  The construction industry has demonstrated a high frequency and severity of
accidents. Construction accidents are the result of the interaction between
unsafe work conditions and workers unsafe behaviors. Given this relation,
perceived risk is determined by an individual response to a potential work
hazard during the work. As such, risk perception is critical to understand
workers unsafe behaviors. Established methods of assessing workers perceived
risk have mainly relied on surveys and interviews. However, these post-hoc
methods, which are limited to monitoring dynamic changes in risk perception and
conducting surveys at a construction site, may prove cumbersome to workers.
Additionally, these methods frequently suffer from self-reported bias. To
overcome the limitations of previous subjective measures, this study aims to
develop a framework for the objective and continuous prediction of construction
workers perceived risk using physiological signals [e.g., electrodermal
activity (EDA)] acquired from workers wristband-type biosensors. To achieve
this objective, physiological signals were collected from eight construction
workers while they performed regular tasks in the field. Various filtering
methods were applied to exclude noises recorded in the signal and to extract
various features of the signals as workers experienced different risk levels.
Then, a supervised machine-learning model was trained to explore the
applicability of the collected physiological signals for the prediction of risk
perception. The results showed that features based on EDA data collected from
wristbands are feasible and useful to the process of continuously monitoring
workers perceived risk during ongoing work. This study contributes to an
in-depth understanding of construction workers perceived risk by developing a
noninvasive means of continuously monitoring workers perceived risk.


  Theoretical and experimental work concerned with dynamic fluctuations has
developed into a very active and fascinating subfield of mesoscopic physics. We
present a review of this development focusing on shot noise in small electric
conductors. Shot noise is a consequence of the quantization of charge. It can
be used to obtain information on a system which is not available through
conductance measurements. In particular, shot noise experiments can determine
the charge and statistics of the quasiparticles relevant for transport, and
reveal information on the potential profile and internal energy scales of
mesoscopic systems. Shot noise is generally more sensitive to the effects of
electron-electron interactions than the average conductance. We present a
discussion based on the conceptually transparent scattering approach and on the
classical Langevin and Boltzmann-Langevin methods; in addition a discussion of
results which cannot be obtained by these methods is provided. We conclude the
review by pointing out a number of unsolved problems and an outlook on the
likely future development of the field.


  Generalised Faraday rotation can induce frequency-dependent conversion
between the linear and circular polarisation spectra of compact radio sources
such as pulsars, fast radio bursts and active galactic nuclei. I devise a
simple phenomenological model that can be used to measure the effects of
generalised Faraday rotation on the linearly and circularly polarised spectra
of these sources. The model is theory-agnostic, with an arbitrary wavelength
dependence, and hence can accommodate for a variety of potential generalised
Faraday rotation inducing media. It can also be combined with additional
observables to infer the physical properties of the intervening medium.


  The REX (Radio-Emitting X-ray sources) is a catalogue produced by
cross-matching X-ray data from the ROSAT-PSPC archive of pointed observations
and radio data from the NRAO VLA Sky Survey, aimed at the selection of blazars.
From the REX catalogue, we select a well defined and statistically complete
sample of high-energy peaked BL Lac (HBL). HBL are expected to be the most
numerous class of extragalactic TeV emitting sources. Specifically, we have
considered only the REX sources in the currently planned CTA extragalactic
survey area satisfying specific criteria and with an optical spectroscopic
confirmation. We obtain 46 HBL candidates that we called Te-REX (TeV-emitting
REX). We estimate the very high-energy gamma-ray emission, in the TeV domain,
using an empirical approach i.e. using specific statistical relations between
gamma-rays (at GeV energies) and radio/X-rays properties observed in bright HBL
from the literature. We compare the spectral energy distributions (SEDs) with
the sensitivities of current and upcoming Cherenkov telescopes and we predict
that 14 Te-REX could be detectable with 50 hours of observations of CTA and 7
of them also with current Cherenkov facilities in 50 hours. By extrapolating
these numbers on the total extragalactic sky, we predict that about 800 HBL
could be visible in pointed CTA observations and about 400 with current
Cherenkov telescopes in 50 hours. Interestingly, our predictions show that a
non-negligible fraction (about 30%) of the HBL that will be detectable by CTA
is composed of relatively weak objects whose optical nuclear emission is
swamped by the host-galaxy light and not (yet) detected by Fermi-LAT.


  We focus on the commonly used synchronous Gradient Descent paradigm for
large-scale distributed learning, for which there has been a growing interest
to develop efficient and robust gradient aggregation strategies that overcome
two key system bottlenecks: communication bandwidth and stragglers' delays. In
particular, Ring-AllReduce (RAR) design has been proposed to avoid bandwidth
bottleneck at any particular node by allowing each worker to only communicate
with its neighbors that are arranged in a logical ring. On the other hand,
Gradient Coding (GC) has been recently proposed to mitigate stragglers in a
master-worker topology by allowing carefully designed redundant allocation of
the data set to the workers. We propose a joint communication topology design
and data set allocation strategy, named CodedReduce (CR), that combines the
best of both RAR and GC. That is, it parallelizes the communications over a
tree topology leading to efficient bandwidth utilization, and carefully designs
a redundant data set allocation and coding strategy at the nodes to make the
proposed gradient aggregation scheme robust to stragglers. In particular, we
quantify the communication parallelization gain and resiliency of the proposed
CR scheme, and prove its optimality when the communication topology is a
regular tree. Moreover, we characterize the expected run-time of CR and show
order-wise speedups compared to the benchmark schemes. Finally, we empirically
evaluate the performance of our proposed CR design over Amazon EC2 and
demonstrate that it achieves speedups of up to 27.2x and 7.0x, respectively
over the benchmarks GC and RAR.


  The well-known technique outlined in the paper of Leon A. Gatys et al., A
Neural Algorithm of Artistic Style, has become a trending topic both in
academic literature and industrial applications. Neural Style Transfer (NST)
constitutes an essential tool for a wide range of applications, such as
artistic stylization of 2D images, user-assisted creation tools and production
tools for entertainment applications. The purpose of this study is to present a
method for creating artistic maps from satellite images, based on the NST
algorithm. This method includes three basic steps (i) application of semantic
image segmentation on the original satellite image, dividing its content into
classes (i.e. land, water), (ii) application of neural style transfer for each
class and (iii) creation of a collage, i.e. an artistic image consisting of a
combination of the two stylized image generated on the previous step.


  Radar sensors are an important part of driver assistance systems and
intelligent vehicles due to their robustness against all kinds of adverse
conditions, e.g., fog, snow, rain, or even direct sunlight. This robustness is
achieved by a substantially larger wavelength compared to light-based sensors
such as cameras or lidars. As a side effect, many surfaces act like mirrors at
this wavelength, resulting in unwanted ghost detections. In this article, we
present a novel approach to detect these ghost objects by applying data-driven
machine learning algorithms. For this purpose, we use a large-scale automotive
data set with annotated ghost objects. We show that we can use a
state-of-the-art automotive radar classifier in order to detect ghost objects
alongside real objects. Furthermore, we are able to reduce the amount of false
positive detections caused by ghost images in some settings.


  We revisit the problem of deciding whether a finitely generated subgroup H is
a free factor of a given free group F. Known algorithms solve this problem in
time polynomial in the sum of the lengths of the generators of H and
exponential in the rank of F. We show that the latter dependency can be made
exponential in the rank difference rank(F) - rank(H), which often makes a
significant change.


  Gamma-ray line observations provide a versatile tool for studies of
nucleosynthesis processes and supernova physics. In particular, the observation
of radioactive species in the interstellar medium probes recent nucleosynthesis
activity on various time-scales for different kinds of sources. Considerable
progress in gamma-ray instrumentation during the last decades has led to the
discovery of several cosmic gamma-ray lines. The best studied of these lines is
today the 1.809 MeV line attributed to the decay of radioactive 26Al within the
interstellar medium. In this review, recent observational results are presented
and their astrophysical implications are discussed.


  We study theoretically the dynamical rectification of a terahertz AC electric
field, ie. the DC current and voltage response to the incident radiation, in
strongly coupled semiconductor superlattices. We address the problem of
stability against electric field domains: A spontaneous DC voltage is known to
appear exactly for parameters for which a spatially homogeneous electron
distribution is unstable. We show that by applying a weak direct current bias
the rectifier can be switched from a zero DC voltage state to one with a finite
voltage in full absence of domains. The switching occurs near the conditions of
dynamical symmetry breaking of an unbiased semiconductor superlattice.
Therefore our scheme allows for the generation of DC voltages that would
otherwise be unreachable due to domain instabilities. Furthermore, for
realistic, highly doped wide miniband superlattices at room temperature the
generated DC field can be nearly quantized, that is, be approximately
proportional to an integer multiple of h\omega/2\pi ea where a is the
superlattice period and \omega\ is the AC field frequency.


  In my previous work, physics/0205011, I reported several observations on
special relativity, its experimental facts and its relations to quantum
mechanics and statistical mechanics. These observations made us conscious:
Special relativity is not a ultimate theory; Some modification is needed; Any
modification must not violate the principles of the constancy of the light
speed and of the local Lorentz invariance; We probably have to change the
assumption on local structures of gravity-free space and time in special
relativity. Actually, such a kind of modification of special relativity has
been already done. The generalized Finslerian structures of gravity-free space
and time in the usual inertial coordinate system have been proposed. Here, in
this lecture, I talk about these structures of gravity-free space and time and
their recognized phenomena.


  Metal/semiconductor interfaces govern the operation of semiconductor devices
through the formation of charge injection barriers that can be controlled by
tuning the metal work function. However, the controlling ability is typically
limited to being static. We show that a dynamic nature can be imparted to the
interfaces using electrode surface modification with a structurally disordered
molecular monolayer. The barrier height at the interfaces is altered
significantly in a reversible way by an external electric field. As a result, a
dramatic change in the carrier transport properties through the interfaces is
observed, such as a reversible polarity reversion of
metal/organic-semiconductor/metal diodes.


  The optimization of the pressure angle in a cam-follower transmission is
reported in this paper. This transmission is based on Slide-o-Cam, a cam
mechanism with multiple rollers mounted on a common translating follower. The
design of Slide-o-Cam, a transmission intended to produce a sliding motion from
a turning drive, or vice versa, was reported elsewhere. This transmission
provides pure-rolling motion, thereby reducing the friction of rack-and-pinions
and linear drives. The pressure angle is a suitable performance index for this
transmission because it determines the amount of force transmitted to the load
vs. that transmitted to the machine frame. Two alternative design strategies
are studied, namely, (i) increase the number of lobes on each cam or (ii)
increase the number of cams. This device is intended to replace the current
ball-screws in Orthoglide, a three-DOF parallel robot for the production of
translational motions, currently under development at Ecole Centrale de Nantes
for machining applications.


