  Fractals are defined as geometric shapes that exhibit symmetry of scale. This
simply implies that fractal is a shape that it would still look the same even
if somebody could zoom in on one of its parts an infinite number of times. This
property is also called self-similarity with several applications including
nano pharmacology and drug nano carriers. We are interested in the study of the
properties of fractal aggregates in a microgravity environment above an
orbiting spacecraft. To model the effect we use a complete expression for the
gravitational acceleration. In particular on the surface of the Earth the
acceleration is corrected for the effect of oblateness and rotation. In the
gravitational acceleration the effect of oblateness can be modeled with the
inclusion of a term that contains the J2 harmonic coefficient, as well as a
term that depends on the square of angular velocity of the Earth. In orbit the
acceleration of gravity at the point of the spacecraft is a function of the
orbital elements and includes only in our case the J2 harmonic since no
coriolis force is felt by the spacecraft. Using the fitting parameter d = 3.0
we have found that the aggregate monomer number N is not significantly affected
and exhibits a minute 0.0001% difference between the geocentric and areocentric
latitudes of 90 degrees and 0 degrees. Finally for circular and elliptical
orbits around Earth and Mars of various inclinations and eccentricities the
aggregate monomer number is not affected at all at the orbital altitude of 300
km.


  The Android operating system is pervasively adopted as the operating system
platform of choice for smart devices. However, the strong adoption has also
resulted in exponential growth in the number of Android based malicious
software or malware. To deal with such cyber threats as part of cyber
investigation and digital forensics, computational techniques in the form of
machine learning algorithms are applied for such malware identification,
detection and forensics analysis. However, such Computational Forensics
modelling techniques are constrained the volume, velocity, variety and veracity
of the malware landscape. This in turn would affect its identification and
detection effectiveness. Such consequence would inherently induce the question
of sustainability with such solution approach. One approach to optimise
effectiveness is to apply dimensional reduction techniques like Principal
Component Analysis with the intent to enhance algorithmic performance. In this
paper, we evaluate the effectiveness of the application of Principle Component
Analysis on Computational Forensics task of detecting Android based malware. We
applied our research hypothesis to three different datasets with different
machine learning algorithms. Our research result showed that the dimensionally
reduced dataset would result in a measure of degradation in accuracy
performance.


  Modern day studies of wind-driven sea waves are usually focused on wind
forcing rather than on the effect of resonant nonlinear wave interactions. The
authors assume that these effects are dominating and propose a simple
relationship between instant wave steepness and time or fetch of wave
development expressed in wave periods or lengths. This law does not contain
wind speed explicitly and relies upon this asymptotic theory. The validity of
this law is illustrated by results of numerical simulations, in situ
measurements of growing wind seas and wind wave tank experiments. The impact of
the new vision of sea wave physics is discussed in the context of conventional
approaches to wave modeling and forecasting.


  We prove endpoint estimates with angular regularity for the wave and Dirac
equations perturbed with a small potential. The estimates are applied to prove
global existence for the cubic Dirac equation perturbed with a small potential,
for small initial $H^{1}$ data with additional angular regularity. This implies
in particular global existence in the critical energy space $H^{1}$ for small
radial data.


  This work covers the effect of droplet deformation on its evaporation rate
under convective flow conditions. The evaporation behavior of a freely
deforming droplet of single component jet fuel surrogate, n-decane, is
investigated by varying Weber number ($We$) from $1-12$ and Reynolds number
($Re$) from $25$ to $120$ under high-pressure environment. These studies
utilize interface capturing Direct Numerical Simulation (DNS). To validate the
accuracy of the solver, the results are compared against correlations by
Abramzon and Sirignano (Int. Journal of Heat and Mass Transfer, 1989) and are
found to be in good agreement with a maximum difference of $5 \%$.
\textcolor{black}{A quasi-steady evaporation approach is implemented to
simulate this problem.} The results suggest a weak dependency of normalized
total evaporation rate (${\dot{m}}_{ND}$) on Weber number at low $Re$ flow.
However, a strong correlation is seen between the total evaporation rate and
$We$ at high $Re$. $20 \%$ enhancement in ${\dot{m}}_{ND}$ is observed at
$We=12$ (highly deformed shape) when compared to $We=1$ at $Re=120$.
  In these cases, the distribution of local evaporation flux on the droplet is
found to be proportional to its curvature up to the point of flow separation
which agrees with low $Re$ theories on droplet evaporation by Tonini and
Cossalli (International Journal of Heat and Mass Transfer 2013), Palmore
(Journal of Heat Transfer 2022). Beyond the flow separation point, evaporation
flux distribution depends on the boundary layer development and flow evolution
downstream of the droplet. For highly deformed droplets, a larger wake region
creates favorable fuel vapor gradients and promotes mixing in droplet wake,
hence higher evaporation flux.


  Single-cell experiments show that gene expression is stochastic and bursty, a
feature that can emerge from slow switching between promoter states with
different activities. One source of long-lived promoter states is the slow
binding and unbinding kinetics of transcription factors to promoters, i.e. the
non-adiabatic binding regime. Here, we introduce a simple analytical framework,
known as a piecewise deterministic Markov process (PDMP), that accurately
describes the stochastic dynamics of gene expression in the non-adiabatic
regime. We illustrate the utility of the PDMP on a non-trivial dynamical system
by analyzing the properties of a titration-based oscillator in the
non-adiabatic limit. We first show how to transform the underlying Chemical
Master Equation into a PDMP where the slow transitions between promoter states
are stochastic, but whose rates depend upon the faster deterministic dynamics
of the transcription factors regulated by these promoters. We show that the
PDMP accurately describes the observed periods of stochastic cycles in
activator and repressor-based titration oscillators. We then generalize our
PDMP analysis to more complicated versions of titration-based oscillators to
explain how multiple binding sites lengthen the period and improve coherence.
Last, we show how noise-induced oscillation previously observed in a
titration-based oscillator arises from non-adiabatic and discrete binding
events at the promoter site.


  Theories with generalised conformal structure contain a dimensionful
parameter, which appears as an overall multiplicative factor in the action.
Examples of such theories are gauge theories coupled to massless scalars and
fermions with Yukawa interactions and quartic couplings for the scalars in
spacetime dimensions other than 4. Many properties of such theories are similar
to that of conformal field theories (CFT), and in particular their 2-point
functions take the same form as in CFT but with the normalisation constant now
replaced by a function of the effective dimensionless coupling $g$ constructed
from the dimensionful parameter and the distance separating the two operators.
Such theories appear in holographic dualities involving non-conformal branes
and this behaviour of the correlators has already been observed at strong
coupling. Here we present a perturbative computation of the two-point function
of the energy-momentum tensor to two loops in dimensions $d= 3, 5$, confirming
the expected structure and determining the corresponding functions of $g$ to
this order, including the effects of renormalisation. We also discuss the d=4
case for comparison. The results for $d=3$ are relevant for holographic
cosmology, and in this case we also study the effect of a $\Phi^6$ coupling,
which while marginal in the usual sense it is irrelevant from the perspective
of the generalised conformal structure. Indeed, the effect of such coupling in
the 2-point function is washed out in the IR but it modifies the UV.


  The MEGAPIE project is a key experiment on the road to Accelerator Driven
Systems and it provides the scientific community with unique data on the
behavior of a liquid lead-bismuth spallation target under realistic and long
term irradiation conditions. The neutronic of such target is of course of prime
importance when considering its final destination as an intense neutron source.
This is the motivation to characterize the inside neutron flux of the target in
operation. A complex detector, made of 8 micro fission-chambers, has been built
and installed in the core of the target, few tens of centimeters from the
proton/Pb-Bi interaction zone. This detector is designed to measure the
absolute neutron flux inside the target, to give its spatial distribution and
to correlate its temporal variations with the beam intensity. Moreover,
integral information on the neutron energy distribution as a function of the
position along the beam axis could be extracted, giving integral constraints on
the neutron production models implemented in transport codes such as MCNPX.


  In this work we propose an extended formulation for the interaction between
neutrinos and gravitational fields. It is based on the parametrized
post-Newtonian aproach, and includes a violation of the universality of the
gravitational interaction which is non diagonal in the weak flavor space. We
find new effects that are not considered in the standard scenario for violation
of the equivalence principle. They are of the same order as the effects
produced by the Newtonian potential, but they are highly directional dependent
and could provide a very clean test of that violation. Phenomenological
consequences are briefly discussed.


  Using light-cone sum rule techniques, we estimate the form factors which
parametrise the hadronic matrix elements that are relevant for semi-leptonic
three-body proton decays. The obtained form factors allow us to determine the
differential rate for the decay of a proton ($p$) into a positron ($e^+$), a
neutral pion ($\pi^0$) and a graviton ($G$), which is the leading proton decay
channel in the effective theory of gravitons and Standard Model particles
(GRSMEFT). The sensitivity of existing and next-generation neutrino experiments
in detecting the $p \to e^+ \pi^0 G$ signature is studied and the
phenomenological implications of our computations for constraints on the
effective mass scale that suppresses the relevant baryon-number violating
GRSMEFT operator are discussed.


  We report on what is to our knowledge the first scattering experiment of
surface waves on an accelerating transcritical flow, which in the Analogue
Gravity context is described by an effective spacetime with a black-hole
horizon. This spacetime has been probed by an incident co-current wave, which
partially scatters into an outgoing counter-current wave on each side of the
horizon. The measured scattering amplitudes are compatible with the predictions
of the hydrodynamical theory, where the kinematical description in terms of the
effective metric is exact.


  We show that the quadratic transportation cost inequality $T_2$ is equivalent
to both a Poincar\'e inequality and a strong form of the Gaussian concentration
property. The main ingredient in the proof is a new family of inequalities,
called modified quadratic transportation cost inequalities in the spirit of the
modified logarithmic-Sobolev inequalities by Bobkov and Ledoux \cite{BL97},
that are shown to hold as soon as a Poincar\'e inequality is satisfied.


