium to
be maintained.


  The two-point Wightman function of the free photon field defined in a
gauge-invariant manner is known to be equivalent to the field-strength
two-point function in any spacetime that is topologically trivial. We show that
the gauge-invariant graviton two-point function defined in a similar manner is
equivalent to the Weyl-tensor two-point function in Minkowski space and in the
Poincare patch of de Sitter space. This implies that in the Poincare patch of
de Sitter space the gauge-invariant graviton two-point function decays like
(distance)^(-4) as a function of coordinate distance for spacelike separation.


  In this paper, we present two variations of an algorithm for signal
reconstruction from one-bit or two-bit noisy observations of the discrete
Fourier transform (DFT). The one-bit observations of the DFT correspond to the
sign of its real part, whereas, the two-bit observations of the DFT correspond
to the signs of both the real and imaginary parts of the DFT. We focus on
images for analysis and simulations, thus using the sign of the 2D-DFT. This
choice of the class of signals is inspired by previous works on this problem.
For our algorithm, we show that the expected mean squared error (MSE) in signal
reconstruction is asymptotically proportional to the inverse of the sampling
rate. The samples are affected by additive zero-mean noise of known
distribution. We solve this signal estimation problem by designing an algorithm
that uses contraction mapping, based on the Banach fixed point theorem.
Numerical tests with four benchmark images are provided to show the
effectiveness of our algorithm. Various metrics for image reconstruction
quality assessment such as PSNR, SSIM, ESSIM, and MS-SSIM are employed. On all
four benchmark images, our algorithm outperforms the state-of-the-art in all of
these metrics by a significant margin.


  One of the interesting topics in quantum contextuality is the construction
for various non-contextual inequalities. By introducing a new structure called
hyper-graph, we present a general method, which seems to be analytic and
extensible, to derive the non-contextual inequalities for the qutrit systems.
Based on this, several typical families of non-contextual inequalities are
discussed. And our approach may also help us to simplify some state-independent
proofs for quantum contextuality in one of our recent works.


  If a photon fluctuates from 'nothing', what would it look like and how would
it behave? Here we examine such a photon and the possible characteristics and
effects it may have. If contrary to theoretical expectation, it is not
short-lived, we find quantitative and qualitative similarities with the
quantitative and qualitative features of the standard big bang model. As it
also seems devoid of some of the horizon, homogenous, flatness, singularity and
temperature problems that plague the big bang model, issues surrounding this
photon's life expectancy may need to be re-visited by cosmologists.


  Background: Despite the widespread use of automated security defect detection
tools, software projects still contain many security defects that could result
in serious damage. Such tools are largely context-insensitive and may not cover
all possible scenarios in testing potential issues, which makes them
susceptible to missing complex security defects. Hence, thorough detection
entails a synergistic cooperation between these tools and human-intensive
detection techniques, including code review. Code review is widely recognized
as a crucial and effective practice for identifying security defects. Aim: This
work aims to empirically investigate security defect detection through code
review. Method: To this end, we conducted an empirical study by analyzing code
review comments derived from four projects in the OpenStack and Qt communities.
Through manually checking 20,995 review comments obtained by keyword-based
search, we identified 614 comments as security-related. Results: Our results
show that (1) security defects are not prevalently discussed in code review,
(2) more than half of the reviewers provided explicit fixing
strategies/solutions to help developers fix security defects, (3) developers
tend to follow reviewers' suggestions and action the changes, (4) Not worth
fixing the defect now and Disagreement between the developer and the reviewer
are the main causes for not resolving security defects. Conclusions: Our
research results demonstrate that (1) software security practices should
combine manual code review with automated detection tools, achieving a more
comprehensive coverage to identifying and addressing security defects, and (2)
promoting appropriate standardization of practitioners' behaviors during code
review remains necessary for enhancing software security.


  We formulate a $3\times3$ Riemann-Hilbert problem to solve the Cauchy problem
for the Sasa-Satsuma equation on the line, which allows us to give a
representation for the solution of Sasa-Satsuma equation. We then apply the
method of nonlinear steepest descent to compute the long-time asymptotics of
the Sasa-Satsuma equation.


  We explore the morphological properties of symmetric Airy beams in the
paraxial and nonparaxial regimes. We consider a 2D electromagnetic realization
with a single transverse component of the electric field, and in the
nonparaxial regime, the longitudinal component along the optic axis. The
general structure of these beams is analyzed with the combination of several
approaches: geometrical optics through the use of caustics, the asymptotic wave
properties of the light field using the stationary wave approximation and
numerical integration. The geometrical optics approach involves locating the
critical points that are later used in the stationary phase approximation. In
the paraxial regime the highest order of the roots is 3, while in the
nonparaxial regime, the order can be of up to 6. The technique yields
conditions to identify interesting features on the beam, like the number of
waves interfering constructively/destructively at the critical positions. The
results are confirmed by the numerical simulations. In this way it is possible
to distinguish and classify phase singularities like optical vortices and
dislocations. The developed algorithm could be used to study any structured
light field.


  Currently, there is no usable machine translation system for Nko, a language
spoken by tens of millions of people across multiple West African countries,
which holds significant cultural and educational value.
  To address this issue, we present a set of tools, resources, and baseline
results aimed towards the development of usable machine translation systems for
Nko and other languages that do not currently have sufficiently large parallel
text corpora available.
  (1) Fria$\parallel$el: A novel collaborative parallel text curation software
that incorporates quality control through copyedit-based workflows.
  (2) Expansion of the FLoRes-200 and NLLB-Seed corpora with 2,009 and 6,193
high-quality Nko translations in parallel with 204 and 40 other languages.
  (3) nicolingua-0005: A collection of trilingual and bilingual corpora with
130,850 parallel segments and monolingual corpora containing over 3 million Nko
words.
  (4) Baseline bilingual and multilingual neural machine translation results
with the best model scoring 30.83 English-Nko chrF++ on FLoRes-devtest.


  The rapid neutron capture or 'r process' of nucleosynthesis is believed to be
responsible for the production of approximately half the natural abundance of
heavy elements found on the periodic table above iron (with proton number
$Z=26$) and all of the heavy elements above bismuth ($Z=83$). In the course of
creating the actinides and potentially superheavies, the r process must
necessarily synthesize superheavy nuclei (those with extreme proton numbers,
neutron numbers or both) far from isotopes accessible in the laboratory. Many
questions about this process remain unanswered, such as 'where in nature may
this process occur?' and 'what are the heaviest species created by this
process?' In this review, we survey at a high level the nuclear properties
relevant for the heaviest elements thought to be created in the r process. We
provide a synopsis of the production and destruction mechanisms of these heavy
species, in particular the actinides and superheavies, and discuss these heavy
elements in relation to the astrophysical r process. We review the
observational evidence of actinides found in the Solar system and in metal-poor
stars and comment on the prospective of observing heavy-element production in
explosive astrophysical events. Finally, we discuss the possibility that future
observations and laboratory experiments will provide new information in
understanding the production of the heaviest elements.


  This paper presents a new type of genetic algorithm for the set covering
problem. It differs from previous evolutionary approaches first because it is
an indirect algorithm, i.e. the actual solutions are found by an external
decoder function. The genetic algorithm itself provides this decoder with
permutations of the solution variables and other parameters. Second, it will be
shown that results can be further improved by adding another indirect
optimisation layer. The decoder will not directly seek out low cost solutions
but instead aims for good exploitable solutions. These are then post optimised
by another hill-climbing algorithm. Although seemingly more complicated, we
will show that this three-stage approach has advantages in terms of solution
quality, speed and adaptability to new types of problems over more direct
approaches. Extensive computational results are presented and compared to the
latest evolutionary and other heuristic approaches to the same data instances.


  A model interaction between a two-state quantum system and a classical
switching device is analysed and shown to lead to the quantum Zeno effect for
large values of the coupling constant k . A minimal piecewise deterministic
random process compatible with the Liouville equation is described, and it is
shown that 1/k can be interpreted as the jump frequency of the classical device


  In wireless deployments, such as Massive-MIMO, where radio front-ends and
back-end processing are connected through a transport network, meeting the
real-time processing requirements is essential to realize the capacity gains
from network scaling. While simple forms of baseband transport have been
implemented, their real-time analysis at much larger scale is lacking.
  Towards this, we present the design, delay, and capacity analysis of baseband
transport networks, utilizing results from real-time systems in the context of
wireless processing. We propose a novel Fat-Tree-based design, called DISTRO,
for baseband transport, which is a real-time network that bounds the maximum
end-to-end transport delay of each baseband packet. It achieves this by placing
design constraints and bounding the queuing delay at each aggregation point in
the network. We further characterize the wireless capacity using DISTRO and
provide an efficient search algorithm for the design of a capacity achieving
baseband transport.


  We prove that the reproducing kernel Hilbert spaces (RKHS) of a deep neural
tangent kernel and the Laplace kernel include the same set of functions, when
both kernels are restricted to the sphere $\mathbb{S}^{d-1}$. Additionally, we
prove that the exponential power kernel with a smaller power (making the kernel
less smooth) leads to a larger RKHS, when it is restricted to the sphere
$\mathbb{S}^{d-1}$ and when it is defined on the entire $\mathbb{R}^d$.