  For a positive integer $m$ and a subgroup $\Lambda$ of the unit group
$(\mathbb{Z}/m\mathbb{Z})^\times$, the corresponding generalized Kloosterman
sum is the function $K(a,b,m,\Lambda) = \sum_{u \in \Lambda}e(\frac{au +
bu^{-1}}{m})$. Unlike classical Kloosterman sums, which are real valued,
generalized Kloosterman sums display a surprising array of visual features when
their values are plotted in the complex plane. In a variety of instances, we
identify the precise number-theoretic conditions that give rise to particular
phenomena.


  I review the milestones of the mathematical work of Krzysztof P.
Wojciechowski. This will at the same time be a tour of Analysis and Geometry of
Boundary Value Problems. Starting in the 80s I will discuss the spectral flow
and the general linear conjugation problem, the Calderon projector and the
topology of space of elliptic boundary problems. The theme of the 90s is the
eta invariant. The paper with Douglas was fundamental for establishing spectral
invariants for manifolds with boundary and for the investigation of the
behavior of spectral invariants under analytic surgery. This was so influential
that many different proofs of the gluing formula for the eta-invariant were
published. Finally turning to the new millennium we will look at the
zeta--determinant. Compared to eta this is a much more rigid spectral invariant
which is technically challenging.
  This paper was presented at the workshop "Krzysztof Wojciechowski - 50 Years"
held in May 2005 near Roskilde/Denmark.


  In this paper we investigated the most important family of proton conducting
oxides, i.e. cerates, by means of pair distribution function analysis (PDF)
obtained from total neutron scattering data. The results clearly demonstrates
that the local structure plays a fundamental role in the protonation process.
Oxygen vacancy creation by acceptor doping reduces the local structure symmetry
which is then restored upon water uptake. This mechanism mainly involves the
Ba-O shell which flexibility seems to be at the basis of the proton conduction
mechanism, thus providing a direct insight on the design of optimal proton
conducting materials.


  What happens to dwarf galaxies as they enter the cluster potential well is
one of the main unknowns in studies of galaxy evolution. Several evidence
suggests that late-type galaxies enter the cluster and are transformed to dwarf
early-type galaxies (dEs). We study the Virgo cluster to understand which
mechanisms are involved in this transformation. We find that the dEs in the
outer parts of Virgo have rotation curves with shapes and amplitudes similar to
late-type galaxies of the same luminosity. These dEs are rotationally
supported, have disky isophotes, and younger ages than those dEs in the center
of Virgo, which are pressure supported, often have boxy isophotes and are
older. Ram pressure stripping, thus, explains the properties of the dEs located
in the outskirts of Virgo. However, the dEs in the central cluster regions,
which have lost their angular momentum, must have suffered a more violent
transformation. A combination of ram pressure stripping and harassment is not
enough to remove the rotation and the spiral/disky structures of these
galaxies. We find that on the the Faber-Jackson and the Fundamental Plane
relations dEs deviate from the trends of massive elliptical galaxies towards
the position of dark matter dominated systems such as the dwarf spheroidal
satellites of the Milky Way and M31. Both, rotationally and pressure supported
dEs, however, populate the same region in these diagrams. This indicates that
dEs have a non-negligible dark matter fraction within their half light radius.


  Algorithms provide powerful tools for detecting and dissecting human bias and
error. Here, we develop machine learning methods to to analyze how humans err
in a particular high-stakes task: image interpretation. We leverage a unique
dataset of 16,135,392 human predictions of whether a neighborhood voted for
Donald Trump or Joe Biden in the 2020 US election, based on a Google Street
View image. We show that by training a machine learning estimator of the Bayes
optimal decision for each image, we can provide an actionable decomposition of
human error into bias, variance, and noise terms, and further identify specific
features (like pickup trucks) which lead humans astray. Our methods can be
applied to ensure that human-in-the-loop decision-making is accurate and fair
and are also applicable to black-box algorithmic systems.


  Introduction This study explores the use of the latest You Only Look Once
(YOLO V7) object detection method to enhance kidney detection in medical
imaging by training and testing a modified YOLO V7 on medical image formats.
Methods Study includes 878 patients with various subtypes of renal cell
carcinoma (RCC) and 206 patients with normal kidneys. A total of 5657 MRI scans
for 1084 patients were retrieved. 326 patients with 1034 tumors recruited from
a retrospective maintained database, and bounding boxes were drawn around their
tumors. A primary model was trained on 80% of annotated cases, with 20% saved
for testing (primary test set). The best primary model was then used to
identify tumors in the remaining 861 patients and bounding box coordinates were
generated on their scans using the model. Ten benchmark training sets were
created with generated coordinates on not-segmented patients. The final model
used to predict the kidney in the primary test set. We reported the positive
predictive value (PPV), sensitivity, and mean average precision (mAP). Results
The primary training set showed an average PPV of 0.94 +/- 0.01, sensitivity of
0.87 +/- 0.04, and mAP of 0.91 +/- 0.02. The best primary model yielded a PPV
of 0.97, sensitivity of 0.92, and mAP of 0.95. The final model demonstrated an
average PPV of 0.95 +/- 0.03, sensitivity of 0.98 +/- 0.004, and mAP of 0.95
+/- 0.01. Conclusion Using a semi-supervised approach with a medical image
library, we developed a high-performing model for kidney detection. Further
external validation is required to assess the model's generalizability.


  There exist several endeavors proposing a new family of extended
distributions using the beta-generating technique. This is a well-known
mechanism in developing flexible distributions, by embedding the cumulative
distribution function (cdf) of a baseline distribution within the beta
distribution that acts as a generator. Univariate beta-generated distributions
offer many fruitful and tractable properties and have applications in
hydrology, biology and environmental sciences amongst other fields. In the
univariate cases, this extension works well, however, for multivariate cases,
the beta distribution generator delivers complex expressions. In this document,
the proposed extension from the univariate to the multivariate domain addresses
the need of flexible multivariate distributions that can model a wide range of
multivariate data. This new family of multivariate distributions, whose
marginals are beta-generated distributed, is constructed with the function
H(x_{1},...,x_{p})=F(G_{1}(x_{1}),G_{2}(x_{2}),...,G_{p}(x_{p})), where
$G_{i}(x_{i})$ are the cdfs of the gamma (baseline) distribution and F(.) as
the cdf of the Dirichlet distribution. Hence as the main example, a general
model having the support [0,1]^{p} (for p variates), using the Dirichlet as the
generator, is developed together with some distributional properties, such as
the moment generating function. The proposed Dirichlet-generated distributions
can be applied to compositional data. The parameters of the model are estimated
by using the maximum likelihood method. The effectiveness and prominence of the
proposed family are illustrated by analyzing simulated as well as two real
datasets. A new model testing technique is introduced to evaluate the
performance of the multivariate models.


  In this paper, we consider an adversarial scenario where one agent seeks to
achieve an objective and its adversary seeks to learn the agent's intentions
and prevent the agent from achieving its objective. The agent has an incentive
to try to deceive the adversary about its intentions, while at the same time
working to achieve its objective. The primary contribution of this paper is to
introduce a mathematically rigorous framework for the notion of deception
within the context of optimal control. The central notion introduced in the
paper is that of a belief-induced reward: a reward dependent not only on the
agent's state and action, but also adversary's beliefs. Design of an optimal
deceptive strategy then becomes a question of optimal control design on the
product of the agent's state space and the adversary's belief space. The
proposed framework allows for deception to be defined in an arbitrary control
system endowed with a reward function, as well as with additional
specifications limiting the agent's control policy. In addition to defining
deception, we discuss design of optimally deceptive strategies under
uncertainties in agent's knowledge about the adversary's learning process. In
the latter part of the paper, we focus on a setting where the agent's behavior
is governed by a Markov decision process, and show that the design of optimally
deceptive strategies under lack of knowledge about the adversary naturally
reduces to previously discussed problems in control design on partially
observable or uncertain Markov decision processes. Finally, we present two
examples of deceptive strategies: a "cops and robbers" scenario and an example
where an agent may use camouflage while moving. We show that optimally
deceptive strategies in such examples follow the intuitive idea of how to
deceive an adversary in the above settings.


  We demonstrate a straightforward way to lithographically fabricate
Mn12-acetate (Mn12O12(CH3COO)16(H2O)4 2CH3COOH 4H2O) thin film patterns on
Si/SiO2 surfaces, a significant step in light of the chemical volatility of
this organic complex. Atomic force microscopy (AFM) images of the film patterns
allow the determination of the pattern dimensions. X-ray photoelectron
spectroscopy (XPS) data indicate that the patterned material is the intact
Mn12-acetate complex. Magnetic measurements of the Mn12-acetate film confirm
that the film properties are reminiscent of crystalline Mn12-acetate,
suggesting that this approach can be used to fabricate lithographically
patterned devices of Mn12-acetate.


  We consider a two-scale reaction diffusion system able to capture the
corrosion of concrete with sulfates. Our aim here is to define and compute two
macroscopic corrosion indicators: typical pH drop and gypsum profiles.
Mathematically, the system is coupled, endowed with micro-macro transmission
conditions, and posed on two different spatially-separated scales: one
microscopic (pore scale) and one macroscopic (sewer pipe scale). We use a
logarithmic expression to compute values of pH from the volume averaged
concentration of sulfuric acid which is obtained by resolving numerically the
two-scale system (microscopic equations with direct feedback with the
macroscopic diffusion of one of the reactants). Furthermore, we also evaluate
the content of the main sulfatation reaction (corrosion) product---the
gypsum---and point out numerically a persistent kink in gypsum's concentration
profile. Finally, we illustrate numerically the position of the free boundary
separating corroded from not-yet-corroded regions.


  In this paper, we will use the normalized intetral Ricci curvature to
investigate Liouville type property of $ p $ harmonic function on Riemannian
manifold. secondly, we will use the BiRic curvature to obtian Liuville theorem
for $ p $ harmonic function or $ p $ harmonic 1 form. Lastly, we we will use
the BiRic curvature to obtian Liouville theorem forharmonic $ q(q\geq 2)$ form.


