  Let S_n be the nth symmetric group. Given a set of permutations Pi we denote
by S_n(Pi) the set of permutations in S_n which avoid Pi in the sense of
pattern avoidance. Consider the generating function Q_n(Pi) = sum_pi F_{Des pi}
where the sum is over all pi in S_n(Pi) and F_{Des pi} is the fundamental
quasisymmetric function corresponding to the descent set of pi. Hamaker,
Pawlowski, and Sagan introduced Q_n(Pi) and studied its properties, in
particular, finding criteria for when this quasisymmetric function is symmetric
or even Schur nonnegative for all n >= 0. The purpose of this paper is to
continue their investigation answering some of their questions, proving one of
their conjectures, as well as considering other natural questions about
Q_n(Pi). In particular we look at Pi of small cardinality, superstandard hooks,
partial shuffles, Knuth classes, and a stability property.


  Torsional oscillator experiments show evidence of mass decoupling in solid
4He. This decoupling is amplitude dependent, suggesting a critical velocity for
supersolidity. We observe similar behavior in the elastic shear modulus. By
measuring the shear modulus over a wide frequency range, we can distinguish
between an amplitude dependence which depends on velocity and one which depends
on some other parameter like displacement. In contrast to the torsional
oscillator behavior, the modulus depends on the magnitude of stress, not
velocity. We interpret our results in terms of the motion of dislocations which
are weakly pinned by 3He impurities but which break away when large stresses
are applied.


  We note a parallel between some ideas of stable model theory and certain
topics in finite combinatorics related to the sum-product phenomenon. For a
simple linear group G, we show that a finite subset X with |X X \^{-1} X |/ |X|
bounded is close to a finite subgroup, or else to a subset of a proper
algebraic subgroup of G. We also find a connection with Lie groups, and use it
to obtain some consequences suggestive of topological nilpotence. Combining
these methods with Gromov's proof, we show that a finitely generated group with
an approximate subgroup containing any given finite set must be
nilpotent-by-finite. Model-theoretically we prove the independence theorem and
the stabilizer theorem in a general first-order setting.


  The nonlocal set has received wide attention over recent years. Shortly
before, Li and Wang arXiv:2202.09034 proposed the concept of a locally stable
set: the only possible orthogonality preserving measurement on each subsystem
is trivial. Locally stable sets present stronger nonlocality than those sets
that are just locally indistinguishable. In this work, we focus on the
constructions of locally stable sets in multipartite quantum systems. First,
two lemmas are put forward to prove that an orthogonality-preserving local
measurement must be trivial. Then we present the constructions of locally
stable sets with minimum cardinality in bipartite quantum systems
$\mathbb{C}^{d}\otimes \mathbb{C}^{d}$ $(d\geq 3)$ and
$\mathbb{C}^{d_{1}}\otimes \mathbb{C}^{d_{2}}$ $(3\leq d_{1}\leq d_{2})$.
Moreover, for the multipartite quantum systems $(\mathbb{C}^{d})^{\otimes n}$
$(d\geq 2)$ and $\otimes^{n}_{i=1}\mathbb{C}^{d_{i}}$ $(3\leq d_{1}\leq
d_{2}\leq\cdots\leq d_{n})$, we also obtain $d+1$ and $d_{n}+1$ locally stable
orthogonal states respectively. Fortunately, our constructions reach the lower
bound of the cardinality on the locally stable sets, which provides a positive
and complete answer to an open problem raised in arXiv:2202.09034 .


  When energy of colliding nuclei is between 100-600 MeV/nucleon then
multifragmentation take place. By studying the fragments (at final stage of
reaction) we can seize the idea about initial condition and various other
parameter which influence the reaction and vice-versa. The symmetry energy Esym
({\rho}) of nuclear matter characterizes how the energy rises as one move away
from equal numbers of neutrons and protons. Both the magnitude and density
dependence of Esym ({\rho}) are critical for understanding the structure of
rare isotopes and the reaction mechanism of heavy ion collisions but also many
interesting issues in astrophysics.


  Users are tapping into massive, heterogeneous entity graphs for many
applications. It is challenging to select entity graphs for a particular need,
given abundant datasets from many sources and the oftentimes scarce information
for them. We propose methods to produce preview tables for compact presentation
of important entity types and relationships in entity graphs. The preview
tables assist users in attaining a quick and rough preview of the data. They
can be shown in a limited display space for a user to browse and explore,
before she decides to spend time and resources to fetch and investigate the
complete dataset. We formulate several optimization problems that look for
previews with the highest scores according to intuitive goodness measures,
under various constraints on preview size and distance between preview tables.
The optimization problem under distance constraint is NP-hard. We design a
dynamic-programming algorithm and an Apriori-style algorithm for finding
optimal previews. Results from experiments, comparison with related work and
user studies demonstrated the scoring measures' accuracy and the discovery
algorithms' efficiency.


  We reprove twice, in a simpler but as elementary way, a result by Hor\'ak and
Skula (1985) who determined, among all sequences of integers defined by
$$u_1=1,\quad u_2=R,\quad u_{n+2}=Pu_{n+1}-Qu_n$$ for some integers $P,Q,R$,
those which satisfy the strong divisibility condition $$\forall i,j\in\mathbb
N^*\quad u_i\land u_j=\left|u_{i\land j}\right|,$$ where $\land$ denotes the
greatest common divisor.


  We apply the Basis Light-Front Quantization (BLFQ) approach to the
Hamiltonian field theory of Quantum Electrodynamics (QED) in free space. We
solve for the mass eigenstates corresponding to an electron interacting with a
single photon in light-front gauge. Based on the resulting non-perturbative
ground state light-front amplitude we evaluate the electron anomalous magnetic
moment. The numerical results from extrapolating to the infinite basis limit
reproduce the perturbative Schwinger result with relative deviation less than
0.6%. We report significant improvements over previous works including the
development of analytic methods for evaluating the vertex matrix elements of
QED.


  We report on the discovery of AT2018lqh (ZTF18abfzgpl) -- a rapidly-evolving
extra-galactic transient in a star-forming host at 242 Mpc. The transient
g-band light curve's duration above half-maximum light is about 2.1 days, where
0.4/1.7 days are spent on the rise/decay, respectively. The estimated
bolometric light curve of this object peaked at about 7x10^42 erg/s -- roughly
seven times brighter than AT2017gfo. We show that this event can be explained
by an explosion with a fast (v~0.08 c) low-mass (~0.07 Msun) ejecta, composed
mostly of radioactive elements. For example, ejecta dominated by Ni-56 with a
time scale of t_0=1.6 days for the ejecta to become optically thin for
gamma-rays fits the data well. Such a scenario requires burning at densities
that are typically found in the envelopes of neutron stars or the cores of
white dwarfs. A combination of circumstellar material (CSM) interaction power
at early times and shock cooling at late times is consistent with the
photometric observations, but the observed spectrum of the event may pose some
challenges for this scenario. The observations are not consistent with a shock
breakout from a stellar envelope, while a model involving a low-mass ejecta
ramming into low-mass CSM cannot explain both the early- and late-time
observations.


  We argue that large fluctuations in the saturation momentum are necessary to
explain the ATLAS and ALICE data on pA collisions measured at the LHC. Using a
form for the distribution of fluctuations motivated by theoretical studies of
the non-linear evolution equations for the Color Glass Condensate, we find a
remarkably good agreement between theory and the measured distributions. If the
saturation momentum fluctuates, we argue that the cross section for a proton
probe should also fluctuate, consistent with previous observations. Finally we
discuss these results and their possible consistency with what is known about
multiplicity fluctuations in such collisions, and attempts to describe the
ridge effect from properties of the initial state.


  We compute the class of arithmetic genus two Teichmueller curves in the
Picard group of pseudo-Hilbert modular surfaces, distinguished according to
their torsion order and spin invariant. As an application, we compute the
number of genus two square-tiled surfaces with these invariants. The main
technical tool is the computation of divisor classes of Hilbert Jacobi forms on
the universal abelian surface over the pseudo-Hilbert modular surface.


  Since its discovery as a pulsar in 2000, the central compact object (CCO) 1E
1207.4-5209 in the supernova remnant PKS 1209-51/52 had been a stable 0.424 s
rotator with an extremely small spin-down rate and weak (Bs ~ 9E10 G) surface
dipole magnetic field. In 2016 we observed a glitch from 1E 1207.4-5209 of at
least Delta f/f = (2.8+/-0.4)E-9, which is typical in size for the general
pulsar population. However, glitch activity is closely correlated with
spin-down rate fdot, and pulsars with fdot as small as that of 1E 1207.4-5209
are never seen to glitch. Unlike in glitches of ordinary pulsars, there may
have been a large increase in fdot as well. The thermal X-ray spectrum of 1E
1207.4-5209, with its unique cyclotron absorption lines that measure the
surface magnetic field strength, did not show any measurable change after the
glitch, which rules out a major disruption in the dipole field as a cause or
result of the glitch. A leading theory of the origin and evolution of CCOs,
involving prompt burial of the magnetic field by fall-back of supernova ejecta,
might hold the explanation for the glitch.


  In this study we focus on the prediction of basketball games in the
Euroleague competition using machine learning modelling. The prediction is a
binary classification problem, predicting whether a match finishes 1 (home win)
or 2 (away win). Data is collected from the Euroleague's official website for
the seasons 2016-2017, 2017-2018 and 2018-2019, i.e. in the new format era.
Features are extracted from matches' data and off-the-shelf supervised machine
learning techniques are applied. We calibrate and validate our models. We find
that simple machine learning models give accuracy not greater than 67% on the
test set, worse than some sophisticated benchmark models. Additionally, the
importance of this study lies in the "wisdom of the basketball crowd" and we
demonstrate how the predicting power of a collective group of basketball
enthusiasts can outperform machine learning models discussed in this study. We
argue why the accuracy level of this group of "experts" should be set as the
benchmark for future studies in the prediction of (European) basketball games
using machine learning.


  Blair, Campisi, Taylor, and Tomova defined the L-invariant L(F) of a knotted
surface F, using pants complexes of trisection surfaces of bridge trisections
of F. After that, Aranda, Pongtanapaisan, and Zhang introduced the L*-invariant
L*(F) using dual curve complexes instead of pants complexes. In this paper, we
determine both of L-invariant and L*-invariant of any finite distant sum of
standard surfaces, and this is the first example of knotted surfaces whose
bridge numbers and these invariants can be arbitrary large.