  We present a multi-scale topological analysis of the temperature fluctuation
maps from the NPIPE and FFP10 datasets, invoking relative homology to account
for the analysis in the presence of masks. For the topological components, we
detect a $2.96\sigma$ deviation between the observations and simulations at $N
= 128, FWHM = 80'$, for the FFP10 dataset. For the topological loops, we
observe a high deviation between the observation and simulations in the number
of loops at $FWHM = 320'$, at a low dimensionless threshold $\nu = -2.5$, for
the NPIPE dataset. Under a Gaussian assumption, this would amount to a
deviation of $\sim 4\sigma$ . However, the distribution in this bin is
manifestly non-Gaussian and does not obey Poisson statistics either. In the
absence of a true theoretical understanding, we simply note that the
significance is higher than what may be resolved by $600$ simulations. The
FFP10 dataset, indicates a $2.77\sigma$ deviation at this resolution and
threshold. The Euler characteristic reflects the deviations in the components
and loops. To assess the significance of combined levels for a given scale, we
employed the empirical and theoretical versions of the $\chi^2$ test as well as
the nonparametric Tukey depth test. Although all statistics exhibit a stable
distribution, we favor the empirical version of the $\chi^2$ test in the final
interpretation, as it indicates the most conservative differences. Even though
both datasets exhibit mild to significant discrepancies, they also exhibit
contrasting behaviors at various instances. Therefore, we do not find it
feasible to convincingly accept or reject the null hypothesis. Disregarding the
large-scale anomalies that persist at similar scales in WMAP and Planck,
observations of the cosmic microwave background are largely consistent with the
standard cosmological model within $2\sigma$.


  Algorithms are often used to produce decision-making rules that classify or
evaluate individuals. When these individuals have incentives to be classified a
certain way, they may behave strategically to influence their outcomes. We
develop a model for how strategic agents can invest effort in order to change
the outcomes they receive, and we give a tight characterization of when such
agents can be incentivized to invest specified forms of effort into improving
their outcomes as opposed to "gaming" the classifier. We show that whenever any
"reasonable" mechanism can do so, a simple linear mechanism suffices.


  Previous work by the authors (this journal, \vol{60} (2008), 1009-1044)
produced equations that hold on certain loci of the Jacobian of a cyclic
$C_{rs}$ curve. A curve of this type generalizes elliptic curves, and the
equations in question are given in terms of (Klein's) generalization of
Weierstrass' $\sigma$-function. The key tool is a matrix with entries that are
polynomial in the coordinates of the affine plane model of the curve, thus can
be expressed in terms of $\sigma$ and its derivatives. The key geometric loci
on the Jacobian of the curve give a stratification of Brill-Noether type. The
results are of the type of Riemann-Kempf singularity theorem, the methods are
germane to those used by J.D. Fay, who gave vanishing tables for Riemann's
$\theta$-function and its derivatives. The main objects we use were developed
by several contemporary authors, aside from the classical definitions:
meromorphic differentials were expressed in terms of the coordinates mainly by
V.M. Buchstaber, J.C. Eilbeck, V.Z. Enolski, D.V. Leykin, and Taylor expansions
for $\sigma$ in terms of Schur polynomials also contributed by A. Nakayashiki,
in terms of Sato's $\tau$-function. Within this framework, following specific
results for $\sigma$-derivatives given by Y. \^Onishi, we arrive at our main
results, namely statements on the vanishing on given strata of the partial
derivatives of $\sigma$ indexed by Young-diagrams subsets that can be worked
out in terms of the Weierstrass semigroup of the curve at its point at
infinity. The combinatorial statements hold not only for Jacobians but for the
stratification of Sato's infinite-dimensional Grassmann manifold as well.


  Quantum memory systems are vital in quantum information processing for
dependable storage and retrieval of quantum states. Inspired by classical
reliability theories that synthesize reliable computing systems from unreliable
components, we formalize the problem of reliable storage of quantum information
using noisy components. We introduce the notion of stable quantum memories and
define the storage rate as the ratio of the number of logical qubits to the
total number of physical qubits, as well as the circuit complexity of the
decoder, which includes both quantum gates and measurements. We demonstrate
that a strictly positive storage rate can be achieved by constructing a quantum
memory system with quantum expander codes. Moreover, by reducing the reliable
storage problem to reliable quantum communication, we provide upper bounds on
the achievable storage capacity. In the case of physical qubits corrupted by
noise satisfying hypercontractivity conditions, we provide a tighter upper
bound on storage capacity using an entropy dissipation argument. Furthermore,
observing that the time complexity of the decoder scales non-trivially with the
number of physical qubits, achieving asymptotic rates may not be possible due
to the induced dependence of the noise on the number of physical qubits. In
this constrained non-asymptotic setting, we derive upper bounds on storage
capacity using finite blocklength communication bounds. Finally, we numerically
analyze the gap between upper and lower bounds in both asymptotic and
non-asymptotic cases, and provide suggestions to tighten the gap.


  We survey various Alexander-type invariants of plane curve complements, with
an emphasis on obstructions on the type of groups that can arise as fundamental
groups of complements to complex plane curves. Also included are some new
computations of higher-order degrees of curves, which are invariants defined in
a previous paper of the authors.


  Unveiling individuals' preferences for connecting with similar others (choice
homophily) beyond the structural factors determining the pool of opportunities,
is a challenging task. Here, we introduce a robust methodology for quantifying
and inferring choice homophily in a variety of social networks. Our approach
employs statistical network ensembles to estimate and standardize homophily
measurements. We control for group size imbalances and activity disparities by
counting the number of possible network configurations with a given number of
inter-group links using combinatorics. This method provides a principled
measure of connection preferences and their confidence intervals. Our framework
is versatile, suitable for undirected and directed networks, and applicable in
scenarios involving multiple groups. To validate our inference method, we test
it on synthetic networks and show that it outperforms traditional metrics. Our
approach accurately captures the generative homophily used to build the
networks, even when we include additional tie-formation mechanisms, such as
preferential attachment and triadic closure. Results show that while triadic
closure has some influence on the inference, its impact is small in homophilic
networks. On the other hand, preferential attachment does not perturb the
results of the inference method. We apply our method to real-world networks,
demonstrating its effectiveness in unveiling underlying gender homophily. Our
method aligns with traditional metrics in networks with balanced populations,
but we obtain different results when the group sizes or degrees are imbalanced.
This finding highlights the importance of considering structural factors when
measuring choice homophily in social networks.


  In domains like bioinformatics, information retrieval and social network
analysis, one can find learning tasks where the goal consists of inferring a
ranking of objects, conditioned on a particular target object. We present a
general kernel framework for learning conditional rankings from various types
of relational data, where rankings can be conditioned on unseen data objects.
We propose efficient algorithms for conditional ranking by optimizing squared
regression and ranking loss functions. We show theoretically, that learning
with the ranking loss is likely to generalize better than with the regression
loss. Further, we prove that symmetry or reciprocity properties of relations
can be efficiently enforced in the learned models. Experiments on synthetic and
real-world data illustrate that the proposed methods deliver state-of-the-art
performance in terms of predictive power and computational efficiency.
Moreover, we also show empirically that incorporating symmetry or reciprocity
properties can improve the generalization performance.


  Chemical imaging based on mid-infrared (MIR) spectroscopic contrast is an
important technique with a myriad of applications, including biomedical imaging
and environmental monitoring. Current MIR cameras, however, lack in performance
and are much less affordable compared to mature Si-based devices, which operate
in the visible and near-infrared. Here we demonstrate fast MIR chemical imaging
through non-degenerate two-photon absorption (NTA) in a standard Si-based
charge-coupled device (CCD). We show that wide-field MIR images can be obtained
at 100 ms exposure times using picosecond pulse energies of only a few fJ per
pixel through NTA directly on the CCD chip. Because this on-chip approach does
not rely on phase-matching, it is alignment-free and does not necessitate
complex post-processing of the images. We emphasize the utility of this
technique through chemically selective MIR imaging of polymers and biological
samples, including MIR videos of moving targets, physical processes and live
nematodes.


  Coarsening dynamics theory has successfully described the equilibration of a
broad class of systems.By studying the relaxation of a periodic array of
microcondensates immersed in a Fermi gas which can mediate long-range spin
interactions to simulate frustrated classical magnets, we show that coarsening
dynamics can be suppressed by geometrical frustration. The system is found to
eventually approach a metastable state which is robust against random field
noise and characterized by finite correlation lengths with the emergence of
topologically stable Z2 vortices. We find universal scaling laws with no
thermal-equilibrium analog that relate the correlation lengths and the number
of vortices to the degree of frustration in the system.


  We report the observation of two signatures of a pressure-induced topological
quantum phase transition in the polar semiconductor BiTeI using x-ray powder
diffraction and infrared spectroscopy. The x-ray data confirm that BiTeI
remains in its ambient-pressure structure up to 8 GPa. The lattice parameter
ratio c/a shows a minimum between 2.0-2.9 GPa, indicating an enhanced c-axis
bonding through pz band crossing as expected during the transition. Over the
same pressure range, the infrared spectra reveal a maximum in the optical
spectral weight of the charge carriers, reflecting the closing and reopening of
the semiconducting band gap. Both of these features are characteristics of a
topological quantum phase transition, and are consistent with a recent
theoretical proposal.


  As secure processors such as Intel SGX (with hyperthreading) become widely
adopted, there is a growing appetite for private analytics on big data. Most
prior works on data-oblivious algorithms adopt the classical PRAM model to
capture parallelism. However, it is widely understood that PRAM does not best
capture realistic multicore processors, nor does it reflect parallel
programming models adopted in practice.
  In this paper, we initiate the study of parallel data oblivious algorithms on
realistic multicores, best captured by the binary fork-join model of
computation. We first show that data-oblivious sorting can be accomplished by a
binary fork-join algorithm with optimal total work and optimal
(cache-oblivious) cache complexity, and in O(log n log log n) span (i.e.,
parallel time) that matches the best-known insecure algorithm. Using our
sorting algorithm as a core primitive, we show how to data-obliviously simulate
general PRAM algorithms in the binary fork-join model with non-trivial
efficiency. We also present results for several applications including list
ranking, Euler tour, tree contraction, connected components, and minimum
spanning forest. For a subset of these applications, our data-oblivious
algorithms asymptotically outperform the best known insecure algorithms. For
other applications, we show data oblivious algorithms whose performance bounds
match the best known insecure algorithms.
  Complementing these asymptotically efficient results, we present a practical
variant of our sorting algorithm that is self-contained and potentially
implementable. It has optimal caching cost, and it is only a log log n factor
off from optimal work and about a log n factor off in terms of span; moreover,
it achieves small constant factors in its bounds.


