  Multiwavelength observations have revealed the highly unusual properties of
the gamma-ray source PMN J1603-4904, which are difficult to reconcile with any
other well established gamma-ray source class. The object is either a very
atypical blazar or compact jet source seen at a larger angle to the line of
sight. In order to determine the physical origin of the high-energy emission
processes in PMN J1603-4904, we study the X-ray spectrum in detail. We
performed quasi-simultaneous X-ray observations with XMM-Newton and Suzaku in
2013 September, resulting in the first high signal-to-noise X-ray spectrum of
this source. The 2-10 keV X-ray spectrum can be well described by an absorbed
power law with an emission line at 5.44$\pm$0.05 keV (observed frame).
Interpreting this feature as a K{\alpha} line from neutral iron, we determine
the redshift of PMN J1603-4904 to be z=0.18$\pm$0.01, corresponding to a
luminosity distance of 872$\pm$54 Mpc. The detection of a redshifted X-ray
emission line further challenges the original BL Lac classification of PMN
J1603-4904. This result suggests that the source is observed at a larger angle
to the line of sight than expected for blazars, and thus the source would add
to the elusive class of gamma-ray loud misaligned-jet objects, possibly a
{\gamma}-ray bright young radio galaxy.


  With the rapid development of mobile Internet and big data, a huge amount of
data is generated in the network, but the data that users are really interested
in a very small portion. To extract the information that users are interested
in from the huge amount of data, the information overload problem needs to be
solved. In the era of mobile internet, the user's characteristics and other
information should be combined in the massive amount of data to quickly and
accurately recommend content to the user, as far as possible to meet the user's
personalized needs. Therefore, there is an urgent need to realize high-speed
and effective retrieval in tens of thousands of micro-videos. Video data
content contains complex meanings, and there are intrinsic connections between
video data. For multimodal information, subspace coding learning is introduced
to build a coding network from public potential representations to multimodal
feature information, taking into account the consistency and complementarity of
information under each modality to obtain a public representation of the
complete eigenvalue. An end-to-end reordering model based on deep learning and
attention mechanism, called interest-related product similarity model based on
multimodal data, is proposed for providing top-N recommendations. The
multimodal feature learning module, interest-related network module and product
similarity recommendation module together form the new model.By conducting
extensive experiments on publicly accessible datasets, the results demonstrate
the state-of-the-art performance of our proposed algorithm and its
effectiveness.


  Epidemics occur in all shapes and forms: infections propagating in our sparse
sexual networks, rumours and diseases spreading through our much denser social
interactions, or viruses circulating on the Internet. With the advent of large
databases and efficient analysis algorithms, these processes can be better
predicted and controlled. In this study, we use different characteristics of
network organization to identify the influential spreaders in 17 empirical
networks of diverse nature using 2 epidemic models. We find that a judicious
choice of local measures, based either on the network's connectivity at a
microscopic scale or on its community structure at a mesoscopic scale, compares
favorably to global measures, such as betweenness centrality, in terms of
efficiency, practicality and robustness. We also develop an analytical
framework that highlights a transition in the characteristic scale of different
epidemic regimes. This allows to decide which local measure should govern
immunization in a given scenario.


  In this paper we construct a new class of surfaces whose geodesic flow is
integrable (in the sense of Liouville). We do so by generalizing the notion of
tubes about curves to 3-dimensional manifolds, and using Jacobi fields we
derive conditions under which the metric of the generalized tubular
sub-manifold admits an ignorable coordinate. Some examples are given,
demonstrating that these special surfaces can be quite elaborate and varied.


  We report a hyperfine-states related weak equivalence principle (WEP) test
which searches for possible WEP violation signal in single atom interferometer.
With the ground hyperfine states $\left|F=1\right\rangle$ and
$\left|F=2\right\rangle$ of $^{87}$Rb atoms simultaneously scanned over
different paths in a Raman Mach-Zehnder interferometer (MZI), the difference of
the free fall accelerations for the atom in the two hyperfine states is encoded
into the phase shift of the MZI, contributing a WEP test signal. The test
signal can be extracted out by reversing the direction of the effective wave
vector of the Raman laser to suppress direction-dependent disturbances. More
importantly, de-Broglie wavelength of cold atoms can be utilized to enhance the
test signal in our scheme, which helps to improve the upper bound of the WEP
test for atoms in different hyperfine states to $2.9\times10^{-11}$, about one
order of magnitude lower than the previous record.


  We present laboratory spectra of the $3p$--$3d$ transitions in Fe$^{14+}$ and
Fe$^{15+}$ excited with a mono-energetic electron beam. In the energy dependent
spectra obtained by sweeping the electron energy, resonant excitation is
confirmed as an intensity enhancement at specific electron energies. The
experimental results are compared with theoretical cross sections calculated
based on fully relativistic wave functions and the distorted-wave
approximation. Comparisons between the experimental and theoretical results
show good agreement for the resonance strength. A significant discrepancy is,
however, found for the non-resonant cross section in Fe$^{14+}$. %, which can
be considered as a fundamental cause of the line intensity ratio problem that
has often been found in both observatory and laboratory measurements. This
discrepancy is considered to be the fundamental cause of the previously
reported inconsistency of the model with the observed intensity ratio between
the $^3\!P_2$ -- $^3\!D_3$ and $^1\!P_1$ -- $^1\!D_2$ transitions.


  By imposing twisted boundary conditions on quark fields it is possible to
access components of momenta other than integer multiples of 2pi/L on a lattice
with spatial volume L^3. We use Chiral Perturbation Theory to study
finite-volume effects with twisted boundary conditions for quantities without
final-state interactions, such as meson masses, decay constants and
semileptonic form factors, and confirm that they remain exponentially small
with the volume. We show that this is also the case for "partially twisted"
boundary conditions, in which (some of) the valence quarks satisfy twisted
boundary conditions but the sea quarks satisfy periodic boundary conditions.
This observation implies that it is not necessary to generate new gluon
configurations for every choice of the twist angle, making the method much more
practicable. For K->pipi decays we show that the breaking of isospin symmetry
by the twisted boundary conditions implies that the amplitudes cannot be
determined in general (on this point we disagree with a recent claim).


  The work of Fisenko S. I., & Fisenko I. S. (2009). The old and new concepts
of physics, 6 (4), 495, shows the key fact of the existence of gravitational
radiation as a radiation of the same level as electromagnetic. The obtained
results strictly correspond to the framework of relativistic theory of
gravitation and quantum mechanics. The given work contributes into further
elaboration of the findings considering their application to dense
high-temperature plasma of multiple-charge ions. This is due to quantitative
character of electron gravitational emission spectrum such that amplification
of gravitational emission may take place only in multiple-charge ion
high-temperature plasma.


  Let $\gg$ be the Lie algebra of a compact Lie group and let $\theta$ be any
automorphism of $\gg$. Let $\gk$ denote the fixed point subalgebra
$\gg^\theta$. In this paper we present LiE programs that, for any finite
dimensional complex representation $\pi$ of $\gg$, give the explicit branching
$\pi|_\gk$ of $\pi$ on $\gk$. Cases of special interest include the cases where
$\theta$ has order 2 (corresponding to compact riemannian symmetric spaces
$G/K$), where $\theta$ has order 3 (corresponding to compact nearly--kaehler
homogeneous spaces $G/K$), where $\theta$ has order 5 (which include the
fascinating 5--symmetric space $E_8/A_4A_4$), and the cases where $\gk$ is the
centralizer of a toral subalgebra of $\gg$.


  We study the ground state of the doped Hubbard model on honeycomb lattice
with both nearest ($t$) and next-nearest neighboring hoppings ($t'$) in the
small doping and strongly interacting region. Previous study on the model
without $t'$ showed the ground state is a half-filled stripe. We employ density
matrix renormalization group and extrapolate the results with truncation errors
in the converged region. In the $t' < 0$ side, we find the half-filled stripe
phase at $t' = 0$ is stable against the frustration of $t'$ until a critical
point $-0.4 < t'_c < -0.3$, beyond which the ground state switches to
anti-ferromagnetic N$\acute e$el phase with charge modulation. With further
increase of $t'$ to $-0.7$, the ground state becomes paramagnetic. In the $t' >
0$ side, the half-filled stripe stretches to $t' \approx 0.7$. We don't find
obvious enhancement of pairing for the range of $t'$ studied. We study width-4
cylinders in this work but the results for spin, charge, and pairing
correlation agree qualitatively for periodic and anti-periodic boundary
conditions in the half-filled stripe and anti-ferromagnetic N$\acute e$el
phases, suggesting the results are likely to be representative for true
two-dimensional systems. The half-filled stripe to anti-ferromagnetic N$\acute
e$el phase transition can be realized on real materials or ultra-cold atom
platform.


  In a recent article, we constructed a hierarchy B_L of outer boundary
conditions for Einstein's field equations with the property that, for a
spherical outer boundary, it is perfectly absorbing for linearized
gravitational radiation up to a given angular momentum number L. In this
article, we generalize B_2 so that it can be applied to fairly general
foliations of spacetime by space-like hypersurfaces and general outer boundary
shapes and further, we improve B_2 in two steps: (i) we give a local boundary
condition C_2 which is perfectly absorbing including first order contributions
in 2M/R of curvature corrections for quadrupolar waves (where M is the mass of
the spacetime and R is a typical radius of the outer boundary) and which
significantly reduces spurious reflections due to backscatter, and (ii) we give
a non-local boundary condition D_2 which is exact when first order corrections
in 2M/R for both curvature and backscatter are considered, for quadrupolar
radiation.


  Euler wrote a formula expressing that l(n)/n is a completely multiplicative
function with sum 0 (a CMO function) , where l(n) is the completely
multiplicative function equal to -1 on the prime numbers (the Liouville
function). We extend this formula to Beurling generalized numbers, using a
result of Diamond. As an application we show how to construct a CMO function
carried by a set of integers whose counting function is of the form D x^a
(1+o(1) ) for any a between 0 and 1.


  The paper is motivated on the open problem of resolution of singularities in
positive characteristic. The aim is to present a form of induction which is
different from that used by Hironaka. In characteristic zero induction is
formulated by restriction to smooth hypersurfaces (hypersurfaces of maximal
contact). Our alternative approach, introduced here, replaces restrictions to
smooth sub-schemes by generic projections on smooth schemes of smaller
dimension. We also introduce a generalization of the discriminant, and our
result makes use of the elimination theory. In the case of fields of
characteristic zero, elimination gives exactly the same information as the form
of induction used by Hironaka.