  Molecular systems are materials that intersect with many different promising
fields such as organic/molecular electronics and spintronics, organic magnetism
and quantum computing1-7. Particularly, magnetism in organic materials is very
intriguing: the possibility to realize long-range magnetic order in completely
metal-free systems means that magnetic moments are coupled to useful properties
of organic materials, such as optical transparency, low-cost fabrication, and
flexible chemical design. Magnetic ordering in light elements, such as nitrogen
and carbon, has been studied in magnetic-edged graphene nanoribbons8 and
bilayers9, and polymers10 while in organic thin films most of the
investigations show this effect as due to the proximity of light atoms to heavy
metals, impurities, or vacancies11. Purely organic radicals are molecules that
carry one unpaired electron giving rise to a permanent magnetic moment, in the
complete absence of metal ions.12-14 Inspired by their tremendous potential,
here we investigate thin films of an exceptionally chemically stable Blatter
radical derivative15 by using X-ray magnetic circular dichroism (XMCD)16-18.
Here we observe XMCD at the nitrogen K-edge. Our results show a magnetic
ordering different than in the single crystals and calculations indicate,
although weak, a long-range intermolecular coupling. We anticipate our work to
be a starting point for investigating and modelling magnetic behaviour in
purely organic thin films. The tuning of the magnetic properties by the
molecular arrangement in organic films is an exciting perspective towards
revealing new properties and applications.


  Recent interest in the use of $L_1$ regularization in the use of value
function approximation includes Petrik et al.'s introduction of
$L_1$-Regularized Approximate Linear Programming (RALP). RALP is unique among
$L_1$-regularized approaches in that it approximates the optimal value function
using off-policy samples. Additionally, it produces policies which outperform
those of previous methods, such as LSPI. RALP's value function approximation
quality is affected heavily by the choice of state-relevance weights in the
objective function of the linear program, and by the distribution from which
samples are drawn; however, there has been no discussion of these
considerations in the previous literature. In this paper, we discuss and
explain the effects of choices in the state-relevance weights and sampling
distribution on approximation quality, using both theoretical and experimental
illustrations. The results provide insight not only onto these effects, but
also provide intuition into the types of MDPs which are especially well suited
for approximation with RALP.


  We present an analysis of the pion-nucleon $\sigma$-term, $\sigma_{\pi N}$,
using six ensembles with 2+1+1-flavor highly improved staggered quark action
generated by the MILC collaboration. The most serious systematic effect in
lattice calculations of nucleon correlation functions is the contribution of
excited states. We estimate these using chiral perturbation theory ($\chi$PT),
and show that the leading contribution to the isoscalar scalar charge comes
from N$\pi$ and N$\pi\pi$ states. Therefore, we carry out two analyses of
lattice data to remove excited-state contamination, the standard one and a new
one including N$\pi$ and N$\pi\pi$ states. We find that the standard analysis
gives $\sigma_{\pi N} = 41.9(4.9)$ MeV, consistent with previous lattice
calculations, while our preferred $\chi$PT-motivated analysis gives
$\sigma_{\pi N} = 59.6(7.4)$ MeV, which is consistent with phenomenological
values obtained using $\pi$N scattering data. Our data on one physical pion
mass ensemble was crucial for exposing this difference, therefore, calculations
on additional physical mass ensembles are needed to confirm our result and
resolve the tension between lattice QCD and phenomenology.


  We first state a special type of It\^o formula involving stochastic integrals
of both standard and fractional Brownian motions. Then we use Doss-Sussman
transformation to establish the link between backward doubly stochastic
differential equations, driven by both standard and fractional Brownian
motions, and backward stochastic differential equations, driven only by
standard Brownian motions. Following the same technique, we further study
associated nonlinear stochastic partial differential equations driven by
fractional Brownian motions and partial differential equations with stochastic
coefficients.


  The accurate prediction of solid-solid structural phase transitions at finite
temperature is a challenging task, since the dynamics is so slow that direct
simulations of the phase transitions by first-principles (FP) methods are
typically not possible. Here, we study the $\alpha$-$\beta$ phase transition of
Zr at ambient pressure by means of on-the-fly machine-learned force fields.
These are automatically generated during FP molecular dynamics (MD) simulations
without the need of human intervention, while retaining almost FP accuracy. Our
MD simulations successfully reproduce the first-order displacive nature of the
phase transition, which is manifested by an abrupt jump of the volume and a
cooperative displacement of atoms at the phase transition temperature. The
phase transition is further identified by the simulated x-ray powder
diffraction, and the predicted phase transition temperature is in reasonable
agreement with experiment. Furthermore, we show that using a singular value
decomposition and pseudo inversion of the design matrix generally improves the
machine-learned force field compared to the usual inversion of the squared
matrix in the regularized Bayesian regression.


  We introduce a geometric evolution equation for 3-manifolds with sectional
curvature of one sign which is in some sense dual to the Ricci flow. On a
closed 3-manifold with negative sectional curvature, we establish short time
existence and a pair of monotonicity formulas for solutions to the flow. One of
these formulas shows that, provided the solution exists for all time, the
metric approaches hyperbolic in an integral sense. Long time existence is still
an open problem.


  Publicly available source-code libraries are continuously growing and
changing. This makes it impossible for models of code to keep current with all
available APIs by simply training these models on existing code repositories.
Thus, existing models inherently cannot generalize to using unseen functions
and libraries, because these would never appear in the training data. In
contrast, when human programmers use functions and libraries for the first
time, they frequently refer to textual resources such as code manuals and
documentation, to explore and understand the available functionality. Inspired
by this observation, we introduce DocPrompting: a natural-language-to-code
generation approach that explicitly leverages documentation by (1) retrieving
the relevant documentation pieces given an NL intent, and (2) generating code
based on the NL intent and the retrieved documentation. DocPrompting is
general: it can be applied to any programming language and is agnostic to the
underlying neural model. We demonstrate that DocPrompting consistently improves
NL-to-code models: DocPrompting improves strong base models such as CodeT5 by
2.85% in pass@1 (52% relative gain) and 4.39% in pass@10 (30% relative gain) in
execution-based evaluation on the popular Python CoNaLa benchmark; on a new
Bash dataset tldr, DocPrompting improves CodeT5 and GPT-Neo1.3B by up to
absolute 6.9% exact match.


  Identifying cohesive subgraphs in hypergraphs is a fundamental problem that
has received recent attention in data mining and engineering fields. Existing
approaches mainly focus on a strongly induced subhypergraph or edge
cardinality, overlooking the importance of the frequency of co-occurrence. In
this paper, we propose a new cohesive subgraph named (k,g)-core, which
considers both neighbour and co-occurrence simultaneously. The $(k,g)$-core has
various applications including recommendation system, network analysis, and
fraud detection. To the best of our knowledge, this is the first work to
combine these factors. We extend an existing efficient algorithm to find
solutions for $(k,g)$-core. Finally, we conduct extensive experimental studies
that demonstrate the efficiency and effectiveness of our proposed algorithm.


  We have found the first convincing evidence for spiral structure in the
accretion disc of a close binary. The eclipsing dwarf nova binary IP Peg,
observed during the end phase of a rise to outburst, shows strong Balmer and
Helium emission lines in its spectra, with asymmetric double peaked velocity
profiles produced in the accretion disc around the white dwarf. To reveal the
two armed spiral on the accretion disc, we de-project the observed emission
line profiles onto a Doppler coordinate frame, a technique known as Doppler
tomography. The two armed spiral structure we see in the Doppler tomograms is
expected to form when the disc becomes sufficiently large in outburst so that
the tides induced by the secondary star can excite waves in the outer disc.
Such spiral waves have been predicted in studies of tidal effects in discs and
are fundamental in understanding the angular momentum budget of accretion
discs.


  The Higgs RNA-Model is studied in regard to finite-time driving protocols
with minimal-work requirement. In this paper, RNA sequences which at low
temperature exhibits hairpins are considered, which are often cited as typical
template systems in stochastic thermodynamics. The optimized work protocols for
this glassy many-particle system are determined numerically using the parallel
tempering method. The protocols show distinct jumps at the beginning and end,
which have been observed previously already for single-particle systems.
Counter intuitively, optimality seems to be achieved by staying close to the
equilibrium unfolding transition point. The change of work distributions,
compared to those resulting from a naive linear driving protocol, are discussed
generally and in terms of free energy estimation as well as the effect of
optimized protocols on rare work process starting conditions.


  1. Introduction
  2. Charged chains at infinite dilution - asymptotic properties
  2.1 Definition of the model and Flory-like calculation
  2.2 Variational approaches
  2.3 Renormalization group calculations
  2.4 Screening of electrostatic interactions
  2.5 Annealed and quenched polyelectrolytes
  3. Local aspects of screening
  3.1 Counterion condensation
  3.2 Poisson Boltzmann approach
  3.3 Attractive electrostatic interactions
  4. Electrostatic rigidity
  4.1 The Odijk-Skolnick-Fixman theory
  4.2 Alternative calculations for flexible chains
  4.3 The case of poor solvents
  5. Charged gels and brushes
  5.1 Grafted polyelectrolyte layers
  5.2 Polyelectrolyte gels
  6. Semidilute solutions
  6.1 Ordering transitions in polyelectrolyte solutions
  6.2 Correlation length and osmotic pressure of semi-dilute polyelectrolyte
solutions
  6.3 Electrostatic rigidity in semidilute solutions
  6.4 Concentrated solutions of flexible polyelectrolytes
  6.5 Mesophase formation in poor solvents
  7. Dynamical properties
  7.1 Mobility and electrophoretic mobility of a single charged chain
  7.2 Viscosity of polyelectrolyte solutions
  8. Conclusions


  (Abridged) Star and planet formation theories predict an evolution in the
density, temperature, and velocity structure as the envelope collapses and
forms an accretion disk. The aim of this work is to model the evolution of the
molecular excitation, line profiles, and related observables during low-mass
star formation. Specifically, the signatures of disks during the deeply
embedded stage are investigated. Semi-analytic 2D axisymmetric models have been
used to describe the evolution of the density, stellar mass, and luminosity
from the pre-stellar to the T-Tauri phase. A full radiative transfer
calculation is carried out to accurately determine the time-dependent dust
temperatures and CO abundance structure. We present non-LTE near-IR, FIR, and
submm lines of CO have been simulated at a number of time steps. In contrast to
the dust temperature, the CO excitation temperature derived from submm/FIR
lines does not vary during the protostellar evolution, consistent with C18O
observations obtained with Herschel and from ground-based telescopes. The
near-IR spectra provide complementary information to the submm lines by probing
not only the cold outer envelope but also the warm inner region. The near-IR
high-J (>8) absorption lines are particularly sensitive to the physical
structure of the inner few AU, which does show evolution. High signal-to-noise
ratio subarcsec resolution data with ALMA are needed to detect the presence of
small rotationally supported disks during the Stage 0 phase and various
diagnostics are discussed.