  We study the transmission over a network in which users send information to a
remote destination through relay nodes that are connected to the destination
via finite-capacity error-free links, i.e., a cloud radio access network. The
relays are constrained to operate without knowledge of the users' codebooks,
i.e., they perform oblivious processing - The destination, or central
processor, however, is informed about the users' codebooks. We establish a
single-letter characterization of the capacity region of this model for a class
of discrete memoryless channels in which the outputs at the relay nodes are
independent given the users' inputs. We show that both relaying \`a-la Cover-El
Gamal, i.e., compress-and-forward with joint decompression and decoding, and
"noisy network coding", are optimal. The proof of the converse part
establishes, and utilizes, connections with the Chief Executive Officer (CEO)
source coding problem under logarithmic loss distortion measure. Extensions to
general discrete memoryless channels are also investigated. In this case, we
establish inner and outer bounds on the capacity region. For memoryless
Gaussian channels within the studied class of channels, we characterize the
capacity under Gaussian channel inputs.


  PHENIX measurements are presented for the cross-section and double-helicity
asymmetry ($A_{LL}$) of inclusive $\pi^{0}$ production ($A_{LL}^{\pi^{0}}$) at
midrapidity from $p+p$ collisions at $\sqrt{s}=510$ GeV from data taken in 2012
and 2013 at the Relativistic Heavy Ion Collider (RHIC). The next-to-leading
order (NLO) perturbative QCD (pQCD) calculation agrees excellently with the
presented cross-section result. The $A_{LL}^{\pi^{0}}$ follows an increasingly
positive asymmetry as functions of $p_{T}$ and $\sqrt{s}$ at the fixed $x_{T}$.
The latest global analysis results, which support the positive spin
contribution of gluon ($\Delta{}G$), agrees excellently with the presented
asymmetry result. The asymmetry result extends the experimental sensitivity to
the previously unexplored $x$ region down to $x\sim0.01$ and provides
additional constraints on $\Delta{}G$.


  A survey is made of semileptonic and nonleptonic kaon decays in the framework
of chiral perturbation theory. The emphasis is on what has been done rather
than how it was done. The theoretical predictions are compared with available
experimental results.


  A ten-dimensional super-Poincare covariant formalism for the superstring was
recently developed which involves a BRST operator constructed from superspace
matter variables and a pure spinor ghost variable. A super-Poincare covariant
prescription was defined for computing tree amplitudes and was shown to
coincide with the standard RNS prescription.
  In this paper, picture-changing operators are used to define functional
integration over the pure spinor ghosts and to construct a suitable $b$ ghost.
A super-Poincare covariant prescription is then given for the computation of
N-point multiloop amplitudes. One can easily prove that massless N-point
multiloop amplitudes vanish for N<4, confirming the perturbative finiteness of
superstring theory. One can also prove the Type IIB S-duality conjecture that
$R^4$ terms in the effective action receive no perturbative contributions above
one loop.


  We demonstrate the existence and uniqueness of the solution to the Dirichlet
problem for a generalization of Hitchin's equation for diagonal harmonic
metrics on cyclic Higgs bundles. The generalized equations are formulated using
subharmonic functions. In this generalization, the coefficient exhibits worse
regularity than that in the original equation.


  The errors-in-variables (EIV) regression model, being more realistic by
accounting for measurement errors in both the dependent and the independent
variables, is widely adopted in applied sciences. The traditional EIV model
estimators, however, can be highly biased by outliers and other departures from
the underlying assumptions. In this paper, we develop a novel nonparametric
regression approach - the robust compound regression (RCR) analysis method for
the robust estimation of EIV models. We first introduce a robust and efficient
estimator called least sine squares (LSS). Taking full advantage of both the
new LSS method and the compound regression analysis method developed in our own
group, we subsequently propose the RCR approach as a generalization of those
two, which provides a robust counterpart of the entire class of the maximum
likelihood estimation (MLE) solutions of the EIV model, in a 1-1 mapping.
Technically, our approach gives users the flexibility to select from a class of
RCR estimates the optimal one with a predefined regression efficiency criterion
satisfied. Simulation studies and real-life examples are provided to illustrate
the effectiveness of the RCR approach.


  We find the optimal scheme for quantum phase estimation in the presence of
loss when no a priori knowledge on the estimated phase is available. We prove
analytically an explicit lower bound on estimation uncertainty, which shows
that, as a function of number of probes, quantum precision enhancement amounts
at most to a constant factor improvement over classical strategies


  HgCdTe detector arrays with a cutoff wavelength of ~10 ${\mu}$m intended for
the NEOCam space mission were subjected to proton beam irradiation at the
University of California Davis Crocker Nuclear Laboratory. Three arrays were
tested - one with 800 $\mu$m substrate intact, one with 30 $\mu$m substrate,
and one completely substrate-removed. The CdZnTe substrate, on which the HgCdTe
detector is grown, has been shown to produce luminescence in shorter wave
HgCdTe arrays that causes elevated signal in non-hit pixels when subjected to
proton irradiation. This testing was conducted to ascertain whether or not full
substrate removal is necessary. At the dark level of the dewar, we detect no
luminescence in non-hit pixels during proton testing for both the
substrate-removed detector array and the array with 30 ${\mu}$m substrate. The
detector array with full 800 ${\mu}$m substrate exhibited substantial
photocurrent for a flux of 103 protons/cm$^2$-s at a beam energy of 18.1 MeV (~
750 e$^-$/s) and 34.4 MeV ($\sim$ 65 e$^-$/s). For the integrated space-like
ambient proton flux level measured by the Spitzer Space Telescope, the
luminescence would be well below the NEOCam dark current requirement of <200
e$^-$/s, but the pattern of luminescence could be problematic, possibly
complicating calibration.


  Applying linear response and the magnetic force theorem in correlated density
functional theory, the inter-sublattice exchange constants of antiferromagnetic
Eu are calculated and found to vanish near the pressure of P$_c$=82 GPa, just
where magnetic order is observed experimentally to be lost. The Eu $4f^7$
moment remains unchanged at high pressure, again in agreement with
spectroscopic measurements, leaving the picture of perfect frustration of
interatomic Ruderman-Kittel-Kasuya-Yoshida couplings in a broad metallic
background, leaving a state of electrons strongly exchange coupled to
arbitrarily oriented, possibly quasistatic local moments. This strongly
frustrated state gives way to superconductivity at T$_c$=1.7K, observed
experimentally. These phenomena, and free energy considerations related to
correlations, suggest an unusual phase of matter that is discussed within the
scenarios of the Doniach Kondo lattice phase diagram, the metallic spin glass
class, and itinerant spin liquid or spin gas systems.


  Since the first appearance of the World Wide Web, people more rely on the Web
for their cyber social activities. The second phase of World Wide Web, named
Web 2.0, has been extensively attracting worldwide people that participate in
building and enjoying the virtual world. Nowadays, the next internet
revolution: Web3 is going to open new opportunities for traditional social
models. The decentralization property of Web3 is capable of breaking the
monopoly of the internet companies. Moreover, Web3 will lead a paradigm shift
from the Web as a publishing medium to a medium of interaction and
participation. This change will deeply transform the relations among users and
platforms, forces and relations of production, and the global economy.
Therefore, it is necessary that we technically, practically, and more broadly
take an overview of Web3. In this paper, we present a comprehensive survey of
Web3, with a focus on current technologies, challenges, opportunities, and
outlook. This article first introduces several major technologies of Web3.
Then, we illustrate the type of Web3 applications in detail. Blockchain and
smart contracts ensure that decentralized organizations will be less trusted
and more truthful than that centralized organizations. Decentralized finance
will be global, and open with financial inclusiveness for unbanked people. This
paper also discusses the relationship between the Metaverse and Web3, as well
as the differences and similarities between Web 3.0 and Web3. Inspired by the
Maslow's hierarchy of needs theory, we further conduct a novel hierarchy of
needs theory within Web3. Finally, several worthwhile future research
directions of Web3 are discussed.


  We show that a Fell bundle B = {B_t}_{t \in F}, over an arbitrary free group
F, is amenable, whenever it is orthogonal (in the sense that B_x^* B_y = 0, if
x and y are distinct generators of F) and semi-saturated (in the sense that
B_{ts} coincides with the closed linear span of B_t B_s, when the
multiplication ``ts'' involves no cancelation).


  The $A$-partition function $p_A(n)$ enumerates those partitions of $n$ whose
parts belong to a fixed (finite or infinite) set $A$ of positive integers. On
the other hand, the extended $A$-partition function
$p_A\left(\boldsymbol{\mu}\right)$ is defined as an multiplicative extension of
the $A$-partition function to a function on $A$-partitions. In this paper, we
investigate the Bessenrodt-Ono type inequality for a wide class of
$A$-partition functions. In particular, we examine the property for both the
$m$-ary partition function $b_m(n)$ and the $d$-th power partition function
$p_d(n)$. Moreover, we show that $b_m(\boldsymbol{\mu})$
($p_d(\boldsymbol{\mu})$) takes its maximum value at an explicitly described
set of $m$-ary partitions (power partitions), where $\boldsymbol{\mu}$ is an
$m$-ary partition (a power partition) of $n$. Additionally, we exhibit
analogous results for the Fibonacci partition function and the `factorial'
partition function. It is worth pointing out that an elementary combinatorial
reasoning plays a crucial role in our investigation.