  The structural and magnetic study of PrMn1-xFexO3(0 <= x <= 1) substitutional
orthorhombical system, was performed on polycrystalline (x <= 0.5) as well as
on the single crystalline (0.5 <= x <= 1) samples.


  Human video generation is a dynamic and rapidly evolving task that aims to
synthesize 2D human body video sequences with generative models given control
conditions such as text, audio, and pose. With the potential for wide-ranging
applications in film, gaming, and virtual communication, the ability to
generate natural and realistic human video is critical. Recent advancements in
generative models have laid a solid foundation for the growing interest in this
area. Despite the significant progress, the task of human video generation
remains challenging due to the consistency of characters, the complexity of
human motion, and difficulties in their relationship with the environment. This
survey provides a comprehensive review of the current state of human video
generation, marking, to the best of our knowledge, the first extensive
literature review in this domain. We start with an introduction to the
fundamentals of human video generation and the evolution of generative models
that have facilitated the field's growth. We then examine the main methods
employed for three key sub-tasks within human video generation: text-driven,
audio-driven, and pose-driven motion generation. These areas are explored
concerning the conditions that guide the generation process. Furthermore, we
offer a collection of the most commonly utilized datasets and the evaluation
metrics that are crucial in assessing the quality and realism of generated
videos. The survey concludes with a discussion of the current challenges in the
field and suggests possible directions for future research. The goal of this
survey is to offer the research community a clear and holistic view of the
advancements in human video generation, highlighting the milestones achieved
and the challenges that lie ahead.


  We derive the three-body quantization condition in a finite volume using an
effective field theory in the particle-dimer picture. Moreover, we consider the
extraction of physical observables from the lattice spectrum using the
quantization condition. To illustrate the general framework, we calculate the
volume-dependent three-particle spectrum in a simple model both below and above
the three-particle threshold. The relation to existing approaches is discussed
in detail.


  In this article we will describe an algorithm to constructively enumerate
non-isomorphic Union closed Sets and Moore sets. We confirm the number of
isomorphism classes of Union closed Sets and Moore sets on n<=6 elements
presented by other authors and give the number of isomorphism classes of Union
closed Sets and Moore sets on 7 elements. Due to the enormous growth of the
number of isomorphism classes it seems unlikely that constructive enumeration
for 8 or more elements will be possible in the foreseeable future.


  We consider ${\cal N}=1$ supersymmetric Born-Infeld actions that have a
second non-linear supersymmetry. We focus on the model proposed by Bagger and
Galperin and show that the breaking of the second supersymmetry is sourced by
the new Fayet-Iliopoulos D-term. Interpreting such an action as the effective
theory of a space-filling (anti) D3-brane leads to an expression for the new
Fayet-Iliopoulos parameter in terms of the brane tension and $\alpha'$.


  Autonomously trained agents that are supposed to play video games reasonably
well rely either on fast simulation speeds or heavy parallelization across
thousands of machines running concurrently. This work explores a third way that
is established in robotics, namely sim-to-real transfer, or if the game is
considered a simulation itself, sim-to-sim transfer. In the case of Rocket
League, we demonstrate that single behaviors of goalies and strikers can be
successfully learned using Deep Reinforcement Learning in the simulation
environment and transferred back to the original game. Although the implemented
training simulation is to some extent inaccurate, the goalkeeping agent saves
nearly 100% of its faced shots once transferred, while the striking agent
scores in about 75% of cases. Therefore, the trained agent is robust enough and
able to generalize to the target domain of Rocket League.


  Observations and modeling for the light curve (LC) and spectra of supernova
(SN) 2005bf are reported. This SN showed unique features: the LC had two
maxima, and declined rapidly after the second maximum, while the spectra showed
strengthening He lines whose velocity increased with time. The double-peaked LC
can be reproduced by a double-peaked $^{56}$Ni distribution, with most
$^{56}$Ni at low velocity and a small amount at high velocity. The rapid
post-maximum decline requires a large fraction of the $\gamma$-rays to escape
from the $^{56}$Ni-dominated region, possibly because of low-density ``holes''.
The presence of Balmer lines in the spectrum suggests that the He layer of the
progenitor was substantially intact. Increasing $\gamma$-ray deposition in the
He layer due to enhanced $\gamma$-ray escape from the $^{56}$Ni-dominated
region may explain both the delayed strengthening and the increasing velocity
of the He lines. The SN has massive ejecta ($\sim6-7\Msun$), normal kinetic
energy ($\sim 1.0-1.5\times 10^{51}$ ergs), high peak bolometric luminosity
($\sim 5\times 10^{42}$ erg s$^{-1}$) for an epoch as late as $\sim$ 40 days,
and a large $^{56}$Ni mass ($\sim0.32\Msun$). These properties, and the
presence of a small amount of H suggest that the progenitor was initially
massive (M$\sim 25-30 \Msun$) and had lost most of its H envelope, and was
possibly a WN star. The double-peaked $^{56}$Ni distribution suggests that the
explosion may have formed jets that did not reach the He layer. The properties
of SN 2005bf resemble those of the explosion of Cassiopeia A.


  Sparsely activated Mixture-of-Experts (SMoE) has shown promise to scale up
the learning capacity of neural networks, however, they have issues like (a)
High Memory Usage, due to duplication of the network layers into multiple
copies as experts; and (b) Redundancy in Experts, as common learning-based
routing policies suffer from representational collapse. Therefore, vanilla SMoE
models are memory inefficient and non-scalable, especially for
resource-constrained downstream scenarios. In this paper, we ask: Can we craft
a compact SMoE model by consolidating expert information? What is the best
recipe to merge multiple experts into fewer but more knowledgeable experts? Our
pilot investigation reveals that conventional model merging methods fail to be
effective in such expert merging for SMoE. The potential reasons are: (1)
redundant information overshadows critical experts; (2) appropriate neuron
permutation for each expert is missing to bring all of them in alignment. To
address this, we propose M-SMoE, which leverages routing statistics to guide
expert merging. Specifically, it starts with neuron permutation alignment for
experts; then, dominant experts and their "group members" are formed; lastly,
every expert group is merged into a single expert by utilizing each expert's
activation frequency as their weight for merging, thus diminishing the impact
of insignificant experts. Moreover, we observed that our proposed merging
promotes a low dimensionality in the merged expert's weight space, naturally
paving the way for additional compression. Hence, our final method, MC-SMoE
(i.e., Merge, then Compress SMoE), further decomposes the merged experts into
low-rank and structural sparse alternatives. Extensive experiments across 8
benchmarks validate the effectiveness of MC-SMoE. For instance, our MC-SMoE
achieves up to 80% memory and a 20% FLOPs reduction, with virtually no loss in
performance.


  The thermodynamical process of Joule-Thomson expansion is extended to the
lower-dimensional spacetimes by considering rotating, charged and charged
rotating BTZ black hole metrics. The Joule-Thomson coefficients, the inversion
curves and the isenthalps are found for all three cases. From the behavior of
inversion curves in the $T-P$ plane, it is observed that there exists only
minimum inversion temperatures for BTZ black holes. The relevant calculations
for rotating BTZ black holes are almost straightforward, while it is more
challenging to address when a charge parameter is added. In the case of charged
BTZ metrics, the black hole system can be considered in two possible
thermodynamical schemes and it is explicitly proved that the Joule-Thomson
expansion is present in a specific scheme (referred to as scheme II) in which
thermodynamic instabilities do not arise. The existence of Joule-Thomson
expansion in all three BTZ cases strongly indicates that these
lower-dimensional black hole spacetimes can be considered as interacting
statistical systems like their higher-dimensional cousins.


  A graph $G$ is 3-colorable if and only if it maps homomorphically to the
complete 3-vertex graph $K_3$. The last condition can be checked by a
$k$-consistency algorithm where the parameter $k$ has to be chosen large
enough, dependent on $G$. Let $W(G)$ denote the minimum $k$ sufficient for this
purpose. For a non-3-colorable graph $G$, $W(G)$ is equal to the minimum $k$
such that $G$ can be distinguished from $K_3$ in the $k$-variable
existential-positive first-order logic. We define the dynamic width of the
3-colorability problem as the function $W(n)=\max_G W(G)$, where the maximum is
taken over all non-3-colorable $G$ with $n$ vertices.
  The assumption $\mathrm{NP}\ne\mathrm{P}$ implies that $W(n)$ is unbounded.
Indeed, a lower bound $W(n)=\Omega(\log\log n/\log\log\log n)$ follows
unconditionally from the work of Nesetril and Zhu on bounded treewidth duality.
The Exponential Time Hypothesis implies a much stronger bound
$W(n)=\Omega(n/\log n)$ and indeed we unconditionally prove that
$W(n)=\Omega(n)$. In fact, an even stronger statement is true: A first-order
sentence distinguishing any 3-colorable graph on $n$ vertices from any
non-3-colorable graph on $n$ vertices must have $\Omega(n)$ variables.
  On the other hand, we observe that $W(G)\le 3\,\alpha(G)+1$ and $W(G)\le
n-\alpha(G)+1$ for every non-3-colorable graph $G$ with $n$ vertices, where
$\alpha(G)$ denotes the independence number of $G$. This implies that
$W(n)\le\frac34\,n+1$, improving on the trivial upper bound $W(n)\le n$.
  We also show that $W(G)>\frac1{16}\, g(G)$ for every non-3-colorable graph
$G$, where $g(G)$ denotes the girth of $G$.
  Finally, we consider the function $W(n)$ over planar graphs and prove that
$W(n)=\Theta(\sqrt n)$ in the case.


  Labeled datasets are essential for supervised machine learning. Various data
labeling tools have been built to collect labels in different usage scenarios.
However, developing labeling tools is time-consuming, costly, and
expertise-demanding on software development. In this paper, we propose a
conceptual framework for data labeling and OneLabeler based on the conceptual
framework to support easy building of labeling tools for diverse usage
scenarios. The framework consists of common modules and states in labeling
tools summarized through coding of existing tools. OneLabeler supports
configuration and composition of common software modules through visual
programming to build data labeling tools. A module can be a human, machine, or
mixed computation procedure in data labeling. We demonstrate the expressiveness
and utility of the system through ten example labeling tools built with
OneLabeler. A user study with developers provides evidence that OneLabeler
supports efficient building of diverse data labeling tools.


