  Intensity mapping of the HI brightness temperature provides a unique way of
tracing large-scale structures of the Universe up to the largest possible
scales. This is achieved by using a low angular resolution radio telescopes to
detect emission line from cosmic neutral Hydrogen in the post-reionization
Universe. We use general relativistic perturbation theory techniques to derive
for the first time the full expression for the HI brightness temperature up to
third order in perturbation theory without making any plane-parallel
approximation. We use this result and the renormalization prescription for
biased tracers to study the impact of nonlinear effects on the power spectrum
of HI brightness temperature both in real and redshift space. We show how mode
coupling at nonlinear order due to nonlinear bias parameters and redshift space
distortion terms modulate the power spectrum on large scales. The large scale
modulation may be understood to be due to the effective bias parameter and
effective shot noise.


  In this paper, we study the problem of distributed transmission control and
video streaming optimization for unmanned aerial vehicles (UAVs) operating in
unlicensed spectrum bands. We develop a rigorous cross-layer analysis framework
that jointly considers three inter-dependent factors: (i) in-band interference
introduced by ground/aerial nodes at the physical (PHY) layer, (ii)
limited-size queues with delay-constrained packet arrival at the medium access
control (MAC) layer, and (iii) video encoding rate at the application layer.
First, we formulate an optimization problem to maximize the throughput by
optimizing the fading threshold. To this end, we jointly analyze the
queue-related packet loss probabilities (i.e., buffer overflow and time
threshold event) as well as the outage probability due to the low
signal-to-interference-plus-noise ratio (SINR). We introduce the Distributed
Transmission Control (DTC) algorithm that maximizes the throughput by adjusting
transmission policies to balance the trade-offs between packet drop from queues
vs. transmission errors due to low SINRs. Second, we incorporate the video
distortion model to develop distributed peak signal-to-noise ratio (PSNR)
optimization for video streaming. The formulated optimization incorporates two
cross-layer parameters, specifically the fading threshold and video encoding
rate. To tackle this problem, we develop the Joint Distributed Video
Transmission and Encoder Control (JDVT-EC) algorithm that enhances the PSNR for
all nodes by fine-tuning transmission policies and video encoding rates to
balance the trade-offs between packet loss and lossy video compression
distortions. Through extensive numerical analysis, we thoroughly examine the
proposed algorithms and demonstrate that they are able to find the optimal
transmission policies and video encoding rates under various scenarios.


  Brain aging is a regional phenomenon, a facet that remains relatively
under-explored within the realm of brain age prediction research using machine
learning methods. Voxel-level predictions can provide localized brain age
estimates that can provide granular insights into the regional aging processes.
This is essential to understand the differences in aging trajectories in
healthy versus diseased subjects. In this work, a deep learning-based multitask
model is proposed for voxel-level brain age prediction from T1-weighted
magnetic resonance images. The proposed model outperforms the models existing
in the literature and yields valuable clinical insights when applied to both
healthy and diseased populations. Regional analysis is performed on the
voxel-level brain age predictions to understand aging trajectories of known
anatomical regions in the brain and show that there exist disparities in
regional aging trajectories of healthy subjects compared to ones with
underlying neurological disorders such as Dementia and more specifically,
Alzheimer's disease. Our code is available at
https://github.com/nehagianchandani/Voxel-level-brain-age-prediction.


  We use an effective field theory (EFT) which includes all possible
gluon-Higgs dimension-5 and dimension-7 operators to study Higgs boson plus jet
production in next-to-leading order QCD. The EFT sheds light on the effect of a
finite top quark mass as well as any Beyond-the-Standard Model (BSM)
modifications of Higgs-gluon effective couplings. In the gluon channel, the
accuracy of the heavy-top approximation for differential distributions arises
from the non-interference between the helicity amplitudes of the G^3 h and G^2
h operators in the m_h < p_T limit at lowest order. One dimension-7 operator
involving quark bilinears, however, contributes significantly at high p_T, and
potentially offers a channel for seeing BSM effects. One-loop renormalization
of these operators is determined, allowing resummation of large logarithms via
renormalization group running. NLO numerical results at the LHC are presented,
which include O(1/m_t^2) contributions in the SM limit.


  Convolutional neural networks (CNNs) have massively impacted visual
recognition in 2D images, and are now ubiquitous in state-of-the-art
approaches. CNNs do not easily extend, however, to data that are not
represented by regular grids, such as 3D shape meshes or other graph-structured
data, to which traditional local convolution operators do not directly apply.
To address this problem, we propose a novel graph-convolution operator to
establish correspondences between filter weights and graph neighborhoods with
arbitrary connectivity. The key novelty of our approach is that these
correspondences are dynamically computed from features learned by the network,
rather than relying on predefined static coordinates over the graph as in
previous work. We obtain excellent experimental results that significantly
improve over previous state-of-the-art shape correspondence results. This shows
that our approach can learn effective shape representations from raw input
coordinates, without relying on shape descriptors.


  We obtain the fluctuations for the occupation time of one-dimensional
symmetric exclusion processes with speed change, where the transition rates
(conductances) are driven by a general function W. The approach does not
require sharp bounds on the spectral gap of the system nor the jump rates to be
bounded from above or below. We present some examples and for one of them, we
observe that the fluctuations of the current are trivial, but the fluctuations
of the occupation time are given by a fractional Brownian Motion. This shows
that, in general, the fluctuations of the current and of the occupation time
are not of same order.


  In many industries, as well as in academic research, information is primarily
transmitted in the form of unstructured documents (this article, for example).
Hierarchically-related data is rendered as tables, and extracting information
from tables in such documents presents a significant challenge. Many existing
methods take a bottom-up approach, first integrating lines into cells, then
cells into rows or columns, and finally inferring a structure from the
resulting 2-D layout. But such approaches neglect the available prior
information relating to table structure, namely that the table is merely an
arbitrary representation of a latent logical structure. We propose a top-down
approach, first using a conditional generative adversarial network to map a
table image into a standardised `skeleton' table form denoting approximate row
and column borders without table content, then deriving latent table structure
using xy-cut projection and Genetic Algorithm optimisation. The approach is
easily adaptable to different table configurations and requires small data set
sizes for training.


  The non-local properties of the noisy three-qubit Greenberger-Horne-Zeilinger
(GHZ) states parameterized by the visibility 0<v<1 are investigated. Based on
the violation of the 2x2x2-setting Mermin inequality, the noisy three-qubit GHZ
states are non-local for the parameter range 1/2<v<1. It has been posed whether
additional settings would allow to lower the threshold visibility. Here we
report on Bell inequalities giving a threshold value smaller than v=1/2. This
rules out the possibility of a local hidden variable model in the limit of
v=1/2. In particular, the lowest threshold visibility we found is v=0.496057,
attainable with 5x5x5 settings, whereas the most economical one in number of
settings corresponds to 3x3x4 settings. The method which enabled us to obtain
these results, and in particular the about 10000 tight Bell inequalities giving
v<1/2 are also discussed in detail.


  Let $K$ be an algebrically closed field and let $n\geq 1$. If $P\in
K[X]=K[X_1,\ldots,X_n]$, $P\neq 0$, we denote by $I(P)$ the support of $P$,
which is the finite subset of $\mathbb N^n$ such that $P=\sum_{i\in
I(P)}a_iX^i$ with $a_i\in K^*$. (If $i=(i_1,\ldots,i_n)$ then
$X^i:=X_1^{i_1}\cdots X_n^{i_n}$.) We determine all finite, nonempty sets
$I\sb\mathbb N^n$ such that every $P\in K[X]$ with $I(P)=I$ is decomposable. We
also consider the problem of finding all $I\sb\mathbb N^n$ such that every
$P\in K[X]$ with $I(P)=I$ is irreducible. We do not solve this problem, which
is very unlikely to have a simple answer. We show however that the answer
depends on the characteristic of $K$ and we determine the nature of this
dependence.


  We consider the 1d Schr\"odinger operator with random decaying potential and
compute the 2nd term asymptotics of the density of states, which shows
substantial differences between the cases $\alpha > \frac 12$, $\alpha < \frac
12$ and $\alpha = \frac 12$.


  Social distancing is an efficient public health practice during the COVID-19
pandemic. However, people would violate the social distancing practice
unconsciously when they conduct some social activities such as handshaking,
hugging, kissing on the face or forehead, etc. In this paper, we present SoDA,
a social distancing practice violation alert system based on smartwatches, for
preventing COVID-19 virus transmission. SoDA utilizes recordings of
accelerometers and gyroscopes to recognize activities that may violate social
distancing practice with simple yet effective Vision Transformer models.
Extensive experiments over 10 volunteers and 1800+ samples demonstrate that
SoDA achieves social activity recognition with the accuracy of 94.7%, 1.8%
negative alert, and 2.2% missing alert.


  We use a self-improvement argument to give a very short and elementary proof
of the result of Bourgain saying that regular trees do not admit bi-Lipschitz
embeddings into uniformly convex Banach spaces.


  Schnyder woods are decompositions of simple triangulations into three
edge-disjoint spanning trees crossing each other in a specific way. In this
article, we define a generalization of Schnyder woods to $d$-angulations (plane
graphs with faces of degree $d$) for all $d\geq 3$. A \emph{Schnyder
decomposition} is a set of $d$ spanning forests crossing each other in a
specific way, and such that each internal edge is part of exactly $d-2$ of the
spanning forests. We show that a Schnyder decomposition exists if and only if
the girth of the $d$-angulation is $d$. As in the case of Schnyder woods
($d=3$), there are alternative formulations in terms of orientations
("fractional" orientations when $d\geq 5$) and in terms of corner-labellings.
Moreover, the set of Schnyder decompositions on a fixed $d$-angulation of girth
$d$ is a distributive lattice. We also show that the structures dual to
Schnyder decompositions (on $d$-regular plane graphs of mincut $d$ rooted at a
vertex $v^*$) are decompositions into $d$ spanning trees rooted at $v^*$ such
that each edge not incident to $v^*$ is used in opposite directions by two
trees. Additionally, for even values of $d$, we show that a subclass of
Schnyder decompositions, which are called even, enjoy additional properties
that yield a reduced formulation; in the case d=4, these correspond to
well-studied structures on simple quadrangulations (2-orientations and
partitions into 2 spanning trees). In the case d=4, the dual of even Schnyder
decompositions yields (planar) orthogonal and straight-line drawing algorithms.
For a 4-regular plane graph $G$ of mincut 4 with $n$ vertices plus a marked
vertex $v$, the vertices of $G\backslash v$ are placed on a $(n-1) \times
(n-1)$ grid according to a permutation pattern, and in the orthogonal drawing
each of the $2n-2$ edges of $G\backslash v$ has exactly one bend. Embedding
also the marked vertex $v$ is doable at the cost of two additional rows and
columns and 8 additional bends for the 4 edges incident to $v$. We propose a
further compaction step for the drawing algorithm and show that the obtained
grid-size is strongly concentrated around $25n/32\times 25n/32$ for a uniformly
random instance with $n$ vertices.