  Following the paradigm of Boltzmann-BBGKY we propose a correlation entropy
(of the nth order) for an interacting quantum field, obtained by `slaving'
(truncation with causal factorization) of the higher (n+1 th) order correlation
functions in the Schwinger-Dyson system of equations. This renders an otherwise
closed system effectively open where dissipation arises. The concept of
correlation entropy is useful for addressing issues related to thermalization.
As a small yet important step in that direction we prove an H-theorem for the
correlation entropy of a quantum mechanical O(N) model with a Closed Time Path
Two Particle Irreducible Effective Action at the level of Next-to-Leading-Order
large N approximation. This model may be regarded as a field theory in $0$
space dimensions.


  Classical modular curves are of deep interest in arithmetic geometry. In this
survey we show how the work of Fumiyuki Momose is involved in order to list the
classical modular curves which satisfy that the set of quadratic points over
$\mathbb{Q}$ is infinite. In particular we recall results of Momose on
hyperelliptic modular curves and on automorphisms groups of modular curves.
Moreover, we fix some inaccuracies of the existing literature in few statements
concerning automorphism groups of modular curves and we make available
different results that are difficult to find a precise reference, for example:
arithmetical results on hyperelliptic and bielliptic curves (like the
arithmetical statement of a Harris and Silverman theorem (or the case $d=2$ of
a Abramovich and Harris theorem)) and on the conductor of elliptic curves over
$\mathbb{Q}$ parametrized by X(N).


  Many cellular processes are tightly connected to the dynamics of microtubules
(MTs). While in neuronal axons MTs mainly regulate intracellular trafficking,
they participate in cytoskeleton reorganization in many other eukaryotic cells,
enabling the cell to efficiently adapt to changes in the environment. We show
that the functional differences of MTs in different cell types and regions is
reflected in the dynamic properties of MT tips. Using plus-end tracking
proteins EB1 to monitor growing MT plus-ends, we show that MT dynamics and life
cycle in axons of human neurons significantly differ from that of fibroblast
cells. The density of plus-ends, as well as the rescue and catastrophe
frequencies increase while the growth rate decreases toward the fibroblast cell
margin. This results in a rather stable filamentous network structure and
maintains the connection between nucleus and membrane. In contrast, plus-ends
are uniformly distributed along the axons and exhibit diverse polymerization
run times and spatially homogeneous rescue and catastrophe frequencies, leading
to MT segments of various lengths. The probability distributions of the
excursion length of polymerization and the MT length both follow nearly
exponential tails, in agreement with the analytical predictions of a two-state
model of MT dynamics.


  During the first step of practical reasoning, i.e. deliberation, an
intelligent agent generates a set of pursuable goals and then selects which of
them he commits to achieve. An intelligent agent may in general generate
multiple pursuable goals, which may be incompatible among them. In this paper,
we focus on the definition, identification and resolution of these
incompatibilities. The suggested approach considers the three forms of
incompatibility introduced by Castelfranchi and Paglieri, namely the terminal
incompatibility, the instrumental or resources incompatibility and the
superfluity. We characterise computationally these forms of incompatibility by
means of arguments that represent the plans that allow an agent to achieve his
goals. Thus, the incompatibility among goals is defined based on the conflicts
among their plans, which are represented by means of attacks in an
argumentation framework. We also work on the problem of goals selection; we
propose to use abstract argumentation theory to deal with this problem, i.e. by
applying argumentation semantics. We use a modified version of the "cleaner
world" scenario in order to illustrate the performance of our proposal.


  Toeplitz's Square Peg Problem asks whether every continuous simple closed
curve in the plane contains the four vertices of a square. It has been proved
for various classes of sufficiently smooth curves, some of which are dense,
none of which are open. In this paper we prove it for several open classes of
curves, one of which is also dense. This can be interpreted in saying that the
Square Peg Problem is solved for generic curves. The latter class contains all
previously known classes for which the Square Peg Problem has been proved in
the affirmative. [footnote]
  We also prove results about rectangles inscribed in immersed curves. Finally,
we show that the problem of finding a regular octahedron on metric 2-spheres
has a "topological counter-example", that is, a certain test map with boundary
condition exists.


  Climate change increases the number of extreme weather events (wind and
snowstorms, heavy rains, wildfires) that compromise power system reliability
and lead to multiple equipment failures. Real-time and accurate detecting of
potential line failures is the first step to mitigating the extreme weather
impact and activating emergency controls. Power balance equations nonlinearity,
increased uncertainty in generation during extreme events, and lack of grid
observability compromise the efficiency of traditional data-driven failure
detection methods. At the same time, modern problem-oblivious machine learning
methods based on neural networks require a large amount of data to detect an
accident, especially in a time-changing environment. This paper proposes a
Physics-InformEd Line failure Detector (FIELD) that leverages grid topology
information to reduce sample and time complexities and improve localization
accuracy. Finally, we illustrate the superior empirical performance of our
approach compared to state-of-the-art methods over various test cases.


  The mass matrix for $\eta-\eta^\prime$ is derived in the flavor basis at
${\cal O}(p^4)$ of the chiral Lagrangian using the large $N$ approximation.
Under certain assumptions, the mixing angle $\phi=41.4^\circ$ and the decay
constants ratio $f_K/f_\pi=1.15$ are calculated in agreement with the data. It
appears that the FKS scheme arises as a special limit of the chiral Lagrangian.
Their mass matrix is obtained without the hypothesis on the mixing pattern of
the decay constants.


  We investigate theoretically the Andreev transport through a quantum dot
strongly coupled with a normal metal/ferromagnet and a superconductor
(N/F-QD-S), in which the interplay between the Kondo resonance and the Andreev
bound states (ABSs) has not been clearly clarified yet. Here we show that the
interference between the Kondo resonance and the ABSs modifies seriously the
lineshape of the Kondo resonance, which manifests as a Fano resonance. The
ferromagnetic lead with spin-polarization induces an effective field, which
leads to splitting both of the Kondo resonance and the ABSs. The
spin-polarization together with the magnetic field applied provides an
alternative way to tune the lineshape of the Kondo resonances, which is
dependent of the relative positions of the Kondo resonance and of the ABSs.
These results indicate that the interplay between the Kondo resonance and the
ABSs can significantly affect the Andreev transport, which could be tested by
experiments.


  The influence of alternating shear orientation and strain amplitude of cyclic
loading on yielding in amorphous solids is investigated using molecular
dynamics simulations. The model glass is represented via a binary mixture that
was rapidly cooled well below the glass transition temperature and then
subjected to oscillatory shear deformation. It was shown that periodic loading
at strain amplitudes above the critical value first induces structural
relaxation via irreversible displacements of clusters of atoms during a number
of transient cycles, followed by an increase in potential energy due to the
formation of a system-spanning shear band. Upon approaching the critical strain
amplitude from above, the number of transient cycles required to reach the
yielding transition increases. Interestingly, it was found that when the shear
orientation is periodically alternated in two or three dimensions, the number
of transient cycles is reduced but the critical strain amplitude remains the
same as in the case of periodic shear along a single plane. After the yielding
transition, the material outside the shear band continues strain-induced
relaxation, except when the shear orientation is alternated in three dimensions
and the glass is deformed along the shear band with the imposed strain
amplitude every third cycle.


  We investigate Anderson localization of light as occurring in ultra-short
excitations. A theory based on time dependent coupled-mode equations predicts
universal features in the spectrum of the transmitted pulse. In particular, the
process of strong localization of light is shown to correspond to the formation
of peaks in both the amplitude and in the group delay of the transmitted pulse.
Parallel ab-initio simulations made with Finite-Difference Time Domain codes
and molecular dynamics confirm theoretical predictions, while showing that
there exist an optimal degree of disorder for the strong localization.


  This article presents results of the observation of a project management
teaching-by-project course. It describe return of experience not only of
student but also of tutors one years after the course. Many problems are
identified like individual student evaluation, tutor distance, lake of
coordination, lake of communication. We ask tutor about the pertinence of an
instrumental solution, based upon dashboard, to solve problems of coordination
and evaluation identified. We made the hypothese that a cognitive tool will
improve too the knowledge construction and the learning process.


  Strong optical nonlinearities play a central role in realizing quantum
photonic technologies. In solid state systems, exciton-polaritons, which result
from the hybridization of material excitations and cavity photons, are an
attractive candidate to realize such nonlinearities. Here, the interaction
between excitons forms the basis of the polaritonic nonlinearity. While the
interaction between ground state excitons generates a notable optical
nonlinearity, the strength of such ground state interactions is generally not
sufficient to reach the regime of quantum nonlinear optics and strong
single-polariton interactions. Excited states, however, feature enhanced
interactions and therefore hold promise for accessing the quantum domain of
single-photon nonlinearities, as demonstrated with high-lying Rydberg states of
cold atomic systems. Excitons in excited states have recently been observed in
monolayer transition metal dichalcogenides. Here we demonstrate the formation
of exciton-polaritons using the first excited excitonic state in monolayer
tungsten diselenide (WSe2) embedded in a microcavity. Owing to the larger
exciton size compared to their ground state counterpart, the realized
polaritons exhibit an enhanced nonlinear response by more than an order of
magnitude, as evidenced through a modification of the cavity Rabi splitting.
The demonstration of excited exciton-polaritons in two-dimensional
semiconductors and their enhanced nonlinear response presents the first step
towards the generation of strong photon interactions in solid state systems, a
necessary building block for quantum photonic technologies.