  M. Freedman and V. Krushkal introduced the notion of a "filling" link in a
3-manifold: a link $L$ is filling in $M$ if for any spine $G$ of $M$ disjoint
from $L$, $\pi_1(G)$ injects into $\pi_1(M \setminus L )$. Freedman and
Krushkal show that there exist links in the $3$-torus $T^3$ that satisfy a
weaker form of filling, but they leave open the question of whether $T^3$
contains an actual filling link. We answer this question affirmatively by
proving in fact that every closed, orientable 3-manifold $M$ with
$\operatorname{rank}(\pi_1(M)) = 3$ contains a filling link.


  In intelligent Internet of Things (IoT) systems, edge servers within a
network exchange information with their neighbors and collect data from sensors
to complete delivered tasks. In this paper, we propose a multiplayer
multi-armed bandit model for intelligent IoT systems to facilitate data
collection and incorporate fairness considerations. In our model, we establish
an effective communication protocol that helps servers cooperate with their
neighbors. Then we design a distributed cooperative bandit algorithm, DC-ULCB,
enabling servers to collaboratively select sensors to maximize data rates while
maintaining fairness in their choices. We conduct an analysis of the reward
regret and fairness regret of DC-ULCB, and prove that both regrets have
logarithmic instance-dependent upper bounds. Additionally, through extensive
simulations, we validate that DC-ULCB outperforms existing algorithms in
maximizing reward and ensuring fairness.


  The Encoder-Decoder architecture is a main stream deep learning model for
biomedical image segmentation. The encoder fully compresses the input and
generates encoded features, and the decoder then produces dense predictions
using encoded features. However, decoders are still under-explored in such
architectures. In this paper, we comprehensively study the state-of-the-art
Encoder-Decoder architectures, and propose a new universal decoder, called
cascade decoder, to improve semantic segmentation accuracy. Our cascade decoder
can be embedded into existing networks and trained altogether in an end-to-end
fashion. The cascade decoder structure aims to conduct more effective decoding
of hierarchically encoded features and is more compatible with common encoders
than the known decoders. We replace the decoders of state-of-the-art models
with our cascade decoder for several challenging biomedical image segmentation
tasks, and the considerable improvements achieved demonstrate the efficacy of
our new decoding method.


  A Josephson junction is made of two superconductors sandwiching an insulator,
and a Josephson vortex is a magnetic vortex (flux tube) absorbed into the
Josephson junction, whose dynamics can be described by the sine-Gordon
equation. In a field theory framework, a flexible Josephson junction was
proposed, in which the Josephson junction is represented by a domain wall
separating two condensations and a Josephson vortex is a sine-Gordon soliton in
the domain wall effective theory. In this paper, we propose a Josephson
junction of non-Abelian color superconductors, that is described by a
non-Abelian domain wall, and show that a non-Abelian vortex (color magnetic
flux tube) absorbed into it is a non-Abelian Josephson vortex represented as a
non-Abelian sine-Gordon soliton in the domain wall effective theory, that is
the $U(N)$ principal chiral model.


  Trajectory representation learning on a network enhances our understanding of
vehicular traffic patterns and benefits numerous downstream applications.
Existing approaches using classic machine learning or deep learning embed
trajectories as dense vectors, which lack interpretability and are inefficient
to store and analyze in downstream tasks. In this paper, an explainable
trajectory representation learning framework through dictionary learning is
proposed. Given a collection of trajectories on a network, it extracts a
compact dictionary of commonly used subpaths called "pathlets", which optimally
reconstruct each trajectory by simple concatenations. The resulting
representation is naturally sparse and encodes strong spatial semantics.
Theoretical analysis of our proposed algorithm is conducted to provide a
probabilistic bound on the estimation error of the optimal dictionary. A
hierarchical dictionary learning scheme is also proposed to ensure the
algorithm's scalability on large networks, leading to a multi-scale trajectory
representation. Our framework is evaluated on two large-scale real-world taxi
datasets. Compared to previous work, the dictionary learned by our method is
more compact and has better reconstruction rate for new trajectories. We also
demonstrate the promising performance of this method in downstream tasks
including trip time prediction task and data compression.


  Two giant flares were observed on 5 March 1979 and 27 August 1998 from the
soft gamma-ray repeaters SGR 0526-66 and SGR 1900+14, respectively. The
striking similarity between these remarkable bursts strongly implies a common
nature. We show that the light curves of the giant bursts may be easily
explained in the model where the burst radiation is produced by the bare quark
surface of a strange star heated, for example, by impact of a massive
comet-like object.


  Exponential family Random Graph Models (ERGMs) can be viewed as expressing a
probability distribution on graphs arising from the action of competing social
forces that make ties more or less likely, depending on the state of the rest
of the graph. Such forces often lead to a complex pattern of dependence among
edges, with non-trivial large-scale structures emerging from relatively simple
local mechanisms. While this provides a powerful tool for probing macro-micro
connections, much remains to be understood about how local forces shape global
outcomes. One simple question of this type is that of the conditions needed for
social forces to stabilize a particular structure. We refer to this property as
local stability and seek a general means of identifying the set of parameters
under which a target graph is locally stable with respect to a set of
alternatives. Here, we provide a complete characterization of the region of the
parameter space inducing local stability, showing it to be the interior of a
convex cone whose faces can be derived from the change-scores of the sufficient
statistics vis-a-vis the alternative structures. As we show, local stability is
a necessary but not sufficient condition for more general notions of stability,
the latter of which can be explored more efficiently by using the ``stable
cone'' within the parameter space as a starting point. In addition, we show how
local stability can be used to determine whether a fitted model implies that an
observed structure would be expected to arise primarily from the action of
social forces, versus by merit of the model permitting a large number of high
probability structures, of which the observed structure is one. We also use our
approach to identify the dyads within a given structure that are the least
stable, and hence predicted to have the highest probability of changing over
time.


  Shock waves driven by the release of energy at the center of a cold ideal gas
sphere of initial density rho\propto r^{-omega} approach a self-similar (SLS)
behavior, with velocity \dot{R}\propto R^delta, as R->\infty. For omega>3 the
solutions are of the second-type, i.e., delta is determined by the requirement
that the flow should include a sonic point. No solution satisfying this
requirement exists, however, in the 3\leq omega\leq omega_{g}(gamma) ``gap''
(\omega_{g}=3.26 for adiabatic index gamma=5/3). We argue that second-type
solutions should not be required in general to include a sonic point. Rather,
it is sufficient to require the existence of a characteristic line r_c(t), such
that the energy in the region r_c(t)<r<R approaches a constant as R->\infty,
and an asymptotic solution given by the SLS solution at r_c(t)<r<R and
deviating from it at r<r_c may be constructed. The two requirements coincide
for omega>omega_g and the latter identifies delta=0 solutions as the asymptotic
solutions for 3\leq omega\leq omega_{g} (as suggested by Gruzinov03). In these
solutions, r_c is a C_0 characteristic. It is difficult to check, using
numerical solutions of the hydrodynamic equations, whether the flow indeed
approaches a delta=0 SLS behavior as R->\infty, due to the slow convergence to
SLS for omega~3. We show that in this case the flow may be described by a
modified SLS solution, d\ln\dot{R}/d\ln R=delta with slowly varying delta(R),
eta\equiv d delta/d\ln R<<1, and spatial profiles given by a sum of the SLS
solution corresponding to the instantaneous value of delta and a SLS correction
linear in eta. The modified SLS solutions provide an excellent approximation to
numerical solutions obtained for omega~3 at large R, with delta->0 (and
eta\neq0) for 3\leq omega\leq omega_{g}. (abridged)


  We propose a theoretical model to describe the strain-induced linear
electro-optic (Pockels) effect in centro-symmetric crystals. The general
formulation is presented and the specific case of the strained silicon is
investigated in detail because of its attractive properties for integrated
optics. The outcome of this analysis is a linear relation between the second
order susceptibility tensor and the strain gradient tensor, depending
generically on fifteen coefficients. The proposed model greatly simplifies the
description of the electro-optic effect in strained silicon waveguides,
providing a powerful and effective tool for design and optimization of optical
devices.


  We present a new technique for removing twin image in in-line digital Fourier
holography using a combination of Fourier transformations. Instead of recording
only a Fourier transform hologram of the object, we propose to record a
combined Fourier transform hologram by simultaneously recording the hologram of
the Fourier transform and the inverse Fourier transform of the object with
suitable weighting coefficients. Twin image is eliminated by appropriate
inverse combined Fourier transformation and proper choice of the weighting
coefficients. An optical configuration is presented for recording combined
Fourier transform holograms. Simulations demonstrate the feasibility of twin
image elimination. The hologram reconstruction is sensitive to phase
aberrations of the object, thereby opening a way for holographic phase sensing.


  In order to understand the nature of the lenses that generate microlensing
events, one would like to measure their mass, distance, and velocity.
Unfortunately, current microlensing experiments measure only one parameter of
the events, the characteristic timescale, which is a combination of the
underlying physical parameters. Other methods are required to extract
additional information. Parallax measurements using a satellite in an
Earth-like orbit yield the projected velocity of the lens: ${\bf{\tilde v}}
={\bf{v}}/(1-z)$, where ${\bf{v}}$ is the transverse velocity (speed and
direction) of the lens relative to the Earth-source line of sight, and $z$ is
the ratio of the distances to the lens and the source. A measurement of
${\bf{\tilde v}}$ could distinguish between lenses belonging to the bulge and
disk populations. We show that for photometric precisions of 1% to 2%, it is
possible to measure the projected speed, $\tilde v$, to an accuracy of $\leq
10%$ for over 70% of disk lenses and over 60% of bulge lenses. For measuring
the projected velocity ${\bf{\tilde v}}$, the percentages are 40% and {30%},
respectively. We find lines of sight $> 2^{\circ}$ away from the ecliptic are
preferable, and an Earth-satellite separation in the range $0.7 {\rm{AU}} -
1.9{\rm{AU}}$ is optimal. The requirements of the satellite for measuring the
projected velocities of events towards the bulge are similar to those for
measurements toward the LMC.