  With the pervasive network based services in smart homes, traditional network
management cannot guarantee end-user quality-of-experience (QoE) for all
applications. End-user QoE must be supported by efficient network
quality-of-service (QoS) measurement and efficient network resource allocation.
With the software-defined network technology, the core network may be
controlled more efficiently by a network service provider. However, end-to-end
network QoS can hardly be improved the managing the core network only. In this
paper, we propose an encrypted packet classification scheme for smart home
gateways to improve end-to-end QoS measurement from the network operator side.
Furthermore, other services such as statistical data collecting, billing to
service providers, etc., can be provided without compromising end-user privacy
nor security of a network. The proposed encrypted packet classification scheme
has a two-level hierarchical structure. One is the service level, which is
based on applications that have the same network QoS requirements. A faster
classification scheme based on deep learning is proposed to achieve real-time
classification with high accuracy. The other one is the application level,
which is based on fine-grained applications. A non-real-time classifier can be
applied to provide high accuracy. Evaluation is conducted on both level
classifiers to demonstrate the efficiency and accuracy of the two types of
classifiers.


  Recently a suggestion has been made that standard textbook representations of
hypersurfaces of simultaneity for the travelling twin in the twin "paradox" are
incorrect. This suggestion is false: the standard textbooks are in agreement
with a proper understanding of the relativity of simultaneity.


  Higher-order corrections to the MSSM Higgs-boson masses are desirable for
accurate predictions currently testable at the LHC. By comparing the prediction
with the measured value of the discovered Higgs signal, viable parameter
regions can be inferred. For an improved theory accuracy, we compute all
two-loop corrections involving the strong coupling for the Higgs-boson mass
spectrum of the MSSM with complex parameters. Apart from the dependence on the
strong coupling, these contributions depend on the weak coupling and Yukawa
couplings, leading to terms of $\mathcal{O}{\left(\alpha\alpha_s\right)}$ and
$\mathcal{O}{\left(\sqrt{\alpha_{q_1}}\sqrt{\alpha_{q_2}}\alpha_s\right)}$,
($q_{1,2}=t,b,c,s,u,d$). The full dependence on the external momentum and all
relevant mass scales is taken into account. The calculation is performed in the
Feynman-diagrammatic approach which is flexible in the choice of the employed
renormalization scheme. For the phenomenological results presented here, a
renormalization scheme consistent with higher-order corrections included in the
code $\texttt{FeynHiggs}$ is adopted. For the evaluation of the results, a
total of $513$ two-loop two-point integrals with up to five different mass
scales are computed fully numerically using the program $\texttt{SecDec}$. A
comparison with existing results in the limit of real parameters and/or
vanishing external momentum is carried out, and the impact on the lightest
Higgs-boson mass is discussed, including the dependence on complex phases. The
new results will be included in the public code $\texttt{FeynHiggs}$.


  Artificial Intelligence (AI) models are vulnerable to information leakage of
their training data, which can be highly sensitive, for example in medical
imaging. Privacy Enhancing Technologies (PETs), such as Differential Privacy
(DP), aim to circumvent these susceptibilities. DP is the strongest possible
protection for training models while bounding the risks of inferring the
inclusion of training samples or reconstructing the original data. DP achieves
this by setting a quantifiable privacy budget. Although a lower budget
decreases the risk of information leakage, it typically also reduces the
performance of such models. This imposes a trade-off between robust performance
and stringent privacy. Additionally, the interpretation of a privacy budget
remains abstract and challenging to contextualize. In this study, we contrast
the performance of AI models at various privacy budgets against both,
theoretical risk bounds and empirical success of reconstruction attacks. We
show that using very large privacy budgets can render reconstruction attacks
impossible, while drops in performance are negligible. We thus conclude that
not using DP -- at all -- is negligent when applying AI models to sensitive
data. We deem those results to lie a foundation for further debates on striking
a balance between privacy risks and model performance.


  The single-source shortest path problem is a classical problem in the
research field of graph algorithm. In this paper, a new single-source shortest
path algorithm for nonnegative weight graph is proposed. The algorithm can
compress multi-round Fibonacci heap operations to one round to save running
time relative to Dijkstra's algorithm using Fibonacci heap. The time complexity
of the algorithm is also O(m+nlogn) in the worst case, where m is the number of
edges and n is the number of nodes. However, the bound can be linear in some
case, for example, when edge weights of a graph are all the same and the hop
count of the longest shortest path is much less than n.Based on the theoretical
analyses, we demonstrate that the algorithm is faster than Dijkstra's algorithm
using Fibonacci heap in average situation when n is large enough.


  In this work we present a gauge-invariant three-dimensional teleparallel
supergravity theory using the Chern-Simons formalism. The present construction
is based on a supersymmetric extension of a particular deformation of the
Poincar\'e algebra. At the bosonic level the theory describes a non-Riemannian
geometry with a non-vanishing torsion. In presence of supersymmetry, the
teleparallel supergravity theory is characterized by a non-vanishing
super-torsion in which the cosmological constant can be seen as a source for
the torsion. We show that the teleparallel supergravity theory presented here
reproduces the Poincar\'e supergravity in the vanishing cosmological limit. The
extension of our results to $\mathcal{N}=p+q$ supersymmetries is also explored.


  We consider a periodic problem for the motion of a charged particle in a
magnetic field. Introducing a notion of Ricci curvature for such Lagrangian
systems and using the methods of the calculus of variations in the large, we
prove the existence of periodic motions for such particles under a condition of
positivity of the Ricci curvature.


  We propose relative entropy-based quantifiers for genuine multipartite total,
quantum, and classical correlations. These correlation measures are applied to
investigate the generation of genuine multiparticle correlations in decoherent
dynamics induced by the interaction of two qubits with local- independent
environments. We consider amplitude- and phase-damping channels and compare
their capabilities to spread information through the creation of many-body
correlations. We identify changes in behavior for the genuine four- and
three-partite total correlations and show that, contrary to amplitude
environments, phase-noise channels transform the bipartite correlation
initially shared between the qubits into genuine multiparticle
system-environment correlations.


  We study the complexity of finding an optimal hierarchical clustering of an
unweighted similarity graph under the recently introduced Dasgupta objective
function. We introduce a proof technique, called the normalization procedure,
that takes any such clustering of a graph $G$ and iteratively improves it until
a desired target clustering of G is reached. We use this technique to show both
a negative and a positive complexity result. Firstly, we show that in general
the problem is NP-complete. Secondly, we consider min-well-behaved graphs,
which are graphs $H$ having the property that for any $k$ the graph $H(k)$
being the join of $k$ copies of $H$ has an optimal hierarchical clustering that
splits each copy of $H$ in the same optimal way. To optimally cluster such a
graph $H(k)$ we thus only need to optimally cluster the smaller graph $H$.
Co-bipartite graphs are min-well-behaved, but otherwise they seem to be scarce.
We use the normalization procedure to show that also the cycle on 6 vertices is
min-well-behaved.


  The Bianchi groups ${\rm Bi}(d)={\rm PSL}(2,\mathcal{O}_d) < {\rm PSL}(2,\C)$
(where $\mathcal{O}_d$ denotes the ring of integers of $\Q (i\sqrt{d})$, with
$d \geqslant 1$ squarefree) can be viewed as subgroups of ${\rm SO}(3,1)$ under
the isomorphism ${\rm PSL}(2,\C) \simeq {\rm SO}^0(3,1)$. We study the
deformations of these groups into the larger Lie groups ${\rm SU}(3,1)$ and
${\rm SL}(4,\R)$ for small values of $d$. In particular we show that ${\rm
Bi}(3)$, which is rigid in ${\rm SO}(3,1)$, admits a 1-dimensional deformation
space into ${\rm SU}(3,1)$ and ${\rm SL}(4,\R)$, whereas any deformation of
${\rm Bi}(1)$ into ${\rm SU}(3,1)$ or ${\rm SL}(4,\R)$ is conjugate to one
inside ${\rm SO}(3,1)$. We also show that none of the deformations into ${\rm
SU}(3,1)$ are both discrete and faithful.


  We derive a closed equation for the empirical concentration of colloidal
particles in the presence of both hydrodynamic and direct interactions. The
ensemble average of our functional Langevin equation reproduces known
deterministic Dynamic Density Functional Theory (DDFT) [Rex and L\"owen, Phys.
Rev. Lett., 101(14):148302, 2008], and, at the same time, it also describes the
microscopic fluctuations around the mean behavior. We suggest separating the
ideal (non-interacting) contribution from additional corrections due to
pairwise interactions. We find that, for an incompressible fluid and in the
absence of direct interactions, the mean concentration follows Fick's law just
as for uncorrelated walkers. At the same time, the nature of the stochastic
terms in fluctuating DDFT is shown to be distinctly different for
hydrodynamically-correlated and uncorrelated walkers. This leads to striking
differences in the behavior of the fluctuations around Fick's law, even in the
absence of pairwise interactions. We connect our own prior work [A. Donev, T.
G. Fai, E. Vanden-Eijnden, J. Stat. Mech., P04004, 2014] on fluctuating
hydrodynamics of diffusion in liquids to the DDFT literature, and demonstrate
that the fluid cannot easily be eliminated from consideration if one wants to
describe the collective diffusion in colloidal suspensions.


  This work opens a new chapter in the 100,000 year-old concept of paint, by
leveraging innovations in nano-technology in the sub-THz frequency range. More
specifically, the groundbreaking concept of Internet of Paint (IoP) is
introduced along with a comprehensive channel model and a capacity analysis for
nano-scale radios embedded in paint and communicating through paint.
Nano-network devices, integrated within a paint medium, communicate via a
multipath strategy, encompassing direct waves, reflections from interfaces, and
lateral wave propagation. The evaluation incorporates three distinct paint
types to assess path losses, received powers, and channel capacity. Analysis of
path loss indicates a slight non-linear increase with both frequency and Line
of Sight (LoS) distance between transceivers. Notably, paints with high
refractive indexes result in the highest path loss. Moreover, burying
transceivers at similar depths near the Air-Paint interface showcases promising
performance of lateral waves with increasing LoS distance. Increasing paint
layer depth leads to amplified attenuation, while total received power exhibits
promising results when in close proximity to the Air-Paint interface but
steeply declines with burial depth. Additionally, a substantial reduction in
channel capacity is observed with LoS distance and burial depth, so
transceivers need to be close together and in proximity of the A-P interface to
communicate effectively. Comparing paint and air mediums, IoP demonstrates
approximately two orders of magnitude reduction in channel capacity compared to
air-based communication channels. This paper provides valuable insights into
the potential of IoP communication within paint mediums and offers a foundation
for further advancements in this emerging field.