  We numerically compute current-induced spin-transfer torques for
antiferromagnetic domain walls, based on a linear response theory in a
tight-binding model. We find that, unlike for ferromagnetic domain wall motion,
the contribution of adiabatic spin torque to antiferromagnetic domain wall
motion is negligible, consistent with previous theories. As a result, the
non-adiabatic spin-transfer torque is a main driving torque for
antiferromagnetic domain wall motion. Moreover, the non-adiabatic spin-transfer
torque for narrower antiferromagnetic domain walls increases more rapidly than
that for ferromagnetic domain walls, which is attributed to the enhanced spin
mistracking process for antiferromagnetic domain walls.


  The long-term X-ray lightcurves of classical supergiant X-ray binaries and
supergiant fast X-ray transients show relatively similar super-orbital
modulations, which are still lacking a sound interpretation. We propose that
these modulations are related to the presence of corotating interaction regions
(CIRs) known to thread the winds of OB supergiants. To test this hypothesis, we
couple the outcomes of 3-D hydrodynamic models for the formation of CIRs in
stellar winds with a simplified recipe for the accretion onto a neutron star.
The results show that the synthetic X-ray light curves are indeed modulated by
the presence of the CIRs. The exact period and amplitude of these modulations
depend on a number of parameters governing the hydrodynamic wind models and on
the binary orbital configuration. To compare our model predictions with the
observations, we apply the 3-D wind structure previously shown to well explain
the appearance of discrete absorption components in the UV time series of a
prototypical B0.5I-type supergiant. Using the orbital parameters of
IGRJ16493-4348 which has the same B0.5I donor spectral type, the period and
modulations in the simulated X-ray light-curve are similar to the observed
ones, thus providing support to our scenario. We propose, that the presence of
CIRs in donor star winds should be considered in future theoretical and
simulation efforts of wind-fed X-ray binaries.


  Although the spectra of heavy quarkonium systems have been successfully
explained by certain QCD motivated potential models, their strong decays are
still an open problem. We perform a microscopic calculation of vector
charmonium strong decays into open-charm mesons where the $q\bar{q}$ pairs are
created from the same interquark interactions acting in the quark model that
has been used to describe its spectrum, and also its leptonic and radiative
decays. We compare the numerical results with those predicted by the
$^{3}P_{0}$ decay model and with the available experimental data, and discuss
the possible influence on the strong widths of the different terms of the
potential. A comparison with other predictions from similar microscopic decay
models is also included.


  Abelian 6d (2,0) theory has SO(5) R symmetry. We twist this theory by
identifying the R symmetry group with the SO(5) subgroup of the SO(1,5) Lorentz
group. This twisted theory can be put on any five-manifold M, times R, while
preserving one scalar supercharge. We subsequently assume the existence of one
unit normalized Killing vector field on M, and we find a corresponding SO(4)
twist that preserves two supercharges and is a generalization of the geometric
Langlands twist of 4d SYM. We generalize the story to non-Abelian gauge group
for the corresponding 5d SYM theories on M. We derive a vanishing theorem for
BPS contact instantons by identifying the 6d potential energy and its BPS
bound, in the 5d theory. To this end we need to perform a Wick rotation that
complexifies the gauge field.


  To comply with the equivalence principle in Einstein-Cartan-like theories of
gravity we propose a modification of the action principle in affine flat spaces
with torsion.


  A scheme is presented based on numbers that represent a manifold in $d$
dimensions for generalizations of textbook cryptosystems. The interlocking or
intersection of geometries, requiring the addition of a series of integers
$q_j$, can be used to enhance a cryptosystem via algorithms based on the form
of the geometry. Further operations besides addition of these numbers, e.g.
sewing of the geometries, can be given such as rotations or contractions.


  In this brief note, we confront our results on diffractive photoproduction of
$J/\psi$ mesons with the putative gluon shadowing ratio defined as $R_g=
\sqrt{\sigma(\gamma A \to J/\psi A)/\sigma_{\rm IA.}}$, where $\sigma_{\rm IA}$
is the result in impulse approximation. Building on our earlier description of
the process in the color-dipole approach, where we took into account the
rescattering of $c \bar c$ states only, we demonstrate that the inclusion of $c
\bar c g$-Fock states improves the description at small $x$ commonly associated
with gluon shadowing.


  (Abridged) Poorly-populated star clusters may have photometric and structural
properties not much different from asterisms, to the point that, in some cases,
widely-used databases present conflicting classifications. We investigate the
nature of a sample of challenging targets that have been classified either as
star clusters or asterisms in different studies. A few objects are studied for
the first time.


  A quantum process encodes the causal structure that relates quantum
operations performed in local laboratories. The process matrix formalism
includes as special cases quantum mechanics on a fixed background space-time,
but also allows for more general causal structures. Motivated by the
interpretation of processes as a resource for quantum information processing
shared by two (or more) parties, with advantages recently demonstrated both for
computation and communication tasks, we investigate the notion of composition
of processes. We show that under very basic assumptions such a composition rule
does not exist. While the availability of multiple independent copies of a
resource, e.g. quantum states or channels, is the starting point for defining
information-theoretic notions such as entropy (both in classical and quantum
Shannon theory), our no-go result means that a Shannon theory of general
quantum processes will not possess a natural rule for the composition of
resources.


  We report the discovery of four blue lurkers with low and extremely low-mass
white dwarf (ELM WDs) companions in the Galactic globular cluster NGC 362 using
AstroSat Ultra Violet Imaging Telescope (UVIT). We analyzed the
multi-wavelength spectral energy distribution (SED) of FUV-bright MS stars
using data from the UVIT, UVOT, GAIA EDR3, and 2.2m ESO/MPI telescopes. Two
each of low-mass WDs and ELM WDs are found as companions for the four blue
lurkers by the fitting of two-component SED models. The effective temperatures,
radii, luminosities, and masses of two low-mass WDs are (35000, 23000) K,
(0.04, 0.05) Rsun , (1.45, 0.22) Lsun , and (0.2, 0.2) Msun, while the two ELM
WDs are (14750, 14750) K, (0.09, 0.10) Rsun, (0.34, 0.40) Lsun, and (0.18,
0.18) Msun. The position of blue lurkers within the cluster shows that they
originated via the Case A/B mass-transfer mechanism in a low-density
environment. This is the first detection of blue lurkers with low-mass WDs and
ELM WDs as companions in a globular cluster. The companion cooling age is less
than 4 Myr, which suggests that they were just recently formed. These binary
systems might have originated due to the cluster recent core collapse.


  The stick number and the edge length of a knot type in the simple hexagonal
lattice (sh-lattice) are the minimal numbers of sticks and edges required,
respectively, to construct a knot of the given type in sh-lattice. By
introducing a linear transformation between lattices, we prove that for any
given knot both values in the sh-lattice are strictly less than the values in
the cubic lattice. Finally, we show that the only non-trivial 11-stick knots in
the sh-lattice are the trefoil knot ($3_1$) and the figure-eight knot ($4_1$).


  In the field of software engineering, there has been a shift towards
utilizing various artificial intelligence techniques to address challenges and
create innovative tools. These solutions are aimed at enhancing efficiency,
automating tasks, and providing valuable support to developers. While the
technical aspects are crucial, the well-being and psychology of the individuals
performing these tasks are often overlooked. This paper argues that a holistic
approach is essential, one that considers the technical, psychological, and
social aspects of software engineering tasks. To address this gap, we introduce
SEWELL-CARE, a conceptual framework designed to assess AI-driven software
engineering tasks from multiple perspectives, with the goal of customizing the
tools to improve the efficiency, well-being, and psychological functioning of
developers. By emphasizing both technical and human dimensions, our framework
provides a nuanced evaluation that goes beyond traditional technical metrics.


  Social network analysis tools can infer various attributes just by
scrutinizing one's connections. Several researchers have studied the problem
faced by an evader whose goal is to strategically rewire their social
connections in order to mislead such tools, thereby concealing their private
attributes. However, to date, this literature has only considered static
networks, while neglecting the more general case of temporal networks, where
the structure evolves over time. Driven by this observation, we study how the
evader can conceal their importance from an adversary armed with temporal
centrality measures. We consider computational and structural aspects of this
problem: Is it computationally feasible to calculate optimal ways of hiding? If
it is, what network characteristics facilitate hiding? This topic has been
studied in static networks, but in this work, we add realism to the problem by
considering temporal networks of edges changing in time. We find that it is
usually computationally infeasible to find the optimal way of hiding. On the
other hand, by manipulating one's contacts, one could add a surprising amount
of privacy. Compared to static networks, temporal networks offer more
strategies for this type of manipulation and are thus, to some extent, easier
to hide in.


  The D0 Collaboration has recently seen a resonant-like peak in the $B_s\pi$
invariant mass spectrum, claimed to be a new state called $X(5568)$. Using a
$B_s\pi$--$B\bar{K}$ coupled channel analysis, implementing unitarity, and with
the interaction derived from Heavy Meson Chiral Perturbation Theory, we are
able to reproduce the reported spectrum, with a pole that can be associated to
the claimed $X(5568)$ state, and with mass and width in agreement with the ones
reported in the experimental analysis. However, if the $T$-matrix
regularization is performed by means of a momentum cutoff, the value for the
latter needed to reproduce the spectrum is $\Lambda = 2.80 \pm 0.04\
\text{GeV}$, much larger than a "natural" value $\Lambda \simeq 1\ \text{GeV}$.
In view of this, it is difficult to interpret the nature of this new state.
This state would not qualify as a resonance dynamically generated by the
unitarity loops. Assuming the observed peak to correspond to a physical state,
we make predictions for partners in the $D$, $D^\ast$, and $B^\ast$ sectors.
Their observation (or lack thereof) would shed light into this issue.