  We study D-branes in topologically twisted N=2 minimal models using the
Landau-Ginzburg realization. In the cases of A and D-type minimal models we
provide what we believe is an exhaustive list of topological branes and compute
the corresponding boundary OPE algebras as well as all disk correlators. We
also construct examples of topological branes in E-type minimal models. We
compare our results with the boundary state formalism, where possible, and find
agreement.


  Recently a prescription to compute the four-dimensional N = 2 superconformal
index in the presence of certain BPS surface defects has been given. These
surface defects are labelled by symmetric representations of SU(N). In the
present paper we give a prescription to compute the superconformal index in the
presence of surface defects labelled by arbitrary representations of SU(N).
Furthermore, we extend the dictionary between the N = 2 superconformal
Schur-index and correlators of q-deformed Yang-Mills to incorporate such
surface defects.


  We present $S^7$-algebras as generalized Kac-Moody algebras. A number of
free-field representations is found. We construct the octonionic projective
spaces ${\O}P^N$.


  Event extraction in commodity news is a less researched area as compared to
generic event extraction. However, accurate event extraction from commodity
news is useful in abroad range of applications such as under-standing event
chains and learning event-event relations, which can then be used for commodity
price prediction. The events found in commodity news exhibit characteristics
different from generic events, hence posing a unique challenge in event
extraction using existing methods. This paper proposes an effective use of
Graph Convolutional Networks(GCN) with a pruned dependency parse tree, termed
contextual sub-tree, for better event ex-traction in commodity news. The event
ex-traction model is trained using feature embed-dings from ComBERT, a
BERT-based masked language model that was produced through domain-adaptive
pre-training on a commodity news corpus. Experimental results show the
efficiency of the proposed solution, which out-performs existing methods with
F1 scores as high as 0.90. Furthermore, our pre-trained language model
outperforms GloVe by 23%, and BERT and RoBERTa by 7% in terms of argument roles
classification. For the goal of re-producibility, the code and trained models
are made publicly available1.


  Grant-free (GF) transmission holds promise in terms of low latency
communication by directly transmitting messages without waiting for any
permissions. However, collision situations may frequently happen when limited
spectrum is occupied by numerous GF users. The non-orthogonal multiple access
(NOMA) technique can be a promising solution to achieve massive connectivity
and fewer collisions for GF transmission by multiplexing users in power domain.
We utilize a semi-grant-free (semi-GF) NOMA scheme for enhancing network
connectivity and spectral efficiency by enabling grant-based (GB) and GF users
to share the same spectrum resources. With the aid of semi-GF protocols, uplink
NOMA networks are investigated by invoking stochastic geometry techniques. We
propose a novel \textit{dynamic protocol} to interpret which part of the GF
users are paired in NOMA transmissions via transmitting various channel quality
thresholds by an added handshake. We utilize open-loop protocol with a fixed
average threshold as the benchmark to investigate performance improvement. It
is observed that dynamic protocol provides more accurate channel quality
thresholds than open-loop protocol, thereby the interference from the GF users
is reduced to a large extent. We analyze the outage performance and diversity
gains under two protocols. Numerical results demonstrate that dynamic protocol
is capable of enhancing the outage performance than open-loop protocol.


  We give a $n^{O(\log n)}$-time ($n$ is the input size) blackbox polynomial
identity testing algorithm for unknown-order read-once oblivious algebraic
branching programs (ROABP). The best result known for this class was
$n^{O(\log^2 n)}$ due to Forbes-Saptharishi-Shpilka (STOC 2014), and that too
only for multilinear ROABP. We get rid of their exponential dependence on the
individual degree. With this, we match the time-complexity for the unknown
order ROABP with the known order ROABP (due to Forbes-Shpilka (FOCS 2013)) and
also with the depth-$3$ set-multilinear circuits (due to Agrawal-Saha-Saxena
(STOC 2013)). Our proof is simpler and involves a new technique called basis
isolation.
  The depth-$3$ model has recently gained much importance, as it has become a
stepping-stone to understanding general arithmetic circuits. Its restriction to
multilinearity has known exponential lower bounds but no nontrivial blackbox
identity tests. In this paper, we take a step towards designing such
hitting-sets. We give the first subexponential whitebox PIT for the sum of
constantly many set-multilinear depth-$3$ circuits. To achieve this, we define
notions of distance and base sets. Distance, for a multilinear depth-$3$
circuit, measures how far are the partitions from a mere refinement. We design
a hitting-set in time $n^{O(d \log n)}$ for $d$-distance. Further, we give an
extension of our result to models where the distance is large but it is small
when restricted to certain base sets (of variables).
  We also explore a new model of ROABP where the factor-matrices are invertible
(called invertible-factor ROABP). We design a hitting-set in time
poly($n^{w^2}$) for width-$w$ invertible-factor ROABP. Further, we could do
without the invertibility restriction when $w=2$. Previously, the best result
for width-$2$ ROABP was quasi-polynomial time (Forbes-Saptharishi-Shpilka, STOC
2014).


  Transport phenomena are ubiquitous in nature and known to be important for
various scientific domains. Examples can be found in physics, electrochemistry,
heterogeneous catalysis, physiology, etc. To obtain new information about
diffusive or Laplacian transport towards a semi-permeable or resistive
interface, one can study the random trajectories of diffusing particles
modeled, in a first approximation, by the partially reflected Brownian motion.
This stochastic process turns out to be a convenient mathematical foundation
for discrete, semi-continuous and continuous theoretical descriptions of
diffusive transport.
  This paper presents an overview of these topics with a special emphasis on
the close relation between stochastic processes with partial reflections and
Laplacian transport phenomena. We give selected examples of these phenomena
followed by a brief introduction to the partially reflected Brownian motion and
related probabilistic topics (e.g., local time process and spread harmonic
measure). A particular attention is paid to the use of the Dirichlet-to-Neumann
operator. Some practical consequences and further perspectives are discussed.


  This paper presents the foundation for a decomposition theory for Boolean
networks, a type of discrete dynamical system that has found a wide range of
applications in the life sciences, engineering, and physics. Given a Boolean
network satisfying certain conditions, there is a unique collection of
subnetworks so that the network can be reconstructed from these subnetworks by
an extension operation. The main result of the paper is that this structural
decomposition induces a corresponding decomposition of the network dynamics.
The theory is motivated by the search for a mathematical framework to formalize
the hypothesis that biological systems are modular, widely accepted in the life
sciences, but not well-defined and well-characterized. As an example of how
dynamic modularity could be used for the efficient identification of phenotype
control, the control strategies for the network can be found by identifying
controls in its modules, one at a time.


  Optical wireless communication (OWC) is a promising technology that has the
potential to provide Tb/s aggregate rates. In this paper, interference
management is studied in a Laser-based optical wireless network where
vertical-cavity surface-emitting (VCSEL) lasers are used for data transmission.
In particular, rate splitting (RS) and hierarchical rate splitting (HRS) are
proposed to align multi-user interference, while maximizing the multiplexing
gain of the network. Basically, RS serves multiple users simultaneously by
splitting a message of a user into common and private messages, each message
with a certain level of power, while on the other side users decode their
messages following a specific methodology. The performance of the conventional
RS scheme is limited in high density wireless networks. Therefore, the HRS
scheme is developed aiming to achieve high rates where users are divided into
multiple groups, and a new message called outer common message is used for
managing inter-group interference. We formulate an optimization problem that
addresses power allocation among the messages of the HRS scheme to further
enhance the performance of the network. The results show that the proposed
approach provides high achievable rates compared with the conventional RS and
HRS schemes in different scenarios.


  This work is concerned with the minimization of quantum entropies under local
constraints of density, current, and energy. The problem arises in the work of
Degond and Ringhofer about the derivation of quantum hydrodynamical models from
first principles, and is an adaptation to the quantum setting of the moment
closure strategy by entropy minimization encountered in kinetic equations. The
main mathematical difficulty is the lack of compactness needed to recover the
energy constraint. We circumvent this issue by a monotonicity argument
involving energy, temperature and entropy, that is inspired by some
thermodynamical considerations.


  Cloud computing is a technology that has become increasingly popular over the
past decade within several enterprises. This popularity can be attributed to
its benefits, including lower operating costs, improved computational
capabilities, increased flexibility and on-demand storage space. As a result,
many enterprises are already in various Cloud Computing (CC) adoption and
implementation stages. This study investigates the decision criteria used by
large enterprises in South Africa (SA) for the adoption of cloud technology.
The majority of large enterprises have comprehensive resources, resulting in
established Information Technology (IT) systems and infrastructure set up
within their organizations. Though this is the case, the adoption of CC by
large enterprises has been on the rise. This may not be a surprise as CC
literature points out to benefits and influencers of CC adoption. However, the
decision criteria used by large enterprises in SA in adopting CC are lacking in
the literature reviewed. The study followed an inductive approach making use of
qualitative methods. Findings revealed that large enterprises do not make use
of a formalized or standardized decision criteria. However, operational cost,
enterprise strategic intent and product efficiency formed key criteria for
adopting CC. In addition, security, cloud service provider adoption frameworks
and data sovereignty were the key criteria used to select a CC service
provider. The research will contribute towards CC technology adoption
literature, particularly for developing countries.


  Background: Generalized polarizabilities (GPs) are important observables to
describe the nucleon structure, and measurements of these observables are still
scarce. Purpose: This paper presents details of a virtual Compton scattering
(VCS) experiment, performed at the A1 setup at the Mainz Microtron by studying
the $e p \to e p \gamma$ reaction. The article focuses on selected aspects of
the analysis. Method: The experiment extracted the $P_{LL} -P_{TT} / \epsilon$
and $P_{LT}$ structure functions, as well as the electric and magnetic GPs of
the proton, at three new values of the four-momentum transfer squared $Q^2$:
0.10, 0.20 and 0.45 GeV$^2$. Results: We emphasize the importance of the
calibration of experimental parameters. The behavior of the measured $e p \to e
p \gamma$ cross section is presented and compared to the theory. A detailed
investigation of the polarizability fits reveals part of their complexity, in
connection with the higher-order terms of the low-energy expansion.
Conclusions: The presented aspects are elements which contribute to minimize
the systematic uncertainties and improve the precision of the physics results.