  How many strict local maxima can a real quadratic function on $\{0,1\}^n$
have? Holzman conjectured a maximum of $n \choose \lfloor n/2 \rfloor$. The aim
of this paper is to prove this conjecture. Our approach is via a generalization
of Sperner's theorem that may be of independent interest.


  Soft amorphous materials are viscoelastic solids ubiquitously found around
us, from clays and cementitious pastes to emulsions and physical gels
encountered in food or biomedical engineering. Under an external deformation,
these materials undergo a noteworthy transition from a solid to a liquid state
that reshapes the material microstructure. This yielding transition was the
main theme of a workshop held from January 9 to 13, 2023 at the Lorentz Center
in Leiden. The manuscript presented here offers a critical perspective on the
subject, synthesizing insights from the various brainstorming sessions and
informal discussions that unfolded during this week of vibrant exchange of
ideas. The result of these exchanges takes the form of a series of open
questions that represent outstanding experimental, numerical, and theoretical
challenges to be tackled in the near future.


  In this paper, we discuss the relationships between stability and almost
periodicity for solutions of stochastic differential equations. Our essential
idea is to get stability of solutions or systems by some inherited properties
of Lyapunov functions. Under suitable conditions besides Lyapunov functions, we
obtain the existence of almost periodic solutions in distribution.


  Stationary equilibria of point vortices with arbitrary choice of circulations
in a background flow are studied. Differential equations satisfied by
generating polynomials of vortex configurations are derived. It is shown that
these equations can be reduced to a single one. It is found that polynomials
that are Wronskians of classical orthogonal polynomials solve the latter
equation. As a consequence vortex equilibria at a certain choice of background
flows can be described with the help of Wronskians of classical orthogonal
polynomials.


  Can vectors with low Schmidt rank form mutually unbiased bases? Can vectors
with high Schmidt rank form positive under partial transpose states? In this
work, we address these questions by presenting several new results related to
Schmidt rank constraints and their compatibility with other properties. We
provide an upper bound on the number of mutually unbiased bases of
$\mathbb{C}^m\otimes\mathbb{C}^n$ $(m\leq n)$ formed by vectors with low
Schmidt rank. In particular, the number of mutually unbiased product bases of
$\mathbb{C}^m\otimes\mathbb{C}^n$ cannot exceed $m+1$, which solves a
conjecture proposed by McNulty et al. Then we show how to create a positive
under partial transpose entangled state from any state supported on the
antisymmetric space and how their Schmidt numbers are exactly related. Finally,
we show that the Schmidt number of operator Schmidt rank 3 states of
$\mathcal{M}_m\otimes \mathcal{M}_n\ (m\leq n)$ that are invariant under left
partial transpose cannot exceed $m-2$.


  Traffic signs are essential map features globally in the era of autonomous
driving and smart cities. To develop accurate and robust algorithms for traffic
sign detection and classification, a large-scale and diverse benchmark dataset
is required. In this paper, we introduce a traffic sign benchmark dataset of
100K street-level images around the world that encapsulates diverse scenes,
wide coverage of geographical locations, and varying weather and lighting
conditions and covers more than 300 manually annotated traffic sign classes.
The dataset includes 52K images that are fully annotated and 48K images that
are partially annotated. This is the largest and the most diverse traffic sign
dataset consisting of images from all over world with fine-grained annotations
of traffic sign classes. We have run extensive experiments to establish strong
baselines for both the detection and the classification tasks. In addition, we
have verified that the diversity of this dataset enables effective transfer
learning for existing large-scale benchmark datasets on traffic sign detection
and classification. The dataset is freely available for academic research:
https://www.mapillary.com/dataset/trafficsign.


  We present a large set of theoretical isochrones, whose distinctive features
mostly reside on the greatly improved treatment of the thermally pulsing
asymptotic giant branch (TP-AGB) phase. Essentially, we have coupled the TP-AGB
tracks described in Paper I, at their stages of pre-flash quiescent H-shell
burning, with the evolutionary tracks for the previous evolutionary phases from
Girardi et al. (2000). Theoretical isochrones for any intermediate value of age
and metallicity are then derived by interpolation in the grids. We take care
that the isochrones keep, to a good level of detail, the several peculiarities
present in these TP-AGB tracks. Theoretical isochrones are then converted to
about 20 different photometric systems -- including traditional ground-based
systems, and those of recent major wide-field surveys such as SDSS, OGLE,
DENIS, 2MASS, UKIDSS, etc., -- by means of synthetic photometry applied to an
updated library of stellar spectra, suitably extended to include C-type stars.
Finally, we correct the predicted photometry by the effect of circumstellar
dust during the mass-losing stages of the AGB evolution, which allows us to
improve the results for the optical-to-infrared systems, and to simulate mid-
and far-IR systems such as those of Spitzer and AKARI. Access to the data is
provided both via a web repository of static tables
(http://stev.oapd.inaf.it/dustyAGB07 and CDS), and via an interactive web
interface (http://stev.oapd.inaf.it/cmd) that provides tables for any
intermediate value of age and metallicity, for several photometric systems, and
for different choices of dust properties.


  For a sound field observed on a sensor array, compressive sensing (CS)
reconstructs the direction-of-arrival (DOA) of multiple sources using a
sparsity constraint. The DOA estimation is posed as an underdetermined problem
by expressing the acoustic pressure at each sensor as a phase-lagged
superposition of source amplitudes at all hypothetical DOAs. Regularizing with
an $\ell_1$-norm constraint renders the problem solvable with convex
optimization, and promoting sparsity gives high-resolution DOA maps. Here, the
sparse source distribution is derived using maximum a posteriori (MAP)
estimates for both single and multiple snapshots. CS does not require inversion
of the data covariance matrix and thus works well even for a single snapshot
where it gives higher resolution than conventional beamforming. For multiple
snapshots, CS outperforms conventional high-resolution methods, even with
coherent arrivals and at low signal-to-noise ratio. The superior resolution of
CS is demonstrated with vertical array data from the SWellEx96 experiment for
coherent multi-paths.


  In this paper we derive from simple and reasonable assumptions a Gaussian
noise model for quantum amplitude estimation. We provide results from quantum
amplitude estimation run on various IBM superconducting quantum computers and
Quantinuum's H1 trapped-ion quantum computer to show that the proposed model is
a good fit for real-world experimental data. We also show that the proposed
Gaussian noise model can be easily composed with other noise models in order to
capture effects that are not well described by Gaussian noise. We then give a
generalised procedure for how to embed this noise model into any
quantum-phase-estimation-free QAE algorithm, such that the amplitude estimation
is ``noise aware''.


  Back in 1964, the theoretical physicists Francois Englert and Robert Brout,
as well as Peter Higgs, suggested an explanation for the fact that most
elementary particles - such as the electron - have a mass. This scenario
predicted a new particle, which has been observed experimentally only just now
at CERN (the European Organization for Nuclear Research). This discovery led to
the Physics Nobel Prize 2013. Here we sketch in simple terms the concept of the
Higgs mechanism, and its importance in particle physics.


  This article provides a self-contained pedagogical introduction to the
relativistic kinetic theory of a dilute gas propagating on a curved spacetime
manifold (M,g) of arbitrary dimension. Special emphasis is made on geometric
aspects of the theory in order to achieve a formulation which is manifestly
covariant on the relativistic phase space. Whereas most previous work has
focussed on the tangent bundle formulation, here we work on the cotangent
bundle associated with (M,g) which is more naturally adapted to the Hamiltonian
framework of the theory. In the first part of this work we discuss the relevant
geometric structures of the cotangent bundle T*M, starting with the natural
symplectic form on T*M, the one-particle Hamiltonian and the Liouville vector
field, defined as the corresponding Hamiltonian vector field. Next, we discuss
the Sasaki metric on T*M and its most important properties, including the role
it plays for the physical interpretation of the one-particle distribution
function. In the second part of this work we describe the general relativistic
theory of a collisionless gas, starting with the derivation of the
collisionless Boltzmann equation for a neutral simple gas. Subsequently, the
description is generalized to a charged gas consisting of several species of
particles and the general relativistic Vlasov-Maxwell equations are derived for
this system. The last part of this work is devoted to a transparent derivation
of the collision term, leading to the general relativistic Boltzmann equation
on (M,g). The meaning of global and local equilibrium and the stringent
restrictions for the existence of the former on a curved spacetime are
discussed. We close this article with an application of our formalism to the
expansion of a homogeneous and isotropic universe filled with a collisional
simple gas and its behavior in the early and late epochs. [abbreviated version]


  We analyze the ionization state of the magnetohydrodynamically turbulent
protoplanetary disks and propose a new mechanism of sustaining ionization.
First, we show that in the quasi-steady state of turbulence driven by
magnetorotational instability in a typical protoplanetary disk with dust
grains, the amount of energy dissipation should be sufficient for providing the
ionization energy that is required for activating magnetorotational
instability. Second, we show that in the disk with dust grains the energetic
electrons that compose electric currents in weakly ionized gas can provide
collisional ionization, depending on the actual saturation state of
magnetorotational turbulence. On the other hand, we show that in the
protoplanetary disks with the reduced effect of dust grains, the turbulent
motion can homogenize the ionization degree, leading to the activation of
magnetorotational instability even in the absence of other ionization
processes. The results in this Letter indicate that most of the regions in
protoplanetary disks remain magnetically active, and we thus require a change
in the theoretical modeling of planet formation.


  Dissipation is generally thought to affect the quantum nature of the system
in an adverse manner, however we show that dissipatively coupled nano systems
can be prepared in states which beat the standard quantum limit of the
mechanical motion. We show that the reactive coupling between the waveguide and
the microdisk resonator can generate the squeezing of the waveguide by
injecting a quantum field and laser into the resonator through the waveguide.
The waveguide can show about 70--75% of maximal squeezing for temperature about
1--10 mK. The maximum squeezing can be achieved with incident pump power of
only 12 $\mu$W for a temperature of about 1 mK. Even for temperatures of 20 mK,
achievable by dilution refrigerators, the maximum squeezing is about 60%.