  We propose free-electron Rabi oscillation by creating an isolated two-level
system in a synthetic energy space induced by laser. The {\pi}/2-pulse and
{\pi}-pulse in synthetic Rabi dynamics can function as 'beam splitters' and
'mirrors' for free-electron interferometry, allowing us to detect local
electromagnetic fields and plasmonic excitations. When the coupling field is
quantized, we can observe quantum and vacuum Rabi oscillations of the two-level
electron, which can be used to investigate the quantum statistics of optical
excitations and electron-photon entanglement. Recent advances in laser control
of electron microscopes and spectroscopes makes the experimental detection of
synthetic Rabi oscillations possible. However, observing the quantum Rabi
oscillation of electrons remains challenging. Our work has the potential to
advance various fundamentals and applications of resonant light-matter
interactions between low-energy electrons and quatum light.


  Main sequence turnoff ages in young open clusters are complicated by turnoffs
that are sparse, have high binarity fractions, can be affected by differential
reddening, and typically include a number of peculiar stars. Furthermore,
stellar rotation can have a significant effect on a star's photometry and
evolutionary timescale. In this paper we analyze in 12 nearby open clusters,
ranging from ages of 50 Myr to 350 Myr, how broadband UBV color-color relations
can be used to identify turnoff stars that are Be stars, blue stragglers,
certain types of binaries, or those affected by differential reddening. This
UBV color-color analysis also directly measures a cluster's E(B-V) and
estimates its [Fe/H]. The turnoff stars unaffected by these peculiarities
create a narrower and more clearly defined cluster turnoff. Using four common
isochronal models, two of which consider rotation, we fit cluster parameters
using these selected turnoff stars and the main sequence. Comparisons of the
photometrically fit cluster distances to those based on Gaia DR2 parallaxes
find that they are consistent for all clusters. For older (>100 Myr) clusters,
like the Pleiades and the Hyades, comparisons to ages based on the lithium
depletion boundary method finds that these cleaned turnoff ages agree to within
~10% for all four isochronal models. For younger clusters, however, only the
Geneva models that consider rotation fit turnoff ages consistent with
lithium-based ages, while the ages based on non-rotating isochrones quickly
diverge to become 30% to 80% younger. This illustrates the importance of
rotation for deriving ages in the youngest (<100 Myr) clusters.


  Superconducting nickelates appear to be difficult to synthesize. Since the
chemical reduction of ABO3 (A: rare earth; B transition metal) with CaH2 may
result in both, ABO2 and ABO2H, we calculate the topotactic H binding energy by
density functional theory (DFT). We find intercalating H is energetically
favorable for LaNiO2 but not for Sr-doped NdNiO2. This has dramatic
consequences for the electronic structure as determined by DFT+dynamical mean
field theory: that of 3d9 LaNiO2 is similar to (doped) cuprates, 3d8 LaNiO2H is
a two-orbital Mott insulator. Topotactical H might hence explain why some
nickelates are superconducting and others are not.


  This study explores the virtualization of classical reality and aims to
establish a clear framework to determine the limits and possibilities of
virtual reality. It addresses two primary questions: whether an observer's
senses can perceive a different reality through appropriate equipment, and
whether it is possible to simulate a reality without the laws of physics. As
virtual and augmented reality are increasingly used in various fields, it is
crucial to provide well-founded responses to these inquiries. Understanding the
limitations and achievability of virtual reality is essential for creating
realistic environments in education, entertainment, and other domains.
Additionally, considering the role of physics and scientific rigor in virtual
contexts is important. The study presents a theoretical framework divided into
three sections: Methods, Results, and Discussion. The Methods section explains
the nature of computers and their ability to create perceived virtual reality.
The Results section introduces the theoretical framework, emphasizing
observable simulation and interactive simulation and highlighting their
distinctions. Finally, the Discussion section builds upon the theoretical
foundation to provide comprehensive insights and answers to the research
questions. This study enhances our understanding of the boundaries and
possibilities of virtual reality, offering concrete answers and valuable
knowledge for the development and application of virtual reality in various
domains.


  We treat the problem of completing the moduli space for roots of line bundles
on curves. Special attention is devoted to higher spin curves within the
universal Picard scheme. Two new different constructions, both using line
bundles on nodal curves as boundary points, are carried out and compared with
pre-existing ones.


  Performing low-rank matrix completion with sensitive user data calls for
privacy-preserving approaches. In this work, we propose a novel noise addition
mechanism for preserving differential privacy where the noise distribution is
inspired by Huber loss, a well-known loss function in robust statistics. The
proposed Huber mechanism is evaluated against existing differential privacy
mechanisms while solving the matrix completion problem using the Alternating
Least Squares approach. We also propose using the Iteratively Re-Weighted Least
Squares algorithm to complete low-rank matrices and study the performance of
different noise mechanisms in both synthetic and real datasets. We prove that
the proposed mechanism achieves {\epsilon}-differential privacy similar to the
Laplace mechanism. Furthermore, empirical results indicate that the Huber
mechanism outperforms Laplacian and Gaussian in some cases and is comparable,
otherwise.


  Continuous-Time Quantum Monte Carlo (CT-QMC) method combined with Dynamical
Mean Field Theory (DMFT) is used to calculate both Periodic Anderson Model
(PAM) and Kondo Lattice Model (KLM). Different parameter sets of both models
are connected by the Schrieffer-Wolff transformation. For degeneracy N=2, a
special particle-hole symmetric case of PAM at half filling which always fixes
one electron per impurity site is compared with the results of the KLM. We find
a good mapping between PAM and KLM in the limit of large on-site Hubbard
interaction U for different properties like self-energy, quasiparticle residue
and susceptibility. This allows us to extract quasiparticle mass
renormalizations for the f electrons directly from KLM. The method is further
applied to higher degenerate case and to realsitic heavy fermion system CeRhIn5
in which the estimate of the Sommerfeld coefficient is proven to be close to
the experimental value.


  We summarize here our investigations on the deeply virtual Compton scattering
(DVCS) in the color dipole approach, implementing the dipole cross section
through the saturation model. The role played by its QCD evolution and the
skewedness effects in the DVCS cross section are discussed. The
phenomenological results are compared to the recent H1 and ZEUS experimental
data.


  We propose a strategy to enhance the atom-to-molecule conversion efficiency
near a Feshbach resonance. Based on the mean-field approximation, we derive the
fixed point solutions of the classical Hamiltonian. Rabi oscillation between
the atomic and molecular states around fixed point solutions and its
oscillation period are discussed. By designing a sequence of magnetic field
pulses in analogy with Ramsey experiments, we show that a much higher
atom-to-molecule conversion efficiency can be accessed by tuning the pulse
durations appropriately.


  The CryoEM single particle imaging method has recently received broad
attention in the field of structural biology for determining the structures of
biological molecules. The structures can be resolved to near-atomic resolutions
after rending a large number of CryoEM images measuring molecules in different
orientations. However, the factors for model resolution need to be further
explored. Here, we provide a theoretical framework in conjunction with
numerical simulations to gauge the influence of several key factors that are
determinant in model resolution. We found that the number of measured
projection images and the quality of each measurement (quantified using average
signal-noise-ratio) can be combined to a single factor, which is dominant to
the constructed model resolution. Furthermore, the intrinsic thermal motion of
the molecules and the defocus levels of the electron microscope both have
significant effects on the model resolution. These effects can be
quantitatively summarized using an analytical formula that provides a
theoretical guideline on structure resolutions for given experimental
measurements.


  The paradigm of Federated learning (FL) deals with multiple clients
participating in collaborative training of a machine learning model under the
orchestration of a central server. In this setup, each client's data is private
to itself and is not transferable to other clients or the server. Though FL
paradigm has received significant interest recently from the research
community, the problem of selecting the relevant clients w.r.t. the central
server's learning objective is under-explored. We refer to these problems as
Federated Relevant Client Selection (FRCS). Because the server doesn't have
explicit control over the nature of data possessed by each client, the problem
of selecting relevant clients is significantly complex in FL settings. In this
paper, we resolve important and related FRCS problems viz., selecting clients
with relevant data, detecting clients that possess data relevant to a
particular target label, and rectifying corrupted data samples of individual
clients. We follow a principled approach to address the above FRCS problems and
develop a new federated learning method using the Shapley value concept from
cooperative game theory. Towards this end, we propose a cooperative game
involving the gradients shared by the clients. Using this game, we compute
Shapley values of clients and then present Shapley value based Federated
Averaging (S-FedAvg) algorithm that empowers the server to select relevant
clients with high probability. S-FedAvg turns out to be critical in designing
specific algorithms to address the FRCS problems. We finally conduct a thorough
empirical analysis on image classification and speech recognition tasks to show
the superior performance of S-FedAvg than the baselines in the context of
supervised federated learning settings.


  The phenomenon of quantum entanglement marks one of the furthest departures
from classical physics and is indispensable for quantum information processing.
Despite its fundamental importance, the distribution of entanglement over long
distances trough photons is unfortunately hindered by unavoidable decoherence
effects. Entanglement distillation is a means of restoring the quality of such
diluted entanglement by concentrating it into a pair of qubits. Conventionally,
this would be done by distributing multiple photon pairs and distilling the
entanglement into a single pair. Here, we turn around this paradigm by
utilising pairs of single photons entangled in multiple degrees of freedom.
Specifically, we make use of the polarisation and the energy-time domain of
photons, both of which are extensively field-tested. We experimentally chart
the domain of distillable states and achieve relative fidelity gains up to 13.8
%. Compared to the two-copy scheme, the distillation rate of our single-copy
scheme is several orders of magnitude higher, paving the way towards
high-capacity and noise-resilient quantum networks.