  The goal of this paper is to derive in the two-dimensional case necessary and
sufficient minimality conditions in terms of the second variation for the
functional \[ v\mapsto\int_{\Omega}\big(|\nabla v|^{2}+\chi_{\{v>0\}}Q^{2}
\big)\,dx, \] introduced in a classical paper of Alt and Caffarelli. For a
special choice of $Q$ this includes water waves. The second variation is
obtained by computing the second derivative of the functional along suitable
variations of the free boundary. It is proved that the strict positivity of the
second variation gives a sufficient condition for local minimality. Also, it is
shown that smooth critical points are local minimizers in a small tubular
neighborhood of the free-boundary.


  Generating videos predicting the future of a given sequence has been an area
of active research in recent years. However, an essential problem remains
unsolved: most of the methods require large computational cost and memory usage
for training. In this paper, we propose a novel method for generating future
prediction videos with less memory usage than the conventional methods. This is
a critical stepping stone in the path towards generating videos with high image
quality, similar to that of generated images in the latest works in the field
of image generation. We achieve high-efficiency by training our method in two
stages: (1) image reconstruction to encode video frames into latent variables,
and (2) latent variable prediction to generate the future sequence. Our method
achieves an efficient compression of video into low-dimensional latent
variables by decomposing each frame according to its hierarchical structure.
That is, we consider that video can be separated into background and foreground
objects, and that each object holds time-varying and time-independent
information independently. Our experiments show that the proposed method can
efficiently generate future prediction videos, even for complex datasets that
cannot be handled by previous methods.


  This paper studies the problem of increasing the connectivity of an ad-hoc
peer-to-peer network subject to cyber-attacks targeting the agents in the
network. The adopted strategy involves the design of local interaction rules
for the agents to locally modify the graph topology by adding and removing
links with neighbors. Two distributed protocols are presented to boost the
algebraic connectivity of the network graph beyond $k-2\sqrt{k-1}$ where $k\in
\mathbb{N}$ is a free design parameter; these two protocols are achieved
through the distributed construction of random (approximate) regular graphs.
One protocol leverages coordinated actions between pairs of neighboring agents
and is mathematically proven to converge to the desired graph topology. The
other protocol relies solely on the uncoordinated actions of individual agents
and it is validated by a spectral analysis through Monte-Carlo simulations.
Numerical simulations offer a comparative analysis with other state-of-the-art
algorithms, showing the ability of both proposed protocols to maintain high
levels of connectivity despite attacks carried out with full knowledge of the
network structure, and highlighting their superior performance.


  We present photometry and spectroscopy of SN2013fs and SN2013fr in the first
100 days post-explosion. Both objects showed transient, relatively narrow
H$\alpha$ emission lines characteristic of SNeIIn, but later resembled normal
SNeII-P or SNeII-L, indicative of fleeting interaction with circumstellar
material (CSM). SN2013fs was discovered within 8hr of explosion. Its light
curve exhibits a plateau, with spectra revealing strong CSM interaction at
early times. It is a less luminous version of the transitional SNIIn PTF11iqb,
further demonstrating a continuum of CSM interaction intensity between SNeII-P
and IIn. It requires dense CSM within 6.5$\times$10$^{14}$~cm of the
progenitor, from a phase of advanced pre-SN mass loss shortly before explosion.
Spectropolarimetry of SN2013fs shows little continuum polarization, but
noticeable line polarization during the plateau phase. SN2013fr morphed from a
SNIIn at early times to a SNII-L. After the first epoch its narrow lines
probably arose from host-galaxy emission, but the bright, narrow H$\alpha$
emission at early times may be intrinsic. As for SN2013fs, this would point to
a short-lived phase of strong CSM interaction if proven to be intrinsic,
suggesting a continuum between SNeIIn and II-L. It is a low-velocity SNII-L,
like SN2009kr but more luminous. SN2013fr also developed an IR excess at later
times, due to warm CSM dust that require a more sustained phase of strong
pre-SN mass loss.


  We model the logarithm of the price (log-price) of a financial asset as a
random variable obtained by projecting an operator stable random vector with a
scaling index matrix $\underline{\underline{E}}$ onto a non-random vector. The
scaling index $\underline{\underline{E}}$ models prices of the individual
financial assets (stocks, mutual funds, etc.). We find the functional form of
the characteristic function of real powers of the price returns and we compute
the expectation value of these real powers and we speculate on the utility of
these results for statistical inference. Finally we consider a portfolio
composed of an asset and an option on that asset. We derive the characteristic
function of the deviation of the portfolio, \mbox{${\mathfrak D}_t^{({\mathfrak
t})}$}, defined as a temporal change of the portfolio diminished by the the
compound interest earned. We derive pseudo-differential equations for the
option as a function of the log-stock-price and time and we find exact
closed-form solutions to that equation. These results were not known before.
Finally we discuss how our solutions correspond to other approximate results
known from literature,in particular to the well known Black & Scholes equation.


  There has been ample demonstration that bibliometrics is superior to
peer-review for national research assessment exercises in the hard sciences. In
this paper we examine the Italian case, taking the 2001-2003 university
performance rankings list based on bibliometrics as benchmark. We compare the
accuracy of the first national evaluation exercise, conducted entirely by
peer-review, to other rankings lists prepared at zero cost, based on indicators
indirectly linked to performance or available on the Internet. The results show
that, for the hard sciences, the costs of conducting the Italian evaluation of
research institutions could have been completely avoided.


  Software testing assures that code changes do not adversely affect existing
functionality. However, a test case can be flaky, i.e., passing and failing
across executions, even for the same version of the source code. Flaky test
cases introduce overhead to software development as they can lead to
unnecessary attempts to debug production or testing code. The state-of-the-art
ML-based flaky test case predictors rely on pre-defined sets of features that
are either project-specific, require access to production code, which is not
always available to software test engineers. Therefore, in this paper, we
propose Flakify, a black-box, language model-based predictor for flaky test
cases. Flakify relies exclusively on the source code of test cases, thus not
requiring to (a) access to production code (black-box), (b) rerun test cases,
(c) pre-define features. To this end, we employed CodeBERT, a pre-trained
language model, and fine-tuned it to predict flaky test cases using the source
code of test cases. We evaluated Flakify on two publicly available datasets
(FlakeFlagger and IDoFT) for flaky test cases and compared our technique with
the FlakeFlagger approach using two different evaluation procedures:
cross-validation and per-project validation. Flakify achieved high F1-scores on
both datasets using cross-validation and per-project validation, and surpassed
FlakeFlagger by 10 and 18 percentage points in terms of precision and recall,
respectively, when evaluated on the FlakeFlagger dataset, thus reducing the
cost bound to be wasted on unnecessarily debugging test cases and production
code by the same percentages. Flakify also achieved significantly higher
prediction results when used to predict test cases on new projects, suggesting
better generalizability over FlakeFlagger. Our results further show that a
black-box version of FlakeFlagger is not a viable option for predicting flaky
test cases.


  This note gives two examples of surfaces with normal crossing singularities.
In the first example the canonical ring is not finitely generated. In the
second, the canonical line bundle is not ample but its pull back to the
normalization is ample. The latter answers in the negative a problem left
unresolved in [EGA,III.2.6.2] and raised again by Viehweg.


  Compositor attribution, the clustering of pages in a historical printed
document by the individual who set the type, is a bibliographic task that
relies on analysis of orthographic variation and inspection of visual details
of the printed page. In this paper, we introduce a novel unsupervised model
that jointly describes the textual and visual features needed to distinguish
compositors. Applied to images of Shakespeare's First Folio, our model predicts
attributions that agree with the manual judgements of bibliographers with an
accuracy of 87%, even on text that is the output of OCR.


  We study the norm approximation to the Schr\"odinger dynamics of $N$ bosons
in $\mathbb{R}^d$ ($d=1,2$) with an interaction potential of the form
$N^{d\beta-1}w(N^{\beta}(x-y))$. Here we are interested in the focusing case
$w\le 0$. Assuming that there is complete Bose-Einstein condensation in the
initial state, we show that in the large $N$ limit, the evolution of the
condensate is effectively described by a nonlinear Schr\"odinger equation and
the evolution of the fluctuations around the condensate is governed by a
quadratic Hamiltonian, resulting from Bogoliubov approximation. Our result
holds true for all $\beta>0$ when $d=1$ and for all $0<\beta<1$ when $d=2$.


  Recent studies reveal that branching bisimilarity is decidable for both nBPP
(normed Basic Parallel Process) and nBPA (normed Basic Process Algebra). These
results lead to the question if there are any other models in the hierarchy of
PRS (Process Rewrite System) whose branching bisimilarity is decidable. It is
shown in this paper that the branching bisimilarity for both nOCN (normed One
Counter Net) and nPA (normed Process Algebra) is undecidable. These results
essentially imply that the question has a negative answer.


  We report radial speed evolution of interplanetary coronal mass ejections
(ICMEs) detected by the SOHO/LASCO coronagraph, interplanetary scintillation
(IPS) at 327 MHz, and in-situ observations. In this study, we analyze solar
wind disturbance factor (g-value) data derived from IPS observations during
1997-2009 covering nearly the whole period of Solar Cycle 23. By comparing
observations from the SOHO/LASCO, IPS, and in situ, we then identify 39 ICMEs
that could be analyzed carefully. Here, we define two speeds V_SOHO and V_bg,
which are initial speed of ICME and the speed of the background solar wind,
respectively. Examinations of these speeds yield the following results; i) Fast
ICMEs (with V_SOHO - V_bg > 500 km/s) rapidly decelerate, moderate ICMEs (with
0 km/s < V_SOHO - V_bg < 500 km/s) show either gradually decelerating or
uniform motion, and slow ICMEs (with V_SOHO - V_bg < 0 km/s) accelerate. The
radial speeds converge on the speed of background solar wind during their
outward propagation. We subsequently find; ii) both the acceleration and
deceleration are nearly complete by 0.79 (+/- 0.04) AU, and those are ended
when the ICME speed reaches a given speed. We find the value of that to be 480
(+/- 21) km/s. iii) For the fast and moderate ICMEs, a linear equation with a
constant coefficient is more appropriate than a quadratic equation to describe
their kinematics, because the chi-square for the linear equation satisfies the
statistical significance level of 0.05, while the quadratic one is not. These
results support the hypothesis that the radial motion of ICMEs is governed by a
drag force due to interaction with the background solar wind. These findings
also suggest that ICMEs propagating faster than background solar wind are
controlled mainly by the hydrodynamic Stokes drag.