  With the rise of cameras and smart sensors, humanity generates an exponential
amount of data. This valuable information, including underrepresented cases
like AI in medical settings, can fuel new deep-learning tools. However, data
scientists must prioritize ensuring privacy for individuals in these untapped
datasets, especially for images or videos with faces, which are prime targets
for identification methods. Proposed solutions to de-identify such images often
compromise non-identifying facial attributes relevant to downstream tasks. In
this paper, we introduce Disguise, a novel algorithm that seamlessly
de-identifies facial images while ensuring the usability of the modified data.
Unlike previous approaches, our solution is firmly grounded in the domains of
differential privacy and ensemble-learning research. Our method involves
extracting and substituting depicted identities with synthetic ones, generated
using variational mechanisms to maximize obfuscation and non-invertibility.
Additionally, we leverage supervision from a mixture-of-experts to disentangle
and preserve other utility attributes. We extensively evaluate our method using
multiple datasets, demonstrating a higher de-identification rate and superior
consistency compared to prior approaches in various downstream tasks.


  We introduce a method for constructing reduced-order models directly from
videos of dynamical systems. The method uses a non-intrusive tracking to
isolate the motion of a user-selected part in the video of an autonomous
dynamical system. In the space of delayed observations of this motion, we
reconstruct a low-dimensional attracting spectral submanifold (SSM) whose
internal dynamics serves as a mathematically justified reduced-order model for
nearby motions of the full system. We obtain this model in a simple polynomial
form that allows explicit identification of important physical system
parameters, such as natural frequencies, linear and nonlinear damping and
nonlinear stiffness. Beyond faithfully reproducing attracting steady states and
limit cycles, our SSM-reduced models can also uncover hidden motion not seen in
the video, such as unstable fixed points and unstable limit cycles forming
basin boundaries. We demonstrate all these features on experimental videos of
five physical systems: a double pendulum, an inverted flag in counter-flow,
water sloshing in tank, a wing exhibiting aeroelastic flutter and a shimmying
wheel.


  The spatial distribution of persistent (unvisited) sites in one dimensional
$A+A\to\emptyset$ model is studied. The `empty interval distribution' $n(k,t)$,
which is the probability that two consecutive persistent sites are separated by
distance $k$ at time $t$ is investigated in detail. It is found that at late
times this distribution has the dynamical scaling form $n(k,t)\sim
t^{-\theta}k^{-\tau}f(k/t^{z})$. The new exponents $\tau$ and $z$ change with
the initial particle density $n_{0}$, and are related to the persistence
exponent $\theta$ through the scaling relation $z(2-\tau)=\theta$. We show by
rigorous analytic arguments that for all $n_{0}$, $1< \tau< 2$, which is
confirmed by numerical results.


  Tensor triangular geometry as introduced by Balmer is a powerful idea which
can be used to extract the ambient geometry from a given tensor triangulated
category. In this paper we provide a general setting for a compactly generated
tensor triangulated category which enables one to classify thick tensor ideals
and the Balmer spectrum. For a classical Lie superalgebra ${\mathfrak
g}={\mathfrak g}_{\bar{0}}\oplus {\mathfrak g}_{\bar{1}}$, we construct a
Zariski space from a detecting subalgebra of ${\mathfrak g}$ and demonstrate
that this topological space governs the tensor triangular geometry for the
category of finite dimensional ${\mathfrak g}$-modules which are semisimple
over ${\mathfrak g}_{\bar{0}}$.


  Scientific documents contain tables that list important information in a
concise fashion. Structure and content extraction from tables embedded within
PDF research documents is a very challenging task due to the existence of
visual features like spanning cells and content features like mathematical
symbols and equations. Most existing table structure identification methods
tend to ignore these academic writing features. In this paper, we adapt the
transformer-based language modeling paradigm for scientific table structure and
content extraction. Specifically, the proposed model converts a tabular image
to its corresponding LaTeX source code. Overall, we outperform the current
state-of-the-art baselines and achieve an exact match accuracy of 70.35 and
49.69% on table structure and content extraction, respectively. Further
analysis demonstrates that the proposed models efficiently identify the number
of rows and columns, the alphanumeric characters, the LaTeX tokens, and
symbols.


  In this work, we develop first near-complete 3D models for NTD-hXPB - the
N-terminal protein domain of the human transcription factor XPB. The results
are very significant as NTD-hXPB plays a critical role in the synthesis of
proteins (specifically transcription) and DNA damage repair (specifically
nucleotide excision repair). NTD-hXPB is directly implicated in rare diseases
XP-B, XP-CS, and TTD2, whose symptoms include neurodegenerative disorders,
premature aging, and decreased fertility. NTDhXPB is also linked to anti-cancer
therapies. As a bi-product we derived 3D models of NTD-mXPB - homologue of
NTD-hXPB in mycobacterium tuberculosis aka MTB (causative agent of most cases
of tuberculosis, which surpassed HIV as #1 infectious disease killer in 2014).
These could be potential target for TB therapeutics. Our ab-initio modelling
protocol takes advantage of recent powerful advances (prediction of contact
residues) in protein structure modeling. Our protocol also includes human in
the loop, inspired by the prevailing theory that computational abilities of
human minds can be powerfully harnessed in engineering/problem-solving. Using
the developed models in this paper, we are able to propose significant insights
into (a) the role of NTD-hXPB in the process of transcription and DNA damage
repair (specifically NER), (b) the critical interactions of NTD-hXPB with
another co-labourer protein p52, (c) diseases associated with NTD-hXPB, and (d)
alterations in functionalities between NTD-hXPB (in human) and NTD-mXPB (in TB
pathogen).


  We provide a characterisation of strongly normalising terms of the
lambda-mu-calculus by means of a type system that uses intersection and product
types. The presence of the latter and a restricted use of the type omega enable
us to represent the particular notion of continuation used in the literature
for the definition of semantics for the lambda-mu-calculus. This makes it
possible to lift the well-known characterisation property for
strongly-normalising lambda-terms - that uses intersection types - to the
lambda-mu-calculus. From this result an alternative proof of strong
normalisation for terms typeable in Parigot's propositional logical system
follows, by means of an interpretation of that system into ours.


  In this paper we study the spherically symmetric characteristic initial data
problem for the Einstein-Maxwell-scalar field system with a positive
cosmological constant in the interior of a black hole, assuming an exponential
Price law along the event horizon. More precisely, we construct open sets of
characteristic data which, on the outgoing initial null hypersurface (taken to
be the event horizon), converges exponentially to a reference
Reissner-N\"{o}rdstrom black hole at infinity.
  We prove the stability of the radius function at the Cauchy horizon, and show
that, depending on the decay rate of the initial data, mass inflation may or
may not occur. In the latter case, we find that the solution can be extended
across the Cauchy horizon with continuous metric and Christoffel symbols in
$L^2_{{\rm loc}}$, thus violating the Christodoulou-Chru\'sciel version of
strong cosmic censorship.


  In this talk I review the status of B mixing in the Standard Model and the
room for new physics in B_s and B_d mixing in the light of recent LHCb data.


  This paper reviews the most important information fusion data-driven
algorithms based on Machine Learning (ML) techniques for problems in Earth
observation. Nowadays we observe and model the Earth with a wealth of
observations, from a plethora of different sensors, measuring states, fluxes,
processes and variables, at unprecedented spatial and temporal resolutions.
Earth observation is well equipped with remote sensing systems, mounted on
satellites and airborne platforms, but it also involves in-situ observations,
numerical models and social media data streams, among other data sources.
Data-driven approaches, and ML techniques in particular, are the natural choice
to extract significant information from this data deluge. This paper produces a
thorough review of the latest work on information fusion for Earth observation,
with a practical intention, not only focusing on describing the most relevant
previous works in the field, but also the most important Earth observation
applications where ML information fusion has obtained significant results. We
also review some of the most currently used data sets, models and sources for
Earth observation problems, describing their importance and how to obtain the
data when needed. Finally, we illustrate the application of ML data fusion with
a representative set of case studies, as well as we discuss and outlook the
near future of the field.


  In this paper, we study the inverse problems of determining the unknown
transverse shear force $g(t)$ in a system governed by the damped
Euler-Bernoulli equation $\rho(x)u_{tt}+\mu(x)u_t+ (r(x)u_{xx})_{xx}+
(\kappa(x)u_{xxt})_{xx}=0, ~(x,t)\in (0,\ell)\times(0,T],$ subject to the
boundary conditions $u(0,t) =0$, $u_{x}(0,t)=0$,
$\left[r(x)u_{xx}+\kappa(x)u_{xxt}\right]_{x=\ell} =0$,
$-\left[\big(r(x)u_{xx}+\kappa(x)u_{xxt}\big)_{x}\right]_{x=\ell}=g(t)$, $t\in
[0,T]$, from the measured deflection $\nu(t):=u(\ell,t)$, $t \in [0,T]$, and
from the bending moment $\omega(t):=-\left(
r(0)u_{xx}(0,t)+\kappa(0)u_{xxt}(0,t) \right)$, $t \in [0,T]$, where the terms
$(\kappa(x)u_{xxt})_{xx}$ and $\mu(x)u_t$ account for the Kelvin-Voigt damping
and external damping, respectively.
  The main purpose of this study is to analyze the Kelvin-Voigt damping effect
on determining the unknown transverse shear force (boundary input) through the
given boundary measurements. The inverse problems are transformed into
minimization problems for Tikhonov functionals, and it is shown that the
regularized functionals admit unique solutions for the inverse problems. By
suitable regularity on the admissible class of shear force $g(t),$ we prove
that these functionals are Fr\'echet differentiable, and the derivatives are
expressed through the solutions of corresponding adjoint problems posed with
measured data as boundary data associated with the direct problem. The
solvability of these adjoint problems is obtained under the minimal regularity
of the boundary data $g(t)$, which turns out to be the regularizing effect of
the Kelvin-Voigt damping in the direct problem.


  A comparison of two thermodynamic models is presented using the water-cesium
nitrate system as case study. Both models were able to model the thermodynamic
properties such as the osmotic coefficient, vapor pressure, mean activity
coefficient and solubility with good accuracy. We show that it is possible to
reproduce the temperature dependency of the properties using a simple set of
parameters in the case of Extended UNIQUAC. Furthermore, COSMO-RS-ES is a
completely predictive model adjusted to data at 298.15 K, which is applied for
the first time to other temperatures.