  The time domain has been identified as one of the most important areas of
astronomical research for the next decade. The Virtual Observatory is in the
vanguard with dedicated tools and services that enable and facilitate the
discovery, dissemination and analysis of time domain data. These range in scope
from rapid notifications of time-critical astronomical transients to annotating
long-term variables with the latest modeling results. In this paper, we will
review the prior art in these areas and focus on the capabilities that the VAO
is bringing to bear in support of time domain science. In particular, we will
focus on the issues involved with the heterogeneous collections of (ancillary)
data associated with astronomical transients, and the time series
characterization and classification tools required by the next generation of
sky surveys, such as LSST and SKA.


  The ever-increasing volume of digital information necessitates efficient
methods for users to extract key insights from lengthy documents. Aspect-based
summarization offers a targeted approach, generating summaries focused on
specific aspects within a document. Despite advancements in aspect-based
summarization research, there is a continuous quest for improved model
performance. Given that large language models (LLMs) have demonstrated the
potential to revolutionize diverse tasks within natural language processing,
particularly in the problem of summarization, this paper explores the potential
of fine-tuning LLMs for the aspect-based summarization task. We evaluate the
impact of fine-tuning open-source foundation LLMs, including Llama2, Mistral,
Gemma and Aya, on a publicly available domain-specific aspect based summary
dataset. We hypothesize that this approach will enable these models to
effectively identify and extract aspect-related information, leading to
superior quality aspect-based summaries compared to the state-of-the-art. We
establish a comprehensive evaluation framework to compare the performance of
fine-tuned LLMs against competing aspect-based summarization methods and
vanilla counterparts of the fine-tuned LLMs. Our work contributes to the field
of aspect-based summarization by demonstrating the efficacy of fine-tuning LLMs
for generating high-quality aspect-based summaries. Furthermore, it opens doors
for further exploration of using LLMs for targeted information extraction tasks
across various NLP domains.


  Pole skipping is a recently discovered subtle effect in the thermal energy
density retarded two point function at a special point in the complex
$(\omega,p)$ planes. We propose that pole skipping is determined by the stress
tensor contribution to many-body chaos, and the special point is at
$(\omega,p)_\text{p.s.}= i \lambda^{(T)}(1,1/u_B^{(T)})$, where
$\lambda^{(T)}=2\pi/\beta$ and $u_B^{(T)}$ are the stress tensor contributions
to the Lyapunov exponent and the butterfly velocity respectively. While this
proposal is consistent with previous studies conducted for maximally chaotic
theories, where the stress tensor dominates chaos, it clarifies that one cannot
use pole skipping to extract the Lyapunov exponent of a theory, which obeys
$\lambda\leq \lambda^{(T)}$. On the other hand, in a large class of strongly
coupled but non-maximally chaotic theories $u_B^{(T)}$ is the true butterfly
velocity and we conjecture that $u_B\leq u_B^{(T)}$ is a universal bound. While
it remains a challenge to explain pole skipping in a general framework, we
provide a stringent test of our proposal in the large-$q$ limit of the SYK
chain, where we determine $\lambda,\, u_B,$ and the energy density two point
function in closed form for all values of the coupling, interpolating between
the free and maximally chaotic limits. Since such an explicit expression for a
thermal correlator is one of a kind, we take the opportunity to analyze many of
its properties: the coupling dependence of the diffusion constant, the
dispersion relations of poles, and the convergence properties of all order
hydrodynamics.


  In some models of thermal relic dark matter, the relic abundance may be set
by inelastic scattering processes (rather than annihilations) becoming
inefficient as the universe cools down. This effect has been called
coscattering. We present a procedure to numerically solve the full
momentum-dependent Boltzmann equations in coscattering, which allows for a
precise calculation of the dark matter relic density including the effects of
early kinetic decoupling. We apply our method to a simple model, containing a
fermionic SU(2) triplet and a fermionic singlet with electroweak-scale masses,
at small triplet-singlet mixing. The relic density can be set by either
coannihilation or, at values of the mixing angle $\theta\lesssim 10^{-5}$, by
coscattering. We identify the parameter ranges which give rise to the observed
relic abundance. As a special case, we study bino-like dark matter in split
supersymmetry at large $\mu$.


  We demonstrate a fully-integrated multipurpose microwave frequency
identification system on silicon-on-insulator platform. Thanks to its
multipurpose features, the chip is able to identify different types of
microwave signals, including single-frequency, multiple-frequency, chirped and
frequency-hopping microwave signals, as well as discriminate instantaneous
frequency variation among the frequency-modulated signals. This demonstration
exhibits fully integrated solution and fully functional microwave frequency
identification, which can meet the requirements in reduction of size, weight
and power for future advanced microwave photonic processor.


  In this note, we concentrate on the backward error of the equality
constrained indefinite least squares problem. For the normwise backward error
of the equality constrained indefinite least square problem, we adopt the
linearization method to derive the tight estimate for the exact backward
normwise error. The numerical examples show that the linearization estimate is
effective for the normwise backward errors.


  Alarmed by the volume of disinformation that was assumed to have taken place
during the 2016 US elections, scholars, politics and journalists predicted the
worst when the first deepfakes began to emerge in 2018. After all, US Elections
2020 were believed to be the most secure in American history. This paper seeks
explanations for an apparent contradiction: we believe that it was precisely
the multiplication and conjugation of different types of warnings and fears
that created the conditions that prevented malicious political deepfakes from
affecting the 2020 US elections. From these warnings, we identified four
factors (more active role of social networks, new laws, difficulties in
accessing Artificial Intelligence and better awareness of society). But while
this formula has proven to be effective in the case of the United States, 2020,
it is not correct to assume that it can be repeated in other political
contexts.


  We investigate properties of Waring decompositions of real homogeneous forms.
We study the moduli of real decompositions, so-called Space of Sums of Powers,
naturally included in the Variety of Sums of Powers. Explicit results are
obtained for quaternary quadrics, relating the algebraic boundary of ${\rm
SSP}$ to various loci in the Hilbert scheme of four points in $\mathbb{P}^3$.
Further, we study the locus of general real forms whose real rank coincides
with the complex rank. In case of quaternary quadrics the boundary of this
locus is a degree forty hypersurface
$J(\sigma_3(v_3(\mathbb{P}^3)),\tau(v_3(\mathbb{P}^3)))$.


  Recently, the results of the first experimental test for entangled photons
closing the detection loophole (also referred to as the fair sampling loophole)
were published (Vienna, 2013). From the theoretical viewpoint the main
distinguishing feature of this long-aspired experiment was that the Eberhard
inequality was used. Almost simultaneously another experiment closing this
loophole was performed (Urbana-Champaign, 2013) and it was based on the
Clauser-Horne inequality (for probabilities). The aim of this note is to
analyze the mathematical and experimental equivalence of tests based on the
Eberhard inequality and various forms on the Clauser-Horne inequality. The
structure of the mathematical equivalence is nontrivial. In particular, it is
necessary to distinguish between algebraic and statistical equivalence.
Although the tests based on these inequalities are algebraically equivalent,
they need not be equivalent statistically, i.e., theoretically the level of
statistical significance can drop under transition from one test to another (at
least for finite samples). Nevertheless, the data collected in the Vienna-test
implies not only a statistically significant violation of the Eberhard
inequality, but also of the Clauser-Horne inequality (in the ratio-rate form):
for both a violation $>60\sigma.$


  Very few low-ionization broad absorption line (LoBAL) QSOs have been found at
high redshifts to date. One high-redshift LoBAL QSO, J0122+1216, was recently
discovered at the Lijiang 2.4-m Telescope with an initial redshift
determination of 4.76. Aiming to investigate its physical properties, we
carried out follow-up observations in the optical and near-IR spectroscopy.
Near-IR spectra from UKIRT and P200 confirms that it is a LoBAL, with a new
redshift determination of $4.82\pm0.01$ based on the \mgii~ emission-line. The
new \mgii~ redshift determination reveals strong blueshifts and asymmetry of
the high-ionization emission lines. We estimated a black hole mass of $\sim
2.3\times 10^9 M_\odot$ and Eddington ratio of $\sim 1.0$ according to the
empirical \mgii-based single-epoch relation and bolometric correction factor.
It is possible that strong outflows are the result of an extreme quasar
environment driven by the high Eddington ratio. A lower limit on the outflowing
kinetic power ($>0.9\% L_{Edd}$) was derived from both emission and absorption
lines, indicating these outflows play a significant role in the feedback
process to regulate the growth of its black hole as well as host galaxy
evolution.


  We establish the existence of a family of piecewise linear invariant curves
in a two-parameter family of piecewise isometries on the upper half-plane which
are embeddings of interval exchange transformations and give rise to layers of
invariant regions. We note that the restriction of the piecewise isometry to
the union of these regions is a piecewise isometry that contains non-convex
atoms, though we conjecture that the non-convexity does not have a pathological
effect on the uniqueness of cell encodings in this case. We also show the
existence of a trapezoidal piecewise isometry for which the dynamics on the top
and bottom edges are distinct 2-interval exchange transformations.