  In this paper, we introduce a sociolinguistic perspective on language
modeling. We claim that large language models are inherently models of
varieties of language, and we consider how this insight can inform the
development and deployment of large language models. We begin by presenting a
technical definition of the concept of a variety of language as developed in
sociolinguistics. We then discuss how this perspective can help address five
basic challenges in language modeling: social bias, domain adaptation,
alignment, language change, and scale. Ultimately, we argue that it is crucial
to carefully define and compile training corpora that accurately represent the
specific varieties of language being modeled to maximize the performance and
societal value of large language models.


  The study of invisibility of an infinite dielectric rod with high refractive
index is based on the two-dimensional Mie scattering problem, and it suggests
strong suppression of scattering due to the Fano interference between
spectrally broad nonresonant waves and narrow Mie-resonant modes. However, when
the dielectric rod has a finite extension, it becomes a resonator supporting
the Fabry-Perot modes which introduce additional scattering and eventually
destroy the invisibility. Here we reveal that for shorter rods with modest
values of the aspect ratio r/L (where r and L are the radius and length of the
rod, respectively), the lowest spectral window of the scattering suppression
recovers completely, so that even a finite-size resonator may become invisible.
We present a direct experimental verification of the concept of switchable
invisibility at microwaves using a cylindrical finite-size resonator with high
refractive index.


  We study time-dependent density fluctuations in the stationary state of
driven diffusive systems with two conserved densities $\rho_\lambda$. Using
Monte-Carlo simulations of two coupled single-lane asymmetric simple exclusion
processes we present numerical evidence for universality classes with dynamical
exponents $z=(1+\sqrt{5})/2$ and $z=3/2$ (but different from the
Kardar-Parisi-Zhang (KPZ) universality class), which have not been reported yet
for driven diffusive systems. The numerical asymmetry of the dynamical
structure functions converges slowly for some of the non-KPZ superdiffusive
modes for which mode coupling theory predicts maximally asymmetric $z$-stable
L\'evy scaling functions. We show that all universality classes predicted by
mode coupling theory for two conservation laws are generic: They occur in
two-component systems with nonlinearities in the associated currents already of
the minimal order $\rho_\lambda^2\rho_\mu$. The macroscopic stationary
current-density relation and the compressibility matrix determine completely
all permissible universality classes through the mode coupling coefficients
which we compute explicitly for general two-component systems.


  The amplification of disk oscillations resulting from nonlinear resonant
couplings between the oscillations and a disk deformation is examined. The disk
is geometrically thin and general relativistic with a non-rotating central
source. A Lagrangian formulation is adopted. The author examined the same
problem a few years ago, but here we derive a general stability criterion in a
more perspective way. Another distinct point from the previous work is that in
addition to the case where the deformation is a warp, the case where the
deformation is a one-armed pattern symmetric with respect to the equatorial
plane is considered. The results obtained show that in addition to the previous
results that the inertial-acoustic mode and g-mode oscillations are amplified
by horizontal resonance in warped disks, they also amplified by horizontal
resonance in disks deformed by one-armed pattern symmetric with respect to the
equatorial plane. If we consider local oscillations that are localized around
boundaries of their propagation region, the resonance occurs at $4r_{\rm g}$,
where $r_{\rm g}$ is the Schwarzschild radius. If nonlocal oscillations are
considered, frequency ranges of oscillations where oscillations are resonantly
amplified are specified.


  The aim of this paper is to revisit some duality results in conic linear
programming and to answer an open problem related to the duality gap function
for Gale's example.


  The Quantum Alternating Operator Ansatz (QAOA+) is one of the Variational
Quantum Algorithm (VQA) specifically developed to tackle combinatorial
optimization problems by exploring the feasible space in search of a target
solution. For constrained optimization problems with unconstrained variables,
which we call Unconstrained-Variables Problems (UVPs), the mixed operators in
the QAOA+ circuit are applied to the constrained variables, while the
single-qubit rotating gates $R_X$ operate on the unconstrained variables. The
expressibility of this circuit is limited by the shortage of two-qubit gates
and the parameter sharing in the $R_X$, which consequently impacts the
performance of QAOA+ for solving UVPs. Therefore, it is crucial to develop a
suitable ansatz for UVPs. In this paper, we propose the Variational Quantum
Algorithm-Preserving Feasible Space (VQA-PFS) ansatz, exemplified by the
Uncapacitated Facility Location Problem (UFLP), that applies mixed operators on
constrained variables while employing Hardware-Efficient Ansatz (HEA) on
unconstrained variables. The numerical results demonstrate that VQA-PFS
significantly enhances the success probability and exhibits faster convergence
compared to QAOA+, Quantum Approximation Optimization Algorithm (QAOA), and
HEA. Furthermore, VQA-PFS reduces the circuit depth dramatically in comparison
to QAOA+ and QAOA. Our algorithm is general and instructive in tackling UVPs.


  In recent years, operator learning, particularly the DeepONet, has received
much attention for efficiently learning complex mappings between input and
output functions across diverse fields. However, in practical scenarios with
limited and noisy data, accessing the uncertainty in DeepONet predictions
becomes essential, especially in mission-critical or safety-critical
applications. Existing methods, either computationally intensive or yielding
unsatisfactory uncertainty quantification, leave room for developing efficient
and informative uncertainty quantification (UQ) techniques tailored for
DeepONets. In this work, we proposed a novel inference approach for efficient
UQ for operator learning by harnessing the power of the Ensemble Kalman
Inversion (EKI) approach. EKI, known for its derivative-free, noise-robust, and
highly parallelizable feature, has demonstrated its advantages for UQ for
physics-informed neural networks [28]. Our innovative application of EKI
enables us to efficiently train ensembles of DeepONets while obtaining
informative uncertainty estimates for the output of interest. We deploy a
mini-batch variant of EKI to accommodate larger datasets, mitigating the
computational demand due to large datasets during the training stage.
Furthermore, we introduce a heuristic method to estimate the artificial
dynamics covariance, thereby improving our uncertainty estimates. Finally, we
demonstrate the effectiveness and versatility of our proposed methodology
across various benchmark problems, showcasing its potential to address the
pressing challenges of uncertainty quantification in DeepONets, especially for
practical applications with limited and noisy data.


  Two methods based on bremsstrahlung were applied to the stable even Mo
isotopes for the experimental determination of the photon strength function
covering the high excitation energy range above 4 MeV with its increasing level
density. Photon scattering was used up to the neutron separation energies Sn
and data up to the maximum of the isovector giant resonance(GDR) were obtained
by photo-activation. After a proper correction for multi-step processes the
observed quasi-continuous spectra of scattered photons show a remarkably good
match to the photon strengths derived from nuclear photo effect data obtained
previously by neutron detection and corrected in absolute scale using the new
activation results. The combined data form an excellent basis to derive a shape
dependence of the E1 strength in the even Mo isotopes with increasing deviation
from the N = 50 neutron shell, i.e. with the impact of quadrupole deformation
and triaxiality. The wide energy coverage of the data allows for a stringent
assessment of the dipole sum-rule, and a test of a novel parameterization
developed previously which is based upon. This parameterization for the
electric dipole strength function in nuclei with A>80 deviates significantly
from prescriptions generally used previously. In astrophysical network
calculations it may help to quantify the role the p-process plays in the cosmic
nucleosynthesis. It also has impact on the accurate analysis of neutron capture
data of importance for future nuclear energy systems and waste transmutation.


  We report the measurement of charged $D^*$ mesons in inclusive jets produced
in proton-proton collisions at a center of mass energy $\sqrt{s}$ = 200 GeV
with the STAR experiment at RHIC. For $D^{*}$ mesons with fractional momenta
$0.2 < z < 0.5$ in inclusive jets with 11.5 GeV mean transverse energy, the
production rate is found to be $N(D^{*+}+D^{*-})/N(\mathrm{jet}) = 0.015 \pm
0.008 (\mathrm{stat}) \pm 0.007 (\mathrm{sys})$. This rate is consistent with
perturbative QCD evaluation of gluon splitting into a pair of charm quarks and
subsequent hadronization.


  In this paper, we show that, the family of all possible union of finite
consecutive cylinders of the same rank of $Q_{\infty}$-expansion is faithful
for the Hausdorff dimension calculation. Applying this result, we give the
necessary and sufficient condition for the family of all cylinders of
$Q_{\infty}$-expansion to be faithful for Hausdorff dimension calculation on
the unit interval, this answers the open problem mentioned in a paper of S.
Albeverio et al..


  Hawking radiation, the spontaneous emission of thermal photons from an event
horizon, is one of the most intriguing and elusive predictions of field theory
in curved spacetimes. A formally analogue phenomenon occurs at the supersonic
transition of a fluid: in this respect, ultracold gases stand out among the
most promising systems but the theoretical modelling of this effect has always
been carried out in semiclassical approximation, borrowing part of the analysis
from the gravitational analogy. Here we discuss the exact solution of a
one-dimensional Bose gas flowing against an obstacle, showing that spontaneous
phonon emission (the analogue of Hawking radiation) is predicted without
reference to the gravitational analogy. Long after the creation of the
obstacle, the fluid settles into a stationary state displaying the emission of
sound waves (phonons) in the upstream direction. A careful analysis shows that
a precise correspondence between this phenomenon and the spontaneous emission
of radiation from an event horizon requires additional conditions to be met in
future experiments aimed at identifying the occurrence of the Hawking-like
mechanism in Bose-Einstein condensates.


  In this note, we study the Swampland Distance Conjecture in TCS $G_2$
manifold compactifications of M-theory. In particular, we are interested in
testing a refined version -- the Emergent String Conjecture, in settings with
4d $N=1$ supersymmetry. We find that a weakly coupled, tensionless fundamental
heterotic string does emerge at the infinite distance limit characterized by
shrinking the $K3$-fibre in a TCS $G_2$ manifold. Such a fundamental
tensionless string leads to the parametrically leading infinite tower of
asymptotically massless states, which is in line with the Emergent String
Conjecture. The tensionless string, however, receives quantum corrections. We
check that these quantum corrections do modify the volume of the shrinking
K3-fibre via string duality and hence make the string regain a non-vanishing
tension at the quantum level, leading to a decompactification. Geometrically,
the quantum corrections modify the metric of the classical moduli space and are
expected to obstruct the infinite distance limit. We also comment on another
possible type of infinite distance limit in TCS $G_2$ compactifications, which
might lead to a weakly coupled fundamental type II string theory.