  We report on the discovery of a variable radio source, VLA J070238.0+385044,
associated with the proposed x-ray counterpart, 1SAX J0702.6+3850 of GRB
980329. The source was monitored from one day after the burst to one month
later at centimeter wavelengths (1.4, 4.9, 8.3 and 15 GHz; Very Large Array --
VLA), and in the 3-mm band (90 GHz; Owen Valley Radio Observatory -- OVRO).
Based on its variability, compactness and spectrum, we identify VLA
J070238.0+385044 as the afterglow from GRB 980329. We interpret the rapid flux
density variations as interstellar scintillation and the sharp turnover in the
radio spectrum below 13 GHz as arising from synchrotron self-absorption. This
suggests that the angular diameter of the fireball from GRB 980329 was of order
a few microarcseconds in the first two weeks. The absence of a readily
detectable afterglow in the optical, but clear detections in both the radio and
infrared, can be understood as the result of extinction by dust. In this
context it is interesting to note that half of all well-localized gamma-ray
bursts have no optical counterpart. Based on our study of GRB 980329 we suggest
that the progenitors of a sizable fraction of gamma-ray bursts are associated
with regions of moderate to high gas density.


  Deep-learning metrics have recently demonstrated extremely good performance
to match image patches for stereo reconstruction. However, training such
metrics requires large amount of labeled stereo images, which can be difficult
or costly to collect for certain applications. The main contribution of our
work is a new semi-supervised method for learning deep metrics from unlabeled
stereo images, given coarse information about the scenes and the optical
system. Our method alternatively optimizes the metric with a standard
stochastic gradient descent, and applies stereo constraints to regularize its
prediction. Experiments on reference data-sets show that, for a given network
architecture, training with this new method without ground-truth produces a
metric with performance as good as state-of-the-art baselines trained with the
said ground-truth. This work has three practical implications. Firstly, it
helps to overcome limitations of training sets, in particular noisy ground
truth. Secondly it allows to use much more training data during learning.
Thirdly, it allows to tune deep metric for a particular stereo system, even if
ground truth is not available.


  Extracting reliable information on certain physical properties of materials,
like thermal behavior, such as thermal transport, which can be very
computationally demanding. Aiming to overcome such difficulties in the
particular case of lattice thermal conductivity (LTC) of 2D nanomaterials, we
propose a simple, fast, and accurate semi-empirical approach for its
calculation.The approach is based on parameterized thermochemical equations and
Arrhenius-like fitting procedures, thus avoiding molecular dynamics or
\textit{ab initio} protocols, which frequently demand computationally expensive
simulations. As proof of concept, we obtain the LTC of some prototypical
physical systems, such as graphene (and other 2D carbon allotropes), hexagonal
boron nitride (hBN), silicene, germanene, binary, and ternary BNC latices and
two examples of the fullerene network family. Our values are in good agreement
with other theoretical and experimental estimations, nonetheless being derived
in a rather straightforward way, at a fraction of the computational cost.


  We study the topological configurations of the two-component condensates of
bosons with the $3$D $\vec{\sigma}\cdot \vec{p}$ Weyl-type spin-orbit coupling
subject to a harmonic trapping potential. The topology of the condensate
wavefunctions manifests in the quaternionic representation. In comparison to
the $U(1)$ complex phase, the quaternionic phase manifold is $S^3$ and the spin
orientations form the $S^2$ Bloch sphere through the 1st Hopf mapping. The
spatial distributions of the quaternionic phases exhibit the 3D skyrmion
configurations, and the spin distributions possess non-trivial Hopf invariants.
Spin textures evolve from the concentric distributions at the weak spin-orbit
coupling regime to the rotation symmetry breaking patterns at the intermediate
spin-orbit coupling regime. In the strong spin-orbit coupling regime, the
single-particle spectra exhibit the Landau-level type quantization. In this
regime, the three-dimensional skyrmion lattice structures are formed when
interactions are below the energy scale of Landau level mixings. Sufficiently
strong interactions can change condensates into spin-polarized plane-wave
states, or, superpositions of two plane-waves exhibiting helical spin spirals.


  Phonons, the fundamental vibrational modes of a crystal lattice, play a
crucial role in determining electronic properties of materials through
electron-phonon interaction. However, it has proved difficult to directly probe
the phonon modes of materials in electrical measurements. Here, we report the
observation of giant quantized phonon peaks of the K and K out-of-plane phonon
in graphene monolayer in magnetic fields via tunneling spectra, which are
usually used to measure local electronic properties of materials. A
perpendicular magnetic field quantizes massless Dirac fermions in graphene into
discrete Landau levels (LLs). We demonstrate that emission or absorption of
phonons of quasiparticles in the LLs of graphene generates a new sequence of
discrete states: the quantized phonon modes. In our tunneling spectra, the
intensity of the observed phonon peaks is about 50 times larger than that of
the LLs because that the K and K out-of-plane phonon opens an inelastic
tunneling channel. We also show that it is possible to switch on off the
quantized phonon modes at nanoscale by controlling interactions between
graphene and the supporting substrate.


  Pre-trained language models, such as BERT, have achieved significant accuracy
gain in many natural language processing tasks. Despite its effectiveness, the
huge number of parameters makes training a BERT model computationally very
challenging. In this paper, we propose an efficient multi-stage layerwise
training (MSLT) approach to reduce the training time of BERT. We decompose the
whole training process into several stages. The training is started from a
small model with only a few encoder layers and we gradually increase the depth
of the model by adding new encoder layers. At each stage, we only train the top
(near the output layer) few encoder layers which are newly added. The
parameters of the other layers which have been trained in the previous stages
will not be updated in the current stage. In BERT training, the backward
computation is much more time-consuming than the forward computation,
especially in the distributed training setting in which the backward
computation time further includes the communication time for gradient
synchronization. In the proposed training strategy, only top few layers
participate in backward computation, while most layers only participate in
forward computation. Hence both the computation and communication efficiencies
are greatly improved. Experimental results show that the proposed method can
achieve more than 110% training speedup without significant performance
degradation.


  We study the intraday behaviour of the statistical moments of the trading
volume of the blue chip equities that composed the Dow Jones Industrial Average
index between 2003 and 2014. By splitting that time interval into semesters, we
provide a quantitative account of the non-stationary nature of the intraday
statistical properties as well. Explicitly, we prove the well-known U-shape
exhibited by the average trading volume-as well as the volatility of the price
fluctuations-experienced a significant change from 2008 (the year of the
sub-prime financial crisis) onwards. That has resulted in a faster relaxation
after the market opening and relates to a consistent decrease in the convexity
of the average trading volume intraday profile. Simultaneously, the last part
of the session has become steeper as well, a modification that is likely to
have been triggered by the new short-selling rules that were introduced in 2007
by the Securities and Exchange Commission. The combination of both results
reveals that the has been turning into a t. Additionally, the analysis of
higher-order cumulants namely the skewness and the kurtosis-shows that the
morning and the afternoon parts of the trading session are each clearly
associated with different statistical features and hence dynamical rules.
Concretely, we claim that the large initial trading volume is due to wayward
stocks whereas the large volume during the last part of the session hinges on a
cohesive increase of the trading volume. That dissimilarity between the two
parts of the trading session is stressed in periods of higher uproar in the
market.


  Chinese auctions are a combination between a raffle and an auction and are
held in practice at charity events or festivals. In a Chinese auction, multiple
players compete for several items by buying tickets, which can be used to win
the items. In front of each item there is a basket, and the players can bid by
placing tickets in the basket(s) corresponding to the item(s) they are trying
to win. After all the players have placed their tickets, a ticket is drawn at
random from each basket and the item is given to the owner of the winning
ticket. While a player is never guaranteed to win an item, they can improve
their chances of getting it by increasing the number of tickets for that item.
  In this paper we investigate the existence of pure Nash equilibria in both
the continuous and discrete settings. When the players have continuous budgets,
we show that a pure Nash equilibrium may not exist for asymmetric games when
some valuations are zero. In that case we prove that the auctioneer can
stabilize the game by placing his own ticket in each basket. On the other hand,
when all the valuations are strictly positive, a pure Nash equilibrium is
guaranteed to exist, and the equilibrium strategies are symmetric when both
valuations and budgets are symmetric. We also study Chinese auctions with
discrete budgets, for which we give both existence results and counterexamples.
While the literature on rent-seeking contests traditionally focuses on
continuous costly tickets, the discrete variant is very natural and more
closely models the version of the auction held in practice.


  The role of neural network modeling in the learning content of the special
course "Foundations of Mathematical Informatics" was discussed. The course was
developed for the students of technical universities - future IT-specialists
and directed to breaking the gap between theoretic computer science and it's
applied applications: software, system and computing engineering. CoCalc was
justified as a learning tool of mathematical informatics in general and neural
network modeling in particular. The elements of technique of using CoCalc at
studying topic "Neural network and pattern recognition" of the special course
"Foundations of Mathematic Informatics" are shown. The program code was
presented in a CoffeeScript language, which implements the basic components of
artificial neural network: neurons, synaptic connections, functions of
activations (tangential, sigmoid, stepped) and their derivatives, methods of
calculating the network's weights, etc. The features of the Kolmogorov-Arnold
representation theorem application were discussed for determination the
architecture of multilayer neural networks. The implementation of the
disjunctive logical element and approximation of an arbitrary function using a
three-layer neural network were given as an examples. According to the
simulation results, a conclusion was made as for the limits of the use of
constructed networks, in which they retain their adequacy. The framework topics
of individual research of the artificial neural networks is proposed.


  Tumors are extremely heterogeneous and comprise of a number of intratumor
microenvironments or sub-regions. These tumor microenvironments may interact
with eac based on complex high-level relationships, which could provide
important insight into the organizational structure of the tumor network. To
that end, we developed a tumor connectomics framework (TCF) to understand and
model the complex functional and morphological interactions within the tumor.
Then, we demonstrate the TCF's potential in predicting treatment response in
breast cancer patients being treated with neoadjuvant chemotherapy. The TCF was
implemented on a breast cancer patient cohort of thirty-four patients with
dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI) undergoing
neodjuvant chemotherapy treatment. The intra-tumor network connections (tumor
connectome) before and after treatment were modeled using advanced graph
theoretic centrality, path length and clustering metrics from the DCE-MRI. The
percentage change of the graph metrics between two time-points (Baseline and
1st cycle) was computed to predict the patient's final response to treatment.
The TCF visualized the inter-voxel network connections across multiple
time-points and was able to evaluate specific changes in the tumor connectome
with treatment. Degree centrality was identified as the most significant
predictor of treatment response with an AUC of 0.83 for classifying responders
from non-responders. In conclusion, the TCF graph metrics produced excellent
biomarkers for prediction of breast cancer treatment response with improved
visualization and interpretability of changes both locally and globally in the
tumor.