  Let Phi be a reduced root system of rank r. A Weyl group multiple Dirichlet
series for Phi is a Dirichlet series in r complex variables s_1,...,s_r,
initially converging for Re(s_i) sufficiently large, that has meromorphic
continuation to C^r and satisfies functional equations under the
transformations of C^r corresponding to the Weyl group of Phi. A heuristic
definition of such series was given in [2], and they have been investigated in
certain special cases in [2-6, 11-14]. In this paper we generalize results in
[13] to construct Weyl group multiple Dirichlet series by a uniform method, and
show in all cases that they have the expected properties.


  Triphosphides, with a chemical formula of XP$_3$ (X is a group IIIA, IVA, or
VA element), have recently attracted much attention due to their great
potential in several applications. Here, using density functional theory
calculations, we describe for the first time the structural and electronic
properties of the bulk bismuth triphosphide (BiP$_3$). Phonon spectra and
molecular dynamics simulations confirm that the 3D crystal of BiP$_3$ is a
metal thermodynamically stable with no bandgap. Unlike the bulk, the mono-,
bi-, tri-, and tetra-layers of BiP$_3$ are semiconductors with a bandgap
ranging from 1.4 to 0.06 eV. However, stackings with more than five layers
exhibit metallic behavior equal to the bulk. The results show that quantum
confinement is a powerful tool for tuning the electronic properties of BiP$_3$
triphosphide, making it suitable for technological applications. Building on
this, the electronic properties of van der Waals heterostructure constructed by
graphene (G) and the BiP$_3$ monolayer (m-BiP$_3$) were investigated. Our
results show that the Dirac cone in graphene remains intact in this
heterostructure. At the equilibrium interlayer distance, the G/m-BiP$_3$ forms
an n-type contact with a Schottky barrier height of 0.5 eV. It is worth noting
that the SHB in the G/m-BiP$_3$ heterostructure can be adjusted by changing the
interlayer distance or applying a transverse electric field. Thus, we show that
few-layers BiP$_3$ is an interesting material for realizing nanoelectronic and
optoelectronic devices and is an excellent option for designing Schottky
nanoelectronic devices.


  We study the influence of the proximity-induced pairing on electronic version
of the Dicke effect in a heterostructure, comprising three quantum dots
vertically coupled between the metallic and superconducting leads. We discuss a
feasible experimental procedure for detecting the narrow/broad
(subradiant/superradiant) contributions by means of the subgap Andreev
spectroscopy. In the Kondo regime and for small energy level detuning the Dicke
effect is manifested in the differential conductance.


  Pseudorandom states (PRSs) are state ensembles that cannot be distinguished
from Haar random states by any efficient quantum algorithm. However, the
definition of PRSs has been limited to pure states and lacks robustness against
noise. In this work, we introduce pseudorandom density matrices (PRDMs),
ensembles of $n$-qubit states that are computationally indistinguishable from
the generalized Hilbert-Schmidt ensemble, which is constructed from
$(n+m)$-qubit Haar random states with $m$ qubits traced out. For a mixedness
parameter $m=0$, PRDMs are equivalent to PRSs, whereas for $m=\omega(\log n)$,
PRDMs are computationally indistinguishable from the maximally mixed state. In
contrast to PRSs, PRDMs with $m=\omega(\log n)$ are robust to unital noise
channels and a recently introduced $\mathsf{PostBQP}$ attack. Further, we
construct pseudomagic and pseudocoherent state ensembles, which possess
near-maximal magic and coherence, but are computationally indistinguishable
from states with zero magic and coherence. PRDMs can exhibit a pseudoresource
gap of $\Theta(n)$ vs $0$, surpassing previously found gaps. We introduce
noise-robust EFI pairs, which are state ensembles that are computationally
indistinguishable yet statistically far, even when subject to noise. We show
that testing entanglement, magic and coherence is not efficient. Further, we
prove that black-box resource distillation requires a superpolynomial number of
copies. We also establish lower bounds on the purity needed for efficient
testing and black-box distillation. Finally, we introduce memoryless PRSs, a
noise-robust notion of PRS which are indistinguishable to Haar random states
for efficient algorithms without quantum memory. Our work provides a
comprehensive framework of pseudorandomness for mixed states, which yields
powerful quantum cryptographic primitives and fundamental bounds on quantum
resource theories.


  Most polymers are long-lasting and produced from monomers derived from fossil
fuel sources. Bio-based and/or biodegradable plastics have been proposed as a
sustainable alternative. Amongst those available, polyhydroxyalkanoate (PHA)
shows great potential across a large variety of applications but is currently
limited to packaging, cosmetics and tissue engineering due to its relatively
poor physical properties. An expansion of its uses can be accomplished by
developing nanocomposites where PHAs are used as the polymer matrix. Herein, a
PHA biopolyester was melt blended with graphene nanoplatelets (GNPs) or with a
1:1 hybrid mixture of GNPs and carbon nanofibers (CNFs). The resulting
nanocomposites exhibited enhanced thermal stability while their Young's modulus
roughly doubled compared to pure PHA. The hybrid nanocomposites percolated
electrically at lower nanofiller loadings compared to the GNP-PHA system. The
electrical conductivity at 15 wt.% loading was ~ 6 times higher than the
GNP-based sample. As a result, the electromagnetic interference shielding
performance of the hybrid material was around 50% better than the pure GNPs
nanocomposites, exhibiting shielding effectiveness above 20 dB, which is the
threshold for common commercial applications. The thermal conductivity
increased significantly for both types of bio-nanocomposites and reached values
around 5 W K-1 m-1 with the hybrid-based material displaying the best
performance. Considering the solvent-free and industrially compatible
production method, the proposed multifunctional materials are promising to
expand the range of application of PHAs and increase the environmental
sustainability of the plastic and plastic electronics industry.


  We consider the partial theta function $\theta
(q,x):=\sum_{j=0}^{\infty}q^{j(j+1)/2}x^j$, where $x\in \mathbb{C}$ is a
variable and $q\in \mathbb{C}$, $0<|q|<1$, is a parameter. We show that, for
any fixed $q$, if $\zeta$ is a multiple zero of the function $\theta (q,.)$,
then $|\zeta |\leq 8^{11}$.


  The nature of particle and entropy flow between two superfluids is often
understood in terms of reversible flow carried by an entropy-free, macroscopic
wavefunction. While this wavefunction is responsible for many intriguing
properties of superfluids and superconductors, its interplay with excitations
in non-equilibrium situations is less understood. Here, we observe large
concurrent flows of both particles and entropy through a ballistic channel
connecting two strongly interacting fermionic superfluids. Both currents
respond nonlinearly to chemical potential and temperature biases. We find that
the entropy transported per particle is much larger than the prediction of
superfluid hydrodynamics in the linear regime and largely independent of
changes in the channel's geometry. In contrast, the timescales of advective and
diffusive entropy transport vary significantly with the channel geometry. In
our setting, superfluidity counterintuitively increases the speed of entropy
transport. Moreover, we develop a phenomenological model describing the
nonlinear dynamics within the framework of generalised gradient dynamics. Our
approach for measuring entropy currents may help elucidate mechanisms of heat
transfer in superfluids and superconducting devices.


  We use our resummed quantum gravity approach to Einstein's general theory of
relativity in the context of the Planck scale cosmology formulation of Bonanno
and Reuter to estimate the value of the cosmological constant as \rho_\Lambda
=(0.0024 eV)^4. We show that the closeness of this estimate to experiment
constrains susy GUT models. We also address various consistency checks on the
calculation.


  Adding magnetic flux to a band structure breaks Bloch's theorem by realizing
a projective representation of the translation group. The resulting Hofstadter
spectrum encodes the non-perturbative response of the bands to flux. Depending
on their topology, adding flux can enforce a bulk gap closing (a Hofstadter
semimetal) or boundary state pumping (a Hofstadter topological insulator). In
this work, we present a real-space classification of these Hofstadter phases.
We give topological indices in terms of symmetry-protected Real Space
Invariants (RSIs) which encode bulk and boundary responses of fragile
topological states to flux. In fact, we find that the flux periodicity in
tight-binding models causes the symmetries which are broken by the magnetic
field to reenter at strong flux where they form projective point group
representations. We completely classify the reentrant projective point groups
and find that the Schur multipliers which define them are Arahanov-Bohm phases
calculated along the bonds of the crystal. We find that a nontrivial Schur
multiplier is enough to predict and protect the Hofstadter response with only
zero-flux topology.


  We analyze the transport of heat along a chain of particles interacting
through anharmonic po- tentials consisting of quartic terms in addition to
harmonic quadratic terms and subject to heat reservoirs at its ends. Each
particle is also subject to an impulsive shot noise with exponentially
distributed waiting times whose effect is to change the sign of its velocity,
thus conserving the en- ergy of the chain. We show that the introduction of
this energy conserving stochastic noise leads to Fourier law. The behavior of
thels heat conductivity for small intensities of the shot noise and large
system sizes are found to obey a finite-size scaling relation. We also show
that the heat conductivity is not constant but is an increasing monotonic
function of temperature.


  We consider distributional approximation by generalized Dickman
distributions, which appear in number theory, perpetuities, logarithmic
combinatorial structures and many other areas. We prove bounds in the
Kolmogorov distance for the approximation of certain weighted sums of Bernoulli
and Poisson random variables by members of this family. While such results have
previously been shown in Bhattacharjee and Goldstein (2019) for distances based
on smoother test functions and for a special case of the random variables
considered in this paper, results in the Kolmogorov distance are new. We also
establish optimality of our rates of convergence by deriving lower bounds. As a
result, some interesting phase transitions emerge depending on the choice of
the underlying parameters. The proofs of our results mainly rely on the use of
Stein's method. In particular, we study the solutions of the Stein equation
corresponding to the test functions associated to the Kolmogorov distance, and
establish their smoothness properties. As applications, we study the runtime of
the Quickselect algorithm and the weighted depth in randomly grown simple
increasing trees.


  We introduce a neural network inspired by Google's Inception model to compute
the Hodge number $h^{1,1}$ of complete intersection Calabi-Yau (CICY) 3-folds.
This architecture improves largely the accuracy of the predictions over
existing results, giving already 97% of accuracy with just 30% of the data for
training. Moreover, accuracy climbs to 99% when using 80% of the data for
training. This proves that neural networks are a valuable resource to study
geometric aspects in both pure mathematics and string theory.