  We investigate the scattering properties of spherical nanoparticles by
employing a Cartesian multipole expansion method which has incorporated
radiating toroidal multipoles. It is shown that toroidal dipoles, which are
negligible under long-wavelength approximations, can be excited within
high-permittivity dielectric nanoparticles and significantly influence the
scattering profile in the optical regime. We further reveal that the scattering
transparencies of core-shell plasmonic nanoparticles can be classified into two
categories: i) the trivial transparency with no effective multipole excitations
within the particle, and ii) the non-trivial one induced by the destructive
interferences of induced electric and toroidal multipoles. The incorporation of
toroidal moments offers new insights into the study into nanoparticle
scattering in both the near- and far-fields, which may shed new light to many
related applications, such as biosensing, nanoantennas, photovoltaic devices
and so on.


  We consider a single particle tunnelling in a tight-binding model with
nearest-neighbour couplings, in the presence of a periodic high-frequency
force. An effective Hamiltonian for the particle is derived using an averaging
method resembling classical canonical perturbation theory. Three cases are
considered: uniform lattice with periodic and open boundary conditions, and
lattice with a parabolic potential. We find that in the latter case, interplay
of the potential and driving leads to appearence of the effective next-nearest
neighbour couplings. In the uniform case with periodic boundary conditions the
second- and third-order corrections to the averaged Hamiltonian are completely
absent, while in the case with open boundary conditions they have a very simple
form, found before in some particular cases by S.Longhi [Phys. Rev. B 77,
195326 (2008)]. These general results may found applications in designing
effective Hamiltonian models in experiments with ultracold atoms in optical
lattices, e.g. for simulating solid-state phenomena.


  A universal quasitriangular $R$--matrix for the non-standard quantum (1+1)
Poincar\'e algebra $U_ziso(1,1)$ is deduced by imposing analyticity in the
deformation parameter $z$. A family $g_\mu$ of ``quantum graded contractions"
of the algebra $U_ziso(1,1)\oplus U_{-z}iso(1,1)$ is obtained; this set of
quantum algebras contains as Hopf subalgebras with two primitive translations
quantum analogues of the two dimensional Euclidean, Poincar\'e and Galilei
algebras enlarged with dilations. Universal $R$--matrices
  for these quantum Weyl algebras and their associated quantum groups are
constructed.


  This paper considers the problem of differentially private semi-supervised
transfer and multi-task learning. The notion of \emph{membership-mapping} has
been developed using measure theory basis to learn data representation via a
fuzzy membership function. An alternative conception of deep autoencoder,
referred to as \emph{Conditionally Deep Membership-Mapping Autoencoder
(CDMMA)}, is considered for transferrable deep learning. Under
practice-oriented settings, an analytical solution for the learning of CDMMA
can be derived by means of variational optimization. The paper proposes a
transfer and multi-task learning approach that combines CDMMA with a tailored
noise adding mechanism to achieve a given level of privacy-loss bound with the
minimum perturbation of the data. Numerous experiments were carried out using
MNIST, USPS, Office, and Caltech256 datasets to verify the competitive robust
performance of the proposed methodology.


  Various face image datasets intended for facial biometrics research were
created via web-scraping, i.e. the collection of images publicly available on
the internet. This work presents an approach to detect both exactly and nearly
identical face image duplicates, using file and image hashes. The approach is
extended through the use of face image preprocessing. Additional steps based on
face recognition and face image quality assessment models reduce false
positives, and facilitate the deduplication of the face images both for intra-
and inter-subject duplicate sets. The presented approach is applied to five
datasets, namely LFW, TinyFace, Adience, CASIA-WebFace, and C-MS-Celeb (a
cleaned MS-Celeb-1M variant). Duplicates are detected within every dataset,
with hundreds to hundreds of thousands of duplicates for all except LFW. Face
recognition and quality assessment experiments indicate a minor impact on the
results through the duplicate removal. The final deduplication data is publicly
available.


  The cross section for Higgs boson production in pp collisions is studied
using the H to WW decay mode, followed by leptonic decays of the W bosons to an
oppositely charged electron-muon pair in the final state. The measurements are
performed using data collected by the CMS experiment at the LHC at a
centre-of-mass energy of 8 TeV, corresponding to an integrated luminosity of
19.4 inverse femtobarns. The Higgs boson transverse momentum (pT) is
reconstructed using the lepton pair pT and missing pT. The differential cross
section times branching fraction is measured as a function of the Higgs boson
pT in a fiducial phase space defined to match the experimental acceptance in
terms of the lepton kinematics and event topology. The production cross section
times branching fraction in the fiducial phase space is measured to be 39 +/- 8
(stat) +/- 9 (syst) fb. The measurements are found to agree, within
experimental uncertainties, with theoretical calculations based on the standard
model.


  To increase the speed of operation and reduce operator burden, humanoid
robots must be able to function autonomously, even in complex, cluttered
environments. For this to be possible, they must be able to quickly and
efficiently compute desired footsteps to reach a goal. In this work, we present
a new A* footstep planner that utilizes a planar region representation of the
environment enable footstep planning over rough terrain. To increase the number
of available footholds, we present an approach to allow the use of partial
footholds during the planning process. The footstep plan solutions are then
post-processed to capture better solutions that lie between the lattice
discretization of the footstep graph. We then demonstrate this planner over a
variety of virtual and real world environments, including some that require
partial footholds and rough terrain using the Atlas and Valkyrie humanoid
robots.


  We consider a system of $N$ bosons interacting through a singular two-body
potential scaling with $N$ and having the form $N^{3\beta-1} V (N^\beta x)$,
for an arbitrary parameter $\beta \in (0,1)$. We provide a norm-approximation
for the many-body evolution of initial data exhibiting Bose-Einstein
condensation in terms of a cubic nonlinear Schr\"odinger equation for the
condensate wave function and of a unitary Fock space evolution with a generator
quadratic in creation and annihilation operators for the fluctuations.


  In this paper, we consider a general K-user Gaussian multiple-input
multiple-output (MIMO) broadcast channel (BC). We assume that the channel state
is deterministic and known to all the nodes. While the private-message capacity
region is well known to be achievable with dirty paper coding (DPC), we are
interested in the simpler linearly precoded transmission schemes. In
particular, we focus on linear precoding schemes combined with rate-splitting
(RS). First, we derive an achievable rate region with minimum mean square error
(MMSE) precoding at the transmitter and joint decoding of the sub-messages at
the receivers. Then, we study the achievable sum rate of this scheme and obtain
two findings: 1) an analytically tractable upper bound on the sum rate that is
shown numerically to be a close approximation, and 2) how to reduce the number
of active streams -- crucial to the overall complexity -- while preserving the
sum rate to within a constant loss. The latter results in two practical
algorithms: a stream elimination algorithm and a stream ordering algorithm.
Finally, we investigate the constant-gap optimality of linearly precoded RS
with respect to the capacity. Our result reveals that, while the achievable
rate of linear precoding alone can be arbitrarily far from the capacity, the
introduction of RS can help achieve the capacity region to within a constant
gap in the two-user case. Nevertheless, we prove that the RS scheme's
constant-gap optimality does not extend to the three-user case. Specifically,
we show, through a pathological example, that the gap between the sum rate and
the sum capacity can be unbounded.


  In this paper, some new inequalities of Ostrowski type established for the
class of m- and (alpha,m)-geometrically convex functions which are
generalizations of geometric convex functions.


  An arc-weighted digraph is a pair $(D,\omega)$ where $D$ is a digraph and
$\omega$ is an \emph{arc-weight function} that assigns\ to each arc $uv$ of $D$
a nonzero real number $\omega(uv)$. Given an arc-weighted digraph $(D,\omega)$
with vertices $v_{1},\ldots,v_{n}$, the weighted adjacency matrix of
$(D,\omega)$ is defined as the matrix $A(D,\omega)=[a_{ij}]$ where
$a_{ij}=\omega(v_{i}v_{j})$, if $v_{i}v_{j}\ $an arc of $D$ and $0$ otherwise.
Let $(D,\omega)$ be a positive arc-weighted digraphs and assume that $D$ is
loopless and symmetric. A skew-signing of $(D,\omega)$ is an arc-weight
function $\omega^{\prime}$ such that $\omega^{\prime}(uv)=\pm \omega(uv)$ and
$\omega^{\prime}(uv)\omega^{\prime}(vu)<0$ for every arc $uv$ of $D$. In this
paper, we give necessary and sufficient conditions under which the
characteristic polynomial of $A(D,\omega^{\prime})$ is the same for every
skew-signing $\omega^{\prime}$ of $(D,\omega)$. Our Main Theorem generalizes a
result of Cavers et al (2012) about skew-adjacency matrices of graphs.


  We consider the Gibbs representation over space-time of non-equilibrium
dynamics of Hamiltonian systems defined on a lattice with local interactions.
We first write the corresponding action functional as a sum of local terms,
defining a local action functional. We replace the local system by a
translation-invariant system whose dynamics has an identical space-time
characterization. We study in details the irreversible properties of the new
dynamics, define the local conductivity and show its equivalence with the
Green-Kubo formula. Given the definition of the local heat conductivity and
using conservation of energy, we derive the shape of the temperature profile.
Next, we find an explicit formula for the non-equilibrium stationary measure of
harmonic systems. Finally, we apply our scheme to various approximations of
anharmonic Hamiltonian models, show how to compute their thermal conductivity
and recover results confirmed in numerical simulations.


  The Dirichlet process mixture (DPM) is a ubiquitous, flexible Bayesian
nonparametric statistical model. However, full probabilistic inference in this
model is analytically intractable, so that computationally intensive techniques
such as Gibb's sampling are required. As a result, DPM-based methods, which
have considerable potential, are restricted to applications in which
computational resources and time for inference is plentiful. For example, they
would not be practical for digital signal processing on embedded hardware,
where computational resources are at a serious premium. Here, we develop
simplified yet statistically rigorous approximate maximum a-posteriori (MAP)
inference algorithms for DPMs. This algorithm is as simple as K-means
clustering, performs in experiments as well as Gibb's sampling, while requiring
only a fraction of the computational effort. Unlike related small variance
asymptotics, our algorithm is non-degenerate and so inherits the "rich get
richer" property of the Dirichlet process. It also retains a non-degenerate
closed-form likelihood which enables standard tools such as cross-validation to
be used. This is a well-posed approximation to the MAP solution of the
probabilistic DPM model.