  We work towards a unifying paradigm for accelerating policy optimization
methods in reinforcement learning (RL) by integrating foresight in the policy
improvement step via optimistic and adaptive updates. Leveraging the connection
between policy iteration and policy gradient methods, we view policy
optimization algorithms as iteratively solving a sequence of surrogate
objectives, local lower bounds on the original objective. We define optimism as
predictive modelling of the future behavior of a policy, and adaptivity as
taking immediate and anticipatory corrective actions to mitigate accumulating
errors from overshooting predictions or delayed responses to change. We use
this shared lens to jointly express other well-known algorithms, including
model-based policy improvement based on forward search, and optimistic
meta-learning algorithms. We analyze properties of this formulation, and show
connections to other accelerated optimization algorithms. Then, we design an
optimistic policy gradient algorithm, adaptive via meta-gradient learning, and
empirically highlight several design choices pertaining to acceleration, in an
illustrative task.


  We study the nucleation of quark matter drops at the center of cold
deleptonized neutron stars. This is relevant in the determination of the
critical mass $M_{cr}$ of hadronic stars above which it is possible a
transition to a quark star (strange or hybrid). We investigate the dependence
of $M_{cr}$ upon the parameters of the quark model (the Bag constant $B$, the
pairing gap $\Delta$, and the surface tension $\sigma$ of the quark-hadron
interphase) and for different parametrization of the hadronic equations of
state. The dependence of $M_{cr}$ on $B$, $\Delta$ and $\sigma$ is mild if the
parameters of the quark model correspond to hybrid stars, and strong if they
correspond to strange stars. For a large part of the parameter space
corresponding to hybrid stars, the critical mass is very close (but smaller
than) the maximum mass of hadronic stars, and therefore compatible with a
"mixed" population of compact stars (pure hadronic up to the critical mass and
hybrid above the critical mass). For very large $B$ the critical mass is never
smaller than the maximum mass of hadronic stars, implying that quark stars
cannot form through the here studied mechanism. The energy released in the
conversion is $3 \times 10^{52}$ erg - $4 \times 10^{53}$ erg, i.e. sufficient
to power a gamma ray burst.


  The generalized Chaplygin gas (GCG) model allows for an unified description
of the cosmologically recent accelerated expansion of the Universe and of the
evolution of energy density perturbations. This dark energy - dark matter
unification is achieved through a rather exotic background fluid whose equation
of state is given by $p = - A/\rho^{\alpha}$, where $A$ is a positive constant.
Observational constraints arising from bounds on the locations of the first few
peaks and troughs of the Cosmic Microwave Background Radiation (CMBR) power
spectrum from recent WMAP and BOOMERanG experiments are consistent with the
model for $\alpha \lsim 0.6$ assuming that $0 < \alpha \le 1$. Most recent
Type-Ia Supernova data indicates however, that the range $\alpha > 1 $ must be
considered.


  We evaluate string one-loop contributions to the Einstein-Hilbert term in
toroidal minimally supersymmetric type IIB orientifolds with D-branes. These
have potential applications to the determination of quantum corrections to the
moduli Kahler metric in these models.


  Deep neural networks are known to be vulnerable to unseen data: they may
wrongly assign high confidence stcores to out-distribuion samples. Recent works
try to solve the problem using representation learning methods and specific
metrics. In this paper, we propose a simple, yet effective post-hoc anomaly
detection algorithm named Test Time Augmentation Anomaly Detection (TTA-AD),
inspired by a novel observation. Specifically, we observe that in-distribution
data enjoy more consistent predictions for its original and augmented versions
on a trained network than out-distribution data, which separates
in-distribution and out-distribution samples. Experiments on various
high-resolution image benchmark datasets demonstrate that TTA-AD achieves
comparable or better detection performance under dataset-vs-dataset anomaly
detection settings with a 60%~90\% running time reduction of existing
classifier-based algorithms. We provide empirical verification that the key to
TTA-AD lies in the remaining classes between augmented features, which has long
been partially ignored by previous works. Additionally, we use RUNS as a
surrogate to analyze our algorithm theoretically.


  An overview of ALICE results on the measurement of J/{\psi} production in pp
collisions at $\sqrt{s}$ = 7 TeV collected during the LHC Run-1 period is
presented, as well as first results at forward rapidity from pp collisions at
$\sqrt{s}$ = 13 TeV collected during the LHC Run-2 period. In particular, the
measurement of J/{\psi} production as a function of transverse momentum and
charged-particle multiplicity are discussed and compared to theoretical model
calculations.


  We study processes at the transition region between hot (rare) and cold
(dense) plasma in the collisionless regime. We use a 3-dimensional
electromagnetic particle-in-cell (3-D PIC) relativistic code. Motivated by the
transition region in the solar atmosphere the temperature and density ratio of
the plasmas is chosen as 100 and 0.01, respectively. For better understanding
of studied processes we make two types of computations: a) without any
interactions among plasma particles (free expansion) and b) with the full
electromagnetic interactions. In both the cases we found that the flux of cold
plasma electrons and protons from colder plasma to hotter one dominates over
the flux of hot plasma electrons and protons in the opposite direction. Thus,
the plasma in the hotter part of the system becomes colder and denser during
time evolution. In the case without any interactions among particles the cold
plasma electrons and protons freely penetrate into the hot plasma. But, the
cold plasma electrons are faster than cold plasma protons and therefore they
penetrate deeper into the hotter part of the system than the protons. Thus, the
cooling of the electron and proton components of the plasma in the hotter part
of the system is different. On the other hand, in the case with the
electromagnetic interactions, owing to the plasma property, which tries to keep
the total electric current constant everywhere (close to zero in our case), the
cold plasma electrons penetrate into the hotter part of the system together
with the cold plasma protons. The plasma waves generated at the transition
region during these processes reduce the number of electrons escaping from the
hot plasma into the colder one. Therefore these waves support a temperature
jump between hot and cold plasma.


  We construct normed spaces of real-valued functions with controlled growth on
possibly infinite-dimensional state spaces such that semigroups of positive,
bounded operators $(P_t)_{t\ge 0}$ thereon with $\lim_{t\to 0+}P_t f(x)=f(x)$
are in fact strongly continuous. This result applies to prove optimal rates of
convergence of splitting schemes for stochastic (partial) differential
equations with linearly growing characteristics and for sets of functions with
controlled growth. Applications are general Da Prato-Zabczyk type equations and
the HJM equations from interest rate theory.


  The primary focus of this dissertation is the study of the Casimir effect and
the possibility that this phenomenon may serve as a mechanism to mediate higher
dimensional stability, and also as a possible mechanism for creating a small
but non-zero vacuum energy density. In chapter one we review the nature of the
quantum vacuum and discuss the different contributions to the vacuum energy
density arising from different sectors of the standard model. Next, in chapter
two, we discuss cosmology and the introduction of the cosmological constant
into Einstein's field equations. In chapter three we explore the Casimir effect
and study a number of mathematical techniques used to obtain a finite physical
result for the Casimir energy. We also review the experiments that have
verified the Casimir force. In chapter four we discuss the introduction of
extra dimensions into physics. We begin by reviewing Kaluza Klein theory, and
then discuss three popular higher dimensional models: bosonic string theory,
large extra dimensions and warped extra dimensions. Chapter five is devoted to
an original derivation of the Casimir energy we derived for the scenario of a
higher dimensional vector field coupled to a scalar field in the fifth
dimension. In chapter six we explore a range of vacuum scenarios and discuss
research we have performed regarding moduli stability. Chapter seven explores a
novel approach to spacecraft propulsion we have proposed based on the idea of
manipulating the extra dimensions of string/M theory. Finally, in chapter 8, we
discuss some issues in heterotic string phenomenology derived from the free
fermionic approach.


  Distinguishing and controlling the extent of Mottness is important for
materials where the energy scales of the onsite Coulomb repulsion U and the
bandwidth W are comparable. Here we report the ultrafast electronic dynamics of
1T-TaS$_2$ by ultrafast time- and angle-resolved photoemission spectroscopy. A
comparison of the electron dynamics for the newly-discovered intermediate phase
(I-phase) as well as the low-temperature commensurate charge density wave
(C-CDW) phase shows distinctive dynamics. While the I-phase is characterized by
an instantaneous response and nearly time-resolution-limited fast relaxation
(~200 fs), the C-CDW phase shows a delayed response and a slower relaxation (a
few ps). Such distinctive dynamics refect the different relaxation mechanisms
and provide nonequilibrium signatures to distinguish the Mott insulating
I-phase from the C-CDW band insulating phase. Moreover, a light-induced
bandwidth reduction is observed in the C-CDW phase, pushing it toward the Mott
insulating phase. Our work demonstrates the power of ultrafast light-matter
interaction in both distinguishing and controlling the extent of Mottness on
the ultrafast timescale.


  Two active galactic nuclei have been detected at TeV energies using the
atmospheric Cherenkov imaging technique. The Whipple Observatory gamma-ray
telescope has been used to observe all the BL Lacertae objects in the northern
hemisphere out to a redshift of 0.1. We report the tentative detection of VHE
emission from a third BL Lac object, 1ES 2344+514. Progress in extending this
survey out to z=0.2 will also be reported.


  This PhD thesis explores the similarities between integrable spin chains and
quantum field theories, such as Super Yang Mills. We first study integrable
spin chains and build explicitly a polynomial "Backlund flow" and polynomial
"Q-operators", which allow to diagonalize the Hamiltonian. We then study
integrable field theories et show how to obtain "Q-functions", analogous to the
Q-operators built for spin chains. It turns out that several important
informations are contained in the analytic properties of these Q -functions.
That allows to obtain, in the framework of the thermodynamic Bethe ansatz, a
finite number of non-linear integral equations encoding the finite-size
spectrum of the theory which we study. This system of equations is equivalent
to an infinite system of equations, known as "Y-system", which had been quite
recently conjectured in the case of the AdS/CFT duality.