  We introduce the concept of smart radio environments, currently intensely
studied for wireless communication in metasurface-programmable meter-scaled
environments (e.g., inside rooms), on the chip scale. Wireless
networks-on-chips (WNoCs) are a candidate technology to improve inter-core
communication on chips but current proposals are plagued by a dilemma: either
the received signal is weak, or it is significantly reverberated such that the
on-off-keying modulation speed must be throttled. Here, we overcome this vexing
problem by endowing the wireless on-chip environment with in situ
programmability which allows us to shape the channel impulse response (CIR);
thereby, we can impose a pulse-like CIR shape despite strong multipath
propagation and without entailing a reduced received signal strength. First, we
design and characterize a programmable metasurface suitable for integration in
the on-chip environment ("on-chip reconfigurable intelligent surface"). Second,
we optimize its configuration to equalize selected wireless on-chip channels
"over the air". Third, by conducting a rigorous communication analysis, we
evidence the feasibility of significantly higher modulation speeds with shaped
CIRs. Our results introduce a programmability paradigm to WNoCs which boosts
their competitiveness as complementary on-chip interconnect solution.


  We calculate spectral functions within the t-J model as relevant to cuprates
in the regime from low to optimum doping. On the basis of equations of motion
for projected operators an effective spin-fermion coupling is derived. The self
energy due to short-wavelength transverse spin fluctuations is shown to lead to
a modified selfconsistent Born approximation, which can explain strong
asymmetry between hole and electron quasiparticles. The coupling to
long-wavelength longitudinal spin fluctuations governs the low-frequency
behavior and results in a pseudogap behavior, which at low doping effectively
truncates the Fermi surface.


  We show that the finite difference, $-i\pi^2 m^2$, between quadratic and
logarithmic divergent integrals $\int d^4p[m^2(p^2-m^2)^{-2}-(p^2-m^2)^{-1}]$,
as encountered in the linear $\sigma$ model, is in fact regularization
independent.


  Power and efficiency of heat engines are two conflicting objectives, and a
tight efficiency bound is expected to give insights on the fundamental
properties of the power-efficiency tradeoff. Here we derive an upper bound on
the efficiency of steady-state heat engines, which incorporates higher-order
fluctuations of the power. In a prototypical model of nonlinear nanostructured
thermoelectrics, we show that the obtained bound is tighter than a
well-established efficiency bound based on the thermodynamic uncertainty
relation, demonstrating that the higher-order terms have rich information about
the thermodynamic efficiency in the nonlinear regime. In particular, we find
that the higher-order bound is exactly achieved if the tight coupling condition
is satisfied. The obtained bound gives a consistent prediction with the
observation that nonlinearity enhances the power-efficiency tradeoff, and would
also be useful for various nanoscale engines.


  We study a stylized multiple testing problem where the test statistics are
independent and assumed to have the same distribution under their respective
null hypotheses. We first show that, in the normal means model where the test
statistics are normal Z-scores, the well-known method of (Benjamini and
Hochberg, 1995) is optimal in some asymptotic sense. We then show that this is
also the case of a recent distribution-free method proposed by Foygel-Barber
and Cand\`es (2015). The method is distribution-free in the sense that it is
agnostic to the null distribution - it only requires that the null distribution
be symmetric. We extend these optimality results to other location models with
a base distribution having fast-decaying tails.


  Number state filtering in coherent states leads to sub-Poissonian photon
statistics. These states are more suitable for phase estimation when compared
with the coherent states. Nonclassicality of these states is quantified in
terms of the negativity of the Wigner function and the entanglement potential.
Filtering of the vacuum from a coherent state is almost like the
photon-addition. However, filtering makes the state more resilient against
dissipation than photon-addition. Vacuum state filtered coherent states perform
better than the photon-added coherent states for a two-way quantum key
distribution protocol. A scheme to generate these states in multi-photon
atom-field interaction is presented.


  We show that the category of mixed Hodge complexes admits a Cartan-Eilenberg
structure, a notion introduced in [GNPR10] leading to a good calculation of the
homotopy category in terms of (co)fibrant objects. This result provides a
conceptual framework from which Beilinson's [Bei86] and Carlson's [Car80]
results on mixed Hodge complexes and extensions of mixed Hodge structures
follow easily.


  The use of accelerated sampling methods such as metadynamics has shown
significant advantage in calculations that involve infrequent events, which
would otherwise require sampling a prohibitive number of configurations to
determine, e.g., difference in free energies between two or more chemically
distinct states such as in the calculation of acid dissociation constants
$K_a$. In this case, the most common method is to bias the system via a single
collective variable (CV) representing the $coordination~number$ of the proton
donor group, which yields results in reasonable agreement with experiments.
Here we study the deprotonation of acetic acid using the reactive force field
ReaxFF and observe a significant dependence of $K_a$ on the simulation box size
when biasing only the coordination number CV, which is due to incomplete
sampling of the deprotonated state for small simulation systems, and
inefficient sampling for larger ones. Incorporating a second CV representing
the distance between the H$_3$O$^+$ cation and the acetate anion results in a
substantially more efficient sampling both accelerating the dynamics and
virtually eliminating the computational box size dependence.


  The diffusion of monovacancies in gold has been studied by computer
simulation. Multiple jumps have been found to play a central role in the atomic
dynamics at high temperature, and have been shown to be responsible for an
upward curvature in the Arrhenius plot of the diffusion coefficient.
Appropriate saddle points on the potential energy surface have been found,
supporting the interpretation of vacancy multiple jumps as distinct migration
mechanisms.


  The low frequency array (LOFAR), is the first radio telescope designed with
the capability to measure radio emission from cosmic-ray induced air showers in
parallel with interferometric observations. In the first $\sim
2\,\mathrm{years}$ of observing, 405 cosmic-ray events in the energy range of
$10^{16} - 10^{18}\,\mathrm{eV}$ have been detected in the band from $30 -
80\,\mathrm{MHz}$. Each of these air showers is registered with up to
$\sim1000$ independent antennas resulting in measurements of the radio emission
with unprecedented detail. This article describes the dataset, as well as the
analysis pipeline, and serves as a reference for future papers based on these
data. All steps necessary to achieve a full reconstruction of the electric
field at every antenna position are explained, including removal of radio
frequency interference, correcting for the antenna response and identification
of the pulsed signal.


  It has been showed by Byde that it is possible to attach a Delaunay-type end
to a compact nondegenerate manifold of positive constant scalar curvature,
provided it is locally conformally flat in a neighborhood of the attaching
point. The resulting manifold is noncompact with the same constant scalar
curvature. The main goal of this paper is to generalize this result. We will
construct a one-parameter family of solutions to the positive singular Yamabe
problem for any compact non-degenerate manifold with Weyl tensor vanishing to
sufficiently high order at the singular point. If the dimension is at most 5,
no condition on the Weyl tensor is needed. We will use perturbation techniques
and gluing methods.


  F. V. Gubarev et al. (``On the significance of the vector potential
squared'', Phys. Rev. Lett. 86, 2220) have argued that the vector potential
itself may have physical meaning, in defiance of the gauge equivalence
principle. Earlier R. I. Khrapko proposed a gauge noninvariant electrodynamics
spin tensor (``Spin density of electromagnetic waves''). The standard
electrodynamics spin tensor is zero.
  Here we point out that the Biot-Savarat formula uniquely results in a
preferred, "true" vector potential field which is generated from a given
magnetic field. A similar integral formula uniquely permits to find a "true"
scalar potential field generated from a given electric field even in the case
of a nonpotential electric field.
  A conception of differential forms is used. We say that an exterior
derivative of a form is the boundary of this form and the integration of a form
by the Biot-Savarat-type formula results in a new form named the generation.
Generating from a generation yields zero. The boundary of a boundary is zero. A
boundary is closed. A generation is sterile. A conjugation is considered. The
conjugation converts closed forms to sterile forms and back. It permits to
construct chains of forms. The conjunction differs from the Hodge star
operation: the conjugation does not imply the dualization. A circularly
polarized wave is considered in view of the electrodynamics spin tensor
problem.
  A new anthropic principle is presented.


  Optical amplification, crucial for modern communication, primarily relies on
erbium-doped fiber amplifiers (EDFAs) to enhance signals without distortion.
However, EDFAs only cover a portion of the low-loss spectrum of optical fibers.
Optical parametric amplification, utilizing material nonlinearities, offers
expanded capacity, but has faced limitations in gain and bandwidth. Addressing
this, we present a high-gain continuous-traveling-wave parametric amplifier,
surpassing the erbium gain window. Leveraging low-loss gallium
phosphide-on-insulator photonic integrated waveguides, we achieve up to 35 dB
of parametric gain, with a fiber-to-fiber net gain exceeding 10 dB across a
wide wavelength range of approximately 140 nm centered at 1550 nm. We
demonstrate the capability to amplify ultra-weak signals, extending over 6
orders of magnitude of input powers, optical frequency combs, and communication
signals, highlighting the practical potential of our photonic-chip-based
amplifier.


  In this paper we investigate the $L^p$ boundedness of the lacunary maximal
function $ M_{\Ha}^{lac} $ associated to the spherical means $ A_r f$ taken
over Koranyi spheres on the Heisenberg group. Closely following an approach
used by M. Lacey in the Euclidean case, we obtain sparse bounds for these
maximal functions leading to new unweighted and weighted estimates. The key
ingredients in the proof are the $L^p$ improving property of the operator
$A_rf$ and a continuity property of the difference $A_rf-\tau_y A_rf$, where
$\tau_yf(x)=f(xy^{-1})$ is the right translation operator.


  While it is generally believed that supermassive black holes (SMBH) lie in
most galaxies with bulges, few SMBHs have been confirmed in bulgeless galaxies.
Identifying such a population could provide important insights to the BH seed
population and secular BH growth. To this end, we obtained near-infrared
spectroscopic observations of a sample of low-redshift bulgeless galaxies with
mid-infrared colors suggestive of AGN. We find additional evidence of AGN
activity (such as coronal lines and broad permitted lines) in 69$\%$ (9/13) of
the sample, demonstrating that mid-infrared selection is a powerful tool to
detect AGN. More than half of the galaxies with confirmed AGN activity show
fast outflows in [O III] in the optical and/or [Si VI] in the NIR, with the
latter generally having much faster velocities that are also correlated to
their spatial extent. We are also able to obtain virial BH masses for some
targets and find they fall within the scatter of other late-type galaxies in
the $M_{\rm{BH}}$-$M_{\rm{stellar}}$ relation. The fact that they lack a
significant bulge component indicates that secular processes, likely
independent of major mergers, grew these BHs to supermassive sizes. Finally, we
analyze the rotational gas kinematics and find two notable exceptions: two AGN
hosts with outflows that appear to be rotating faster than expected. There is
an indication that these two galaxies have stellar masses significantly lower
than expected from their dark matter halo masses. This, combined with the
observed AGN activity and strong gas outflows may be evidence of the effects of
AGN feedback.