  Using {\it ab initio} total energy density-functional theory calculations, we
investigate the electronic, structural and magnetic properties of Manganese
doped Germanium nanowires. The nanowires have been constructed along the [110]
direction and the dangling bonds on the surface have been saturated by hydrogen
atoms. We observed that the Mn has lower formation energy at the center of the
wire when compared to regions close to the surface. The Mn-Mn coupling has
lower energy for a high-spin configuration except when they are first nearest
neighbors. These results show that Ge:Mn nanowires are potential candidates for
ferromagnetic quasi-one dimentional systems.


  We study the Sagnac effect for matter beams, in order to estimate the
kinematic corrections to the basic formula, deriving from the position and the
extent of the interferometer, and discuss the analogy with the Aharonov-Bohm
effect. We show that the formula for the Sagnac time delay is the same for
matter and light beams in arbitrary stationary space-times, provided that a
suitable condition on the speed of the beams is fulfilled. Hence, the same
results obtained for light beams apply to matter beams.


  In this paper normal functions (in the sense of Griffiths) are used to solve
and refine geometric questions about moduli spaces of curves. The first
application is to a problem posed by Eliashberg: compute the class in the
cohomology of M_{g,n}^c of the pullback of the zero section of the universal
jacobian along the section that takes [C;x_1,...,x_n] to Sum d_j x_j in Jac
(C), where d_1 + ... + d_n = 0. The second application is to slope inequalities
of the type discovered by Moriwaki. There is also a discussion of height
jumping and its relevance to slope inequalilties.


  Breaking of the inversion symmetry at the interface between different
materials may dramatically enhance spin-orbit interaction in the vicinity of
the interface. We incorporate the effects of this interfacial spin-orbit
coupling (ISOC) into the standard drift-diffusion theory by deriving
generalized boundary conditions for diffusion equations. Our theoretical scheme
is based on symmetry arguments, providing a natural classification and
parametrization of all spin-charge and spin-spin conversion effects that occur
due to ISOC at macroscopically isotropic interfaces between nonmagnetic
materials. We illustrate our approach with specific examples of spin-charge
conversion in hybrid structures. In particular, for a lateral metal-insulator
structure we predict an "ISOC-gating" effect which can be used to detect spin
currents in metallic films with weak bulk SOC.


  Complex functional brain networks are large networks of brain regions and
functional brain connections. Statistical characterizations of these networks
aim to quantify global and local properties of brain activity with a small
number of network measures. Important functional network measures include
measures of modularity (measures of the goodness with which a network is
optimally partitioned into functional subgroups) and measures of centrality
(measures of the functional influence of individual brain regions).
Characterizations of functional networks are increasing in popularity, but are
associated with several important methodological problems. These problems
include the inability to characterize densely connected and weighted functional
networks, the neglect of degenerate topologically distinct high-modularity
partitions of these networks, and the absence of a network null model for
testing hypotheses of association between observed nontrivial network
properties and simple weighted connectivity properties. In this study we
describe a set of methods to overcome these problems. Specifically, we
generalize measures of modularity and centrality to fully connected and
weighted complex networks, describe the detection of degenerate high-modularity
partitions of these networks, and introduce a weighted-connectivity null model
of these networks. We illustrate our methods by demonstrating degenerate
high-modularity partitions and strong correlations between two complementary
measures of centrality in resting-state functional magnetic resonance imaging
(MRI) networks from the 1000 Functional Connectomes Project, an open-access
repository of resting-state functional MRI datasets. Our methods may allow more
sound and reliable characterizations and comparisons of functional brain
networks across conditions and subjects.


  We report on a comprehensive analysis of the kilo-Hz (>~600 Hz)
quasi-periodic oscillations (kHz QPOs) detected from the neutron star X-ray
transient Aquila X-1 (Aql X-1) with the Rossi X-ray Timing Explorer, between
1997 and 2007. Among kHz QPO sources, Aql X-1 is peculiar because so far only
one kHz QPO has been reported, whereas in most sources, two kHz QPOs are
usually detected (a lower and an upper kHz QPO). The identification of the QPOs
reported so far has therefore been ambiguous, although it has been proposed
that they were likely to be the lower QPO. Following up on previous work, we
confirm the identification of the QPOs previously reported as lower QPOs,
because of their high quality factors and the quality factor versus frequency
dependency, which are similar to those observed in other sources. Combining all
segments of data containing a lower QPO, we detect for the first time an upper
kHz QPO. As in other sources for which the neutron star spin frequency is
larger than 400 Hz (550.25 Hz in Aql X-1), the frequency difference between the
two kHz QPOs is close to half the spin frequency. Based on this result, we
re-examine the link between the neutron star spin and the frequency of the kHz
QPOs, to show that a model in which the separation of the lower and upper QPOs
relates to the neutron star spin frequency is still as good as any comparably
simple model.


  Complementarity - the absence of a phase boundary separating the Higgs and
confinement phases of a gauge theory - can be violated by the addition of
chiral fermions. We utilize chiral symmetry violating fermion correlators such
as $ \langle \bps \psi \rangle $ as order parameters to investigate this issue.
Using inequalities similar to those of Vafa-Witten and Weingarten, we show that
SU(2) gauge theories with Higgs and fermion fields in the fundamental
representation exhibit chiral symmetry breaking in the confined phase and
therefore do {\it not} lead to massless composite fermions. We discuss the
implications for the Abbott-Farhi strongly interacting standard model.


  Generalized Uncertainty Principle (GUP) was obtained in string theory and
quantum gravity and suggested the existence of a fundamental minimal length
which, as was established, can be obtained within the deformed Heisenberg
algebra. We use the deformed commutation relations or in classical case
(studied in this paper) the deformed Poisson brackets, which are invariant with
respect to the translation in configurational space. We have found
transformations relating coordinates and times of moving and rest frames of
reference in the space with GUP in the first order over parameter of
deformation. For the non-relativistic case we find the deformed Galilean
transformation which is similar to the Lorentz one written for Euclidean space
with signature $(+,+,+,+)$. The role of the speed of light here plays some
velocity $u$ related to the parameter of deformation, which as we estimate is
many order of magnitude larger than the speed of light $u\simeq 1.2 \times
10^{22} c$. The coordinates of the rest and moving frames of reference for
relativistic particle in the space with GUP satisfy the Lorentz transformation
with some effective speed of light. We estimate that the relative deviation of
this effective speed of light $\tilde c$ from $c$ is ${(\tilde c-c)/ c}\simeq
3.5\times 10^{-45}$. The influence of GUP on the motion of particle and the
Lorentz transformation in the first order over parameter of deformation is
hidden in $1/c^2$ relativistic effects.


  We discuss a force arising from zero-temperature quantum fluctuations in a
weakly interacting Bose-Einstein condensate (BEC). We argue that there is a
drag force on an object moving at speeds well below Landau's critical velocity,
and motivate our argument by an analogy to the Casimir force in an
electromagnetic vacuum. We sketch the calculation of this force for an object
described by a general potential. We comment about the relevance of our results
to the stability of superfluid flow, arguing that this effect is consistent
with the observation of persistent currents and that this effect introduces new
experimental observables. Finally, we describe a new hydryodynamic boundary
condition for superfluid flow that takes into account the scattering of quantum
fluctuations off a rough surface.


  Technical documents contain a fair amount of unnatural language, such as
tables, formulas, pseudo-codes, etc. Unnatural language can be an important
factor of confusing existing NLP tools. This paper presents an effective method
of distinguishing unnatural language from natural language, and evaluates the
impact of unnatural language detection on NLP tasks such as document
clustering. We view this problem as an information extraction task and build a
multiclass classification model identifying unnatural language components into
four categories. First, we create a new annotated corpus by collecting slides
and papers in various formats, PPT, PDF, and HTML, where unnatural language
components are annotated into four categories. We then explore features
available from plain text to build a statistical model that can handle any
format as long as it is converted into plain text. Our experiments show that
removing unnatural language components gives an absolute improvement in
document clustering up to 15%. Our corpus and tool are publicly available.


  The Federal Open Market Committee within the Federal Reserve System is
responsible for managing inflation, maximizing employment, and stabilizing
interest rates. Meeting minutes play an important role for market movements
because they provide the birds eye view of how this economic complexity is
constantly re-weighed. Therefore, There has been growing interest in analyzing
and extracting sentiments on various aspects from large financial texts for
economic projection. However, Aspect-based Sentiment Analysis is not widely
used on financial data due to the lack of large labeled dataset. In this paper,
I propose a model to train ABSA on financial documents under weak supervision
and analyze its predictive power on various macroeconomic indicators.


  Low CO2 prices have prompted discussion about political measures aimed at
increasing the cost of carbon dioxide emissions. These costs affect, inter
alia, integrated district heating system operators (DHSO), often owned by
municipalities with some political influence, that use a variety of (CO2 emis-
sion intense) heat generation technologies. We examine whether DHSOs have an
incentive to support measures that increase CO2 emission prices in the short
term. Therefore, we (i) develop a simplified analytical framework to analyse
optimal decisions of a district heating operator, and (ii) investigate the
market-wide effects of increasing emission prices, in particular the pass-
through from emission costs to electricity prices. Using a numerical model of
the common Austrian and German power system, we estimate a pass-through from
CO2 emission prices to power prices between 0.69 and 0.53 as of 2017, depending
on the absolute emission price level. We find the CO2 emission cost
pass-through to be sufficiently high so that low-emission district heating
systems operating at least moderately efficient generation units benefit from
rising CO2 emission prices in the short term.


  We describe a system that simplifies the process of debugging programs
produced by computer-aided parallelization tools. The system uses relative
debugging techniques to compare serial and parallel executions in order to show
where the computations begin to differ. If the original serial code is correct,
errors due to parallelization will be isolated by the comparison.
  One of the primary goals of the system is to minimize the effort required of
the user. To that end, the debugging system uses information produced by the
parallelization tool to drive the comparison process. In particular, the
debugging system relies on the parallelization tool to provide information
about where variables may have been modified and how arrays are distributed
across multiple processes. User effort is also reduced through the use of
dynamic instrumentation. This allows us to modify the program execution without
changing the way the user builds the executable.
  The use of dynamic instrumentation also permits us to compare the executions
in a fine-grained fashion and only involve the debugger when a difference has
been detected. This reduces the overhead of executing instrumentation.