  Thermal plasma characteristics inside an atmospheric pressure Radio-Frequency
Argon plasma torch have been studied by numerically solving axis-symmetric 2-D
Magnetohydrodynamics equations, energy transport equations and species
conservation equation coupled with 2D Maxwell equations in the vector potential
form. A renormalization group k - epsilon model was employed to study the
turbulence within the torch. Helium is mixed with Argon for injection as the
sheath gas, and its effect on the control characteristics of the torch has been
studied. A control volume approach and semi-implicit pressure linked equations
revised (SIMPLER) algorithm was used to solve the above set of equations to
obtain the flow, temperature, turbulence and EM source fields within the torch.
Finally, a comparison of the results obtained in our present calculation has
been made with other works of similar nature. The torch geometry, flow rates
and power dissipation values used in the present calculation are similar to the
standard ones available in literature.


  From our sample of spotted late-type stars showing surface differential
rotation we find that the relationship between the rotation period and the
surface shear coefficient $\alpha=\Delta\Omega/\Omega_{\rm eq}$ is
significantly different for single stars compared to members in close binaries.
Single stars follow a general trend that $\alpha$ increases with the rotation
period. However, differential rotation of stars in close binary systems shows
much weaker dependence on the rotation, if any, suggesting that in such systems
tidal forces operate as a controlling mechanism of differential rotation.


  Transport properties of metal-molecule-metal junctions containing monolayer
of conjugated and saturated molecules with characteristic dimensions in the
range of 30-300 nm are correlated with microscopic topography, stress and
chemical bonding at metal-molecule interfaces. Our statistically significant
dataset allows us to conclude that the conductivity of organic molecules ~1.5
nm long is at least 4 orders of magnitude lower than is commonly believed.


  This paper investigates censorship from a linguistic perspective. We collect
a corpus of censored and uncensored posts on a number of topics, build a
classifier that predicts censorship decisions independent of discussion topics.
Our investigation reveals that the strongest linguistic indicator of censored
content of our corpus is its readability.


  Static authentication methods, like passwords, grow increasingly weak with
advancements in technology and attack strategies. Continuous authentication has
been proposed as a solution, in which users who have gained access to an
account are still monitored in order to continuously verify that the user is
not an imposter who had access to the user credentials. Mouse dynamics is the
behavior of a users mouse movements and is a biometric that has shown great
promise for continuous authentication schemes. This article builds upon our
previous published work by evaluating our dataset of 40 users using three
machine learning and deep learning algorithms. Two evaluation scenarios are
considered: binary classifiers are used for user authentication, with the top
performer being a 1-dimensional convolutional neural network with a peak
average test accuracy of 85.73% across the top 10 users. Multi class
classification is also examined using an artificial neural network which
reaches an astounding peak accuracy of 92.48% the highest accuracy we have seen
for any classifier on this dataset.


  Vocalizations and less often gestures have been the object of linguistic
research over decades. However, the development of a general theory of
communication with human language as a particular case requires a clear
understanding of the organization of communication through other means.
Infochemicals are chemical compounds that carry information and are employed by
small organisms that cannot emit acoustic signals of optimal frequency to
achieve successful communication. Here the distribution of infochemicals across
species is investigated when they are ranked by their degree or the number of
species with which it is associated (because they produce or they are sensitive
to it). The quality of the fit of different functions to the dependency between
degree and rank is evaluated with a penalty for the number of parameters of the
function. Surprisingly, a double Zipf (a Zipf distribution with two regimes
with a different exponent each) is the model yielding the best fit although it
is the function with the largest number of parameters. This suggests that the
world wide repertoire of infochemicals contains a chemical nucleus shared by
many species and reminiscent of the core vocabularies found for human language
in dictionaries or large corpora.


  In this work, we address the problem of finding globally optimal power
allocation strategies to maximize the users sum-rate (SR) as well as system
energy efficiency (EE) in the downlink of single-cell multicarrier
non-orthogonal multiple access (MC-NOMA) systems. Each NOMA cluster includes a
set of users in which the well-known superposition coding (SC) combined with
successive interference cancellation (SIC) technique is applied among them. By
obtaining the closed-form expression of intra-cluster power allocation, we show
that MC-NOMA can be equivalently transformed to a virtual orthogonal multiple
access (OMA) system, where the effective channel gain of these virtual OMA
users is obtained in closed-form. Then, the SR and EE maximization problems are
solved by using very fast water-filling and Dinkelbach algorithms,
respectively. The equivalent transformation of MC-NOMA to the virtual OMA
system brings new theoretical insights, which are discussed throughout the
paper. The extensions of our analysis to other scenarios, such as considering
users rate fairness, admission control, long-term performance, and a number of
future next-generation multiple access (NGMA) schemes enabling recent advanced
technologies, e.g., reconfigurable intelligent surfaces are discussed.
Extensive numerical results are provided to show the performance gaps between
single-carrier NOMA (SC-NOMA), OMA-NOMA, and OMA.


  There has been a growing interest in extracting formal descriptions of the
system behaviors from data. Signal Temporal Logic (STL) is an expressive formal
language used to describe spatial-temporal properties with interpretability.
This paper introduces TLINet, a neural-symbolic framework for learning STL
formulas. The computation in TLINet is differentiable, enabling the usage of
off-the-shelf gradient-based tools during the learning process. In contrast to
existing approaches, we introduce approximation methods for max operator
designed specifically for temporal logic-based gradient techniques, ensuring
the correctness of STL satisfaction evaluation. Our framework not only learns
the structure but also the parameters of STL formulas, allowing flexible
combinations of operators and various logical structures. We validate TLINet
against state-of-the-art baselines, demonstrating that our approach outperforms
these baselines in terms of interpretability, compactness, rich expressibility,
and computational efficiency.


  We report the results of a search for axionlike dark matter using nuclear
magnetic resonance (NMR) techniques. This search is part of the multi-faceted
Cosmic Axion Spin Precession Experiment (CASPEr) program. In order to
distinguish axionlike dark matter from magnetic fields, we employ a
comagnetometry scheme measuring ultralow-field NMR signals involving two
different nuclei ($^{13}$C and $^{1}$H) in a liquid-state sample of
acetonitrile-2-$^{13}$C ($^{13}$CH$_{3}$CN). No axionlike dark matter signal
was detected above background. This result constrains the parameter space
describing the coupling of the gradient of the axionlike dark matter field to
nucleons to be $g_{aNN}<6\times 10^{-5}$ GeV$^{-1}$ (95$\%$ confidence level)
for particle masses ranging from $10^{-22}$ eV to $1.3\times10^{-17}$ eV,
improving over previous laboratory limits for masses below $10^{-21}$ eV. The
result also constrains the coupling of nuclear spins to the gradient of the
square of the axionlike dark matter field, improving over astrophysical limits
by orders of magnitude over the entire range of particle masses probed.


  Nearly every massive galaxy contains a supermassive black hole (BH) at its
center. For decades, both theory and numerical simulations have indicated that
BHs play a central role in regulating the growth and quenching of galaxies.
Specifically, BH feedback by heating or blowing out the interstellar medium
(ISM) serves as the groundwork for current models of massive galaxy formation.
However, direct evidence for such an impact on the galaxy-wide ISM from BHs has
only been found in some extreme objects. For general galaxy populations, it
remains unclear whether and how BHs impact the ISM. Here based on a large
sample of nearby galaxies with measurements of masses of both black holes and
atomic hydrogen, the major component of cold ISM, we reveal that the atomic
hydrogen content ($f_{\rm HI} = M_{\rm HI}/M_{\star}$) is tightly and
anti-correlated with black hole mass ($M_{\rm BH}$) with $f_{\rm HI} \propto
M^{-\alpha}_{\rm BH}$ ($\alpha \sim 0.5-0.6$). This correlation is valid across
five orders of magnitude in $M_{\rm BH}$. Once this correlation is taken into
account, $f_{\rm HI}$ loses dependence on other galactic parameters,
demonstrating that $M_{\rm BH}$ serves as the primary driver of $f_{\rm HI}$.
These findings provide critical evidence for how the accumulated energy from BH
accretion impacts galaxy-wide ISM, representing a crucial step forward in our
understanding on the role of BHs in regulating the growth and quenching of
massive galaxies.


  The gamma -> 3 pi form factor was calculated in a simple-minded constituent
model with a constant quark mass parameter, as well as in the Schwinger-Dyson
approach. The comparison of these and various other theoretical results on this
anomalous process, as well as the scarce already available data (hopefully to
be supplemented by more accurate CEBAF data), seem to favor Schwinger-Dyson
modeling which would yield relatively small low-momentum values of the
constituent (dynamically dressed) quark mass function.


  An overview of the theory of the upper critical field in dirty two-gap
superconductors, with a particular emphasis on MgB$_2$ is given. We focus here
on the maximum $H_{c2}$ which may be achieved by increasing intraband
scattering, and on the limitations imposed by weak interband scattering and
paramagnetic effects. In particular, we discuss recent experiments which have
recently demonstrated ten-fold increase of $H_{c2}$ in dirty carbon-doped films
as compared to single crystals, so that the $H_{c2}(0)$ parallel to the ab
planes may approach the BCS paramagnetic limit, $H_p[T] = 1.84T_c[K] \simeq
60-70T$. New effects produced by weak interband scattering in the two-gap
Ginzburg-Landau equations and $H_{c2}(T)$ in ultrathin MgB$_2$ films are
addressed.


  We report spatially resolved spectroscopy of both components of the low-mass
pre-main-sequence binary GV Tau. High resolution spectroscopy in the K- and
L-bands is used to characterize the stellar properties of the binary and to
explore the nature of the circumstellar environment. We find that the southern
component, GV Tau S, is a radial velocity variable, possibly as a result of an
unseen low-mass companion. The strong warm gaseous HCN absorption reported
previously toward GV Tau S (Gibb et al. 2007) was not present during the epoch
of our observations. Instead, we detect warm (~500 K) molecular absorption with
similar properties toward the northern infrared companion, GV Tau N. At the
epoch of our observations, the absorbing gas toward GV Tau N was approximately
at the radial velocity of the GV Tau molecular envelope, but it was redshifted
with respect to the star by ~13 km/s. One interpretation of our results is that
GV Tau N is also a binary and that most of the warm molecular absorption arises
in a circumbinary disk viewed close to edge-on.