  As a consequence of the financial crises, risk management became more
important and real-world dynamics of interest-rate models moved into the focus
of interest. Since risk-neutral dynamics are classically important to compute
prices of financial derivatives, it is interesting when real-world dynamics can
be related to risk-neutral dynamics via an equivalent change of measures. In
this article we give deterministic conditions in a general Heath-Jarrow-Morton
framework driven by a Hilbert space valued Brownian motion and a Poisson random
measure. Our conditions are of Lipschitz type and therefore easy to verify.


  In this paper, we study the joint impact of three major RF im-pairments,
namely, oscillator phase noise, power amplifier non-linearity and I/Q imbalance
on the performance of a mm-wave communication link based on OFDM modulation.
General im-pairment models are first derived for describing the joint effects
in each TX, each RX as well as a mm-wave communication link. Based on the
obtained signal models and initial air interface de-sign from the mmMAGIC
project, we numerically evaluate the impact of RF impairments on channel
estimation in terms of channel-to-noise ratio (CNR) and also channel
fluctuation due to common phase error (CPE) caused by phase noise within the
channel coherence time. Then the impact on the link performance in terms of
maximum sum rate is evaluated using extensive com-puter simulations. The
simulation results show that the used air interface design is generally robust
to the presence of RF impair-ments. With regard to the use of high order
modulation alphabet and implementation of low-power and low-cost RF
transceivers in mm-wave communication, special attention needs to be paid on
phase noise where the inter-carrier-interference (ICI) can become a major
limiting factor.


  A new generation of sub-orbital platforms will be operational in the next few
years. These new telescopes will operate from airborne and balloon-borne
platforms where the atmosphere is transparent enough to allow sensitive
measurements to be made in the submillimeter bands. The telescopes will take
advantage of state-of-the-art instrumentation including large format bolometer
arrays and spectrometers. Other papers in this volume will deal specifically
with the potential of these bands. In this paper will review the capabilities
the BLAST balloon-borne telescope.


  This article presents hitherto unpublished correspondence of Struble in 1947
with Menger, Chandrasekhar, and eventually Einstein, about a possible
observational test supporting Einstein's special relativity against Ritz's
emission theory using binary stars. This `Struble effect,' an acceleration
Doppler effect in emission theory, appears to have been overlooked, and the
historical context, including de Sitter's binary star test of special
relativity, is also discussed.


  We prove "untyping" theorems: in some typed theories (semirings, Kleene
algebras, residuated lattices, involutive residuated lattices), typed equations
can be derived from the underlying untyped equations. As a consequence, the
corresponding untyped decision procedures can be extended for free to the typed
settings. Some of these theorems are obtained via a detour through fragments of
cyclic linear logic, and give rise to a substantial optimisation of standard
proof search algorithms.


  We present a simple algorithm to find the Moore machine with the minimum
number of states equivalent to a given one.


  This work focuses on a class of elliptic boundary value problems with
diffusive, advective and reactive terms, motivated by the study of
three-dimensional heterogeneous physical systems composed of two or more media
separated by a selective interface. We propose a novel approach for the
numerical approximation of such heterogeneous systems combining, for the first
time: (1) a dual mixed hybrid (DMH) finite element method (FEM) based on the
lowest order Raviart-Thomas space (RT0); (2) a Three-Field (3F) formulation;
and (3) a Streamline Upwind/Petrov-Galerkin (SUPG) stabilization method. Using
the abstract theory for generalized saddle-point problems and their
approximation, we show that the weak formulation of the proposed method and its
numerical counterpart are both uniquely solvable and that the resulting finite
element scheme enjoys optimal convergence properties with respect to the
discretization parameter. In addition, an efficient implementation of the
proposed formulation is presented. The implementation is based on a systematic
use of static condensation which reduces the method to a nonconforming finite
element approach on a grid made by three-dimensional simplices. Extensive
computational tests demonstrate the theoretical conclusions and indicate that
the proposed DMH-RT0 FEM scheme is accurate and stable even in the presence of
marked interface jump discontinuities in the solution and its associated normal
flux. Results also show that in the case of strongly dominating advective
terms, the proposed method with the SUPG stabilization is capable of resolving
accurately steep boundary and/or interior layers without introducing spurious
unphysical oscillations or excessive smearing of the solution front.


  Let $X, X_1, X_2,\ldots $ be a sequence of non-lattice i.i.d. random
variables with ${\bf E} X=0,$ ${\bf E} X=1,$ and let $S_n:= X_1+ \cdots+ X_n$,
$n\ge 1.$ We refine Stone's integro-local theorem by deriving the first term in
the asymptotic expansion for the probability ${\bf P} \bigl(S_n\in
[x,x+\Delta)\bigr)$ with $x\in\mathbb R,$ $\Delta >0,$ as $n\to\infty$ and
establishing uniform bounds for the remainder term, under the assumption that
the distribution of $X$ satisfies Cram\'er's strong non-lattice condition and
${\bf E} |X|^r<\infty$ for some $r\ge 3$.


  Black holes are the simplest objects in the universe. They correspond to
extreme deformations of spacetime geometry, and can exist even devoid of
matter. In general relativity, (electro)vacuum black holes are uniquely
determined by their mass, charge and angular momentum. This feature follows
from a uniqueness theorem, which can be evaded if one considers higher
dimensions or matter fields coupled to gravity. Here we find that Einsteinian
cubic gravity, a well-motivated modification of Einstein gravity that includes
third-order curvature corrections in accordance with low-energy effective
theory expectations, admits black hole solutions with charge greater than mass,
when minimally coupled to a Maxwell field. Moreover, we find that, in this
regime, there can be two asymptotically flat black holes with the same charge
and mass, posing the first example of vacuum black hole nonuniqueness in four
dimensions that is free from pathologies. Examination of these black hole's
thermodynamics reveals that when two branches coexist only the larger black
hole is thermodynamically stable, while the smaller branch has negative
specific heat. Einsteinian cubic gravity unveils two further surprising
features. The charged black holes do not possess an inner horizon, in contrast
with the usual Reissner-Nordstr\"om spacetime, thus avoiding the need to resort
to strong cosmic censorship to uphold determinism. In addition to black holes,
there exists a one-parameter family of naked singularity spacetimes sharing the
same mass and charge as the former, but not continuously connected with them.
These naked singularities exist in the under-extremal regime, being present
even in pure (uncharged) Einsteinian cubic gravity.


  A notion of biologic system or just a system implies a functional wholeness
of comprising system components. Positive and negative feedback are the
examples of how the idea to unite anatomical elements in the whole functional
structure was successfully used in practice to explain regulatory mechanisms in
biology and medicine. There are numerous examples of functional and metabolic
pathways which are not regulated by feedback loops and have a structure of
reciprocal relationships. Expressed in the matrix form positive feedback,
negative feedback, and reciprocal links represent three basis elements of a Lie
algebra sl(2,R)of a special linear group SL(2,R). It is proposed that the
mathematical group structure can be realized through the three regulatory
elements playing a role of a functional basis of biologic systems. The
structure of the basis elements endows the space of biological variables with
indefinite metric. Metric structure resembles Minkowski's space-time (+, -, -)
making the carrier spaces of biologic variables and the space of
transformations inhomogeneous. It endows biologic systems with a rich
functional structure, giving the regulatory elements special differentiating
features to form steady autonomous subsystems reducible to one-dimensional
components.


  This paper considers the impact of general hardware impairments in a
multiple-antenna base station and user equipments on the uplink performance.
First, the effective channels are analytically derived for distortion-aware
receivers when using finite-sized signal constellations. Next, a deep
feedforward neural network is designed and trained to estimate the effective
channels. Its performance is compared with state-of-the-art distortion-aware
and unaware Bayesian linear minimum mean-squared error (LMMSE) estimators. The
proposed deep learning approach improves the estimation quality by exploiting
impairment characteristics, while LMMSE methods treat distortion as noise.


  The inclusive and exclusive semileptonic decay distributions for b -> c decay
are computed in the Shifman-Voloshin limit. The inclusive decay distributions
(computed using an operator product expansion) depend on quark masses, and the
exclusive decay distributions depend on hadron masses. Nevertheless, we show
explicitly how the first two terms in the 1/m expansion match between the
inclusive and exclusive decays. Agreement between the inclusive and exclusive
decay rates requires a minimum smearing region of size Lambda_QCD before local
duality holds in QCD. The alpha_s corrections to the inclusive and exclusive
decay rates are also shown to agree to order (log m)/m^2. The alpha_s/m^2
corrections are used to obtain the alpha_s correction to Bjorken's inequality
on the slope of the Isgur-Wise function.


  Thanks to the Cassini Huygens mission, it is now established that the first
aerosols in Titan s upper atmosphere are found from an altitude of about 1200
km. Once they are formed and through their descent towards the surface, these
nanoparticles are submitted to persistent Far Ultra-Violet (FUV) radiation that
can reach lower atmospheric layers. Such an interaction has an impact,
especially on the chemistry and charge budget of the atmospheric compounds.
Models are useful to understand this photoprocessing, but they lack important
input data such as the photoemission threshold or the absolute
photoabsorption/emission cross sections of the aerosols. In order to quantify
the photoemission processes, analogs of Titan s aerosols have been studied with
the DESIRS FUV beamline at the synchrotron SOLEIL as isolated substrate-free
nanoparticles. We present here the corresponding ARPES (Angle-Resolved
PhotoElectron Spectroscopy) data recorded at different FUV photon energies. The
results show a very low photoionization threshold (6.0 +/- 0.1 eV~ 207 nm) and
very high absolute ionization cross sections (~106 Mb) indicating that FUV
photoemission from aerosols is an intense source of slow electrons which has to
be taken into account in photochemical models of Titan s atmosphere.