  Despite several decades of both experimental and theoretical work the nature
of the hidden order transition at THO = 17.5 K in URu2Si2 remains enigmatic. We
report here low field DC magnetization as well as AC susceptibility
measurements performed on single crystals with field along the c-axis. A peak
in the first order AC susceptibility is observed at T=16 K in close proximity
to the well known change in slope at THO=17.5 K. Third order susceptibility
measurements on the other hand reveal a signature only at 16 K with no
discernible change at THO. However, both transitions are visible in the fifth
order susceptibility. A signature at this lower transition, as a spontaneous
ferromagnetic signal, also appears in low field DC magnetization measurements.
A similar but larger ferromagnetic response appears at T~35 K. Both these
ferromagnetic signatures are suppressed in a small field (B ~ 40 Gauss
||c-axis). The close proximity of the lower signature to the hidden order
transition and the simultaneous presence and suppression of a ferromagnetic
signature at 35 K could be due to the removal of degeneracy in the complex
order-parameter of the hidden order transition due a "symmetry breaking field",
at least locally within the crystals of URu2Si2.


  Developing safety and efficiency applications for Connected and Automated
Vehicles (CAVs) require a great deal of testing and evaluation. The need for
the operation of these systems in critical and dangerous situations makes the
burden of their evaluation very costly, possibly dangerous, and time-consuming.
As an alternative, researchers attempt to study and evaluate their algorithms
and designs using simulation platforms. Modeling the behavior of drivers or
human operators in CAVs or other vehicles interacting with them is one of the
main challenges of such simulations. While developing a perfect model for human
behavior is a challenging task and an open problem, we present a significant
augmentation of the current models used in simulators for driver behavior. In
this paper, we present a simulation platform for a hybrid transportation system
that includes both human-driven and automated vehicles. In addition, we
decompose the human driving task and offer a modular approach to simulating a
large-scale traffic scenario, allowing for a thorough investigation of
automated and active safety systems. Such representation through Interconnected
modules offers a human-interpretable system that can be tuned to represent
different classes of drivers. Additionally, we analyze a large driving dataset
to extract expressive parameters that would best describe different driving
characteristics. Finally, we recreate a similarly dense traffic scenario within
our simulator and conduct a thorough analysis of various human-specific and
system-specific factors, studying their effect on traffic network performance
and safety.


  The study of the existence of free groups in skew linear groups have been
begun since the last decades of the 20-th century. The starting point is the
theorem of Tits (1972), now often is referred as Tits' Alternative, stating
that every finitely generated subgroup of the general linear group $\GL_n(F)$
over a field $F$ either contains a non-cyclic free subgroup or it is
solvable-by-finite. In this paper, we study the existence of non-cyclic free
subgroups in maximal subgroups of an almost subnormal subgroup of the general
skew linear group over a locally finite division ring.


  Hemaspaandra, Hempel, and Wechsung [cs.CC/9909020] initiated the field of
query order, which studies the ways in which computational power is affected by
the order in which information sources are accessed. The present paper studies,
for the first time, query order as it applies to the levels of the polynomial
hierarchy. We prove that the levels of the polynomial hierarchy are
order-oblivious. Yet, we also show that these ordered query classes form new
levels in the polynomial hierarchy unless the polynomial hierarchy collapses.
We prove that all leaf language classes - and thus essentially all standard
complexity classes - inherit all order-obliviousness results that hold for P.


  In this paper, we exhibit non-uniqueness of Leray weak solutions of the
forced magnetohydrodynamic (MHD for short) equations. Similar to the solutions
constructed in \cite{ABC2}, we first find a special steady solution of ideal
MHD equations whose linear unstability was proved in \cite{Lin}. It is possible
to perturb the unstable scenario of ideal MHD to 3D viscous and resistive MHD
equations, which can be regarded as the first unstable "background" solution.
Our perturbation argument is based on the spectral theoretic approach
\cite{Kato}. The second solution we would construct is a trajectory on the
unstable manifold associated to the unstable steady solution. It is worth
noting that these solutions live precisely on the borderline of the known
well-posedness theory.


  A critical point of second order, belonging to the universality class of the
3d Ising model, has recently been advocated as a strong candidate for the
critical behaviour (at high temperatures) of QCD with non-zero quark masses.
The implications of this conjecture are investigated in the multiparticle
environment of high-energy collisions. A universal intermittency pattern of
pion-density fluctuations is found, at the critical point, and its association
to the critical exponents is discussed. A Monte Carlo simulation of critical
events, in heavy-ion collisions, reveals the detailed structure of these
fluctuations, suggesting a framework of (event-by-event) measurements in which
the critical theory of QCD may become falsifiable.


  Trans-planckian frequencies can be mimicked outside a black-hole horizon as a
tail of an exponentially large amplitude wave that is mostly hidden behind the
horizon. The present proposal requires implementing a final state condition.
This condition involves only frequencies below the cutoff scale. It may be
interpreted as a condition on the singularity. Despite the introduction of the
cutoff, the Hawking radiation is restored for static observers. Freely falling
observers see empty space outside the horizon, but are "heated" as they cross
the horizon.


  In this paper we propose a generalized R redundancy cycle technique that
provides optical networks almost fault-tolerant communications. More
importantly, when applied using only single cycles rather than the standard
paired cycles, the generalized R redundancy technique is shown to almost halve
the necessary light-trail resources in the network while maintaining the
fault-tolerance and dependability expected from cycle-based routing. For
efficiency and distributed control, it is common in distributed systems and
algorithms to group nodes into intersecting sets referred to as quorum sets.
Optimal communication quorum sets forming optical cycles based on light-trails
have been shown to flexibly and efficiently route both point-to-point and
multipoint-to-multipoint traffic requests. Commonly cycle routing techniques
will use pairs of cycles to achieve both routing and fault-tolerance, which
uses substantial resources and creates the potential for underutilization.
Instead, we intentionally utilize R redundancy within the quorum cycles for
fault-tolerance such that every point-to-point communication pairs occur in at
least R cycles. The result is a set of R = 3 redundant cycles with 93.23-99.34%
fault coverage even with two simultaneous faults all while using 38.85-42.39%
fewer resources.


  Dark matter and dark energy dominate the behavior of our universe. The dark
matter usually forms halo structures in large number of galaxies. Properties of
dark matter halo can be revealed and understood from the gravitational lensing
observations. In this work, a comprehensive study on the gravitational lensing
of black holes immersed in dark matter halos is presented. To effectively model
the supermassive black hole in a galaxy center (which is surrounded by dark
matter halo) in a simple way, we investigate the Schwarzschild black hole and
charged Reissner-Nordstr\"om black hole immersed in a perfect fluid dark matter
halo. In the present work, several basic quantities in gravitational lensing
(the gravitational deflection angle of light, photon sphere, black hole shadow
radius, gravitational lens equation and Einstein ring) are calculated and
analyzed analytically and numerically. A second order analytical expansion of
gravitational deflection angle is obtained in the weak deflection limit, and
the full gravitational deflection angle (including all order perturbation
contributions applicable to both weak and strong deflection limits) is also
calculated numerically as comparisons. It enables us to analyze the perfect
fluid dark matter influences on gravitational deflection angle and
gravitational lensing beyond the leading order, which were not sufficiently
studied in previous works. Assuming $M \sim \lambda_{\text{DM}} \sim Q$, our
results show that dark matter can greatly influence the gravitational lensing
of central black holes.


  Analysis of the experimental data of joint Russian - Hungarian research was
carried out at Tien Shan station on the search of sources of primary cosmic
rays (PCR) at energies 0.1-1.0 PeV. Maps of extensive air shower arrival
directions were presented where the standard deviation of mean event numbers in
equatorial co-ordinates exceeded a definite value. The excess of EAS number was
observed from an Galaxy object - the SN remnant and some other directions. The
young pulsar PSR 0656+14 located near the centre of this object.


  Ben-Israel and Vaidman (Found Phys (2017). doi:10.1007/s10701-017-0071-x)
have raised objections to my arguments that there are cases where a quantum
mechanical weak value can be said not to represent the system to which it
pertains. They are correct in pointing out that some of my conclusions were too
general. However, for weak values of projection operators my conclusions still
stand.


  The non-orientable 4-genus of a knot in the 3-sphere is defined as the
smallest first Betti number of any non-orientable surface smoothly and properly
embedded in the 4-ball, with boundary the given knot. We compute the
non-orientable 4-genus for all knots with crossing number 8 or 9. As
applications we prove a conjecture of Murakami's and Yasuhara's, and give a new
lower bound for the slicing number of knot.


  Recently, an analogue over $\mathbb{F}_q[T]$ of Landau's theorem on sums of
two squares was considered by Bary-Soroker, Smilansky and Wolf. They counted
the number of monic polynomials in $\mathbb{F}_q[T]$ of degree $n$ of the form
$A^2+TB^2$, which we denote by $B(n,q)$. They studied $B(n,q)$ in two limits:
fixed $n$ and large $q$; and fixed $q$ and large $n$. We generalize their
result to the most general limit $q^n \to \infty$. More precisely, we prove
\begin{equation*} B(n,q) \sim K_q \cdot \binom{n-\frac{1}{2}}{n} \cdot q^n ,
\qquad q^n \to \infty, \end{equation*} for an explicit constant $K_q =
1+O\left(1/q\right)$. Our methods are different and are based on giving
explicit bounds on the coefficients of generating functions. These methods also
apply to other problems, related to polynomials with prime factors of even
degree.


  In this paper, we prove the Hardy-Leray inequality and related
  inequalities in variable Lebesgue spaces. Our proof is based on a
  version of the Stein-Weiss inequality in variable Lebesgue spaces
  derived from two weight inequalities due to Melchiori and Pradolini. We also
discuss an application of our results to establish an existence result for the
degenerate $\pp$-Laplace operator.


  We consider an infinite system of coupled stochastic differential equations
(SDE) describing dynamics of the following infinite particle system. Each
partricle is characterised by its position $x\in \mathbb{R}^{d}$ and internal
parameter (spin) $\sigma _{x}\in \mathbb{R}$. While the positions of particles
form a fixed ("quenched") locally-finite set (configuration) $ \gamma \subset $
$\mathbb{R}^{d}$, the spins $\sigma _{x}$ and $\sigma _{y}$ interact via a pair
potential whenever $\left\vert x-y\right\vert <\rho $, where $\rho >0$ is a
fixed interaction radius. The number $n_{x}$ of particles interacting with a
particle in positionn $x$ is finite but unbounded in $x$. The growth of $n_{x}$
as $x\rightarrow \infty $ creates a major technical problem for solving our SDE
system. To overcome this problem, we use a finite volume approximation combined
with a version of the Ovsjannikov method, and prove the existence and
uniqueness of the solution in a scale of Banach spaces of weighted sequences.
As an application example, we construct stochastic dynamics associated with
Gibbs states of our particle system.