  Spin-orbit coupling is key to all-electrical control of quantum-dot spin
qubits, and is frequently stronger for holes than for electrons. Here we
investigate Pauli spin blockade for two heavy holes in a gated double quantum
dot in an in-plane magnetic field. The interplay of the complex Zeeman and
spin-orbit couplings causes a blockade leakage current anisotropic in the field
direction. The period of the anisotropic leakage is critically dependent on the
relative magnitude of Zeeman interaction terms linear and cubic in the magnetic
field. The current and singlet-triplet exchange splitting can be effectively
adjusted by an appropriate choice of field direction, providing a simple
control variable for quantum information processing and a way of tailoring
magnetic interactions in hole spin qubits.


  Friction is one of the main sources of dissipation at liquid water/solid
interfaces. Despite recent progress, a detailed understanding of water/solid
friction in connection with the structure and energetics of the solid surface
is lacking. Here we show for the first time that \textit{ab initio} molecular
dynamics can be used to unravel the connection between the structure of
nanoscale water and friction for liquid water in contact with graphene and with
hexagonal boron nitride. We find that whilst the interface presents a very
similar structure between the two sheets, the friction coefficient on boron
nitride is $\approx 3$ times larger than that on graphene. This comes about
because of the greater corrugation of the energy landscape on boron nitride
arising from specific electronic structure effects. We discuss how a subtle
dependence of the friction on the atomistic details of a surface, that is not
related to its wetting properties, may have a significant impact on the
transport of water at the nanoscale, with implications for the development of
membranes for desalination and for osmotic power harvesting.


  Conditionally on the Riemann Hypothesis we obtain bounds of the correct order
of magnitude for the 2k-th moment of the Riemann zeta-function for all positive
real k < 2.181. This provides for the first time an upper bound of the correct
order of magnitude for some k > 2; the case of k = 2 corresponds to a classical
result of Ingham. We prove our result by establishing a connection between
moments with k > 2 and the so-called "twisted fourth moment". This allows us to
appeal to a recent result of Hughes and Young. Furthermore we obtain a
point-wise bound for |zeta(1/2 + it)|^{2r} (with 0 < r < 1) that can be
regarded as a multiplicative analogue of Selberg's bound for S(T). We also
establish asymptotic formulae for moments (k < 2.181) slightly off the
half-line.


  We investigate functors between abelian categories having a left adjoint and
a right adjoint that are \emph{similar} (these functors are called
\emph{quasi-Frobenius functors}). We introduce the notion of a
\emph{quasi-Frobenius bimodule} and give a characterization of these bimodules
in terms of quasi-Frobenius functors. Some applications to corings and graded
rings are presented. In particular, the concept of quasi-Frobenius homomorphism
of corings is introduced. Finally, a version of the endomorphism ring Theorem
for quasi-Frobenius extensions in terms of corings is obtained.


  We consider an invariant quantum Hamiltonian $H=-\Delta_{LB}+V$ in the
$L^{2}$ space based on a Riemannian manifold $\tilde{M}$ with a countable
discrete symmetry group $\Gamma$. Typically, $\tilde{M}$ is the universal
covering space of a multiply connected Riemannian manifold $M$ and $\Gamma$ is
the fundamental group of $M$. On the one hand, following the basic step of the
Bloch analysis, one decomposes the $L^{2}$ space over $\tilde{M}$ into a direct
integral of Hilbert spaces formed by equivariant functions on $\tilde{M}$. The
Hamiltonian $H$ decomposes correspondingly, with each component $H_{\Lambda}$
being defined by a quasi-periodic boundary condition. The quasi-periodic
boundary conditions are in turn determined by irreducible unitary
representations $\Lambda$ of $\Gamma$. On the other hand, fixing a
quasi-periodic boundary condition (i.e., a unitary representation $\Lambda$ of
$\Gamma$) one can express the corresponding propagator in terms of the
propagator associated to the Hamiltonian $H$. We discuss these procedures in
detail and show that in a sense they are mutually inverse.


  We give a new decay framework for general dissipative hyperbolic system and
hyperbolic-parabolic composite system, which allow us to pay less attention on
the traditional spectral analysis in comparison with previous efforts. New
ingredients lie in the high-frequency and low-frequency decomposition of a
pseudo-differential operator and an interpolation inequality related to
homogeneous Besov spaces of negative order. Furthermore, we develop the
Littlewood-Paley pointwise energy estimates and new time-weighted energy
functionals to establish the optimal decay estimates on the framework of
spatially critical Besov spaces for degenerately dissipative hyperbolic system
of balance laws. Based on the $L^{p}(\mathbb{R}^{n})$ embedding and improved
Gagliardo-Nirenberg inequality, the optimal
$L^{p}(\mathbb{R}^{n})$-$L^{2}(\mathbb{R}^{n})(1\leq p<2)$ decay rates and
$L^{p}(\mathbb{R}^{n})$-$L^{q}(\mathbb{R}^{n})(1\leq p<2\leq q\leq\infty)$
decay rates are further shown. Finally, as a direct application, the optimal
decay rates for 3D damped compressible Euler equations are also obtained.


  Different aspects concerning the rigorous definition of the traces and
determinants of the operators involved in a procedure ---proposed by Neuberger
and others--- for avoiding fermion doublers on the lattice, are considered. A
result of the analysis is that it seems unclear that the consequences derived
from the independent treatment of the traces of the two operators contributing
to the index relation on the lattice, as carried out in recent manuscripts, can
be given rigorous mathematical footing, in particular, that these treatments
can commute with the continuum limit ---the lattice regularized trace being
additive all the way through the limit, while the otherwise regularized trace
in the continuum is not so.


  In this paper, we propose a certified reduced basis (RB) method for
quasilinear elliptic problems together with its application to nonlinear
magnetostatics equations, where the later model permanent magnet synchronous
motors (PMSM). The parametrization enters through the geometry of the domain
and thus, combined with the nonlinearity, drives our reduction problem. We
provide a residual-based a-posteriori error bound which, together with the
Greedy approach, allows to construct reduced-basis spaces of small dimensions.
We use the empirical interpolation method (EIM) to guarantee the efficient
offline-online computational procedure. The reduced-basis solution is then
obtained with the surrogate of the Newton's method. The numerical results
indicate that the proposed reduced-basis method provides a significant
computational gain, compared to a finite element method.


  In this paper it is studied a space-time duality web that maps electric into
magnetic (and magnetic into electric) charged classical stationary rotating
solutions for $2+1$-dimensional Abelian Einstein Maxwell Chern-Simons theories.
A first duality map originally suggested by Kogan for static charged solutions
is extended to stationary rotating space-times and are suggested two new
space-time dualities maps. The three dualities complete a close duality web. It
is also shown that in $3+1$-dimensions these dualities are only possible for
systems which exhibit non-projected cylindrical symmetry and are not related to
the standard electromagnetic duality of Maxwell equations which acts on the
physical fields and charges. Generalization to $N$-form theories in higher
dimensional space-times is briefly discussed.


  We prove an entropic uncertainty relation for two quantum channels, extending
the work of Frank and Lieb for quantum measurements. This is obtained via a
generalized strong super-additivity (SSA) of quantum entropy. Motivated by
Petz's algebraic SSA inequality, we also obtain a generalized SSA for quantum
relative entropy. As a special case, it gives an improved data processing
inequality.


  We investigate the quantum dynamics of a periodically kicked Bose-Einstein
Condensate confined in a one dimensional (1D) Box both numerically and
theoretically, emphasizing on the phenomena of quantum resonance and
anti-resonance. The quantum resonant behavior of BEC is different from the
single particle case but the anti-resonance condition ($T = 2\pi$ and $\alpha =
0$) is not affected by the atomic interaction. For the anti-resonance case, the
nonlinearity (atom interaction) causes the transition between oscillation and
quantum beating. For the quantum resonance case, because of the coherence of
BEC, the energy increase is oscillating and the rate is dramatically affected
by the many-body interaction. We also discuss the relation between the quantum
resonant behavior and the KAM or non-KAM property of the corresponding
classical system.


  For a given m>=1, we consider the finite non-abelian groups G for which
|C_G(g):<g>|<=m for every g in G\Z(G). We show that the order of G can be
bounded in terms of m and the largest prime divisor of the order of G. Our
approach relies on dealing first with the case where G is a non-abelian finite
p-group. In that situation, if we take m=p^k to be a power of p, we show that
|G|<=p^{2k+2} with the only exception of Q_8. This bound is best possible, and
implies that the order of G can be bounded by a function of m alone in the case
of nilpotent groups.


  We propose a new analogue model of gravity - the evolving quark gluon plasma
(QGP) produced in relativistic heavy ion collisions. This quark gluon plasma is
the "most inviscid" fluid known. Such low kinematic viscosity is believed to
reflect strongly correlated nature for QGP in these experiments. Hence, it may
provide a good example of a quantum fluid naturally suited to studies of
acoustic Hawking radiation. Due to rapid longitudinal expansion, presence of a
sonic horizon is also naturally guaranteed here, though, in general, this
horizon is not static. Using Ultra relativistic quantum molecular dynamics
(UrQMD) simulations, we show that, under certain conditions, the longitudinal
velocity of the plasma, near the sonic horizon, can become time independent for
a short span during the evolution of the system. During this period, we can
have a conformally static acoustic metric with a (conformal) Killing horizon
coinciding with the apparent horizon. An asymptotic observer will then see a
thermal flux of phonons, constituting the Hawking radiation, coming from the
horizon. For the relatively low energy collision considered here, where the
resulting QCD system is governed by non-relativistic hydrodynamics, we estimate
the Hawking temperature to be about 4-5 MeV (with the temperature of the QCD
fluid being about 135 MeV). We discuss the experimental signatures of this
Hawking radiation in terms of a thermal component in the rapidity dependence of
the transverse momentum distribution of detected particles. We also discuss
extension to ultra-relativistic case which should lead to a higher Hawking
temperature, along with the effects of dynamical horizon leading to blue/red
shift of the temperature.


  A formulation of non-relativistic quantum mechanics in terms of Newtonian
particles is presented in the shape of a set of three postulates. In this new
theory, quantum systems are described by ensembles of signed particles which
behave as field-less classical objects which carry a negative or positive sign
and interact with an external potential by means of creation and annihilation
events only. This approach is shown to be a generalization of the signed
particle Wigner Monte Carlo method which reconstructs the time-dependent Wigner
quasi-distribution function of a system and, therefore, the corresponding
Schroedinger time-dependent wave-function. Its classical limit is discussed and
a physical interpretation, based on experimental evidences coming from quantum
tomography, is suggested. Moreover, in order to show the advantages brought by
this novel formulation, a straightforward extension to relativistic effects is
discussed. To conclude, quantum tunnelling numerical experiments are performed
to show the validity of the suggested approach.