  Weak gravitational lensing provides a potentially powerful method for the
detection of clusters. In addition to cluster candidates, a large number of
objects with possibly no optical or X-ray component have been detected in
shear-selected samples. We develop an analytic model to investigate the claim
of Weinberg & Kamionkowski (2002) that unvirialised protoclusters account for a
significant number of these so-called "dark" lenses. In our model, a
protocluster consists of a small virialised region surrounded by in-falling
matter. We find that, in order for a protocluster to simultaneously escape
X-ray detection and create a detectable weak lensing signal, it must have a
small virial mass (~10^{13} \Msun) and large total mass (~ 10^{15} \Msun), with
a relatively flat density profile outside of the virial radius. Such objects
would be characterized by rising tangential shear profiles well beyond the
virial radius. We use a semi-analytic approach based on the excursion set
formalism to estimate the abundance of lensing protoclusters with a low
probability of X-ray detection. We find that they are extremely rare,
accounting for less than 0.4 per cent of the total lenses in a survey with
background galaxy density n = 30 arcmin^{-2} and an intrinsic ellipticity
dispersion of 0.3. We conclude that lensing protoclusters with undetectable
X-Ray luminosities are too rare to account for a significant number of dark
lenses.


  We consider a setting where an agent's uncertainty is represented by a set of
probability measures, rather than a single measure. Measure-by-measure updating
of such a set of measures upon acquiring new information is well-known to
suffer from problems; agents are not always able to learn appropriately. To
deal with these problems, we propose using weighted sets of probabilities: a
representation where each measure is associated with a weight, which denotes
its significance. We describe a natural approach to updating in such a
situation and a natural approach to determining the weights. We then show how
this representation can be used in decision-making, by modifying a standard
approach to decision making -- minimizing expected regret -- to obtain minimax
weighted expected regret (MWER). We provide an axiomatization that
characterizes preferences induced by MWER both in the static and dynamic case.


  Edit distance is a measure of similarity of two strings based on the minimum
number of character insertions, deletions, and substitutions required to
transform one string into the other. The edit distance can be computed exactly
using a dynamic programming algorithm that runs in quadratic time. Andoni,
Krauthgamer, and Onak (2010) gave a nearly linear time algorithm that
approximates edit distance within an approximation factor $\text{poly}(\log
n)$.
  In this paper, we provide an algorithm with running time
$\tilde{O}(n^{2-2/7})$ that approximates the edit distance within a constant
factor.


  We have observed again two stars inside the ZZ Ceti instability strip that
were previously classified as not-observed-to-vary (NOV) by Mukadam et al.
(2004) and found them to be low-amplitude variables. Some evidence points to a
pure ZZ Ceti instability strip; other evidence contests it. The two stars
previously classified as NOV have Sloan Digital Sky Survey (SDSS) spectroscopic
effective temperatures that place them inside the ZZ Ceti instability strip,
and they were "contaminating" the strip as constant stars, which could indicate
that the instability strip was no longer a simple evolutionary stage. A pure
instability strip indicates that pulsation is a normal phase which all DAs must
go through. We used effective temperatures derived from SDSS optical spectra by
comparing them with model atmospheres to look for pulsators through
time-resolved photometry and stars previously classified as NOV. Our new
results indicate, but do not prove, a pure instability strip, because there are
still other NOV stars that need to be observed again. Additionally, we have
discovered five other ZZ Ceti stars based on their effective temperatures.


  In: S.G. Barwick and W.A. Jackson. Sublines and subplanes of PG(2,q^3) in the
Bruck--Bose representation in PG(6,q). Finite Fields Th. App. 18 (2012)
93--107., the authors determine the representation of order-q-subplanes and
order-q-sublines of PG(2,q^3) in the Bruck-Bose representation in PG(6,q). In
particular, they showed that an order-q-subplane of PG(2,q^3) corresponds to a
certain ruled surface in PG(6,q). In this article we show that the converse
holds, namely that any ruled surface satisfying the required properties
corresponds to a tangent order-q-subplane of PG(2,q^3).


  In this work we aim to discover high quality speech features and linguistic
units directly from unlabeled speech data in a zero resource scenario. The
results are evaluated using the metrics and corpora proposed in the Zero
Resource Speech Challenge organized at Interspeech 2015. A Multi-layered
Acoustic Tokenizer (MAT) was proposed for automatic discovery of multiple sets
of acoustic tokens from the given corpus. Each acoustic token set is specified
by a set of hyperparameters that describe the model configuration. These sets
of acoustic tokens carry different characteristics fof the given corpus and the
language behind, thus can be mutually reinforced. The multiple sets of token
labels are then used as the targets of a Multi-target Deep Neural Network
(MDNN) trained on low-level acoustic features. Bottleneck features extracted
from the MDNN are then used as the feedback input to the MAT and the MDNN
itself in the next iteration. We call this iterative deep learning framework
the Multi-layered Acoustic Tokenizing Deep Neural Network (MAT-DNN), which
generates both high quality speech features for the Track 1 of the Challenge
and acoustic tokens for the Track 2 of the Challenge. In addition, we performed
extra experiments on the same corpora on the application of query-by-example
spoken term detection. The experimental results showed the iterative deep
learning framework of MAT-DNN improved the detection performance due to better
underlying speech features and acoustic tokens.


  Due to the finite bandwidth of practical wireless systems, one multipath
component can manifest itself as a discrete pulse consisting of multiple taps
in the digital delay domain. This effect is called channel leakage, which
complicates the multipath delay estimation problem. In this paper, we develop a
new algorithm to estimate multipath delays of leaked channels by leveraging the
knowledge of pulse-shaping functions, which can be used to support fine-grained
WiFi sensing applications. Specifically, we express the channel impulse
response (CIR) as a linear combination of overcomplete basis vectors
corresponding to different delays. Considering the limited number of paths in
physical environments, we formulate the multipath delay estimation as a sparse
recovery problem. We then propose a sparse Bayesian learning (SBL) method to
estimate the sparse vector and determine the number of physical paths and their
associated delay parameters from the positions of the nonzero entries in the
sparse vector. Simulation results show that our algorithm can accurately
determine the number of paths, and achieve superior accuracy in path delay
estimation and channel reconstruction compared to two benchmarking schemes.


  We consider the problem of maximizing a nonnegative submodular set function
$f:2^{\mathcal{N}} \rightarrow \mathbb{R}^+$ subject to a $p$-matchoid
constraint in the single-pass streaming setting. Previous work in this context
has considered streaming algorithms for modular functions and monotone
submodular functions. The main result is for submodular functions that are {\em
non-monotone}. We describe deterministic and randomized algorithms that obtain
a $\Omega(\frac{1}{p})$-approximation using $O(k \log k)$-space, where $k$ is
an upper bound on the cardinality of the desired set. The model assumes value
oracle access to $f$ and membership oracles for the matroids defining the
$p$-matchoid constraint.


  The chromatic number of the plane is the chromatic number of the uncountably
infinite graph that has as its vertices the points of the plane and has an edge
between two points if their distance is 1. This chromatic number is denoted
$\chi(\mathcal{R}^2)$. The problem was introduced in 1950, and shortly
thereafter it was proved that $4\le \chi(\mathcal{R}^2)\le 7$. These bounds are
both easy to prove, but after more than 60 years they are still the best known.
In this paper, we investigate $\chi_f(\mathcal{R}^2)$, the fractional chromatic
number of the plane. The previous best bounds (rounded to five decimal places)
were $3.5556 \le \chi_f(\mathcal{R}^2)\le 4.3599$. Here we improve the lower
bound to $76/21\approx3.6190$.


  In continuous-time system identification, the intersample behavior of the
input signal is known to play a crucial role in the performance of estimation
methods. One common input behavior assumption is that the spectrum of the input
is band-limited. The sinc interpolation property of these input signals yields
equivalent discrete-time representations that are non-causal. This observation,
often overlooked in the literature, is exploited in this work to study
non-parametric frequency response estimators of linear continuous-time systems.
We study the properties of non-causal least-square estimators for
continuous-time system identification, and propose a kernel-based non-causal
regularized least-squares approach for estimating the band-limited equivalent
impulse response. The proposed methods are tested via extensive numerical
simulations.


  As well known, Hebb's learning traces its origin in Pavlov's Classical
Conditioning, however, while the former has been extensively modelled in the
past decades (e.g., by Hopfield model and countless variations on theme), as
for the latter modelling has remained largely unaddressed so far; further, a
bridge between these two pillars is totally lacking. The main difficulty
towards this goal lays in the intrinsically different scales of the information
involved: Pavlov's theory is about correlations among \emph{concepts} that are
(dynamically) stored in the synaptic matrix as exemplified by the celebrated
experiment starring a dog and a ring bell; conversely, Hebb's theory is about
correlations among pairs of adjacent neurons as summarized by the famous
statement {\em neurons that fire together wire together}. In this paper we rely
on stochastic-process theory and model neural and synaptic dynamics via
Langevin equations, to prove that -- as long as we keep neurons' and synapses'
timescales largely split -- Pavlov mechanism spontaneously takes place and
ultimately gives rise to synaptic weights that recover the Hebbian kernel.


  The Ep,i - Eiso correlation is one of the most intriguing and debated
observational evidences in Gamma-Ray Bursts (GRB) astrophysics. Swift, with its
high sensitivity and fast pointing capabilities, is reducing a lot the impact
of selection effects in the sample of GRBs with known redshift (and thus Ep,i
and Eiso). Moreover, in several cases it allows the detection of the soft tail
of the prompt emission, and thus a more accurate estimate of Ep,i with respect
to previous satellites. I present and discuss the location in the Ep,i - Eiso
plane of Swift GRBs with known redshift and estimated Ep,i, showing that all
long events (including peculiar events like GRB060218 and GRB060614) are
consistent with the Ep,i - Eiso correlation. In contrast, short GRBs are not
consistent with it, an evidence further supporting the hypothesis of different
emission mechanisms at work in the two classes of GRBs. I also show, and
briefly discuss, the intriguing evidence that the soft tail of the short
GRB050724 is consistent with the correlation.


  A single fermion is bound by a softcore central Coulomb potential V(r) =
-v/(r^q + b^q)^(1/q), v>0, b>0, q \ge 1, in d>1 spatial dimensions. Envelope
theory is used to construct analytic lower bounds for the discrete Dirac energy
spectrum. The results are compared to accurate eigenvalues obtained
numerically.