  We consider the problem of finding cryptographically suitable Jacobians. By
applying a probabilistic generic algorithm to compute the zeta functions of low
genus curves drawn from an arbitrary family, we can search for Jacobians
containing a large subgroup of prime order. For a suitable distribution of
curves, the complexity is subexponential in genus 2, and O(N^{1/12}) in genus
3. We give examples of genus 2 and genus 3 hyperelliptic curves over prime
fields with group orders over 180 bits in size, improving previous results. Our
approach is particularly effective over low-degree extension fields, where in
genus 2 we find Jacobians over F_{p^2) and trace zero varieties over F_{p^3}
with near-prime orders up to 372 bits in size. For p = 2^{61}-1, the average
time to find a group with 244-bit near-prime order is under an hour on a PC.


  We revisit the question of characterizing the convergence rate of plug-in
estimators of optimal transport costs. It is well known that an empirical
measure comprising independent samples from an absolutely continuous
distribution on $\mathbb{R}^d$ converges to that distribution at the rate
$n^{-1/d}$ in Wasserstein distance, which can be used to prove that plug-in
estimators of many optimal transport costs converge at this same rate. However,
we show that when the cost is smooth, this analysis is loose: plug-in
estimators based on empirical measures converge quadratically faster, at the
rate $n^{-2/d}$. As a corollary, we show that the Wasserstein distance between
two distributions is significantly easier to estimate when the measures are
well-separated. We also prove lower bounds, showing not only that our analysis
of the plug-in estimator is tight, but also that no other estimator can enjoy
significantly faster rates of convergence uniformly over all pairs of measures.
Our proofs rely on empirical process theory arguments based on tight control of
$L^2$ covering numbers for locally Lipschitz and semi-concave functions. As a
byproduct of our proofs, we derive $L^\infty$ estimates on the displacement
induced by the optimal coupling between any two measures satisfying suitable
concentration and anticoncentration conditions, for a wide range of cost
functions.


  This letter develops a novel transmit beamforming (BF) design for canceling
self-interference (SI) in analog in-band full-duplex phased arrays. Our design
maximizes transmit BF gain in a desired direction while simultaneously reducing
SI power to below a specified threshold on per-antenna basis to avoid
saturating receive-chain components, such as LNAs. Core to our approach is that
it accounts for real-world phase shifters used in analog phased array systems,
whose limited resolution imposes non-convex constraints on BF design. We
overcome this by transforming these non-convex constraints into convex polygon
constraints, which we then solve through semidefinite relaxation and a rank
refinement procedure. Numerical results show that our proposed BF scheme
reliably cancels SI to the target power threshold at each receive antenna while
sacrificing little in transmit BF gain, even with modest phase shifter
resolution.


  Three-dimensional numerical simulations show that large-scale latent heating
resulting from condensation of water vapor can produce multiple zonal jets
similar to those on the gas giants (Jupiter and Saturn) and ice giants (Uranus
and Neptune). For plausible water abundances (3-5 times solar on Jupiter/Saturn
and 30 times solar on Uranus/Neptune), our simulations produce ~20 zonal jets
for Jupiter and Saturn and 3 zonal jets on Uranus and Neptune, similar to the
number of jets observed on these planets. Moreover, these Jupiter/Saturn cases
produce equatorial superrotation whereas the Uranus/Neptune cases produce
equatorial subrotation,consistent with the observed equatorial jet direction on
these planets.Sensitivity tests show that water abundance, planetary rotation
rate,and planetary radius are all controlling factors, with water playing the
most important role; modest water abundances, large planetary radii, and fast
rotation rates favor equatorial superrotation, whereas large water abundances
favor equatorial subrotation regardless of the planetary radius and rotation
rate. Given the larger radii, faster rotation rates, and probable lower water
abundances of Jupiter and Saturn relative to Uranus and Neptune, our
simulations therefore provide a possible mechanism for the existence of
equatorial superrotation on Jupiter and Saturn and the lack of superrotation on
Uranus and Neptune. Nevertheless, Saturn poses a possible difficulty, as our
simulations were unable to explain the unusually high speed (~400m/s) of that
planet's superrotating jet. The zonal jets in our simulations exhibit modest
violations of the barotropic and Charney-Stern stability criteria. Overall, our
simulations, while idealized, support the idea that latent heating plays an
important role in generating the jets on the giant planets.


  Recently, multiple time scale characteristics of heart dynamics have received
much attention for distinguishing healthy and pathologic cardiac systems.
Despite structural peculiarities of the fetal cardiovascular system, the fetal
heart rate(FHR) displays multiple time scale characteristics similar to the
adult heart rate due to the autorhythmicity of its different oscillatory
tissues and its interaction with other neural controllers. In this paper, we
investigate the event and time scale characteristics of the normal and two
pathologic fetal heart rate groups with the help of the new measure, called the
Unit Time Block Entropy(UTBE), which approximates the entropy at each event and
time scale based on symbolic dynamics. This method enables us to match the
measurement time and the number of words between fetal heart rate data sets
simultaneously. We find that in the small event scale and the large time scale,
the normal fetus and the two pathologic fetus are completely distinguished. We
also find that in the large event scale and the small time scale, the presumed
distress fetus and the acidotic distress fetus are significantly distinguished.


  A simple dynamical model, Biased Random Organization, BRO, appears to produce
configurations known as Random Close Packing (RCP) as BRO's densest critical
point in dimension $d=3$. We conjecture that BRO likewise produces RCP in any
dimension; if so, then RCP does not exist in $d=1-2$ (where BRO dynamics lead
to crystalline order). In $d=3-5$, BRO produces isostatic configurations and
previously estimated RCP volume fractions 0.64, 0.46, and 0.30, respectively.
For all investigated dimensions ($d=2-5$), we find that BRO belongs to the
Manna universality class of dynamical phase transitions by measuring critical
exponents associated with the steady-state activity and the long-range density
fluctuations. Additionally, BRO's distribution of near-contacts (gaps) displays
behavior consistent with the infinite-dimensional theoretical treatment of RCP
when $d \ge 4$. The association of BRO's densest critical configurations with
Random Close Packing implies that RCP's upper-critical dimension is consistent
with the Manna class $d_{uc} = 4$.


  A strategy to address the inverse Galois problem over Q consists of
exploiting the knowledge of Galois representations attached to certain
automorphic forms. More precisely, if such forms are carefully chosen, they
provide compatible systems of Galois representations satisfying some desired
properties, e.g. properties that reflect on the image of the members of the
system. In this article we survey some results obtained using this strategy.


  The local environment of a barium monofluoride (BaF) molecule embedded in an
argon matrix is calculated. A substitution of a BaF molecule for four Ar atoms
is found to be strongly favoured compared to substitutions for other numbers of
Ar atoms. The equilibrium positions of the BaF molecule and its nearby Ar
neighbours are found by minimizing the total energy. The potential barrier that
prevents the migration of the BaF molecule within the solid and the barrier
that prevents its rotation are calculated. At the cryogenic temperatures used
by the EDM$^3$ collaboration, these barriers are sufficiently large to fix the
position and orientation of the molecule. Knowledge of the local environment of
matrix-isolated BaF molecules is essential for the EDM$^3$ collaboration, which
is using them in a precision measurement of the electron electric dipole
moment.


  The aim of this work is to theoretically investigate the possibility of Kerr
frequency combs in mechanical systems. In particular, whether
microelectrome-chanical devices (MEMS) can be used to generate frequency combs
in a manner that is analogous to the optical frequency combs generated in
optical microresona-tors with Kerr-type nonlinearity. The analysis assumes a
beam-like micromechani-cal structure, and starting from the Euler-Bernoulli
beam equation derives the nec-essary conditions in parameter space for the comb
generation. The chapter equally presents potential means for the physical
implementation of mechanical Kerr combs.


  We develop Weyl-Titchmarsh theory for self-adjoint Schr\"odinger operators
$H_{\alpha}$ in $L^2((a,b);dx;\cH)$ associated with the operator-valued
differential expression $\tau =-(d^2/dx^2)+V(\cdot)$, with
$V:(a,b)\to\cB(\cH)$, and $\cH$ a complex, separable Hilbert space. We assume
regularity of the left endpoint $a$ and the limit point case at the right
endpoint $b$. In addition, the bounded self-adjoint operator $\alpha= \alpha^*
\in \cB(\cH)$ is used to parametrize the self-adjoint boundary condition at the
left endpoint $a$ of the type $$ \sin(\alpha)u'(a)+\cos(\alpha)u(a)=0, $$ with
$u$ lying in the domain of the underlying maximal operator $H_{\max}$ in
$L^2((a,b);dx;\cH)$ associated with $\tau$. More precisely, we establish the
existence of the Weyl-Titchmarsh solution of $H_{\alpha}$, the corresponding
Weyl-Titchmarsh $m$-function $m_{\alpha}$ and its Herglotz property, and
determine the structure of the Green's function of $H_{\alpha}$.
  Developing Weyl-Titchmarsh theory requires control over certain
(operator-valued) solutions of appropriate initial value problems. Thus, we
consider existence and uniqueness of solutions of 2nd-order differential
equations with the operator coefficient $V$, -y" + (V - z) y = f \, \text{on}
\, (a,b), y(x_0) = h_0, \; y'(x_0) = h_1, under the following general
assumptions: $(a,b)\subseteq\bbR$ is a finite or infinite interval,
$x_0\in(a,b)$, $z\in\bbC$, $V:(a,b)\to\cB(\cH)$ is a weakly measurable
operator-valued function with $\|V(\cdot)\|_{\cB(\cH)}\in L^1_\loc((a,b);dx)$,
and $f\in L^1_{\loc}((a,b);dx;\cH)$, with $\cH$ a complex, separable Hilbert
space. We also study the analog of this initial value problem with $y$ and $f$
replaced by operator-valued functions $Y, F \in \cB(\cH)$.
  Our hypotheses on the local behavior of $V$ appear to be the most general
ones to date.


  The reasons which restrict opportunities of classical mechanics at the
description of nonequilibrium systems are discussed. The way of overcoming of
the key restrictions is offered. This way is based on an opportunity of
representation of nonequilibrium system as a set of equilibrium subsystems. The
equation of motion and the general Lagrange, Hamilton and Liouville equations
for subsystems have been obtained. The way of a substantiation of
thermodynamics is offered.