  Procedural planning aims to implement complex high-level goals by
decomposition into sequential simpler low-level steps. Although procedural
planning is a basic skill set for humans in daily life, it remains a challenge
for large language models (LLMs) that lack a deep understanding of the
cause-effect relations in procedures. Previous methods require manual exemplars
to acquire procedural planning knowledge from LLMs in the zero-shot setting.
However, such elicited pre-trained knowledge in LLMs induces spurious
correlations between goals and steps, which impair the model generalization to
unseen tasks. In contrast, this paper proposes a neuro-symbolic procedural
PLANner (PLAN) that elicits procedural planning knowledge from the LLMs with
commonsense-infused prompting. To mitigate spurious goal-step correlations, we
use symbolic program executors on the latent procedural representations to
formalize prompts from commonsense knowledge bases as a causal intervention
toward the Structural Causal Model. Both automatic and human evaluations on
WikiHow and RobotHow show the superiority of PLAN on procedural planning
without further training or manual exemplars.


  Simulating quantum physical processes has been one of the major motivations
for quantum information science. Quantum channels, which are completely
positive and trace preserving processes, are the standard mathematical language
to describe quantum evolution, while in recent years quantum superchannels have
emerged as the substantial extension. Superchannels capture effects of quantum
memory and non-Markovianality more precisely, and have found broad applications
in universal models, algorithm, metrology, discrimination tasks, as examples.
Here, we report an experimental simulation of qubit superchannels in a nuclear
magnetic resonance (NMR) system with high accuracy, based on a recently
developed quantum algorithm for superchannel simulation. Our algorithm applies
to arbitrary target superchannels, and our experiment shows the high quality of
NMR simulators for near-term usage. Our approach can also be adapted to other
experimental systems and demonstrates prospects for more applications of
superchannels.


  In recent years, there has been a growing interest in the effects of data
poisoning attacks on data-driven control methods. Poisoning attacks are
well-known to the Machine Learning community, which, however, make use of
assumptions, such as cross-sample independence, that in general do not hold for
linear dynamical systems. Consequently, these systems require different attack
and detection methods than those developed for supervised learning problems in
the i.i.d.\ setting. Since most data-driven control algorithms make use of the
least-squares estimator, we study how poisoning impacts the least-squares
estimate through the lens of statistical testing, and question in what way data
poisoning attacks can be detected. We establish under which conditions the set
of models compatible with the data includes the true model of the system, and
we analyze different poisoning strategies for the attacker. On the basis of the
arguments hereby presented, we propose a stealthy data poisoning attack on the
least-squares estimator that can escape classical statistical tests, and
conclude by showing the efficiency of the proposed attack.


  We apply the ideas of derived algebraic geometry and topological field theory
to the representation theory of reductive groups. Our focus is the Hecke
category of Borel-equivariant D-modules on the flag variety of a complex
reductive group G (equivalently, the category of Harish Chandra bimodules of
trivial central character) and its monodromic variant. The Hecke category is a
categorified analogue of the finite Hecke algebra, which is a
finite-dimensional semi-simple symmetric Frobenius algebra. We establish
parallel properties of the Hecke category, showing it is a two-dualizable
Calabi-Yau monoidal category, so that in particular, its monoidal (Drinfeld)
center and trace coincide. We calculate that they are identified through the
Springer correspondence with Lusztig's unipotent character sheaves. It follows
that Hecke module categories, such as categories of Lie algebra representations
and Harish Chandra modules for G and its real forms, have characters which are
themselves character sheaves. Furthermore, the Koszul duality for Hecke
categories provides a Langlands duality for unipotent character sheaves. This
can be viewed as part of a dimensionally reduced version of the geometric
Langlands correspondence, or as S-duality for a maximally supersymmetric gauge
theory in three dimensions.


  We determine the distribution of cooling ages of massive Gaia EDR3 white
dwarfs identified with over 90% probability within 200 pc and with mass in the
range 0.95-1.25 $M_\odot$. Using three sets of publicly available models, we
consider sub-samples of these white dwarfs sorted into three equally spaced
mass bins. Under the assumption of a constant white dwarf formation rate, we
find an excess of white dwarfs both along the Q branch and below it,
corresponding respectively to stars that are in the process of freezing and
those that are completely frozen. We compare the cooling age distributions for
each of these bins to the recently determined time-varying star formation rate
of Gaia DR2 main sequence stars. For white dwarfs in the two lightest mass
bins, spanning the mass range 0.95-1.15 $M_\odot$, we find that the cumulative
cooling age distribution is statistically consistent with the expectation from
the star formation rate. For white dwarfs in the heaviest mass bin, 1.15-1.25
$M_\odot$, we find that their cumulative distribution is inconsistent with the
star formation rate for all of the models considered; instead, we find that
their cooling age distribution is well fitted by a linear combination of the
distribution expected for single stellar evolution products and the
distribution expected for double white dwarf merger products when approximately
40-50% of the 1.15-1.25 $M_\odot$ white dwarfs that formed over the past 4 Gyr
are produced through double white dwarf mergers.


  The aim of this paper is to show the existence of a canonical distance
$\mathsf d'$ defined on a locally Minkowski metric measure space $(\mathsf
X,\mathsf d,\mathfrak m)$ such that:
  i) $\mathsf d'$ is equivalent to $\mathsf d$,
  ii) $(\mathsf X, \mathsf d', \mathfrak m)$ is infinitesimally Hilbertian.
  This new regularity assumption on $(\mathsf X, \mathsf d,\mathfrak m)$
essentially forces the structure to be locally similar to a Minkowski space and
defines a class of metric measure structures which includes all the Finsler
manifolds, and it is actually strictly larger. The required distance $\mathsf
d'$ will be the intrinsic distance $\mathsf d_\mathsf{KS}$ associated to the
so-called Korevaar-Schoen energy, which is proven to be a quadratic form. In
particular, we show that the Cheeger energy associated to the metric measure
space $(\mathsf X, \mathsf d_\mathsf{KS}, \mathfrak m)$ is in fact the
Korevaar-Schoen energy.


  Jake Goodman and Ulrich Kr\"ahmer have recently shown that a twisted
Calabi-Yau algebra $A$ with modular automorphism $\sigma$ and dimension $d$ can
be "untwisted," in the sense that the Ore extensions $A[X;\sigma]$ and
$A[X^{\pm1};\sigma]$ are Calabi-Yau algebras of dimension $d+1$. In this note
we show that this in fact extends more generally to the case where we start
with an algebra with van den Bergh duality.


  The ARAPUCA concept has been proposed as a simple and neat solution for
increasing the effective collection area of SiPMs through the shifting and
trapping of scintillation light in noble liquids, thus with great potential for
improving timing and calorimetry resolution in neutrino and dark matter search
experiments using time projection chambers. It is expected to achieve a single
photon detection efficiency larger than 1\%. The initial design consists of a
box made of highly reflective internal surface material and with an acceptance
window for photons composed of two shifters and a dichroic filter. The first
shifter converts liquid argon scintillation VUV light to a photon of wavelength
smaller than the dichroic cutoff, so the surface is highly transparent to it.
When passing through the dichroic filter, it reaches the second shifter which
allows the photon to be shifted to the visible region and be detected by the
SiPM nested inside it. When it enters the box, the photon will likely reflect a
few times, including on the dichroic filter surface, before being detected. We
present a full numerical description of the device using a Monte Carlo
framework, including characterization of the acceptance window, models of
reflection of different materials, and sensor quantum efficiency, that can now
be used to further improve the detection efficiency by comparing different
geometries, positions of SiPM and materials. Estimates of simulated
efficiencies, number of reflections and acquisition time are presented and
compared to analytical calculations. Those are very promising results, giving a
total efficiency for the detection of scintillation light in liquid argon of
1.7$\rm \pm$0.3\%. Comparison of the estimated total efficiency with a
preliminary result from an experimental test with an ARAPUCA prototype made in
Brazil is also presented.


  A distributed order fractional diffusion equation is considered. Distributed
order derivatives are fractional derivatives that have been integrated over the
order of the derivative within a given range. In this paper sub-diffusive cases
are considered. That is, the order of the time derivative ranges from zero to
one. The equation is solved for Dirichlet, Neumann, and Cauchy boundary
conditions. The time dependence for each of the three cases is found to be a
functional of the diffusion parameter. This functional is shown to have decay
properties. Upper and lower bounds are computed for the functional. Examples
are also worked out for comparative decay rates.


  In the present paper we prove that for any open connected set
$\Omega\subset\mathbb{R}^{n+1}$, $n\geq 1$, and any $E\subset \partial \Omega$
with $\mathcal{H}^n(E)<\infty$, absolute continuity of the harmonic measure
$\omega$ with respect to the Hausdorff measure on $E$ implies that $\omega|_E$
is rectifiable. This solves an open problem on harmonic measure which turns out
to be an old conjecture even in the planar case $n=1$.


  There has been an increased interest in multimodal language processing
including multimodal dialog, question answering, sentiment analysis, and speech
recognition. However, naturally occurring multimodal data is often imperfect as
a result of imperfect modalities, missing entries or noise corruption. To
address these concerns, we present a regularization method based on tensor rank
minimization. Our method is based on the observation that high-dimensional
multimodal time series data often exhibit correlations across time and
modalities which leads to low-rank tensor representations. However, the
presence of noise or incomplete values breaks these correlations and results in
tensor representations of higher rank. We design a model to learn such tensor
representations and effectively regularize their rank. Experiments on
multimodal language data show that our model achieves good results across
various levels of imperfection.


  We consider a spatially-heterogeneous generalization of a well-established
model for the dynamics of the Human Immunodeficiency Virus-type 1 (HIV) within
a susceptible host. The model consists of a nonlinear system of three coupled
reaction-diffusion equations with parameters that may vary spatially. Upon
formulating the model, we prove that it preserves the positivity of initial
data and construct global-in-time solutions that are both bounded and smooth.
Finally, additional results concerning the local and global asymptotic behavior
of these solutions are also provided.


  The Casimir interaction energy for a class of discrete self-similar
configuration of parallel plates is evaluated using existing methods. The
similarities to characteristics of an attractive Casimir force is deduced only
at infinite range of configuration. Further, the emergence of Casimir-like
energy is qualitatively described for a Gaussian model of Landau-Ginzburg
scalar field. Its relevance to self-similarity in the statistical field is
shown at infinite range of fluctuations.


