  We present a distributed and price-based control approach for frequency
regulation in power grids with nonzero line conductances. Both grid and
controller are modeled as a port-Hamiltonian system, where the grid model
consists of differential as well as algebraic equations. Simulations show that
the resulting controller asymptotically stabilizes the frequency while
maintaining minimum overall generation costs in steady state and being robust
in terms of clock drifts and uncontrollable loads. Moreover, it is shown that
active power sharing can be achieved by an appropriate choice of the cost
function.


  Multi-person 3D human pose estimation from a single image is a challenging
problem, especially for in-the-wild settings due to the lack of 3D annotated
data. We propose HG-RCNN, a Mask-RCNN based network that also leverages the
benefits of the Hourglass architecture for multi-person 3D Human Pose
Estimation. A two-staged approach is presented that first estimates the 2D
keypoints in every Region of Interest (RoI) and then lifts the estimated
keypoints to 3D. Finally, the estimated 3D poses are placed in
camera-coordinates using weak-perspective projection assumption and joint
optimization of focal length and root translations. The result is a simple and
modular network for multi-person 3D human pose estimation that does not require
any multi-person 3D pose dataset. Despite its simple formulation, HG-RCNN
achieves the state-of-the-art results on MuPoTS-3D while also approximating the
3D pose in the camera-coordinate system.


  We prove three results conjectured or stated by Chartrand, Fink and Zhang
[European J. Combin {\bf 21} (2000) 181--189, Disc. Appl. Math. {\bf 116}
(2002) 115--126, and pre-print of ``The hull number of an oriented graph''].
For a digraph $D$, Chartrand et al. defined the geodetic, hull and convexity
number -- $g(D)$, $h(D)$ and $con(D)$, respectively. For an undirected graph
$G$, $g^{-}(G)$ and $g^{+}(G)$ are the minimum and maximum geodetic numbers
over all orientations of $G$, and similarly for $h^{-}(G)$, $h^{+}(G)$,
$con^{-}(G)$ and $con^{+}(G)$. Chartrand and Zhang gave a proof that $g^{-}(G)
< g^{+}(G)$ for any connected graph with at least three vertices. We plug a gap
in their proof, allowing us also to establish their conjecture that $h^{-}(G) <
h^{+}(G)$.
  If $v$ is an end-vertex, then in any orientation of $G$, $v$ is either a
source or a sink. It is easy to see that graphs without end-vertices can be
oriented to have no source or sink; we show that, in fact, we can avoid all
extreme vertices. This proves another conjecture of Chartrand et al., that
$con^{-}(G) < con^{+}(G)$ iff $G$ has no end-vertices.


  "Grid" computing has emerged as an important new field, distinguished from
conventional distributed computing by its focus on large-scale resource
sharing, innovative applications, and, in some cases, high-performance
orientation. In this article, we define this new field. First, we review the
"Grid problem," which we define as flexible, secure, coordinated resource
sharing among dynamic collections of individuals, institutions, and
resources-what we refer to as virtual organizations. In such settings, we
encounter unique authentication, authorization, resource access, resource
discovery, and other challenges. It is this class of problem that is addressed
by Grid technologies. Next, we present an extensible and open Grid
architecture, in which protocols, services, application programming interfaces,
and software development kits are categorized according to their roles in
enabling resource sharing. We describe requirements that we believe any such
mechanisms must satisfy, and we discuss the central role played by the
intergrid protocols that enable interoperability among different Grid systems.
Finally, we discuss how Grid technologies relate to other contemporary
technologies, including enterprise integration, application service provider,
storage service provider, and peer-to-peer computing. We maintain that Grid
concepts and technologies complement and have much to contribute to these other
approaches.


  The radiation transport equation is a mesoscopic equation in high dimensional
phase space. Moment methods approximate it via a system of partial differential
equations in traditional space-time. One challenge is the high computational
intensity due to large vector sizes (1600 components for P39) in each spatial
grid point. In this work, we extend the calculable domain size in 3D
simulations considerably, by implementing the StaRMAP methodology within the
massively parallel HPC framework NAStJA, which is designed to use current
supercomputers efficiently. We apply several optimization techniques, including
a new memory layout and explicit SIMD vectorization. We showcase a simulation
with 200 billion degrees of freedom, and argue how the implementations can be
extended and used in many scientific domains.