  We made point-contact measurements with Au tips on La_{2-x}Sr_{x}CuO_{4}
samples with 0.08 < x < 0.20 to investigate the relationship between
superconducting gap and pseudogap. We obtained junctions whose conductance
curves presented typical Andreev reflection features at all temperatures from
4.2 K up to T_c^A close to the bulk T_c. Their fit with the
BTK-Tanaka-Kashiwaya model gives good results if a (s+d)-wave gap symmetry is
used. The doping dependence of the low temperature dominant isotropic gap
component Delta_{s} follows very well the T_{c} vs. x curve. These results
support the separation between the superconducting (Andreev) gap and the
pseudogap measured by angle-resolved photoemission spectroscopy (ARPES) and
tunneling.


  Let $C$ be a smooth curve of genus $g \geq 1$ and let $C^{(2)}$ be its second
symmetric product. In this note we prove that if $C$ is very general, then the
blow-up of $C^{(2)}$ at a very general point has non-polyhedral
pseudo-effective cone. The strategy is to consider first the case of
hyperelliptic curves and then to show that having polyhedral pseudo-effective
cone is a closed property for families of surfaces.


  We construct infinite number of conserved nonlocal charges for type IIB
superstring on the AdS5xS5 space in the conformal gauge without assuming any
kappa gauge fixing, and show that they satisfy the super Yangian algebra. The
resultant algebra is the same as our previous work, where a special gauge was
assumed in such a way that the Noether current satisfies a flatness condition.
However the flatness condition for the Noether current of a superstring on the
AdS space is broken in general. We show that the anomalous contribution is
absorbed into the current where fermionic constraints play an essential role,
and a resultant conserved nonlocal charge has different expression satisfying
the same super Yangian algebra.


  Statistical properties of spike trains measured from a sensory neuron in-vivo
are studied experimentally and theoretically. Experiments are performed on an
identified neuron in the visual system of the blowfly. It is shown that the
spike trains exhibit universal behavior over short time, modulated by a
stimulus-dependent envelope over long time. A model of the neuron as a
nonlinear oscillator driven by noise and an external stimulus, is suggested to
account for these results. The model enables a theoretic distinction of the
effects of internal neuronal properties from effects of external stimulus
properties, and their identification in the measured spike trains. The
universal regime is characterized by one dimensionless parameter, representing
the internal degree of irregularity, which is determined both by the
sensitivity of the neuron and by the properties of the noise. The envelope is
related in a simple way to properties of the input stimulus as seen through
nonlinearity of the neural response. Explicit formulas are derived for
different statistical properties in both the universal and the
stimulus-dependent regimes. These formulas are in very good agreement with the
data in both regimes.


  The production of W-pairs is analysed in a data sample collected by ALEPH at
a mean centre-of-mass energy of 188.6 GeV, corresponding to an integrated
luminosity of 174.2 pb^-1. Cross sections are given for different topologies of
W decays into leptons or hadrons. Combining all final states and assuming
Standard Model branching fractions, the total W-pair cross section is measured
to be 15.71 +- 0.34 (stat) +- 0.18 (syst) pb. Using also the W-pair data
samples collected by ALEPH at lower centre-of-mass energies, the decay
branching fraction of the W boson into hadrons is measured to be BR (W >
hadrons) = 66.97 +- 0.65 (stat) +- 0.32 (syst) %, allowing a determination of
the CKM matrix element |V(cs)|= 0.951 +- 0.030 (stat) +- 0.015 (syst).


  We consider a three-particle quantum system in dimension three composed of
two identical fermions of mass one and a different particle of mass $m$. The
particles interact via two-body short range potentials. We assume that the
Hamiltonians of all the two-particle subsystems do not have bound states with
negative energy and, moreover, that the Hamiltonians of the two subsystems made
of a fermion and the different particle have a zero-energy resonance. Under
these conditions and for $m<m^* = (13.607)^{-1}$, we give a rigorous proof of
the occurrence of the Efimov effect, i.e., the existence of infinitely many
negative eigenvalues for the three-particle Hamiltonian $H$. More precisely, we
prove that for $m>m^*$ the number of negative eigenvalues of $H$ is finite and
for $m<m^*$ the number $N(z)$ of negative eigenvalues of $H$ below $z<0$ has
the asymptotic behavior $N(z) \sim \mathcal C(m) |\log|z||$ for $z \rightarrow
0^-$. Moreover, we give an upper and a lower bound for the positive constant
$\mathcal C(m)$.


  We investigate the role of equilibrium methods and stress transfer range in
describing the process of damage. We find that equilibrium approaches are not
applicable to the description of damage and the catastrophic failure mechanism
if the stress transfer is short ranged. In the long range limit, equilibrium
methods apply only if the healing mechanism associated with ruptured elements
is instantaneous. Furthermore we find that the nature of the catastrophic
failure depends strongly on the stress transfer range. Long range transfer
systems have a failure mechanism that resembles nucleation. In short range
stress transfer systems, the catastrophic failure is a continuous process that,
in some respects, resembles a critical point.


  Network operators are looking towards LTE License Assisted Access (LAA) as a
means of extending capacity by offloading traffic to unlicensed bands. However,
operation in these bands requires abiding to certain coexistence rules in terms
of channel access. The description of these rules in existing literature is not
always in line with the latest standards. Therefore, in this paper, we clarify
the operation of LAA, focusing on channel access and methods of providing
Quality of Service (QoS) support. In terms of coexistence, we evaluate the
impact of LAA under its various QoS settings on Wi-Fi performance in an
experimental testbed. Finally, we describe the upcoming research challenges for
LTE-based technologies in unlicensed bands considering the latest developments.


  The consequences of structured flows continue to be a pressing topic in
relating spectral data to physical processes occurring in massive star winds.
In a preceding paper, our group reported on hydrodynamic simulations of
hypersonic flow past a rigid spherical clump to explore the structure of bow
shocks that can form around wind clumps. Here we report on profiles of emission
lines that arise from such bow shock morphologies. To compute emission line
profiles, we adopt a two component flow structure of wind and clumps using two
"beta" velocity laws. While individual bow shocks tend to generate double
horned emission line profiles, a group of bow shocks can lead to line profiles
with a range of shapes with blueshifted peak emission that depends on the
degree of X-ray photoabsorption by the interclump wind medium, the number of
clump structures in the flow, and the radial distribution of the clumps. Using
the two beta law prescription, the theoretical emission measure and temperature
distribution throughout the wind can be derived. The emission measure tends to
be power law, and the temperature distribution broad in terms of wind velocity.
Although restricted to the case of adiabatic cooling, our models highlight the
influence of bow shock effects for hot plasma temperature and emission measure
distributions in stellar winds and their impact on X-ray line profile shapes.
Previous models have focused on geometrical considerations of the clumps and
their distribution in the wind. Our results represent the first time that the
temperature distribution of wind clump structures are explicitly and
self-consistently accounted in modeling X-ray line profile shapes for massive
stars.


  We present a complete solution to the cyclotron-synchrotron radiation due to
an isotropic distribution of electrons moving in a magnetic field. We make no
approximations in the calculations other than artificially broadening the
harmonics by a small amount in order to facilitate the numerics. In contrast to
previous calculations, we sum over all relevant harmonics and integrate over
all particle and observer angles relative to the magnetic field. We present
emission spectra for electron temperatures $T=5\times10^8$ K, $10^9$ K,
$2\times10^9$ K to $3.2\times10^{10}$ K, and provide simple fitting formulae
which give a fairly accurate representation of the detailed results. For
$T\geq3.2\times10^{10}$ K, the spectrum is represented well by the asymptotic
synchrotron formula, which is obtained by assuming that the radiating electrons
have Lorentz factors large compared to unity. We give an improved fitting
formula also for this asymptotic case.


  Kernel methods provide a powerful framework for non parametric learning. They
are based on kernel functions and allow learning in a rich functional space
while applying linear statistical learning tools, such as Ridge Regression or
Support Vector Machines. However, standard kernel methods suffer from a
quadratic time and memory complexity in the number of data points and thus have
limited applications in large-scale learning. In this paper, we propose Snacks,
a new large-scale solver for Kernel Support Vector Machines. Specifically,
Snacks relies on a Nystr\"om approximation of the kernel matrix and an
accelerated variant of the stochastic subgradient method. We demonstrate
formally through a detailed empirical evaluation, that it competes with other
SVM solvers on a variety of benchmark datasets.


  Let $H = (V_H, A_H)$ be a digraph which may contain loops, and let $D = (V_D,
A_D)$ be a loopless digraph with a coloring of its arcs $c: A_D \to V_H$. An
$H$-walk of $D$ is a walk $(v_0, \dots, v_n)$ of $D$ such that $(c(v_{i-1},
v_i), c(v_i, v_{i+1}))$ is an arc of $H$, for every $1 \le i \le n-1$. For $u,
v \in V_D$, we say that $u$ reaches $v$ by $H$-walks if there exists an
$H$-walk from $u$ to $v$ in $D$. A subset $S \subseteq V_D$ is a kernel by
$H$-walks of $D$ if every vertex in $V_D \setminus S$ reaches by $H$-walks some
vertex in $S$, and no vertex in $S$ can reach another vertex in $S$ by
$H$-walks.
  A panchromatic pattern is a digraph $H$ such that every arc-colored digraph
$D$ has a kernel by $H$-walks. In this work, we prove that every digraph $H$ is
either a panchromatic pattern, or the problem of determining whether an
arc-colored digraph $D$ has a kernel by $H$-walks is $NP$-complete.