  We count the Bethe states of quantum integrable models with twisted boundary
conditions using the Witten index of 2d supersymmetric gauge theories. For
multi-component models solvable by the nested Bethe ansatz, the result is a
novel restricted occupancy problem. For the SU(3) spin chain and the t-J model,
we propose formulae for the solution count on singular loci in the space of
twist parameters.


  Satisfiability Modulo Theories (SMT) solvers incorporate decision procedures
for theories of data types that commonly occur in software. This makes them
important tools for automating verification problems. A limitation frequently
encountered is that verification problems are often not fully expressible in
the theories supported natively by the solvers. Many solvers allow the
specification of application-specific theories as quantified axioms, but their
handling is incomplete outside of narrow special cases.
  In this work, we show how SMT solvers can be used to obtain complete decision
procedures for local theory extensions, an important class of theories that are
decidable using finite instantiation of axioms. We present an algorithm that
uses E-matching to generate instances incrementally during the search,
significantly reducing the number of generated instances compared to eager
instantiation strategies. We have used two SMT solvers to implement this
algorithm and conducted an extensive experimental evaluation on benchmarks
derived from verification conditions for heap-manipulating programs. We believe
that our results are of interest to both the users of SMT solvers as well as
their developers.


  This paper considers links between the original risk-sensitive performance
criterion for quantum control systems and its recent quadratic-exponential
counterpart. We discuss a connection between the minimization of these cost
functionals and robustness with respect to uncertainty in system-environment
quantum states whose deviation from a nominal state is described in terms of
the quantum relative entropy. These relations are similar to those in minimax
LQG control for classical systems. The results of the paper can be of use in
providing a rational choice of the risk-sensitivity parameter in the context of
robust quantum control with entropy theoretic quantification of statistical
uncertainty in the system-field state.


  Supernova Ia are bright explosive events that can be used to estimate
cosmological distances, allowing us to study the expansion of the Universe.
They are understood to result from a thermonuclear detonation in a white dwarf
that formed from the exhausted core of a star more massive than the Sun.
However, the possible progenitor channels leading to an explosion are a
long-standing debate, limiting the precision and accuracy of supernova Ia as
distance indicators. Here we present HD265435, a binary system with an orbital
period of less than a hundred minutes, consisting of a white dwarf and a hot
subdwarf -- a stripped core-helium burning star. The total mass of the system
is 1.65+/-0.25 solar-masses, exceeding the Chandrasekhar limit (the maximum
mass of a stable white dwarf). The system will merge due to gravitational wave
emission in 70 million years, likely triggering a supernova Ia event. We use
this detection to place constraints on the contribution of hot subdwarf-white
dwarf binaries to supernova Ia progenitors.


  We address highly dynamic distributed systems modeled by time-varying graphs
(TVGs). We interest in proof of impossibility results that often use informal
arguments about convergence. First, we provide a distance among TVGs to define
correctly the convergence of TVG sequences. Next, we provide a general
framework that formally proves the convergence of the sequence of executions of
any deterministic algorithm over TVGs of any convergent sequence of TVGs.
Finally, we illustrate the relevance of the above result by proving that no
deterministic algorithm exists to compute the underlying graph of any
connected-over-time TVG, i.e., any TVG of the weakest class of long-lived TVGs.


  Let $I\subset S=K[x_1,...,x_n]$ be a lexsegment edge ideal or the Alexander
dual of such an ideal. In both cases it turns out that the arithmetical rank of
$I$ is equal to the projective dimension of $S/I.$


  Since the first cellular networks were trialled in the 1970s, we have
witnessed an incredible wireless revolution. From 1G to 4G, the massive traffic
growth has been managed by a combination of wider bandwidths, refined radio
interfaces, and network densification, namely increasing the number of antennas
per site. Due its cost-efficiency, the latter has contributed the most. Massive
MIMO (multiple-input multiple-output) is a key 5G technology that uses massive
antenna arrays to provide a very high beamforming gain and spatially
multiplexing of users, and hence, increases the spectral and energy efficiency.
It constitutes a centralized solution to densify a network, and its performance
is limited by the inter-cell interference inherent in its cell-centric design.
Conversely, ubiquitous cell-free Massive MIMO refers to a distributed Massive
MIMO system implementing coherent user-centric transmission to overcome the
inter-cell interference limitation in cellular networks and provide additional
macro-diversity. These features, combined with the system scalability inherent
in the Massive MIMO design, distinguishes ubiquitous cell-free Massive MIMO
from prior coordinated distributed wireless systems. In this article, we
investigate the enormous potential of this promising technology while
addressing practical deployment issues to deal with the increased
back/front-hauling overhead deriving from the signal co-processing.


  The interrelation between classicality/quantumness and symmetry of states is
discussed within the phase-space formulation of finite-dimensional quantum
systems. We derive representations for classicality measures
$\mathcal{Q}_N[H_{\varrho}]$ of states from the stratum of given symmetry type
$[H_{\varrho}]$ for the Hilbert-Schmidt ensemble of qudits. The expressions for
measures are given in terms of the permanents of matrices constructed from the
vertices of the special Wigner function's positivity polytope. The supposition
about the partial order of classicality indicators $\mathcal{Q}_N[H_{\varrho}]$
in accordance with the symmetry type of stratum is formulated.


  A "wireless fingerprint" which exploits hardware imperfections unique to each
device is a potentially powerful tool for wireless security. Such a fingerprint
should be able to distinguish between devices sending the same message, and
should be robust against standard spoofing techniques. Since the information in
wireless signals resides in complex baseband, in this paper, we explore the use
of neural networks with complex-valued weights to learn fingerprints using
supervised learning. We demonstrate that, while there are potential benefits to
using sections of the signal beyond just the preamble to learn fingerprints,
the network cheats when it can, using information such as transmitter ID (which
can be easily spoofed) to artificially inflate performance. We also show that
noise augmentation by inserting additional white Gaussian noise can lead to
significant performance gains, which indicates that this counter-intuitive
strategy helps in learning more robust fingerprints. We provide results for two
different wireless protocols, WiFi and ADS-B, demonstrating the effectiveness
of the proposed method.


  Under the advocacy of the international community, more and more research
topics have been built around the ocean. This paper proposed an implementation
scheme of marine wireless sensor network monitoring system based on LoRa and
MQTT. Different from the traditional network architecture, the system was
constructed by combining with two network forms, and according to their
respective characteristics, the overall design followed the transition from
LoRa to MQTT. We first used LoRa to interconnect the sensor nodes with the
gateway, and on this basis, the collected data was sent to the server
visualization platform through MQTT, the backend management server would
continuously refresh the monitoring page. At the same time, the client could
use a browser-based web application to directly access and call data for global
maritime information monitoring. In the future, we will further improve the
system and optimize the algorithm, to achieve more dimensions and deeper
exploration of the underwater world.


  Neyman-Scott is a classic example of an estimation problem with a
partially-consistent posterior, for which standard estimation methods tend to
produce inconsistent results. Past attempts to create consistent estimators for
Neyman-Scott have led to ad-hoc solutions, to estimators that do not satisfy
representation invariance, to restrictions over the choice of prior and more.
We present a simple construction for a general-purpose Bayes estimator,
invariant to representation, which satisfies consistency on Neyman-Scott over
any non-degenerate prior. We argue that the good attributes of the estimator
are due to its intrinsic properties, and generalise beyond Neyman-Scott as
well.


  Using a novel transformation involving the Jacobi Last Multiplier (JLM) we
derive an old integrability criterion due to Chiellini for the Li\'enard
equation. By combining the Chiellini condition for integrability and Jacobi's
Last Multiplier the Lagrangian and Hamiltonian of the Li\'enard equation is
derived. We also show that the Kukles equation is the only equation in the
Li\'enard family which satisfies both the Chiellini integrability and the
Sabatini criterion for isochronicity conditions. In addition we examine this
result by mapping the Li\'enard equation to a harmonic oscillator equation
using tacitly Chiellini's condition. Finally we provide a metriplectic and
complex Hamiltonian formulation of the Li\'enard equation through the use of
Chiellini condition for integrability.


  CP2 stars show periodic photometric, spectroscopic, and magnetic variations
with the rotational period. They are generally slow rotators, with rotational
periods exceeding half a day, except for the late B-type star HD 60431, which
has an unusually short rotational period of 0.4755 days. As slow rotation is
deemed a necessary criterion for the establishment of chemical peculiarities,
this characteristic renders HD 60431 a special object that might offer valuable
insight into, and constraints on, the formation and evolution of CP2 stars. Our
study aims at analysing the light variability, deriving atmospheric abundances,
and determining detailed physical parameters of HD 60431 to confirm its status
as the CP2 star with the shortest known rotational period, with special
emphasis on the rotational period evolution. Photometric indices and
high-resolution spectroscopy were employed to derive physical parameters,
evolutionary status, and atmospheric abundances of our target star. A light
variability study was carried out using combined sets of photometric data from
ground- and space-based facilities. A circularly polarised spectrum was
employed to check the presence of a longitudinal magnetic field in the star.
With an age of only 10 Myr, HD 60431 is situated close to the zero-age main
sequence and a member of the open cluster NGC 2547 in the Vela OB2 complex. We
confirm its status as a classical late B-type CP2 star showing strong
overabundances of Mg (1.8 dex), Si (1.9 dex), Ca (1.6 dex), Ti (2.2 dex), and
Fe (1.8 dex). No conclusive evidence for the presence of a strong magnetic
field was found in the available spectroscopic data. The available photometric
time series data confirm the short rotational period and indicate a slight
secular increase of the rotational period of P' = 7.5(6) ms/yr. HD 60431 is
indeed the CP2 star with the shortest known rotational period.


  We show that adiabatic, super-Hubble, and almost scale invariant density
fluctuations are produced by cosmic strings in a contracting universe. An
essential point is that isocurvature perturbations produced by topological
defects such as cosmic strings on super-Hubble scales lead to a source term
which seeds the growth of curvature fluctuations on these scales. Once the
symmetry has been restored at high temperatures, the isocurvature seeds
disappear, and the fluctuations evolve as adiabatic ones in the expanding
phase. Thus, cosmic strings may be resurrected as a mechanism for generating
the primordial density fluctuations observed today.


  In this talk I give an overview of the work done during the last 15 years in
collaboration with the late Adrian Patrascioiu. In this work we accumulated
evidence against the commonly accepted view that theories with nonabelian
symmetry -- either two dimensional nonlinear $\sigma$ models or four
dimensional Yang-Mills theories -- have the property of asymptotic freedom (AF)
usually ascribed to them.