  We clarify different definitions of the density matrix by proposing the use
of different names, the full density matrix for a single-closed quantum system,
the compressed density matrix for the averaged single molecule state from an
ensemble of molecules, and the reduced density matrix for a part of an
entangled quantum system, respectively. We show that ensembles with the same
compressed density matrix can be physically distinguished by observing
fluctuations of various observables. This is in contrast to a general belief
that ensembles with the same compressed density matrix are identical. Explicit
expression for the fluctuation of an observable in a specified ensemble is
given. We have discussed the nature of nuclear magnetic resonance quantum
computing. We show that the conclusion that there is no quantum entanglement in
the current nuclear magnetic resonance quantum computing experiment is based on
the unjustified belief that ensembles having the same compressed density matrix
are identical physically. Related issues in quantum communication are also
discussed.


  This paper shows that wirelessly powered backscatter communications is
subject to a fundamental tradeoff between the harvested energy at the tag and
the reliability of the backscatter communication, measured in terms of SNR at
the reader. Assuming the RF transmit signal is a multisine waveform adaptive to
the channel state information, we derive a systematic approach to optimize the
transmit waveform weights (amplitudes and phases) in order to enlarge as much
as possible the SNRenergy region. Performance evaluations confirm the
significant benefits of using multiple frequency components in the adaptive
transmit multisine waveform to exploit the nonlinearity of the rectifier and a
frequency diversity gain.


  Diffusive motion in an externally driven potential is considered. It is shown
that the distribution of work required to drive the system from an initial
equilibrium state to another is Gaussian for slow but finite driving. Our
result is obtained by projection method techniques exploiting a small parameter
defined as the switching rate between the two states of the system. The exact
solution for a simple model system shows that such an expansion may fail in
higher orders, since the mean and the variance following from the exact
distribution show non-analytic behavior.


  The superiority of many natural surfaces at resisting soft, sticky
biofoulants has inspired the integration of dynamic topography with mechanical
instability to promote self-cleaning artificial surfaces. The physics behind
this novel mechanism is currently limited to elastic biofoulants where surface
energy, bending stiffness, and topographical wavelength are key factors.
However, the viscoelastic nature of many biofoulants causes a complex interplay
between these factors with time-dependent characteristics such as material
softening and loading rate. Here, we enrich the current elastic theory of
topographic de-adhesion using analytical and finite element models to elucidate
the non-linear, time-dependent interaction of three physical, dimensionless
parameters: biofoulant's stiffness reduction, product of relaxation time and
loading rate, and the critical strain for short-term elastic de-adhesion.
Theoretical predictions, in good agreement with numerical simulations, provide
insight into tuning these control parameters to optimize surface renewal via
topographic de-adhesion in the viscoelastic regime.


  A fast simulation algorithm for the calculation of multitime correlation
functions of open quantum systems is presented. It is demonstrated that any
stochastic process which ``unravels'' the quantum Master equation can be used
for the calculation of matrix elements of reduced Heisenberg picture operators,
and thus for the calculation of multitime correlation functions, by extending
the stochastic process to a doubled Hilbert space. The numerical performance of
the stochastic simulation algorithm is investigated by means of a standard
example.


  Large Language Models (LLMs) have exploded a new heatwave of AI for their
ability to engage end-users in human-level conversations with detailed and
articulate answers across many knowledge domains. In response to their fast
adoption in many industrial applications, this survey concerns their safety and
trustworthiness. First, we review known vulnerabilities and limitations of the
LLMs, categorising them into inherent issues, attacks, and unintended bugs.
Then, we consider if and how the Verification and Validation (V&V) techniques,
which have been widely developed for traditional software and deep learning
models such as convolutional neural networks as independent processes to check
the alignment of their implementations against the specifications, can be
integrated and further extended throughout the lifecycle of the LLMs to provide
rigorous analysis to the safety and trustworthiness of LLMs and their
applications. Specifically, we consider four complementary techniques:
falsification and evaluation, verification, runtime monitoring, and regulations
and ethical use. In total, 370+ references are considered to support the quick
understanding of the safety and trustworthiness issues from the perspective of
V&V. While intensive research has been conducted to identify the safety and
trustworthiness issues, rigorous yet practical methods are called for to ensure
the alignment of LLMs with safety and trustworthiness requirements.