  The problem of calculating the four--nucleon bound state properties for the
case of realistic two- and three-body nuclear potentials is studied using the
hyperspherical harmonic (HH) approach. A careful analysis of the convergence of
different classes of HH functions has been performed. A restricted basis is
chosen to allow for accurate estimates of the binding energy and other
properties of the 4He ground state. Results for various modern two-nucleon and
two- plus three-nucleon interactions are presented. The 4He asymptotic
normalization constants for separation in 2+2 and 1+3 clusters are also
computed.


  Symmetries and conservation laws are studied for two classes of physically
and analytically interesting radial wave equations with power nonlinearities in
multi-dimensions. The results consist of two main classifications: all
symmetries of point type and all conservation laws of a general energy-momentum
type are explicitly determined, including those such as dilations, inversions,
similarity energies and conformal energies that exist only for special powers
or dimensions. In particular, all variational cases (when a Lagrangian
formulation exists) and non-variational cases (when no Lagrangian exists) for
these wave equations are considered. As main results, the classification yields
generalized energies and radial momenta in certain non-variational cases, which
are shown to arise from a new type of Morawetz dilation identity that produces
conservation laws for each of the two wave equations in a different way than
Noether's theorem.


  We investigate the fluctuations and correlations involving baryon number in
hot hadronic matter with modified masses of negative-parity baryons, in the
context of the hadron resonance gas. Temperature-dependent masses are adopted
from the recent lattice QCD results and from a chiral effective model which
implements the parity doubling structure with respect to the chiral symmetry.
Confronting the baryon number susceptibility, baryon-charge correlation, and
baryon-strangeness correlation and their ratios with the lattice QCD data, we
show that the strong downward mass shift in hyperons can accidentally reproduce
some correlation ratios, however it also tends to overshoot the individual
fluctuations and correlations. This indicates, that in order to correctly
account for the influence of the chiral symmetry restoration on the fluctuation
observables, a consistent framework of in-medium effects beyond hadron mass
shifts is required.


  This paper considers the joint-decoding (JD) problem for finite-state
channels (FSCs) and low-density parity-check (LDPC) codes. In the first part,
the linear-programming (LP) decoder for binary linear codes is extended to JD
of binary-input FSCs. In particular, we provide a rigorous definition of LP
joint-decoding pseudo-codewords (JD-PCWs) that enables evaluation of the
pairwise error probability between codewords and JD-PCWs in AWGN. This leads
naturally to a provable upper bound on decoder failure probability. If the
channel is a finite-state intersymbol interference channel, then the joint LP
decoder also has the maximum-likelihood (ML) certificate property and all
integer-valued solutions are codewords. In this case, the performance loss
relative to ML decoding can be explained completely by fractional-valued
JD-PCWs. After deriving these results, we discovered some elements were
equivalent to earlier work by Flanagan on LP receivers.
  In the second part, we develop an efficient iterative solver for the joint LP
decoder discussed in the first part. In particular, we extend the approach of
iterative approximate LP decoding, proposed by Vontobel and Koetter and
analyzed by Burshtein, to this problem. By taking advantage of the dual-domain
structure of the JD-LP, we obtain a convergent iterative algorithm for joint LP
decoding whose structure is similar to BCJR-based turbo equalization (TE). The
result is a joint iterative decoder whose per-iteration complexity is similar
to that of TE but whose performance is similar to that of joint LP decoding.
The main advantage of this decoder is that it appears to provide the
predictability of joint LP decoding and superior performance with the
computational complexity of TE. One expected application is coding for magnetic
storage where the required block-error rate is extremely low and system
performance is difficult to verify by simulation.


  Neutron cross section matrices for fission and scattering data are required
for each material, temperature, and enrichment level to calculate the neutron
transport equation accurately. This information can be a limiting factor when
using the multigroup discrete ordinates (SN) method when the number of energy
groups is large. Machine Learning (ML) can be used to replace the need for the
cross section matrices by reproducing the function that maps the scalar flux to
the scattering and fission sources. Through the use of autoencoders and Deep
Jointly-Informed Neural Networks (DJINN), the data storage requirements are
reduced by 94% of the original data for a 618 group problem. This is
accomplished while preserving the scalar flux, maintaining generality, and
decreasing wall clock times.


  We present an optical transmission spectrum for WASP-94A b, the first
atmospheric characterisation of this highly-inflated hot Jupiter. The planet
has a reported radius of $1.72^{+0.06}_{-0.05}$ R$_{\textrm{Jup}}$, a mass of
only $0.456^{+0.032}_{-0.036}$ M$_{\textrm{Jup}}$, and an equilibrium
temperature of $1508 \pm 75$ K. We observed the planet transit
spectroscopically with the EFOSC2 instrument on the ESO New Technology
Telescope (NTT) at La Silla, Chile: the first use of NTT/EFOSC2 for
transmission spectroscopy. We achieved an average transit-depth precision of
$128$ ppm for bin widths of $\sim200$ Angstrom. This high precision was
achieved in part by linking Gaussian Process hyperparameters across all
wavelength bins. The resulting transmission spectrum, spanning a wavelength
range of $3800 - 7140$ Angstrom, exhibits a sodium absorption with a
significance of $4.9\sigma$, suggesting a relatively cloud-free atmosphere. The
sodium signal may be broadened, with a best fitting width of $78_{-32}^{+67}$
Angstrom in contrast to the instrumental resolution of $27.2 \pm 0.2$ Angstrom.
We also detect a steep slope in the blue end of the transmission spectrum,
indicating the presence of Rayleigh scattering in the atmosphere of WASP-94A b.
Retrieval models show evidence for the observed slope to be super-Rayleigh and
potential causes are discussed. Finally, we find narrow absorption cores in the
CaII H&K lines of WASP-94A, suggesting the star is enshrouded in gas escaping
the hot Jupiter.


  Rectified linear unit (ReLU) activations can also be thought of as 'gates',
which, either pass or stop their pre-activation input when they are 'on' (when
the pre-activation input is positive) or 'off' (when the pre-activation input
is negative) respectively. A deep neural network (DNN) with ReLU activations
has many gates, and the on/off status of each gate changes across input
examples as well as network weights. For a given input example, only a subset
of gates are 'active', i.e., on, and the sub-network of weights connected to
these active gates is responsible for producing the output. At randomised
initialisation, the active sub-network corresponding to a given input example
is random. During training, as the weights are learnt, the active sub-networks
are also learnt, and potentially hold very valuable information. In this paper,
we analytically characterise the role of active sub-networks in deep learning.
To this end, we encode the on/off state of the gates of a given input in a
novel 'neural path feature' (NPF), and the weights of the DNN are encoded in a
novel 'neural path value' (NPV). Further, we show that the output of network is
indeed the inner product of NPF and NPV. The main result of the paper shows
that the 'neural path kernel' associated with the NPF is a fundamental quantity
that characterises the information stored in the gates of a DNN. We show via
experiments (on MNIST and CIFAR-10) that in standard DNNs with ReLU activations
NPFs are learnt during training and such learning is key for generalisation.
Furthermore, NPFs and NPVs can be learnt in two separate networks and such
learning also generalises well in experiments.


  We present and analyse integral-field observations of six type-II QSOs with
z=0.3-0.4, selected from the Sloan Digital Sky Survey (SDSS). Two of our sample
are found to be surrounded by a nebula of warm ionized gas, with the largest
nebula extending across 8" (40 kpc). Some regions of the extended nebulae show
kinematics that are consistent with gravitational motion, while other regions
show relatively perturbed kinematics: velocity shifts and line widths too large
to be readily explained by gravitational motion. We propose that a ~20 kpc x20
kpc outflow is present in one of the galaxies. Possible mechanisms for
triggering the outflow are discussed. In this object, we also find evidence for
ionization both by shocks and the radiation field of the AGN.


  Let $T=(V,A)$ be a tournament. For $X\subseteq V$, the subtournament of $T$
induced by $X$ is denoted by $T[X]$. A subset $I$ of $V$ is an interval of $T$
provided that for every $a,b\in I$ and $x\in V\setminus I$, $(a,x)\in A$ if and
only if $(b,x)\in A$. For example, $\varnothing $, ${x}$ ($x \in V$) and $V$
are intervals of $T$, called trivial intervals. The tournament $T$ is
indecomposable if all its intervals are trivial, otherwise, it is decomposable.
A critical tournament is an indecomposable tournament $T$ of cardinality
$\geqslant 5$ such that every vertex $x$ of $T$ is critical, i.e., the
subtournament $T[V(T)\setminus\{x\}]$ is decomposable. Given an indecomposable
tournament $T$, a vertex $x$ of $T$ is strongly critical, if for every
$X\subseteq V(T)$ such that $x\in X$, $\vert X\vert \geqslant 5$ and $T[X]$ is
indecomposable, $x$ is a critical vertex of $T[X]$. Let $T$ be an
indecomposable tournament and let $\mathscr{C}(T)$ be the set of the strongly
critical vertices of $T$. We prove that, if $T$ is non-critical, then
$f(T):=\vert \mathscr{C}(T)\vert \leqslant 4$, and that the correspondence
$f(T)$ is decreasing from the class of indecomposable and non-critical
tournaments (defined by means of embedding) to $\{0,1,2,3,4\}$. By giving
examples, we also verify that the bounds 0 and 4 are optimal. This article is
an extract from my master's thesis \cite{mon mast\`ere}.


  Seismic attenuation in granular porous media is of paramount importance in
rock physics and seismology. Unlike sandstones, shales are mixtures of sand
grains and clays with extremely low porosity and permeability. Swelling of
clays upon wetting induce micro-cracks at grain-clay interfaces and results in
the strong elastic wave scattering. Such scattering prevents adequate
measurements of the absorption from ballistic wave attenuations. Here we infer
this intrinsic attenuation from multiply scattered waves as in seismology and
ultrasonics. We find that increasing confining pressure reduces the scattering
attenuation by micro-crack closure but increases surprisingly the absorption,
likely due to the viscous dissipation involved with more liquids adsorbed in
clays and at grain surfaces. Also, we observe that cyclic heating and cooling
causes the shrinkage of clays and the growth of microcracks as well as the
nucleation of macro-fractures. This leads to a predominant chaotic
reverberation in this fractured shale. Numerical simulations based on X-ray
tomography of the fractured sample confirm the multiple scattering behavior and
reveal the increase of a characteristic length from an initial intact to a
finally fractured shale. This study helps to improve acoustic techniques for
multiscale exploration of gas and oil in shales and other fractured rocks.