  One-way quantum computing allows any quantum algorithm to be implemented
easily using just measurements. The difficult part is creating the universal
resource, a cluster state, on which the measurements are made. We propose a
radically new approach: a scalable method that uses a single, multimode optical
parametric oscillator (OPO). The method is very efficient and generates a
continuous-variable cluster state, universal for quantum computation, with
quantum information encoded in the quadratures of the optical frequency comb of
the OPO.


  Incorporating symmetry as an inductive bias into multi-agent reinforcement
learning (MARL) has led to improvements in generalization, data efficiency, and
physical consistency. While prior research has succeeded in using perfect
symmetry prior, the realm of partial symmetry in the multi-agent domain remains
unexplored. To fill in this gap, we introduce the partially symmetric Markov
game, a new subclass of the Markov game. We then theoretically show that the
performance error introduced by utilizing symmetry in MARL is bounded, implying
that the symmetry prior can still be useful in MARL even in partial symmetry
situations. Motivated by this insight, we propose the Partial Symmetry
Exploitation (PSE) framework that is able to adaptively incorporate symmetry
prior in MARL under different symmetry-breaking conditions. Specifically, by
adaptively adjusting the exploitation of symmetry, our framework is able to
achieve superior sample efficiency and overall performance of MARL algorithms.
Extensive experiments are conducted to demonstrate the superior performance of
the proposed framework over baselines. Finally, we implement the proposed
framework in real-world multi-robot testbed to show its superiority.


  A drastic rise in potentially life-threatening misinformation has been a
by-product of the COVID-19 pandemic. Computational support to identify false
information within the massive body of data on the topic is crucial to prevent
harm. Researchers proposed many methods for flagging online misinformation
related to COVID-19. However, these methods predominantly target specific
content types (e.g., news) or platforms (e.g., Twitter). The methods'
capabilities to generalize were largely unclear so far. We evaluate fifteen
Transformer-based models on five COVID-19 misinformation datasets that include
social media posts, news articles, and scientific papers to fill this gap. We
show tokenizers and models tailored to COVID-19 data do not provide a
significant advantage over general-purpose ones. Our study provides a realistic
assessment of models for detecting COVID-19 misinformation. We expect that
evaluating a broad spectrum of datasets and models will benefit future research
in developing misinformation detection systems.


  Transport barrier formation and its relation to sheared flows in fluids and
plasmas are of fundamental interest in various natural and laboratory
observations and of critical importance in achieving an economical energy
production in a magnetic fusion device. Here we report the first observation of
an edge transport barrier formation event in a gyrokinetic simulation carried
out in a realistic tokamak edge geometry. The results show that turbulent
Reynolds stress driven sheared ExB flows act in concert with neoclassical orbit
loss to quench turbulent transport and form a transport barrier just inside the
last closed magnetic flux surface.


  We study the critical set C of the nonlinear differential operator F(u) = -u"
+ f(u) defined on a Sobolev space of periodic functions H^p(S^1), p >= 1. Let
R^2_{xy} \subset R^3 be the plane z = 0 and, for n > 0, let cone_n be the cone
x^2 + y^2 = tan^2 z, |z - 2 pi n| < pi/2; also set Sigma = R^2_{xy} U U_{n > 0}
cone_n. For a generic smooth nonlinearity f: R -> R with surjective derivative,
we show that there is a diffeomorphism between the pairs (H^p(S^1), C) and
(R^3, Sigma) x H where H is a real separable infinite dimensional Hilbert
space.


  This report presents double helicity asymmetry in inclusive $\pi^0$
production in polarized proton-proton collisions at a center-of-mass energy
($\sqrt{s}$) of 200 GeV. The data were collected with the PHENIX detector at
the Relativistic Heavy Ion Collider (RHIC) during the 2004 run. The data are
compared to a next-to-leading order perturbative quantum chromodynamic (NLO
pQCD) calculation.


  In a recent paper [Phys. Rev. B {\bf 105}, L180415 (2022)], Ly and Manchon
used open source code {\tt TKWANT} for time-dependent computational quantum
transport to predict surprising features in the mature field of current pumping
by magnetization dynamics in spintronics -- in the presence of spin-orbit (SO)
coupling, the pumped charge current oscillates at both the frequency $\omega_0$
of magnetization precession and high harmonics $N=\omega/\omega_0$, reaching
{\em astonishingly high} cutoff \mbox{$N_\mathrm{max} \simeq 1000$} by
increasing the SO coupling. However, results in the paper violate two basic
theorems of time-dependent quantum transport: ({\em i}) current response to
time-periodic external field {\em must be perfectly periodic} itself in the
long time limit for a two-terminal device because its active region is attached
to two semi-infinite leads bringing continuous energy spectrum; and ({\em ii})
no DC component of charge current is allowed in the left-right symmetric
two-terminal devices, or in asymmetric devices its value cannot be changed by
simply increasing the SO coupling. We illustrate these two theorems by using
completely different calculations applied to one-dimensional two-terminal
devices with either ferromagnetic (for which the device is left-right
symmetric) and antiferromagnetic (for the device is left-right asymmetric)
active region hosting the Rashba SO coupling. We conclude that harmonics in
pumped current in the presence of SO coupling do exist, but their ``ultrahigh''
cutoff is an artifact of either ``bugs'' or inadequate algorithms selected
within {\tt TKWANT}. Finally, we suggest strategies for {\em validating}
time-dependent quantum transport codes, or selection of algorithms by a user
within putatively validated (by developers) code, prior to deploying them to
produce research papers.


  Three programs are presented for automatically generating and calculating
Feynman diagrams: the diagrams are generated with FeynArts, algebraically
simplified with FormCalc, and finally evaluated numerically using the LoopTools
package. The calculations are performed analytically as far as possible, with
results given in a form well suited for numerical evaluation. The latter is
then straightforward using the implementations of the one-loop integrals in
LoopTools.


  The first steps toward planet formation involve the coagulation of small
microscopic grains into larger and larger pebbles and rocks in gas-rich disks
around young stars and brown dwarfs. Observations in the sub-millimeter can
trace mm/cm-sized pebbles in the outer disks, and investigate the mechanisms of
coagulation/fragmentation and radial migration of these solids. These represent
key, yet not fully understood ingredients for our understanding of the
formation of planetesimals, the building blocks of planets. Here we present the
first results from an observational program using the ALMA and CARMA sub-mm/mm
interferometers aimed at characterizing the dust properties and disk structure
of young disks around brown dwarfs and very low mass stars. Given the physical
conditions expected for these disks, they represent critical test beds for the
models of the early stages of planet formation in proto-planetary disks.


  Piezoelectrics play a critical role in various applications. The permanent
dipole associated with the molecular cations in organometal-halide perovskites
(OMHPs) may lead to spontaneous polarization and thus piezoelectricity. Here,
we explore the piezoelectric properties of OMHPs with density functional
theory. We find that the piezoelectric coefficient depends sensitively on the
molecular ordering, and that the experimentally observed light-enhanced
piezoelectricity is due to to a non-polar to polar structural transition. By
comparing OMHPs with different atomic substitutions in the $ABX_3$
architecture, we find that the displacement of the $B$-site cation contributes
to nearly all the piezoelectric response, and that the competition between
$A$-$X$ hydrogen bond and $B$-$X$ metal-halide bond in OMHPs controls the
piezoelectric properties. These results highlight the potential of the OMHP
architecture for designing new functional photoferroelectrics and
photopiezoelectrics.


  Beam-driven instabilities are considered in a pulsar plasma assuming that
both the background plasma and the beam are relativistic J\"uttner
distributions. In the rest frame of the background, the only waves that can
satisfy the resonance condition are in a tiny range of slightly subluminal
phase speeds. The growth rate for the kinetic (or maser) version of the
weak-beam instability is much smaller than has been estimated for a
relativistically streaming Gaussian distribution, and the reasons for this are
discussed. The growth rate for the reactive version of the weak-beam
instability is treated in a conventional way. We compare the results with exact
calculations, and find that the approximate solutions are not consistent with
the exact results. We conclude that, for plausible parameters, there is no
reactive version of the instability. The growth rate in the pulsar frame is
smaller than that in the rest frame of the background plasma by a factor
$2\gamma_{\rm s}$, where $\gamma_{\rm s} = 10^2 {\rm -} 10^3$ is the Lorentz
factor of the bulk motion of the background plasma, placing a further
constraint on effective wave growth. Based on these results, we argue that
beam-driven wave growth probably plays no role in pulsar radio emission.


  Let $u_{g}$ the unique solution of a parabolic variational inequality of
second kind, with a given $g$. Using a regularization method, we prove, for all
$g_{1}$ and $g_{2}$, a monotony property between $\mu u_{g_{1}} +
(1-\mu)u_{g_{2}}$ and $u_{\mu g_{1} + (1-\mu)g_{2}}$ for $\mu \in [0, 1]$. This
allowed us to prove the existence and uniqueness results to a family of optimal
control problems over $g$ for each heat transfer coefficient $h>0$, associated
to the Newton law, and of another optimal control problem associated to a
Dirichlet boundary condition. We prove also, when $h\to +\infty$, the strong
convergence of the optimal controls and states associated to this family of
optimal control problems with the Newton law to that of the optimal control
problem associated to a Dirichlet boundary condition.


  We examine the B -> phi K decays within the framework of SUGRA models making
use of the improved QCD factorization method of Beneke et al. which allows
calculations of non-factorizable contributions. All other experimental
constraints (B -> X_S gamma, neutron and electron electric dipole moments, dark
matter constraints, etc.) are imposed. We calculate the CP violating parameters
S_{phi K_S}, C_{phi K_S} and A_{phi K^{-+}} as well as the branching ratios
(BR) of B^0 and B^{+-}, Br[B -> phi K]. We find for the Standard Model(SM) and
mSUGRA it is not possible to account for the observed 2.7 sigma deviation
between S_{phi K_S} and S_{J/Psi K_S}. In general the BRs are also in 3 sigma
disagreement with experiment, except in the parameter region where the weak
annihilation terms dominate the decay (and hence where the theory is least
reliable). Thus if future data confirm the current numbers, this would
represent the first significant breakdown of both the SM and mSUGRA. We show
then that adding a SUGRA non-universal A soft breaking left-right term mixing
the second and third generations in either the down or up quark sector, all
data can be accommodated for a wide range of parameters. The full 6x6 quark
mass matrices are used and the SUSY contributions calculated without
approximation.