  Non-parallel voice conversion (VC) is typically achieved using lossy
representations of the source speech. However, ensuring only speaker identity
information is dropped whilst all other information from the source speech is
retained is a large challenge. This is particularly challenging in the scenario
where at inference-time we have no knowledge of the text being read, i.e.,
text-free VC. To mitigate this, we investigate information-preserving VC
approaches.
  Normalising flows have gained attention for text-to-speech synthesis, however
have been under-explored for VC. Flows utilize invertible functions to learn
the likelihood of the data, thus provide a lossless encoding of speech. We
investigate normalising flows for VC in both text-conditioned and text-free
scenarios. Furthermore, for text-free VC we compare pre-trained and
jointly-learnt priors. Flow-based VC evaluations show no degradation between
text-free and text-conditioned VC, resulting in improvements over the
state-of-the-art. Also, joint-training of the prior is found to negatively
impact text-free VC quality.


  Let $A$ be a regular domain containing a field $K$ of characteristic zero,
$G$ be a finite subgroup of the group of automorphisms of $A$ and $B=A^G$ be
the ring of invariants of $G$. Let $S= A[X_1,\ldots, X_m]$ and $R= B[X_1,
\ldots, X_m]$ be standard graded with $\ deg \ A=0$, $\ deg \ B=0$ and $\ deg \
X_i=1$ for all $i$. Extend the action of $G$ on $A$ to $S$ by fixing $X_i$.
Note $S^G=R$. Let $I$ be an arbitrary homogeneous ideal in $R$. The main goal
of this paper is to establish a comparative study of graded components of local
cohomology modules $H_I^i(R)$ that would be analogs to those proven in a
previous paper of the first author for $H_J^i(S)$ where $J$ is an arbitrary
homogeneous ideal in $S$.


  This paper firstly considers the research problem of fairness in
collaborative deep learning, while ensuring privacy. A novel reputation system
is proposed through digital tokens and local credibility to ensure fairness, in
combination with differential privacy to guarantee privacy. In particular, we
build a fair and differentially private decentralised deep learning framework
called FDPDDL, which enables parties to derive more accurate local models in a
fair and private manner by using our developed two-stage scheme: during the
initialisation stage, artificial samples generated by Differentially Private
Generative Adversarial Network (DPGAN) are used to mutually benchmark the local
credibility of each party and generate initial tokens; during the update stage,
Differentially Private SGD (DPSGD) is used to facilitate collaborative
privacy-preserving deep learning, and local credibility and tokens of each
party are updated according to the quality and quantity of individually
released gradients. Experimental results on benchmark datasets under three
realistic settings demonstrate that FDPDDL achieves high fairness, yields
comparable accuracy to the centralised and distributed frameworks, and delivers
better accuracy than the standalone framework.


  Support Vector Machines (SVM) with $\ell_1$ penalty became a standard tool in
analysis of highdimensional classification problems with sparsity constraints
in many applications including bioinformatics and signal processing. Although
SVM have been studied intensively in the literature, this paper has to our
knowledge first non-asymptotic results on the performance of $\ell_1$-SVM in
identification of sparse classifiers. We show that a $d$-dimensional $s$-sparse
classification vector can be (with high probability) well approximated from
only $O(s\log(d))$ Gaussian trials. The methods used in the proof include
concentration of measure and probability in Banach spaces.


  A new experiment is described to detect a permanent electric dipole moment of
the proton with a sensitivity of $10^{-29}e\cdot$cm by using polarized "magic"
momentum $0.7$~GeV/c protons in an all-electric storage ring. Systematic errors
relevant to the experiment are discussed and techniques to address them are
presented. The measurement is sensitive to new physics beyond the Standard
Model at the scale of 3000~TeV.


  We study nonlinear modes in subwavelength slot waveguides created by a
nonlinear dielectric slab sandwiched between two metals. We present the
dispersion diagrams of the families of nonlinear plasmonic modes and reveal
that the symmetric mode undergoes the symmetry-breaking bifurcation with the
energy primarily localized near one of the interfaces. We also find that the
antisymmetric mode may split into two brunches giving birth to two families of
nonlinear antisymmetric modes.


  This paper studies integer solutions to the ABC equation A+B+C=0 in which
none of A, B, C has a large prime factor. Set H(A,B, C)= max(|A|,|B|,|C|) and
set the smoothness S(A, B, C) to be the largest prime factor of ABC. We
consider primitive solutions (gcd(A, B, C)=1) having smoothness no larger than
a fixed power p of log H. Assuming the abc Conjecture we show that there are
finitely many solutions if p<1. We discuss a conditional result, showing that
the Generalized Riemann Hypothesis (GRH) implies there are infinitely many
primitive solutions when p>8. We sketch some details of the proof of the latter
result.


  Via molecular dynamics simulations, we unveil the hysteretic nature of the
jamming transition of soft repulsive frictionless spheres, as it occurs varying
the volume fraction or the shear stress. In a given range of control parameters
the system may be found both in a flowing and in an jammed state, depending on
the preparation protocol. The hysteresis is due to an underlying energy
landscape with many minima, as explained by a simple model, and disappears in
the presence of strong viscous forces and in the small $\sigma$ limit. In this
limit, structural quantities are continuous at the transition, while the
asymptotic values of two time quantities such as the self-intermediate
scattering function are discontinuous, giving to the jamming transition a mixed
first-order second-order character close to that found at the glass transition
of thermal systems.


  We present electrical transport measurements of a van-der-Waals
heterostructure consisting of a graphene nanoribbon separated by a thin boron
nitride layer from a micron-sized graphene sheet. The interplay between the two
layers is discussed in terms of screening or, alternatively, quantum
capacitance. The ribbon can be tuned into the transport gap by applying gate
voltages. Multiple sites of localized charge leading to Coulomb blockade are
observed in agreement with previous experiments. Due to the strong capacitive
coupling between the ribbon and the graphene top layer sheet, the evolution of
the Coulomb blockade peaks in gate voltages can be used to obtain the local
density of states and therefore the quantum capacitance of the graphene top
layer. Spatially varying density and doping are found which are attributed to a
spatial variation of the dielectric due to fabrication imperfections.


  We prove new strong converse results in a variety of group testing settings,
generalizing a result of Baldassini, Johnson and Aldridge. These results are
proved by two distinct approaches, corresponding to the non-adaptive and
adaptive cases. In the non-adaptive case, we mimic the hypothesis testing
argument introduced in the finite blocklength channel coding regime by
Polyanskiy, Poor and Verd\'{u}. In the adaptive case, we combine a formulation
based on directed information theory with ideas of Kemperman, Kesten and
Wolfowitz from the problem of channel coding with feedback. In both cases, we
prove results which are valid for finite sized problems, and imply capacity
results in the asymptotic regime. These results are illustrated graphically for
a range of models.


  Software teams are increasingly adopting different tools and communication
channels to aid the software collaborative development model and coordinate
tasks. Among such resources, Programming Community-based Question Answering
(PCQA) forums have become widely used by developers. Such environments enable
developers to get and share technical information. Interested in supporting the
development and management of Open Source Software (OSS) projects, GitHub
announced GitHub Discussions - a native forum to facilitate collaborative
discussions between users and members of communities hosted on the platform. As
GitHub Discussions resembles PCQA forums, it faces challenges similar to those
faced by such environments, which include the occurrence of related discussions
(duplicates or near-duplicated posts). While duplicate posts have the same
content - and may be exact copies - near-duplicates share similar topics and
information. Both can introduce noise to the platform and compromise project
knowledge sharing. In this paper, we address the problem of detecting related
posts in GitHub Discussions. To do so, we propose an approach based on a
Sentence-BERT pre-trained model: the RD-Detector. We evaluated RD-Detector
using data from different OSS communities. OSS maintainers and Software
Engineering (SE) researchers manually evaluated the RD-Detector results, which
achieved 75% to 100% in terms of precision. In addition, maintainers pointed
out practical applications of the approach, such as merging the discussions'
threads and making discussions as comments on one another. OSS maintainers can
benefit from RD-Detector to address the labor-intensive task of manually
detecting related discussions and answering the same question multiple times.


  The class of Basic Feasible Functionals BFF is the second-order counterpart
of the class of first-order functions computable in polynomial time. We present
several implicit characterizations of BFF based on a typed programming language
of terms. These terms may perform calls to non-recursive imperative procedures.
The type discipline has two layers: the terms follow a standard simply-typed
discipline and the procedures follow a standard tier-based type discipline. BFF
consists exactly of the second-order functionals that are computed by typable
and terminating programs. The completeness of this characterization
surprisingly still holds in the absence of lambda-abstraction. Moreover, the
termination requirement can be specified as a completeness-preserving instance,
which can be decided in time quadratic in the size of the program. As typing is
decidable in polynomial time, we obtain the first tractable (i.e., decidable in
polynomial time), sound, complete, and implicit characterization of BFF, thus
solving a problem opened for more than 20 years.


  Some variants of the (block) Gauss--Seidel iteration for the solution of
linear systems with $M$-matrices in (block) Hessenberg form are discussed.
  Comparison results for the asymptotic convergence rate of some regular
splittings are derived: in particular, we prove that for a lower-Hessenberg
M-matrix $\rho(P_{GS})\geq \rho(P_S)\geq \rho(P_{AGS})$, where $P_{GS}, P_S,
P_{AGS}$ are the iteration matrices of the Gauss--Seidel, staircase, and
anti-Gauss--Seidel method. This is a result that does not seem to follow from
classical comparison results, as these splittings are not directly comparable.
It is shown that the concept of stair partitioning provides a
  powerful tool for the design of new variants
  that are suited for parallel computation.


  We consider the application of feedback control strategies with point
actuators to stabilise desired interface shapes. We take a multidimensional
Kuramoto--Sivashinsky equation as a test case; this equation arises in the
study of thin liquid films, exhibiting a wide range of dynamics in different
parameter regimes, including unbounded growth and full spatiotemporal chaos. In
the case of limited observability, we utilise a proportional control strategy
where forcing at a point depends only on the local observation. We find that
point-actuated controls may inhibit unbounded growth of a solution, if they are
sufficient in number and in strength, and can exponentially stabilise the
desired state. We investigate actuator arrangements, and find that the
equidistant case is optimal, with heavy penalties for poorly arranged
actuators. We additionally consider the problem of synchronising two chaotic
solutions using proportional controls. In the case when the full interface is
observable, we construct feedback gain matrices using the linearised dynamics.
Such controls improve on the proportional case, and are applied to stabilise
non-trivial steady and travelling wave solutions.