  Discussion of "Calibrated Bayes, for Statistics in General, and Missing Data
in Particular" by R. Little [arXiv:1108.1917]


  Saliency map estimation in computer vision aims to estimate the locations
where people gaze in images. Since people tend to look at objects in images,
the parameters of the model pretrained on ImageNet for image classification are
useful for the saliency map estimation. However, there is no research on the
relationship between the image classification accuracy and the performance of
the saliency map estimation. In this paper, it is shown that there is a strong
correlation between image classification accuracy and saliency map estimation
accuracy. We also investigated the effective architecture based on multi scale
images and the upsampling layers to refine the saliency-map resolution. Our
model achieved the state-of-the-art accuracy on the PASCAL-S, OSIE, and MIT1003
datasets. In the MIT Saliency Benchmark, our model achieved the best
performance in some metrics and competitive results in the other metrics.


  The Hawkes process is a class of point processes whose future depends on
their own history. Previous theoretical work on the Hawkes process is limited
to a special case in which a past event can only increase the occurrence of
future events, and the link function is linear. However, in neuronal networks
and other real-world applications, inhibitory relationships may be present, and
the link function may be non-linear. In this paper, we develop a new approach
for investigating the properties of the Hawkes process without the restriction
to mutual excitation or linear link functions. To this end, we employ a
thinning process representation and a coupling construction to bound the
dependence coefficient of the Hawkes process. Using recent developments on
weakly dependent sequences, we establish a concentration inequality for
second-order statistics of the Hawkes process. We apply this concentration
inequality to cross-covariance analysis in the high-dimensional regime, and we
verify the theoretical claims with simulation studies.


  Building an accurate computer-aided diagnosis system based on data-driven
approaches requires a large amount of high-quality labeled data. In medical
imaging analysis, multiple expert annotators often produce subjective estimates
about "ground truth labels" during the annotation process, depending on their
expertise and experience. As a result, the labeled data may contain a variety
of human biases with a high rate of disagreement among annotators, which
significantly affect the performance of supervised machine learning algorithms.
To tackle this challenge, we propose a simple yet effective approach to combine
annotations from multiple radiology experts for training a deep learning-based
detector that aims to detect abnormalities on medical scans. The proposed
method first estimates the ground truth annotations and confidence scores of
training examples. The estimated annotations and their scores are then used to
train a deep learning detector with a re-weighted loss function to localize
abnormal findings. We conduct an extensive experimental evaluation of the
proposed approach on both simulated and real-world medical imaging datasets.
The experimental results show that our approach significantly outperforms
baseline approaches that do not consider the disagreements among annotators,
including methods in which all of the noisy annotations are treated equally as
ground truth and the ensemble of different models trained on different label
sets provided separately by annotators.


  The life-times due to Auger-electron emission for a hole on a deep electronic
shell of neutral and charged sodium clusters are studied for different sizes.
We consider spherical clusters and calculate the Auger-transition probabilities
using the energy levels and wave functions calculated in the
Local-Density-Approximation (LDA).
  We obtain that Auger emission processes are energetically not allowed for
neutral and positively charged sodium clusters. In general, the Auger
probabilities in small Na$_N^-$ clusters are remarkably different from the
atomic ones and exhibit a rich size dependence.
  The Auger decay times of most of the cluster sizes studied are orders of
magnitude larger than in atoms and might be comparable with typical
fragmentation times.


  Although the need for gender-inclusivity in software itself is gaining
attention among both SE researchers and SE practitioners, and methods have been
published to help, little has been reported on how to make such methods work in
real-world settings. For example, how do busy software practitioners use such
methods in low-cost ways? How do they endeavor to maximize benefits from using
them? How do they avoid the controversies that can arise in talking about
gender? To find out how teams were handling these and similar questions, we
turned to 10 real-world software teams. We present these teams experiences "in
the trenches," in the form of 12 practices and 3 potential pitfalls, so as to
provide their insights to other real-world software teams trying to engineer
gender-inclusivity into their software products.


  Sign languages are multi-channel visual languages, where signers use a
continuous 3D space to communicate.Sign Language Production (SLP), the
automatic translation from spoken to sign languages, must embody both the
continuous articulation and full morphology of sign to be truly understandable
by the Deaf community. Previous deep learning-based SLP works have produced
only a concatenation of isolated signs focusing primarily on the manual
features, leading to a robotic and non-expressive production.
  In this work, we propose a novel Progressive Transformer architecture, the
first SLP model to translate from spoken language sentences to continuous 3D
multi-channel sign pose sequences in an end-to-end manner. Our transformer
network architecture introduces a counter decoding that enables variable length
continuous sequence generation by tracking the production progress over time
and predicting the end of sequence. We present extensive data augmentation
techniques to reduce prediction drift, alongside an adversarial training regime
and a Mixture Density Network (MDN) formulation to produce realistic and
expressive sign pose sequences.
  We propose a back translation evaluation mechanism for SLP, presenting
benchmark quantitative results on the challenging PHOENIX14T dataset and
setting baselines for future research. We further provide a user evaluation of
our SLP model, to understand the Deaf reception of our sign pose productions.


  Modelling the scrape-off layer of a stellarator is challenging due to the
complex magnetic 3D geometry. The here presented study analyses simulations of
the scrape-off layer (SOL) of the stellarator Wendelstein 7-X (W7-X) using the
EMC3-EIRENE code for the magnetic standard configuration. Comparing with
experimental observations, the transport model is validated. Based on the
experimentally observed strike line width, the anomalous transport
coefficients, used as input to the code are determined to around
$0.2\,$m$^2/$s. This is however in disagreement with upstream measurements,
where such small cross-field transport leads to temperatures higher than
measured experimentally.


  The note presents a modified proof of a loss bound for the exponentially
weighted average forecaster with time-varying potential. The regret term of the
algorithm is upper-bounded by sqrt{n ln(N)} (uniformly in n), where N is the
number of experts and n is the number of steps.


  Based on two-sided heat kernel estimates for a class of symmetric jump
processes on metric measure spaces, the laws of the iterated logarithm (LILs)
for sample paths, local times and ranges are established. In particular, the
LILs are obtained for $\beta$-stable-like processes on $\alpha$-sets with
$\beta>0$.


  We investigate a slowly rotating black hole in four-dimensional extended
Chern-Simons modified gravity. We obtain an approximate solution that reduces
to the Kerr solution when a coupling constant vanishes. The Chern-Simons
correction effectively reduces the frame-dragging effect around a black hole in
comparison with that of the Kerr solution.


  In this paper we extend the color dipole formalism to the study of exclusive
processes associated with a leading neutron in $ep$ collisions at high
energies. The exclusive $\rho$, $\phi$ and $J/\Psi$ production, as well as the
Deeply Virtual Compton Scattering, are analysed assuming a diffractive
interaction between the color dipole and the pion emitted by the incident
proton. We compare our predictions with the HERA data on $\rho$ production and
estimate the magnitude of the absorption corrections. We show that the color
dipole formalism is able to describe the current data. Finally, we present our
estimate for the exclusive cross sections which can be studied at HERA and in
future electron-proton colliders.


  Cancer is a primary cause of human death, but discovering drugs and tailoring
cancer therapies are expensive and time-consuming. We seek to facilitate the
discovery of new drugs and treatment strategies for cancer using variational
autoencoders (VAEs) and multi-layer perceptrons (MLPs) to predict anti-cancer
drug responses. Our model takes as input gene expression data of cancer cell
lines and anti-cancer drug molecular data and encodes these data with our {\sc
{GeneVae}} model, which is an ordinary VAE model, and a rectified junction tree
variational autoencoder ({\sc JTVae}) model, respectively. A multi-layer
perceptron processes these encoded features to produce a final prediction. Our
tests show our system attains a high average coefficient of determination
($R^{2} = 0.83$) in predicting drug responses for breast cancer cell lines and
an average $R^{2} = 0.845$ for pan-cancer cell lines. Additionally, we show
that our model can generates effective drug compounds not previously used for
specific cancer cell lines.


  We present new concentration of measure inequalities for Markov chains,
generalising results for chains that are contracting in Wasserstein distance.
These are particularly suited to establishing the cut-off phenomenon for
suitable chains. We apply our discrete-time inequality to the well-studied
Bernoulli-Laplace model of diffusion, and give a probabilistic proof of
cut-off, recovering and improving the bounds of Diaconis and Shahshahani. We
also extend the notion of cut-off to chains with an infinite state space, and
illustrate this in a second example, of a two-host model of disease in
continuous time. We give a third example, giving concentration results for the
supermarket model, illustrating the full generality and power of our results.


  The energy spectra of ultra-high energy cosmic rays (CRs) measured with giant
extensive air shower (EAS) arrays exhibit discrepancies between the flux
intensities and/or estimated CR energies exceeding experimental errors. The
well-known intensity correction factor due to the dispersion of the measured
quantity in the presence of a rapidly falling energy spectrum is insufficient
to explain the divergence. Another source of systematic energy determination
error is proposed concerning the charged particle density measured with the
surface arrays, which arises due to simplifications (namely, the superposition
approximation) in nucleus-nucleus interaction description applied to the shower
modeling. Making use of the essential correction factors results in congruous
CR energy spectra within experimental errors. Residual differences in the
energy scales of giant arrays can be attributed to the actual overall accuracy
of the EAS detection technique used. CR acceleration and propagation model
simulations using the dip and ankle scenarios of the transition from galactic
to extragalactic CR components are in agreement with the combined energy
spectrum observed with EAS arrays.


  We report the detection of a transiting Earth-size planet around GJ 357, a
nearby M2.5V star, using data from the Transiting Exoplanet Survey Satellite
(TESS). GJ 357 b (TOI-562.01) is a transiting, hot, Earth-sized planet
(Teq=525+-11 K) with a radius of Rb=1.217+-0.084 Re and an orbital period of
Pb=3.93 d. Precise stellar radial velocities from CARMENES and PFS, as well as
archival data from HIRES, UVES, and HARPS also display a 3.93-day periodicity,
confirming the planetary nature and leading to a planetary mass of
Mb=1.84+-0.31 Me. In addition to the radial velocity signal for GJ 357 b, more
periodicities are present in the data indicating the presence of two further
planets in the system: GJ 357 c, with a minimum mass of Mc=3.40+-0.46 Me in a
9.12 d orbit, and GJ 357 d, with a minimum mass of Md=6.1+-1.0 Me in a 55.7 d
orbit inside the habitable zone. The host is relatively inactive and exhibits a
photometric rotation period of Prot=78+-2 d. GJ 357 b is to date the second
closest transiting planet to the Sun, making it a prime target for further
investigations such as transmission spectroscopy. Therefore, GJ 357 b
represents one of the best terrestrial planets suitable for atmospheric
characterization with the upcoming JWST and ground-based ELTs.