  In this paper we investigate the spectral and the scattering theory of
Schr\"odinger operators acting on perturbed periodic discrete graphs. The
perturbations considered are of two types: either a multiplication operator by
a short-range or a long-range function, or a short-range type modification of
the measure defined on the vertices and on the edges of the graph. Mourre
theory is used for describing the nature of the spectrum of the underlying
operators. For short-range perturbations, existence and completeness of local
wave operators are also proved.


  Interacting systems are prevalent in nature, from dynamical systems in
physics to complex societal dynamics. The interplay of components can give rise
to complex behavior, which can often be explained using a simple model of the
system's constituent parts. In this work, we introduce the neural relational
inference (NRI) model: an unsupervised model that learns to infer interactions
while simultaneously learning the dynamics purely from observational data. Our
model takes the form of a variational auto-encoder, in which the latent code
represents the underlying interaction graph and the reconstruction is based on
graph neural networks. In experiments on simulated physical systems, we show
that our NRI model can accurately recover ground-truth interactions in an
unsupervised manner. We further demonstrate that we can find an interpretable
structure and predict complex dynamics in real motion capture and sports
tracking data.


  Quantitative (or controlled) $K$-theory for $C^*$-algebras was used by
Guoliang Yu in his work on the Novikov conjecture, and later developed more
formally by Yu together with Herv\'e Oyono-Oyono. In this paper, we extend
their work by developing a framework of quantitative $K$-theory for the class
of algebras of bounded linear operators on subquotients (i.e., subspaces of
quotients) of $L_p$ spaces. We also prove the existence of a controlled
Mayer-Vietoris sequence in this framework.


  The present ongoing global pandemic caused by SARS-CoV-2 virus is creating
havoc across the world. The absence of any vaccine as well as any definitive
drug to cure, has made the situation very grave. Therefore only few effective
tools are available to contain the rapid pace of spread of this disease, named
as COVID-19. On 24th March, 2020, the the Union Government of India made an
announcement of unprecedented complete lockdown of the entire country effective
from the next day. No exercise of similar scale and magnitude has been ever
undertaken anywhere on the globe in the history of entire mankind. This study
aims to scientifically analyze the implications of this decision using a
kinetic model covering more than 96% of Indian territory. This model was
further constrained by large sets of realistic parameters pertinent to India in
order to capture the ground realities prevailing in India, such as: (i) true
state wise population density distribution, (ii) accurate state wise infection
distribution for the zeroth day of simulation (20th March, 2020), (iii)
realistic movements of average clusters, (iv) rich diversity in movements
patterns across different states, (v) migration patterns across different
geographies, (vi) different migration patterns for pre- and post-COVID-19
outbreak, (vii) Indian demographic data based on the 2011 census, (viii) World
Health Organization (WHO) report on demography wise infection rate and (ix)
incubation period as per WHO report. This model does not attempt to make a
long-term prediction about the disease spread on a standalone basis; but to
compare between two different scenarios (complete lockdown vs. no lockdown). In
the framework of model assumptions, our model conclusively shows significant
success of the lockdown in containing the disease within a tiny fraction of the
population and in the absence of it, it would have led to a very grave
situation.


  The compound decision problem for a vector of independent Poisson random
variables with possibly different means has half a century old solution.
However, it appears that the classical solution needs smoothing adjustment even
when there are many observations and relatively small means such that the
empirical distribution is close to its mean. We discuss three such adjustments.
We also present another approach that first transforms the problem into the
normal compound decision problem.


  In this paper we establish a constructive method in order to show global
existence and regularity for a class of degenerate parabolic Cauchy problems
which satisfy a weak Hoermander condition on a subset of the domain where the
data are measurable and which have regular data on the complementary set of the
domain. This result has practical incentives related to the computation of
Greeks in reduced LIBOR market models, which are standard computable
approximations of the HJM-description of interest rate markets. The method
leads to a probabilistic scheme for the computation of the value function and
its sensitivities based on Malliavin calculus. From a practical perspective the
main contribution of the paper is an Monte-Carlo algorithm which includes
weight corrections for paths which move in time into a region where a (weak)
Hoermander condition holds.


  The determination of the Avogadro constant plays a key role in the
redefinition of the kilogram in terms of a fundamental constant. The present
experiment makes use of a silicon single-crystal highly enriched in 28Si that
must have a total impurity mass fraction smaller than a few parts in 109. To
verify this requirement, we previously developed a relative analytical method
based on neutron activation for the elemental characterization of a sample of
the precursor natural silicon crystal WASO 04. The method is now extended to
fifty-nine elements and applied to a monoisotopic 28Si single-crystal that was
grown to test the achievable enrichment. Since this crystal was likely
contaminated, this measurement tested also the detection capabilities of the
analysis. The results quantified contaminations by Ge, Ga, As, Tm, Lu, Ta, W
and Ir and, for a number of the detectable elements, demonstrated that we can
already reach the targeted 1 ng/g detection limit.


  The immense dependence of the glass transition temperature $T_g$ on molecular
weight $M$ is one of the most fundamentally and practically important features
of polymer glass formation. Here, we report on molecular dynamics simulation of
three model linear polymers of substantially different complexity demonstrating
that the 70-year-old canonical explanation of this dependence (a simple chain
end dilution effect) is likely incorrect at leading order. Our data shows that
end effects are present only in relatively stiff polymers and, furthermore,
that the magnitude of this end effect diminishes on cooling. Instead, we find
that $T_g(M)$ trends are instead dominated by shifts in $T_g$ throughout the
entire polymer chain rather than through a chain end effect. We show that these
data are consistent with a generic two-barrier model of $T_g$ and its
$M$-dependence, motivated by the Elastically Collective Nonlinear Langevin
Equation (ECNLE) theory. More broadly, this work indicates both a need to
reassess the canonical understanding of $T_g(M)$ in linear polymers (and
macromolecules at large) and an opportunity to reveal new glass formation
physics with renewed study of $M$ effects on $T_g$.


  We show that a combination of the simplest $\alpha$-attractors and KKLTI
models related to Dp-brane inflation covers most of the area in the ($n_{s}$,
$r$) space favored by Planck 2018. For $\alpha$-attractor models, there are
discrete targets $3\alpha=1,2,...,7$, predicting 7 different values of $r =
12\alpha/N^{2}$ in the range $10^{-2} \gtrsim r \gtrsim 10^{-3}$. In the small
$r$ limit, $\alpha$-attractors and Dp-brane inflation models describe vertical
$\beta$-stripes in the ($n_{s}$, $r$) space, with $n_{s}=1-\beta/N$, $\beta=2,
{5\over 3},{8\over 5}, {3\over 2},{4\over 3}$. A phenomenological description
of these models and their generalizations can be achieved in the context of
pole inflation. Most of the $1\sigma$ area in the ($n_{s}$, $r$) space favored
by Planck 2018 can be covered models with $\beta = 2$ and $\beta = 5/3$. Future
precision data on $n_s$ may help to discriminate between these models even if
the precision of the measurement of $r$ is insufficient for the discovery of
gravitational waves produced during inflation.


  A continuum theory of partially fluidized granular flows is developed. The
theory is based on a combination of the equations for the flow velocity and
shear stresses coupled with the order parameter equation which describes the
transition between flowing and static components of the granular system. We
apply this theory to several important granular problems: avalanche flow in
deep and shallow inclined layers, rotating drums and shear granular flows
between two plates. We carry out quantitative comparisons between the theory
and experiment.


  The set of possible spectra (\lambda,\mu,\nu) of zero-sum triples of
Hermitian matrices forms a polyhedral cone. We give a complete determination of
its facets, finishing a long story with recent highlights by [Helmke-Rosenthal,
Klyachko, Belkale]. We introduce_puzzles_, which are new combinatorial gadgets
to compute Grassmannian Schubert calculus, and will probably be the main point
of interest for many readers. As the proofs indicate, the Hermitian sum problem
is very naturally studied using puzzles directly, and their connection to
Schubert calculus is quite incidental to our approach. In particular, we get
new, puzzle-theoretic, proofs of the results in [H,Kly,HR,Be]. Along the way we
give a characterization of ``rigid'' puzzles, which we use to prove a
conjecture of W. Fulton: ``if for a triple of dominant weights \lambda,\mu,\nu
of GL(n,C) the irreducible representation V_\nu appears exactly once in
V_\lambda tensor V_\mu, then for all N\in \naturals, V_{N\lambda} appears
exactly once in V_{N\lambda} tensor V_{N\mu}.''


  We consider a model of Parisi where a single particle hops on an
infinite-dimensional hypercube, under the influence of a uniform but disordered
magnetic flux. We reinterpret the hypercube as the Fock-space graph of a
many-body Hamiltonian and the flux as a frustration of the return amplitudes in
Fock space. We will identify the set of observables that have the same
correlation functions as the double-scaled Sachdev-Ye-Kitaev (DS-SYK) model,
and hence the hypercube model is an equally good quantum model for
near-AdS$_2$/near-CFT$_{1}$ (NAdS$_2$/NCFT$_1$) holography. Unlike the SYK
model, the hypercube Hamiltonian is not $p$ local. Instead, the SYK model can
be understood as a Fock-space model with similar frustrations. Hence we propose
this type of Fock-space frustration as the broader characterization for
NAdS$_2$/NCFT$_1$ microscopics, which encompasses the hypercube and the DS-SYK
models as two specific examples. We then speculate on the possible origin of
such frustrations.


  We have derived a non-abelian analog for the two-dimensional discrete Toda
lattice which possesses solutions in terms of quasideterminants and admits Lax
pairs of different forms. Its connection with non-abelian analogs for several
well-known (1+1) and one-dimensional lattices is discussed. In particular, we
consider a non-commutative analog of the scheme: discrete Toda equations
$\rightarrow$ Somos-$N$ sequences $\rightarrow$ discrete Painlev\'e equations.