  While users tend to perceive instructional videos as an experience rather
than a lesson with a set of instructions, instructional videos are more
effective and appealing than textual user manuals and eliminate the ambiguity
in text-based descriptions. However, most software vendors only offer document
manuals that describe how to install and use their software, leading burden for
non-professionals to comprehend the instructions. In this paper, we present a
framework called M2V to generate instructional videos automatically based on
the provided instructions and images in user manuals. M2V is a two-step
framework. First, an action sequence is extracted from the given user manual
via natural language processing and computer vision techniques. Second, M2V
operates the software sequentially based on the extracted actions; meanwhile,
the operation procedure is recorded into an instructional video. We evaluate
the usability of automatically generated instructional videos via user studies
and an online survey. The evaluation results show, with our toolkit, the
generated instructional videos can better assist non-professional end users
with the software operations. Moreover, more than 85% of survey participants
prefer to use the instructional videos rather than the original user manuals.


  As the technology is advancing, audio recognition in machine learning is
improved as well. Research in audio recognition has traditionally focused on
speech. Living creatures (especially the small ones) are part of the whole
ecosystem, monitoring as well as maintaining them are important tasks. Species
such as animals and birds are tending to change their activities as well as
their habitats due to the adverse effects on the environment or due to other
natural or man-made calamities. For those in far deserted areas, we will not
have any idea about their existence until we can continuously monitor them.
Continuous monitoring will take a lot of hard work and labor. If there is no
continuous monitoring, then there might be instances where endangered species
may encounter dangerous situations. The best way to monitor those species are
through audio recognition. Classifying sound can be a difficult task even for
humans. Powerful audio signals and their processing techniques make it possible
to detect audio of various species. There might be many ways wherein audio
recognition can be done. We can train machines either by pre-recorded audio
files or by recording them live and detecting them. The audio of species can be
detected by removing all the background noise and echoes. Smallest sound is
considered as a syllable. Extracting various syllables is the process we are
focusing on which is known as audio recognition in terms of Machine Learning
(ML).


  In this paper, we study the deformation of the n-dimensional strictly convex
hypersurface in $\mathbb R^{n+1}$ whose speed at a point on the hypersurface is
proportional to $\alpha$-power of positive part of Gauss Curvature. For
$\frac{1}{n}<\alpha \leq 1$, we prove that there exist the strictly convex
smooth solutions if the initial surface is strictly convex and smooth and the
solution hypersurfaces converge to a point. We also show the asymptotic
behavior of the rescaled hypersurfaces, in other words, the rescaled manifold
converges to a strictly convex smooth manifold. Moreover, there exists a
subsequence whose the limit satisfies a certain equation.


  Disparity by Block Matching stereo is usually used in applications with
limited computational power in order to get depth estimates. However, the
research on simple stereo methods has been lesser than the energy based
counterparts which promise a better quality depth map with more potential for
future improvements. Semi-global-matching (SGM) methods offer good performance
and easy implementation but suffer from the problem of very high memory
footprint because it's working on the full disparity space image. On the other
hand, Block matching stereo needs much less memory. In this paper, we introduce
a novel multi-scale-hierarchical block-matching approach using a pyramidal
variant of depth and cost functions which drastically improves the results of
standard block matching stereo techniques while preserving the low memory
footprint and further reducing the complexity of standard block matching. We
tested our new multi block matching scheme on the Middlebury stereo benchmark.
For the Middlebury benchmark we get results that are only slightly worse than
state of the art SGM implementations.


  We present a dynamical mean field theory study of the valence transition
($f^{14} \to f^{13}$) in elemental, metallic Yb under pressure. Our
calculations reproduce the observed valence transition as reflected in the
volume dependence of the $4f$ occupation. The transition is accelerated by
heating, and suggests quasiparticle or Kondo-like structure in the spectra of
the trivalent end state, consistent with the early lanthanides. Results for the
local charge fluctuations and susceptibility, however, show novel signatures
uniquely associated with the valence transition itself, indicating that Yb is a
fluctuating valence material in contrast to the intermediate valence behavior
seen in the early trivalent lanthanides Ce, Pr, and Nd.


  We extend our previous result on the nonlinear Klein-Gordon equation to the
nonlinear Schrodinger equation with the focusing cubic nonlinearity in three
dimensions, for radial data of energy at most slightly above that of the ground
state. We prove that the initial data set splits into nine nonempty, pairwise
disjoint regions which are characterized by the distinct behaviors of the
solution for large time: blow-up, scattering to 0, or scattering to the family
of ground states generated by the phase and scaling freedom. Solutions of this
latter type form a smooth center-stable manifold, which contains the ground
states and separates the phase space locally into two connected regions
exhibiting blow-up and scattering to 0, respectively. The special solutions
found by Duyckaerts and Roudenko appear here as the unique one-dimensional
unstable/stable manifolds emanating from the ground states. In analogy with the
Klein-Gordon case, the proof combines the hyperbolic dynamics near the ground
states with the variational structure away from them. The main technical
ingredient in the proof is a "one-pass" theorem which precludes "almost
homoclinic orbits", i.e., those solutions starting in, then moving away from,
and finally returning to, a small neighborhood of the ground states. The main
new difficulty compared with the Klein-Gordon case is the lack of finite
propagation speed. We need the radial Sobolev inequality for the error estimate
in the virial argument. Another major difference from the Klein-Gordon case is
the need to control two modulation parameters.


  Context. The detection of Earth-like planets with the radial-velocity (RV)
method is extremely challenging today due to the presence of non-Doppler
signatures such as stellar activity and instrumental signals that mimic and
hide the signals of exoplanets. In a previous paper, we presented the YARARA
pipeline, which implements corrections for telluric absorption, stellar
activity and instrumental systematics at the spectral level, then extracts
line-by-line (LBL) RVs with significantly better precision than standard
pipelines. Aims. In this paper, we demonstrate that further gains in RVs
precision can be achieved by performing Principal Component Analysis (PCA)
decomposition on the LBL RVs. Methods. The mean-insensitive nature of PCA means
that it is unaffected by true Doppler shifts, and thus can be used to isolate
and correct nuisance signals other than planets. Results. We analysed the data
of 20 intensively observed HARPS targets by applying our PCA approach on the
LBL RVs obtained by YARARA. The first principal components show similarities
across most of the stars and correspond to newly identified instrumental
systematics, which we can now correct for. For several targets, this results in
an unprecedented RV root-mean-square of around 90 cm/s over the full lifetime
of HARPS. We use the corrected RVs to confirm a previously published 120-day
signal around 61Vir, and to detect a Super-Earth candidate (K = 60 +/- 6 cm/s,
m sin i = 6.6 +/- 0.7 Earth mass) around the G6V star HD20794, which spends
part of its 600-day orbit within the habitable zone of the host star.
Conclusions. This study highlights the potential of LBL PCA to identify and
correct hitherto unknown, long-term instrumental effects and thereby extend the
sensitivity of existing and future instruments towards the Earth analogue
regime.


  Adequate labeled data and expensive compute resources are the prerequisites
for the success of neural architecture search(NAS). It is challenging to apply
NAS in meta-learning scenarios with limited compute resources and data. In this
paper, an across-task neural architecture search (AT-NAS) is proposed to
address the problem through combining gradient-based meta-learning with
EA-based NAS to learn over the distribution of tasks. The supernet is learned
over an entire set of tasks by meta-learning its weights. Architecture encodes
of subnets sampled from the supernet are iteratively adapted by evolutionary
algorithms while simultaneously searching for a task-sensitive meta-network.
Searched meta-network can be adapted to a novel task via a few learning steps
and only costs a little search time. Empirical results show that AT-NAS
surpasses the related approaches on few-shot classification accuracy. The
performance of AT-NAS on classification benchmarks is comparable to that of
models searched from scratch, by adapting the architecture in less than an hour
from a 5-GPU-day pretrained meta-network.


  All prior applications of Diffusing-Wave Spectroscopy (DWS) to aqueous foams
rely upon the assumption that the electric field of the detected light is a
Gaussian random variable and that, hence, the Siegert relation applies. Here we
test this crucial assumption by simultaneous measurement of both second and
third-order temporal intensity correlations. We find that the electric field is
Gaussian for typical experimental geometries equivalent to illumination and
detection with a plane wave, both for backscattering and transmission through
an optically-thick slab. However, we find that the Gaussian character breaks
down for point-in / point-out backscattering geometries in which the
illumination spot size is not sufficiently large in comparison with the size of
the intermittent rearrangement events.


  In this paper we investigate the derivations of filiform Leibniz algebras.
Recall that the set of filiform Leibniz algebras of fixed dimension is
decomposed into three non-intersected families. We found sufficient conditions
under which filiform Leibniz algebras of the first family are
characteristically nilpotent. Moreover, for the first family we classify
non-characteristically nilpotent algebras by means of Catalan numbers. In
addition, for the rest two families of filiform Leibniz algebras we describe
non-characteristically nilpotent algebras, i.e., those filiform Leibniz
algebras which lie in the complementary set to those characteristically
nilpotent.


  Project-based learning (PBL) is a student-centered and learn-by-doing
approach that organizes learning around projects. While entrepreneurship and
PBL in SE education are thrilling research topics, there seems to be very
little work focusing on the pros and cons of involving external stakeholders to
support real demands in software engineering education. Working on real
projects also supports students to acquire leadership skills, such as
communication, project management, and teamwork. This paper describes a case
study integrating students from different Software Engineering programs and
involving external stakeholders, underpinned by PBL concepts. We present how
this study was designed and implemented in a large institution, in four steps,
summarized as follows: (I) requirements gathering and design; (II) information
system development and implementation; (III) integration tests and deployment
process; (IV) support and maintenance activities. The study had the
participation of 59 students from a professional technical course in step one,
working in teams, and 10 undergraduate students from a Bachelor's program in
Information Systems in the following steps, working in pairs. Overall, the
feedback from stakeholders and students exceeded expectations, although it
increased the workload of teachers. We were able to distill a new set of
lessons learned, and we expect that at least some of them will be useful for
anyone implementing a similar course. As a consequence of this study, we plan
to institutionally formalize the PBL course improvement process by defining
specific outcomes and measurements.