  A vertex partition $\pi = \{V_1, V_2, \ldots, V_k\}$ of $G$ is called a
\emph{transitive partition} of size $k$ if $V_i$ dominates $V_j$ for all $1\leq
i<j\leq k$. For two disjoint subsets $A$ and $B$ of $V$, we say $A$
\emph{strongly dominates} $B$ if for every vertex $y\in B$, there exists a
vertex $x\in A$, such that $xy\in E$ and $deg_G(x)\geq deg_G(y)$. A vertex
partition $\pi = \{V_1, V_2, \ldots, V_k\}$ of $G$ is called a \emph{strong
transitive partition} of size $k$ if $V_i$ strongly dominates $V_j$ for all
$1\leq i<j\leq k$. The \textsc{Maximum Strong Transitivity Problem} is to find
a strong transitive partition of a given graph with the maximum number of
parts. In this article, we initiate the study of this variation of transitive
partition from algorithmic point of view. We show that the decision version of
this problem is NP-complete for chordal graphs. On the positive side, we prove
that this problem can be solved in linear time for trees and split graphs.


  We describe how the accurate characterization of exoplanetary atmospheres in
the ELT and JWST era will inevitably require taking into consideration the
stellar inhomogeneities caused by convection and magnetic fields. The existing
evidence that demonstrates the mixture of stellar and planetary signatures in
observed transiting spectra is presented. Finally, we discuss how to
disentangle these two components through a multipronged approach that includes
new solar reference spectra, improved MHD modeling, and synergistic
collaborations between the communities involved, from solar to stellar and
exoplanet astronomers.


  We review recent rigorous mathematical results about the macroscopic
behaviour of harmonic chains with the dynamics perturbed by a random exchange
of velocities between nearest neighbor particles. The random exchange models
the effects of nonlinearities of anharmonic chains and the resulting dynamics
have similar macroscopic behaviour. In particular there is a superdiffusion of
energy for unpinned acoustic chains. The corresponding evolution of the
temperature profile is governed by a fractional heat equation. In non-acoustic
chains we have normal diffusivity, even if momentum is conserved.


  In order to understand both up-type and down-type Yukawa couplings, F-theory
is a better framework than the perturbative Type IIB string theory. The duality
between the Heterotic and F-theory is a powerful tool in gaining more insights
into F-theory description of low-energy chiral multiplets. Because chiral
multiplets from bundles /\^2 V and /\^2 V^x as well as those from a bundle V
are all involved in Yukawa couplings in Heterotic compactification, we need to
translate descriptions of all those kinds of matter multiplets into F-theory
language through the duality. We find that chiral matter multiplets in F-theory
are global holomorphic sections of line bundles on what we call covering matter
curves. The covering matter curves are formulated in Heterotic theory in
association with normalization of spectral surface, while they are where
M2-branes wrapped on a vanishing two-cycle propagate in F-theory. Chirality
formulae are given purely in terms of (possibly primitive) four-form flux. In
order to complete the translation, the dictionary of the Heterotic--F theory
duality has to be refined in some aspects. A precise map of spectral surface
and complex structure moduli is obtained, and with the map, we find that
divisors specifying the line bundles correspond precisely to codimension-3
singularities in F-theory.


  We study the existence of mixed-strategy equilibria in concurrent games
played on graphs. While existence is guaranteed with safety objectives for each
player, Nash equilibria need not exist when players are given arbitrary
terminal-reward objectives, and their existence is undecidable with qualitative
reachability objectives (and only three players). However, these results rely
on the fact that the players can enforce infinite plays while trying to improve
their payoffs. In this paper, we introduce a relaxed notion of equilibria,
where deviations are imprecise. We prove that contrary to Nash equilibria, such
(stationary) equilibria always exist, and we develop a PSPACE algorithm to
compute one.


  If we are ever to unravel the mysteries of brain function at its most
fundamental level, we will need a precise understanding of how its component
neurons connect to each other. Electron Microscopes (EM) can now provide the
nanometer resolution that is needed to image synapses, and therefore
connections, while Light Microscopes (LM) see at the micrometer resolution
required to model the 3D structure of the dendritic network. Since both the
topology and the connection strength are integral parts of the brain's wiring
diagram, being able to combine these two modalities is critically important.
  In fact, these microscopes now routinely produce high-resolution imagery in
such large quantities that the bottleneck becomes automated processing and
interpretation, which is needed for such data to be exploited to its full
potential. In this paper, we briefly review the Computer Vision techniques we
have developed at EPFL to address this need. They include delineating dendritic
arbors from LM imagery, segmenting organelles from EM, and combining the two
into a consistent representation.


  Gradient Boosting Machine (GBM) is an extremely powerful supervised learning
algorithm that is widely used in practice. GBM routinely features as a leading
algorithm in machine learning competitions such as Kaggle and the KDDCup. In
this work, we propose Accelerated Gradient Boosting Machine (AGBM) by
incorporating Nesterov's acceleration techniques into the design of GBM. The
difficulty in accelerating GBM lies in the fact that weak (inexact) learners
are commonly used, and therefore the errors can accumulate in the momentum
term. To overcome it, we design a "corrected pseudo residual" and fit best weak
learner to this corrected pseudo residual, in order to perform the z-update.
Thus, we are able to derive novel computational guarantees for AGBM. This is
the first GBM type of algorithm with theoretically-justified accelerated
convergence rate. Finally we demonstrate with a number of numerical experiments
the effectiveness of AGBM over conventional GBM in obtaining a model with good
training and/or testing data fidelity.


  It is conjectured that the anomalous spin dynamics observed in the normal
state of cuprate superconductors might find its origin in a nearly ordered spin
system which is kept in motion by thermally meandering charged domain walls.
`Temperature sets the scale' finds a natural explanation, while a crossover to
a low temperature quantum domain wall fluid is implied.


  We describe the conditional and unconditional dynamics of two coupled quantum
dots when one dot is subjected to a measurement of its occupation number using
a single electron transistor (SET). The measurement is made when the bare
tunneling rate though the SET is changed by the occupation number of one of the
dots. We show that there is a difference between the time scale for the
measurement-induced decoherence between the localized states of the dots and
the time scale on which the system becomes localized due to the measurement. A
comparison between theory and current experiments is made.


  I describe the projective resolution of a codimension 4 Gorenstein ideal,
aiming to extend Buchsbaum and Eisenbud's famous result in codimension 3. The
main result is a structure theorem stating that the ideal is determined by its
(k+1) x 2k matrix of first syzygies, viewed as a morphism from the ambient
regular space to the Spin-Hom variety SpH_k in Mat(k+1,2k). This is a general
result encapsulating some theoretical aspects of the problem, but, as it
stands, is still some way from tractable applications.


  Approximating complex curves with simple parametric curves is widely used in
CAGD, CG, and CNC. This paper presents an algorithm to compute a certified
approximation to a given parametric space curve with cubic B-spline curves. By
certified, we mean that the approximation can approximate the given curve to
any given precision and preserve the geometric features of the given curve such
as the topology, singular points, etc. The approximated curve is divided into
segments called quasi-cubic B\'{e}zier curve segments which have properties
similar to a cubic rational B\'{e}zier curve. And the approximate curve is
naturally constructed as the associated cubic rational B\'{e}zier curve of the
control tetrahedron of a quasi-cubic curve. A novel optimization method is
proposed to select proper weights in the cubic rational B\'{e}zier curve to
approximate the given curve. The error of the approximation is controlled by
the size of its tetrahedron, which converges to zero by subdividing the curve
segments. As an application, approximate implicit equations of the approximated
curves can be computed. Experiments show that the method can approximate space
curves of high degrees with high precision and very few cubic B\'{e}zier curve
segments.


  Critical transitions, ubiquitous in nature and technology, necessitate
anticipation to avert adverse outcomes. While many studies focus on
bifurcation-induced tipping, where a control parameter change leads to
destabilization, alternative scenarios are conceivable, e.g. noise-induced
tipping by an increasing noise level in a multi-stable system. Although the
generating mechanisms can be different, the observed time series can exhibit
similar characteristics. Therefore, we propose a Bayesian Langevin approach,
implemented in an open-source tool, which is capable of quantifying both
deterministic and intrinsic stochastic dynamics simultaneously. After a
detailed proof of concept, we analyse two bus voltage frequency time series of
the historic North America Western Interconnection blackout on 10th August
1996. Our results unveil the intricate interplay of changing resilience and
noise influence. A comparison with the blackout's timeline supports our
frequency dynamics' Langevin model, with the BL-estimation indicating a
permanent grid state change already two minutes before the officially defined
triggering event. A tree-related high impedance fault or sudden load increases
may serve as earlier triggers during this event, as suggested by our findings.
This study underscores the importance of distinguishing destabilizing factors
for a reliable anticipation of critical transitions, offering a tool for better
understanding such events across various disciplines.


  The aim of this paper is to understand whether Distributed Ledger
Technologies (DLTs) are ready to support complex services, such as those
related to Intelligent Transportation Systems (ITS). In smart transportation
services, a huge amount of sensed data is generated by a multitude of vehicles.
While DLTs provide very interesting features, such as immutability,
traceability and verifiability of data, some doubts on the scalability and
responsiveness of these technologies appear to be well-founded. We propose an
architecture for ITS that resorts to DLT features. Moreover, we provide
experimental results of a real test-bed over IOTA, a promising DLT for IoT.
Results clearly show that, while the viability of the proposal cannot be
rejected, further work is needed on the responsiveness of DLT infrastructures.


  By finding all integral points on certain elliptic and hyperelliptic curves
we completely solve the Diophantine equation $\binom{n}{k}=\binom{m}{l}+d$ for
$-3\leq d\leq 3$ and $(k,l)\in\{(2,3),\; (2,4),\;(2,5),\; (2,6),\; (2,8),\;
(3,4),\; (3,6),\; (4,6), \; (4,8)\}.$ Moreover, we present some other
observations of computational and theoretical nature concerning the title
equation.


  We develop a generalization to non-Witt spaces of the intersection homology
theory of Goresky-MacPherson. The second author has described the self-dual
sheaves compatible with intersection homology, and the other authors have
described a generalization of Cheeger's L2 de Rham cohomology. In this paper we
extend both of these cohomologies by describing all sheaf complexes in the
derived category of constructible sheaves that are compatible with middle
perversity intersection cohomology, though not necessarily self-dual. On
Thom-Mather stratified spaces this refined intersection cohomology theory
coincides with the analytic de Rham theory.