  Jet energy scale measurements and their systematic uncertainties are reported
for jets measured with the ATLAS detector using proton-proton collision data
with a center-of-mass energy of $\sqrt{s} = 13$ TeV, corresponding to an
integrated luminosity of 3.2 fb$^{-1}$ collected during 2015 at the LHC. Jets
are reconstructed from energy deposits forming topological clusters of
calorimeter cells, using the anti-$k_{t}$ algorithm with radius parameter $R =
0.4$. Jets are calibrated with a series of simulation-based corrections and in
situ techniques. In situ techniques exploit the transverse momentum balance
between a jet and a reference object such as a photon, $Z$ boson, or multijet
system for jets with $20 < p_{T} < 2000$ GeV and pseudorapidities of
$|\eta|<4.5$, using both data and simulation. An uncertainty in the jet energy
scale of less than 1% is found in the central calorimeter region ($|\eta| <
1.2$) for jets with $100 < p_{T} < 500$ GeV. An uncertainty of about 4.5% is
found for low-$p_{T}$ jets with $p_{T} = 20$ GeV in the central region,
dominated by uncertainties in the corrections for multiple proton-proton
interactions. The calibration of forward jets ($|\eta| > 0.8$) is derived from
dijet $p_{T}$ balance measurements. For jets of $p_{T} = 80$ GeV, the
additional uncertainty for the forward jet calibration reaches its largest
value of about 2% in the range $|\eta| > 3.5$ and in a narrow slice of $2.2 <
|\eta| < 2.4$.


  One of the distinctive features of hole-doped cuprate superconductors is the
onset of a `pseudogap' below a temperature $T^*$. Recent experiments suggest
that there may be a connection between the existence of the pseudogap and the
topology of the Fermi surface. Here, we address this issue by studying the
two-dimensional Hubbard model with two distinct numerical methods. We find that
the pseudogap only exists when the Fermi surface is hole-like and that, for a
broad range of parameters, its opening is concomitant with a Fermi surface
topology change from electron- to hole-like. We identify a common link between
these observations: the pole-like feature of the electronic self-energy
associated with the formation of the pseudogap is found to also control the
degree of particle-hole asymmetry, and hence the Fermi surface topology
transition. We interpret our results in the framework of an SU(2) gauge theory
of fluctuating antiferromagnetism. We show that a mean-field treatment of this
theory in a metallic state with U(1) topological order provides an explanation
of this pole-like feature, and a good description of our numerical results. We
discuss the relevance of our results to experiments on cuprates.


  We present the results of a program that monitored the near-IR spectroscopic
variability of a sample of 19 embedded protostars. Spectra were taken on time
intervals from 2 days to 3 years, over a wavelength range from 0.85 {\mu}m to
2.45 {\mu}m, for 4-9 epochs of observations per target. We found that the
spectra of all targets are variable, and that every emission feature observed
is also variable (although not for all targets). With one exception, there were
no drastic changes in the continua of the spectra, nor did any line completely
disappear, nor did any line appear that was not previously apparent. This
analysis focuses on understanding the connection between accretion (traced by H
Br $\gamma$ and CO) and the wind (traced by He I, [FeII], and sometimes H$_2$).
For both accretion and wind tracers, the median variability was constant versus
time interval between observations, however the maximum variability that we
observed increased with time interval between observations. Extinction is
observed to vary within the minimum sampling time of 2 days, suggesting
extinguishing material within a few stellar radii at high disk latitudes. The
variability of [FeII] and H$_2$ were correlated for most (but not all) of the 7
YSOs showing both features, and the amplitude of the variability depends on the
veiling. Although the occurrence of CO and Br $\gamma$ emission are connected,
their variability is uncorrelated, suggesting that these emissions originate in
separate regions near the protostar (e.g., disk and wind).


  We present observations of Taurus-Auriga Class I/II protostars obtained with
the Spitzer InfraRed Spectrograph. Detailed spectral fits to the 6 and 15
micron features are made, using publicly-available laboratory data, to
constrain the molecular composition, abundances, and levels of thermal
processing along the lines of sight. We provide an inventory of the molecular
environments observed, which have an average composition dominated by water ice
with ~12% CO_2 (abundance relative to H_2O), >~2-9% CH_3OH, <~14% NH_3, ~4%
CH_4, ~2% H_2CO, ~0.6% HCOOH, and ~0.5% SO_2. We find CO_2/H_2O ratios nearly
equivalent to those observed in cold clouds and lines of sight toward the
galactic center. The unidentified 6.8 micron profiles vary from source to
source, and it is shown to be likely that even combinations of the most common
candidates (NH_4+ and CH_3OH) are inadequate to explain the feature fully. We
discuss correlations among SED spectral indices, abundance ratios, and
thermally-processed ice fractions and their implications for CO_2 formation and
evolution. Comparison of our spectral fits with cold molecular cloud
sight-lines indicates abundant prestellar ice environments made even richer by
the radiative effects of protostars. Our results add additional constraints and
a finer level of detail to current full-scale models of protostellar and
protoplanetary systems.


  Multiple-input multiple-output (MIMO) has become a key technology for
contemporary wireless communication systems. For typical MIMO systems, antenna
arrays are separated by half of the signal wavelength, which are termed
collocated arrays. In this paper, we ask the following question: For future
wireless communication systems, is it possible to achieve better performance
than collocated arrays by using sparse arrays, whose element spacing is larger
than half wavelength? The answer to this question is not immediately clear
since while sparse arrays may achieve narrower beam for the main lobe, they
also generate undesired grating lobes. In this paper, we show that the answer
to the above question is affirmative. To this end, we first provide an
insightful explanation by investigating the key properties of beam patterns of
sparse and collocated arrays, together with the typical distribution of spatial
angle difference \Delta, which all critically impact the inter-user
interference (IUI). In particular, we show that sparse arrays are less likely
to experience severe IUI than collocated arrays, since the probability of
\Delta typically reduces with the increasing of |\Delta|. This naturally helps
to reject those higher-order grating lobes of sparse arrays, especially when
users are densely located. Then we provide a rigorous derivation of the
achievable data rate for sparse and collocated arrays, and derive the condition
under which sparse arrays strictly outperform collocated counterparts. Finally,
numerical results are provided to validate our theoretical studies.


  Graph states have been used for quantum error correction by Schlingemann et
al. [Physical Review A 65.1 (2001): 012308]. Hypergraph states [Physical Review
A 87.2 (2013): 022311] are generalizations of graph states and they have been
used in quantum algorithms. We for the first time demonstrate how hypergraph
states can be used for quantum error correction. We also point out that they
are more efficient than graph states in the sense that to correct equal number
of errors on the same graph topology, suitably defined hypergraph states
require less number of gate operations than the corresponding graph states.


  We study $^{208}$Pb+$^{40,48}$Ca reactions at $E_{\rm beam}$ = 50, 100 AMeV
with DJBUU and SQMD transport codes. We compare the large primary fragments
from the two codes at the end of the simulation time. We observe that overall
the two models produce similar fragments. However, we see a noticeable
difference between DJBUU and SQMD at $E_{\rm beam}=100$ AMeV with the impact
parameter $b$ = 0 fm and discuss this difference in terms of the difference in
the equation of state adopted in the two models and the difference in stability
inherent to the BUU-type and QMD-type models.


  Inclusive-jet and dijet differential cross sections have been measured in
neutral current deep inelastic ep scattering for exchanged boson virtualities
Q2 > 125 GeV2 with the ZEUS detector at HERA using an integrated luminosity of
82 pb-1. Jets were identified in the Breit frame using the kt cluster
algorithm. Jet cross sections are presented as functions of several kinematic
and jet variables. The results are also presented in different regions of Q2.
Next-to-leading-order QCD calculations describe the measurements well. Regions
of phase space where the theoretical uncertainties are small have been
identified. Measurements in these regions have the potential to constrain the
gluon density in the proton when used as inputs to global fits of the proton
parton distribution functions.


  The 1.5 Seyfert galaxy NGC 3227 has been observed by several X-ray missions.
We carried out a combined analysis of the data obtained by more recent major
observations of the source: two observations performed by XMM-Newton in 2000
and 2006 and six observations performed by Suzaku in 2008. A unified model,
which is consistent with all eight observations by the two satellites with
large intensity and spectral changes, was constructed. The model consists of a
hard power law withe the spectral index of Gamma Hard = 1.4-1.7, which is
interpreted as the Comptonized emission from the corona above an accretion
disk. In the high-flux states, an additional soft excess component dominates,
which is consistent with a model with either a steeper power law with Gamma
Soft = 3.3-3.85, or the warm Comptonization component. These emissions from the
central engine are absorbed by a partial covering material and warm absorbers.
A reflection component and several emission lines are also present. We examined
the relationship between the intrinsic luminosity and the absorbers' physical
parameters such as the column density, which suggests that the source expanded
significantly during the bright states when the soft excess is greatly
enhanced.


  Both theoretical and applied economics have a great deal to say about many
aspects of the firm, but the literature on the extinctions, or demises, of
firms is very sparse. We use a publicly available data base covering some 6
million firms in the US and show that the underlying statistical distribution
which characterises the frequency of firm demises - the disappearances of firms
as autonomous entities - is closely approximated by a power law. The exponent
of the power law is, intriguingly, close to that reported in the literature on
the extinction of biological species.


  Dipolar susceptibility of interfacial water and the corresponding interface
dielectric constant were calculated from numerical molecular dynamics
simulations for neutral and charged states of buckminsterfullerene C$_{60}$.
Dielectric constants in the range 10--22, depending on temperature and solute
charge, were found. The hydration water undergoes a structural crossover as a
function of the solute charge. Its main signatures include the release of
dangling O-H bonds pointing toward the solute and the change in the
preferential orientations of hydration water from those characterizing
hydrophobic to charged substrates. The interface dielectric constant marks the
structural transition with a spike. The computational formalism adopted here
provides direct access to interface susceptibility from configurations produced
by computer simulations. The required property is the cross-correlation between
the radial projection of the dipole moment of the solvation shell and the
electrostatic potential of the solvent inside the solute.


  A summary of work on distributed games and strategies done within the first
three years of the ERC project ECSYM is presented.


  Quantum engineering now allows to design and construct multi-qubit states in
a range of physical systems. These states are typically quite complex in
nature, with disparate, but relevant properties that include both single and
multi-qubit coherences and even entanglement. All these properties can be
assessed by reconstructing the density matrix of those states - but the large
parameter space can mean physical insight of the nature of those states and
their coherence can be hard to achieve. Here we explore how the Wigner function
of a multipartite system and its visualization provides rich information on the
nature of the state, not only at illustrative level but also at the
quantitative level. We test our tools in a photonic architecture making use of
the multiple degrees of freedom of two photons.


  It was shown that N=1 super-symmetry algebra can be constructed in de Sitter
space, through calculation of charge conjugation in the ambient space notation.
Calculation of N=2 super-symmetry algebra constitutes the main frame of this
paper. N=2 super-symmetry algebra was presented in. In this paper, we obtain an
alternative N=2 super-symmetry algebra.