  The estimate of coefficients of the Convection-Diffusion Equation (CDE) from
experimental measurements belongs in the category of inverse problems, which
are known to come with issues of ill-conditioning or singularity. Here we
concentrate on a particular class that can be reduced to a linear algebraic
problem, with explicit solution. Ill-conditioning of the problem corresponds to
the vanishing of one eigenvalue of the matrix to be inverted. The comparison
with algorithms based upon matching experimental data against numerical
integration of the CDE sheds light on the accuracy of the parameter estimation
procedures, and suggests a path for a more precise assessment of the profiles
and of the related uncertainty. Several instances of the implementation of the
algorithm to real data are presented.


  Superstring field theory was recently used to derive a covariant action for a
self-dual five-form field strength. This action is shown to be a
ten-dimensional version of the McClain-Wu-Yu action. By coupling to D-branes,
it can be generalized in the presence of sources. In four dimensions, this
gives a local Maxwell action with electric and magnetic sources.


  Context: The study of dust emission at millimeter wavelengths is important to
shed light on the dust properties and physical structure of pre-stellar cores,
the initial conditions in the process of star and planet formation. Aims: Using
two new continuum facilities, AzTEC at the LMT and MUSTANG-2 at the GBO, we aim
to detect changes in the optical properties of dust grains as a function of
radius for the well-known pre-stellar core L1544. Methods: We determine the
emission profiles at 1.1 and 3.3 mm and examine whether they can be reproduced
in terms of the current best physical models for L1544. We also make use of
various tools to determine the radial distributions of the density,
temperature, and the dust opacity in a self-consistent manner. Results: We find
that our observations cannot be reproduced without invoking opacity variations.
With the new data, new temperature and density profiles, as well as opacity
variations across the core, have been derived. The opacity changes are
consistent with the expected variations between uncoagulated bare grains,
toward the outer regions of the core, and grains with thick ice mantles, toward
the core center. A simple analytical grain growth model predicts the presence
of grains of ~3-4 um within the central 2000 au for the new density profile.


  We present sensitive near-infrared spectroscopic observations for a sample of
five z ~ 6 quasars. These are amongst the most distant, currently known quasars
in the universe. The spectra have been obtained using ISAAC at the VLT and
include the CIV, MgII and FeII lines. We measure the FeII/MgII line ratio, as
an observational proxy for the Fe/alpha element ratio. We derive a ratio of
2.7+/-0.8 for our sample, which is similar to that found for lower redshift
quasars, i.e., we provide additional evidence for the lack of evolution in the
FeII/MgII line ratio of quasars up to the highest redshifts. This result
demonstrates that the sample quasars must have undergone a major episode of
iron enrichment in less than one Gyr and star formation must have commenced at
z > 8. The linewidths of the MgII and CIV lines give two estimates for the
black hole masses. A third estimate is given by assuming that the quasars emit
at their Eddington luminosity. The derived masses using these three methods
agree well, implying that the quasars are not likely to be strongly lensed. We
derive central black hole masses of 0.3-5.2 10^9 solar masses. We use the
difference between the redshift of MgII (a proxy for the systemic redshift of
the quasar) and the onset of the Gunn Peterson trough to derive the extent of
the ionized Stromgren spheres around our target quasars. The derived physical
radii are about five Mpc. Using a simple ionization model, the emission of the
central quasars would need of order 10^6-10^8 year to create these cavities in
a surrounding intergalactic medium with a neutral fraction between 0.1 and 1.0.
As the e-folding time scale for the central accreting black hole is on the
order of a few times 10^7 year, it can grow by one e-folding or less within
this time span.


  Using the large acceptance apparatus FOPI, we study central and semi-central
collisions in the reactions (energies in A GeV are given in parentheses):
40Ca+40Ca (0.4, 0.6, 0.8, 1.0, 1.5, 1.93), 58Ni+58Ni (0.15, 0.25, 0.4),
96Ru+96Ru (0.4, 1.0, 1.5), 96Zr+96Zr (0.4, 1.0, 1.5), 129Xe+CsI (0.15, 0.25,
0.4), 197Au+197Au (0.09, 0.12, 0.15, 0.25, 0.4, 0.6, 0.8, 1.0, 1.2, 1.5). The
observables include directed and elliptic flow. The data are compared to
earlier data where possible and to transport model simulations. A stiff nuclear
equation of state is found to be incompatible with the data. Evidence for
extra-repulsion of neutrons in compressed asymmetric matter is found.


  BRAHMS has the ability to study relativistic heavy ion collisions from the
final freeze-out of hadrons all the way back to the initial wave-function of
the gold nuclei. This is accomplished by studying hadrons with a very wide
range of momenta and angles. In doing so we can scan various phases of QCD,
from a hadron gas, to a quark gluon plasma and perhaps to a color glass
condensate.


  Puzzled by the indication of a new critical theory for the spin-1/2
Heisenberg model with a spatially staggered anisotropy on the square lattice as
suggested in \cite{Wenzel08}, we re-investigate the phase transition of this
model induced by dimerization using first principle Monte Carlo simulations. We
focus on studying the finite-size scaling of $\rho_{s1} L$ and $\rho_{s2} L$,
where $L$ stands for the spatial box size used in the simulations and
$\rho_{si}$ with $i \in \{1,2\}$ is the spin-stiffness in $i$-direction. From
our Monte Carlo data, we find that $\rho_{s2} L$ suffers a much less severe
correction compared to that of $\rho_{s1} L$. Therefore $\rho_{s2} L$ is a
better quantity than $\rho_{s1} L$ for finite-size scaling analysis concerning
the limitation of the availability of large volumes data in our study. Further,
motivated by the so-called cubical regime in magnon chiral perturbation theory,
we additionally perform a finite-size scaling analysis on our Monte Carlo data
with the assumption that the ratio of spatial winding numbers squared is fixed
through all simulations. As a result, the physical shape of the system remains
fixed in our calculations. The validity of this new idea is confirmed by
studying the phase transition driven by spatial anisotropy for the ladder
anisotropic Heisenberg model. With this new strategy, even from $\rho_{s1} L$
which receives the most serious correction among the observables considered in
this study, we arrive at a value for the critical exponent $\nu$ which is
consistent with the expected $O(3)$ value by using only up to $L = 64$ data
points.


  We reduce the classification of all supersymmetric backgrounds of IIB
supergravity to the evaluation of the Killing spinor equations and their
integrability conditions, which contain the field equations, on five types of
spinors. This extends the work of [hep-th/0503046] to IIB supergravity. We give
the expressions of the Killing spinor equations on all five types of spinors.
In this way, the Killing spinor equations become a linear system for the
fluxes, geometry and spacetime derivatives of the functions that determine the
Killing spinors. This system can be solved to express the fluxes in terms of
the geometry and determine the conditions on the geometry of any supersymmetric
background. Similarly, the integrability conditions of the Killing spinor
equations are turned into a linear system. This can be used to determine the
field equations that are implied by the Killing spinor equations for any
supersymmetric background. We show that these linear systems simplify for
generic backgrounds with maximal and half-maximal number of $H$-invariant
Killing spinors, $H\subset Spin(9,1)$. In the maximal case, the Killing spinor
equations factorize, whereas in the half-maximal case they do not. As an
example, we solve the Killing spinor equations of backgrounds with two
$SU(4)\ltimes \bR^8$-invariant Killing spinors. We also solve the linear
systems associated with the integrability conditions of maximally
supersymmetric $Spin(7)\ltimes\bR^8$- and $SU(4)\ltimes\bR^8$-backgrounds and
determine the field equations that are not implied by the Killing spinor
equations.


  Precision calorimetry using highly granular sampling calorimeters is being
developed based on the particle flow concept within the CALICE collaboration.
One design option of a hadron calorimeter is based on silicon photomultipliers
(SiPMs) to detect photons generated in plastic scintillator tiles. Driven by
the need of automated mass assembly of around ten million channels stringently
required by the high granularity, we developed a design of scintillator tiles
directly coupled with surface-mounted SiPMs. A cavity is created in the center
of the bottom surface of each tile to provide enough room for the whole SiPM
package and to improve collection of the light produced by incident particles
penetrating the tile at different positions. The cavity design has been
optimized using a GEANT4-based full simulation model to achieve a high response
to a Minimum Ionizing Particles (MIP) and also good spatial uniformity. The
single-MIP response for scintillator tiles with an optimized cavity design has
been measured using cosmic rays, which shows that a SiPM with a sensitive area
of only $\mathbf{1\times1~mm^2}$ (Hamamatsu MPPC S12571-025P) reaches a mean
response of more than 23 photon equivalents with a dynamic range of many tens
of MIPs. A recent uniformity measurement for the same tile design is performed
by scanning the tile area using focused electrons from a $\mathbf{^{90}Sr}$
source, which shows that around 97% (80%) of the tile area is within 90% (95%)
response uniformity. This optimized design is well beyond the requirements for
a precision hadron calorimeter.


  The flat electronic bands in magic-angle twisted bilayer graphene (MATBG)
host a variety of correlated insulating ground states, many of which are
predicted to support charged excitations with topologically non-trivial spin
and/or valley skyrmion textures. However, it has remained challenging to
experimentally address their ground state order and excitations, both because
some of the proposed states do not couple directly to experimental probes, and
because they are highly sensitive to spatial inhomogeneities in real samples.
Here, using a scanning single-electron transistor, we observe thermodynamic
gaps at even integer moir\'e filling factors at low magnetic fields. We find
evidence of a field-tuned crossover from charged spin skyrmions to bare
particle-like excitations, suggesting that the underlying ground state belongs
to the manifold of strong-coupling insulators. From the spatial dependence of
these states and the chemical potential variation within the flat bands, we
infer a link between the stability of the correlated ground states and local
twist angle and strain. Our work advances the microscopic understanding of the
correlated insulators in MATBG and their unconventional excitations.


  In this work, we derive and present the coupled amplitude equations to
describe the evolutions of different spectral components in different
transverse modes for Raman fiber amplifiers (RFAs). Both the effects of the
four-wave-mixing in the fundamental mode (FM FWM) and the inter-modal
four-wave-mixing (IM FWM) on high-power RFAs are demonstrated through numerical
simulations. Specifically, effective FM FWM interactions could occur and lead
to a drop of the Raman threshold for RFAs by over 50%, despite that the
corresponding wave-vector mismatch is rather big. In addition, the IM FWM could
also impact the Raman threshold for RFAs with additional generation of the
first order Raman Stokes light in the higher-order mode. We also investigate
the effects of the intensity fluctuations in the initial inserted pump and seed
lasers on high-power RFAs. It reveals that the temporal stability of the
initial inserted pump laser have much more significant impacts on high-power
RFAs than that of the initial inserted seed laser. Notably, through applying
temporal stable laser as the initial inserted pump laser, both the FM FWM and
IM FWM effects could be effectively suppressed, and the Raman threshold for
high-power RFAs could be increased by over twice.