  Various applications in the field of autonomous driving are based on
convolutional neural networks (CNNs), especially for processing camera data.
The optimization of such CNNs is a major challenge in continuous development.
Newly learned features must be brought into vehicles as quickly as possible,
and as such, it is not feasible to spend redundant GPU hours during
compression. In this context, we present Learning to Prune Faster which details
a multi-task, try-and-learn method, discretely learning redundant filters of
the CNN and a continuous action of how long the layers have to be fine-tuned.
This allows us to significantly speed up the convergence process of learning
how to find an embedded-friendly filter-wise pruned CNN. For ResNet20, we have
achieved a compression ratio of 3.84 x with minimal accuracy degradation.
Compared to the state-of-the-art pruning method, we reduced the GPU hours by
1.71 x.


  Our Visual Analytics (VA) tool ScrutinAI supports human analysts to
investigate interactively model performanceand data sets. Model performance
depends on labeling quality to a large extent. In particular in medical
settings, generation of high quality labels requires in depth expert knowledge
and is very costly. Often, data sets are labeled by collecting opinions of
groups of experts. We use our VA tool to analyse the influence of label
variations between different experts on the model performance. ScrutinAI
facilitates to perform a root cause analysis that distinguishes weaknesses of
deep neural network (DNN) models caused by varying or missing labeling quality
from true weaknesses. We scrutinize the overall detection of intracranial
hemorrhages and the more subtle differentiation between subtypes in a publicly
available data set.


  We study the physical properties (size, stellar mass, luminosity, star
formation rate) and scaling relations for a sample of 166 star-forming clumps
with redshift $z \sim 2-6.2$. They are magnified by the Hubble Frontier Field
galaxy cluster MACS~J0416 and have robust lensing magnification ($2\lesssim \mu
\lesssim 82$) computed by using our high-precision lens model, based on 182
multiple images. Our sample extends by $\sim 3$ times the number of
spectroscopically-confirmed lensed clumps at $z \gtrsim 2$. We identify clumps
in ultraviolet continuum images and find that, whenever the effective spatial
resolution (enhanced by gravitational lensing) increases, they fragment into
smaller entities, likely reflecting the hierarchically-organized nature of star
formation. Kpc-scale clumps, most commonly observed in field, are not found in
our sample. The physical properties of our sample extend the parameter space
typically probed by $z \gtrsim 1$ field observations and simulations, by
populating the low mass (M$_\star \lesssim 10^7$ M$_\odot$), low star formation
rate (SFR $\lesssim 0.5$ M$_\odot$ yr$^{-1}$), and small size (R$_\mathrm{eff}
\lesssim 100$ pc) regime. The new domain probed by our study approaches the
regime of compact stellar complexes and star clusters. In the mass-size plane,
our sample spans the region between galaxies and globular clusters, with a few
clumps in the region populated by young star clusters and globular-clusters.
For the bulk of our sample, we measure star-formation rates which are higher
than those observed locally in compact stellar systems, indicating different
conditions for star formation at high redshift than in the local Universe.


  This paper introduces a novel idea of coordinated vehicle platooning such
that platoon followers inside the platoon communicates only to the platoon
leader. A novel dynamic model is proposed to take driving safety into account
when there is communication delay. Some general results of linear stability are
proved mathematically, and numerical simulations are conducted to show the
effect of model parameters for both ring road with an initial disturbance and
infinite road with a periodic disturbance. The simulation results are
consistent with theoretical analysis, and demonstrate that the proposed
look-to-the-leader platooning strategy is far superior than the
follow-one-vehicle-ahead or follow-two-vehicle-ahead conventional car-following
(CF) strategies in stabilizing traffic flow. This paper provides a new
perspective for the organization of platoons of autonomous vehicles.


  We have observed the BL Lac object 1ES2344+514 (z = 0.044) in Very High
Energy (VHE) gamma-ray and near-infrared wavelength bands with TACTIC and MIRO
telescopes respectively. The observations were made from 18th October to 9th
December 2004 and 27th October 2005 to 1st January 2006. Detailed analysis of
the TACTIC data indicates absence of a statistically significant gamma-ray
signal both in overall data and on a nightly basis from the source direction.
We estimate an upper limit of I($\geq$1.5 TeV)$\leq 3.84 \times 10^{-12}$
photons cm$^{-2}$ s$^{-1}$ at a 3$\sigma$ confidence level on the integrated
$\gamma$-ray flux. In addition, we have also compared TACTIC TeV light curves
with those of the RXTE ASM (2-12keV) for the contemporary period and find that
there are no statistically significant increases in the signal strengths from
the source in both these energy regions. During 2004 IR observations,
1ES2344+514 shows low level (~0.06 magnitude) day-to-day variation in both, J &
H bands. However, during 2005 observation epoch, the source brightens up by
about 0.41 magnitude from its October 2005 level J magnitude= 12.64 to J =
12.23 on December 6, 2005. It then fades by about 0.2 magnitude during 6 to 10
December, 2005. The variation is seen in both, J & H, bands simultaneously. The
light travel time arguments suggest that the emission region size is of the
order of $10^{17}$ cms.


  Realistic music generation has always remained as a challenging problem as it
may lack structure or rationality. In this work, we propose a deep learning
based music generation method in order to produce old style music particularly
JAZZ with rehashed melodic structures utilizing a Bi-directional Long Short
Term Memory (Bi-LSTM) Neural Network with Attention. Owing to the success in
modelling long-term temporal dependencies in sequential data and its success in
case of videos, Bi-LSTMs with attention serve as the natural choice and early
utilization in music generation. We validate in our experiments that Bi-LSTMs
with attention are able to preserve the richness and technical nuances of the
music performed.


  Wind power is one of the most important renewable energy sources and accurate
wind power forecasting is very significant for reliable and economic power
system operation and control strategies. This paper proposes a novel framework
with spatiotemporal attention networks (STAN) for wind power forecasting. This
model captures spatial correlations among wind farms and temporal dependencies
of wind power time series. First of all, we employ a multi-head self-attention
mechanism to extract spatial correlations among wind farms. Then, temporal
dependencies are captured by the Sequence-to-Sequence (Seq2Seq) model with a
global attention mechanism. Finally, experimental results demonstrate that our
model achieves better performance than other baseline approaches. Our work
provides useful insights to capture non-Euclidean spatial correlations.


  In this paper, we give a two dimensional analogue of the Euler-MacLaurin
summation formula. By using this formula, we obtain an integral representation
of Weil's elliptic functions which was introduced in the book "Elliptic
functions according to Eisenstein and Kronecker".


  The first results of the solar dynamo model that allows for the diamagnetic
effect of inhomogeneous turbulence and the nonlocal alpha-effect due to the
rise of magnetic loops are discussed. The nonlocal alpha-effect is not subject
to the catastrophic quenching related to the conservation of magnetic helicity.
Given the diamagnetic pumping, the magnetic fields are concentrated near the
base of the convection zone, although the distributed-type model covers the
entire thickness of the convection zone. The magnetic cycle period, the
equatorial symmetry of the field, its meridional drift, and the
polar-to-toroidal field ratio obtained in the model are in agreement with
observations. There is also some disagreement with observations pointing the
ways of improving the model.


  We study the exponential functional $\int_0^\infty e^{-\xi_{s-}} \, d\eta_s$
of two one-dimensional independent L\'evy processes $\xi$ and $\eta$, where
$\eta$ is a subordinator. In particular, we derive an integro-differential
equation for the density of the exponential functional whenever it exists.
Further, we consider the mapping $\Phi_\xi$ for a fixed L\'evy process $\xi$,
which maps the law of $\eta_1$ to the law of the corresponding exponential
functional $\int_0^\infty e^{-\xi_{s-}} \, d\eta_s$, and study the behaviour of
the range of $\Phi_\xi$ for varying characteristics of $\xi$. Moreover, we
derive conditions for selfdecomposable distributions and generalized Gamma
convolutions to be in the range. On the way we also obtain new
characterizations of these classes of distributions.


  The purpose of the following proposal is to create a new class of antennas of
low weight but with a large transmitting and receiving surface made of
metallized fabric. This class of antennas will be stationed in low satellite
orbits, at about 2000 km from sea level and will be easily steerable by
exploiting the interaction between the earth's magnetic field and an
electromagnetic field generated on the antenna. The possibility of orienting
very large ultra-light balloon-like MW antennas, orbiting in the Earth magnetic
field, through electric currents flowing in conductive wires embedded in the
antennas walls, are examined. It is shown that such currents may easily provide
the needed forces without the necessity of mechanically orienting the antenna
itself. The antenna is extremely light, inexpensive, easily directional. The
antenna has the shape of a spheroid in which the southern hemisphere has a
parabolic shape made of metallized fabric; the northern hemisphere, transparent
to the electromagnetic radiation, has a radius of curvature such that the north
pole coincides with the focus of the parabola.


  We describe our work towards the manufacture of micro-optical arrays using
freeform diamond machining techniques. Simulations have been done to show the
feasibility of manufacturing micro-lens arrays using the slow-tool servo
method. Using this technique, master shapes can be produced for replication of
micro-lens arrays of either epoxy-on-glass or monolthic glass types. A machine
tool path programme has been developed on the machine software platform
DIFFSYS, allowing the production of spherical, aspherical and toric arrays. In
addition, in theory spatially varying lenslets, sparse arrays and dithered
lenslet arrays (for high contrast applications) are possible to produce. In
practice, due to the diamond tool limitations not all formats are feasible.
Investigations into solving this problem have been carried out and a solution
is presented here.


  We propose an experimentally feasible scheme for dissipative preparation of
tripartite entangled state with atoms separately trapped in an array of three
coupled cavities. The combination of coherent driving fields and
quantum-jump-based feedback control will drive the system into a
non-equilibrium steady state, which has a nearly perfect overlap with the
genuine three-atom singlet state. Different control strategies are investigated
and the corresponding optimal parameters are confirmed. Moreover, the fidelity
of target state is insensitive to detection inefficiencies, and it oversteps
90\% for a wide range of decoherence parameters as long as the single-atom
cooperativity parameter $C\equiv g^2/(\gamma\kappa)>350$.


  In this paper we investigate a class of solutions of Einstein equations for
the plane-symmetric perfect fluid case with shear and vanishing acceleration.
If these solutions have shear, they must necessarily be non-static. We examine
the integrable cases of the field equations systematically. Among the cases
with shear we find three classes of solutions.