  Herein, the canonical Fowler-Nordheim theory is extended by computing the
zero-temperature transmission probability for the more general case of a
barrier described by a fractional power law. An exact analytical formula is
derived, written in terms of Gauss hypergeometric functions, that fully capture
the transmission probability for this generalized problem, including screened
interaction with the image potential. First, the quality of approximation
against the so far most advanced formulation of Fowler-Nordheim, where the
transmission is given in terms of elliptic integrals, is benchmarked. In the
following, as the barrier is given by a power law, in detail, the dependence of
the transmission probability on the exponent of the power law is analyzed. The
formalism is compared with results of numerical calculations and its possible
experimental relevance is discussed. Finally, it is discussed how the presented
solution can be linked in some specific cases with an exact quantum-mechanical
solution of the quantum well problem.


  Fermilab E791, a very high statistics charm particle experiment, recently
completed its data taking at Fermilab's Tagged Photon Laboratory. Over 20
billion events were recorded through a loose transverse energy trigger and
written to 8mm tape in the the 1991-92 fixed target run at Fermilab. This
unprecedented data sample containing charm is being analysed on many-thousand
MIP RISC computing farms set up at sites in the collaboration. A glimpse of the
data taking and analysis effort is presented. We also show some preliminary
results for common charm decay modes. Our present analysis indicates a very
rich yield of over 200K reconstructed charm decays.


  The author has recently introduced an abstract algebraic framework of
analogical proportions within the general setting of universal algebra. This
paper studies analogical proportions in the boolean domain consisting of two
elements 0 and 1 within his framework. It turns out that our notion of boolean
proportions coincides with two prominent models from the literature in
different settings. This means that we can capture two separate modellings of
boolean proportions within a single framework which is mathematically appealing
and provides further evidence for the robustness and applicability of the
general framework.


  Implementing automated emotion recognition on mobile devices could provide an
accessible diagnostic and therapeutic tool for those who struggle to recognize
emotion, including children with developmental behavioral conditions such as
autism. Although recent advances have been made in building more accurate
emotion classifiers, existing models are too computationally expensive to be
deployed on mobile devices. In this study, we optimized and profiled various
machine learning models designed for inference on edge devices and were able to
match previous state of the art results for emotion recognition on children.
Our best model, a MobileNet-V2 network pre-trained on ImageNet, achieved 65.11%
balanced accuracy and 64.19% F1-score on CAFE, while achieving a 45-millisecond
inference latency on a Motorola Moto G6 phone. This balanced accuracy is only
1.79% less than the current state of the art for CAFE, which used a model that
contains 26.62x more parameters and was unable to run on the Moto G6, even when
fully optimized. This work validates that with specialized design and
optimization techniques, machine learning models can become lightweight enough
for deployment on mobile devices and still achieve high accuracies on difficult
image classification tasks.


  We investigate the Hubble tension in the non-flat Super-$\Lambda {\rm CDM}$
model. The non-flat Super-$\Lambda {\rm CDM}$ model extends the Super-$\Lambda
{\rm CDM}$ model by including the spatial curvature as a free parameter. The
Super-$\Lambda {\rm CDM}$ model extends the standard $\Lambda {\rm CDM}$ model
of cosmology through additional parameters accounting for the possible effect
of a trispectrum in the primordial fluctuations. In the cosmic microwave
background data, this effect can be parameterized using parameters that change
the observed angular power spectrum from the theoretical power spectrum due to
a trispectrum that couples long and short wavelength modes. In this work, we
perform Markov Chain Monte Carlo (MCMC) data analysis on the recent Planck 2018
temperature and polarization fluctuations data and the local Hubble constant
measurements from supernovae data assuming a non-flat Super-$\Lambda {\rm CDM}$
model. We find that there is a preference for non-zero values of the spatial
curvature parameter $\Omega_k$ and the Super-$\Lambda {\rm CDM}$ parameter
$A_0$ at a level of $\Delta \chi^2$ improvement of approximately 23.


  Resource allocation is the problem that a process may enter a critical
section CS of its code only when its resource requirements are not in conflict
with those of other processes in their critical sections. For each execution of
CS, these requirements are given anew. In the resource requirements, levels can
be distinguished, such as e.g. read access or write access. We allow infinitely
many processes that communicate by reliable asynchronous messages and have
finite memory. A simple starvation-free solution is presented. Processes only
wait for one another when they have conflicting resource requirements. The
correctness of the solution is argued with invariants and temporal logic. It
has been verified with the proof assistant PVS.


  Photo-assisted tunneling in scanning tunneling microscopy has attracted
considerable interest to combine sub-picosecond and sub-nanometer resolutions.
The illumination of a junction with visible or infrared light, however, induces
thermal expansion of the tip and the sample, which strongly affects the
measurements. Employing free-space THz pulses instead of visible light has been
proposed to solve these thermal issues while providing photo-induced currents
of similar magnitude. Here we compared the impact of illuminating the same
tunneling junction, reaching comparable photo-induced current, with red light
and with THz radiations. Our data provide a clear and direct evidence of
thermal expansion with red light-illumination, while such thermal effects are
negligible with THz radiations.


  In future wireless systems, a large number of users may access the networks
via moving relays (MRs) installed on top of vehicles. One of the main
challenges of MRs is rapid channel variation which may make channel estimation,
and its following procedures, difficult. To address these issues, various
schemes are designed, among which predictor antenna (PA) is a candidate. The PA
setup refers to a system with two (sets of) antennas on top of a vehicle, where
the PA(s) positioned in front of the vehicle is(are) utilized to predict the
channel state information required for data transmission to the receive
antennas (RAs) aligned behind the PA. In this paper, we introduce the concept
and the potentials of PA systems. Moreover, summarizing the field trials for
PAs and the 3GPP attempts on (moving) relays, we compare the performance of
different PA and non-PA methods for vehicle communications in both urban and
rural areas with the PA setup backhauled through terrestrial or satellite
technology, respectively. As we show, with typical parameter settings and
vehicle speeds, a single-antenna PA-assisted setup can boost the backhaul
throughput of MRs, compared to state-of-the-art open-loop schemes, by up to
50%.


  In this paper, we study the solvability of a general class of fully nonlinear
curvature equations, which can be viewed as generalizations of the equations
for Christoffel-Minkowski problem in convex geometry. We will also study the
Dirichlet problem of the corresponding degenerate equations as an extension of
the equations studied by Krylov.


  Across machine learning (ML) sub-disciplines, researchers make explicit
mathematical assumptions in order to facilitate proof-writing. We note that,
specifically in the area of fairness-accuracy trade-off optimization
scholarship, similar attention is not paid to the normative assumptions that
ground this approach. Such assumptions presume that 1) accuracy and fairness
are in inherent opposition to one another, 2) strict notions of mathematical
equality can adequately model fairness, 3) it is possible to measure the
accuracy and fairness of decisions independent from historical context, and 4)
collecting more data on marginalized individuals is a reasonable solution to
mitigate the effects of the trade-off. We argue that such assumptions, which
are often left implicit and unexamined, lead to inconsistent conclusions: While
the intended goal of this work may be to improve the fairness of machine
learning models, these unexamined, implicit assumptions can in fact result in
emergent unfairness. We conclude by suggesting a concrete path forward toward a
potential resolution.


  In previous papers the authors established the prime avoidance property of
$k$-th powers of prime numbers and of prime numbers within Beatty sequences. In
this paper the authors consider $k$-th powers of Piatetski-Shapiro primes.


  We will study a certain synchronizing property of subshifts called
$\lambda$-synchronization. The $\lambda$-synchronizing subshifts form a large
class of irreducible subshifts containing irreducible sofic shifts. We prove
that the $\lambda$-synchronization is invariant under flow equivalence of
subshifts. The $\lambda$-synchronizing K-groups and the $\lambda$-synchronizing
Bowen-Franks groups are studied and proved to be invariant under flow
equivalence of $\lambda$-synchronizing subshifts. They are new flow equivalence
invariants for $\lambda$-synchronizing subshifts.


  We show how the multiloop bosonic Green function of closed string theory
reduces to the world-line Green function as defined by Schmidt and Schubert in
the limit where the string world-sheet degenerates into a $\Phi^3$ particle
diagram. To obtain this correspondence we have to make an appropriate choice of
the local coordinates defined on the degenerate string world sheet. We also
present a set of simple rules that specify, in the explicit setting of the
Schottky parametrization, which is the corner of moduli space corresponding to
a given multiloop $\Phi^3$ diagram.


  We compute the mass loss rate from a disk orbiting a stellar mass black hole
assuming the flow is guided along magnetic field lines attached to the disk. We
then estimate the Lorentz factor of the wind at infinity. We find that the
Lorentz factor can reach high values only if severe constraints on the field
geometry and the conditions of energy injection are satisfied. We discuss our
results in the context of different scenarios for gamma-ray bursts. We mention
a risk of 'contamination' of the Blandford-Znajek process by wind material
emitted from the disk.


  This work considers how the properties of hydrogen bonded complexes,
D-H....A, are modified by the quantum motion of the shared proton. Using a
simple two-diabatic state model Hamiltonian, the analysis of the symmetric
case, where the donor (D) and acceptor (A) have the same proton affinity, is
carried out. For quantitative comparisons, a parametrization specific to the
O-H....O complexes is used. The vibrational energy levels of the
one-dimensional ground state adiabatic potential of the model are used to make
quantitative comparisons with a vast body of condensed phase data, spanning a
donor-acceptor separation (R) range of about 2.4-3.0 A, i.e., from strong to
weak bonds. The position of the proton and its longitudinal vibrational
frequency, along with the isotope effects in both are discussed. An analysis of
the secondary geometric isotope effects, using a simple extension of the
two-state model, yields an improved agreement of the predicted variation with R
of frequency isotope effects. The role of the bending modes in also considered:
their quantum effects compete with those of the stretching mode for certain
ranges of H-bond strengths. In spite of the economy in the parametrization of
the model used, it offers key insights into the defining features of H-bonds,
and semi-quantitatively captures several experimental trends.