  The outbreak of enterohemorrhagic Escherichia coli (EHEC) in May 2011 warns
the potential threats of the world vegetables trade network (VTN) in spreading
fatal infectious diseases. The heterogeneous weight distribution and
multi-scale activity of intermediary networks affects the diffusion,
proliferation and extinction of epidemics. Here, we constructed a dual-weighted
VTN with 118 major countries and territories from FAO 2008 statistic data about
global vegetation production and trade, and develop a reaction-diffusion model
to simulate the epidemic behaviors in through VTN. We found an emerged
asymmetric threshold of epidemic on VTN, in which local proliferation within
nodes plays a more critical role than global diffusion in spreading of
EHEC-like diseases, i.e. sufficient local proliferation is the precondition for
global diffusion. We also found that a strong modularity on VTN structure,
which restricts the spreading of EHEC-like diseases; however, within the
communities, the diffusion is quick and easy. There is, moreover, a critical
"epidemic stem", in which a serial of positive feedback loop for amplifying the
proliferation and diffusion pathogens has been identified from entire VTN.
Surprisingly, statistical analysis shows a well consistency between theoretical
composition of stem and actual pattern of EHEC. The results provide a chance to
design gradient control strategies for controlling disease global diffusion.
Our analysis provided the first inspect of global epidemics mediated by trade
networks for improved control and immunity strategies in the future.


  This paper is a modified chapter of the author's Ph.D. thesis. We introduce
the notions of sequentially approximated types and sequentially approximated
Keisler measures. As the names imply, these are types which can be approximated
by a sequence of realized types and measures which can be approximated by a
sequence of `averaging measures' on tuples of realized types. We show that both
generically stable types (in arbitrary theories) and Keisler measures which are
finitely satisfiable over a countable model (in NIP theories) are sequentially
approximated. We also introduce the notion of a smooth sequence in a measure
over a model and give an equivalent characterization of generically stable
measures (in NIP theories) via this definition. In the last section, we take
the opportunity to generalize the main result of [8].


  We define a notion of (one-sided) edge shift spaces associated to
ultragraphs. In the finite case our notion coincides with the edge shift space
of a graph. In general, we show that our space is metrizable and has a
countable basis of clopen sets. We show that for a large class of ultragraphs
the basis elements of the topology are compact. We examine shift morphisms
between these shift spaces, and, for the locally compact case, show that if two
(possibly infinite) ultragraphs have edge shifts that are conjugate, via a
conjugacy that preserves length, then the associated ultragraph C*-algebras are
isomorphic. To prove this last result we realize the relevant ultragraph
C*-algebras as partial crossed products.


  By considering the three dimensional Heisenberg group $\mathbb{H}_1$ as a
flat model of pseudo-hermitian manifolds, the authors in [8] derived the
Frenet-Serret formulas for curves in $\mathbb{H}_1$. In this notes we show
three applications of the Frenet-Serret formulas. The first is the Ces\'{a}ro
immobility condition, which provides the criterion of curves being contained in
a given rotationally symmetric surface. Secondly, we show that any horizontally
regular curve is a Bertrand curve, and give all characterizations of those
curves. The final application is a classification of curves depending on
whether the position vector of the curve lies on the planes spanned by any pair
of its unit tangent, normal, and binormal vectors.


  Quasilinear theory has long been used to treat the problem of a weak electron
beam interacting with plasma and generating Langmuir waves. Its extension to
weak-turbulence theory treats resonant interactions of these Langmuir waves
with other plasma wave modes, in particular ion-sound waves. These are strongly
damped in plasma of equal ion and electron temperatures, as sometimes seen in,
for example, the solar corona and wind. Weak turbulence theory is derived in
the weak damping limit, with a term describing ion-sound wave damping then
added. In this paper we use the EPOCH particle-in-cell code to numerically test
weak turbulence theory for a range of electron-ion temperature ratios. We find
that in the cold ion limit the results agree well, but increasing ion
temperature the three-wave resonance becomes broadened in proportion to the
ion-sound wave damping rate. This may be important in, for example, the theory
of solar radio bursts, where the spectrum of Langmuir waves is critical.
Additionally we establish lower limits on the number of simulation particles
needed to accurately reproduce the electron and wave distributions in their
saturated states, and to reproduce their intermediate states and time
evolution.


  In this paper, we investigate the decentralized statistical inference
problem, where a network of agents cooperatively recover a (structured) vector
from private noisy samples without centralized coordination. Existing
optimization-based algorithms suffer from issues of model mismatch and poor
convergence speed, and thus their performance would be degraded, provided that
the number of communication rounds is limited. This motivates us to propose a
learning-based framework, which unrolls well-noted decentralized optimization
algorithms (e.g., Prox-DGD and PG-EXTRA) into graph neural networks (GNNs). By
minimizing the recovery error via end-to-end training, this learning-based
framework resolves the model mismatch issue. Our convergence analysis (with
PG-EXTRA as the base algorithm) reveals that the learned model parameters may
accelerate the convergence and reduce the recovery error to a large extent. The
simulation results demonstrate that the proposed GNN-based learning methods
prominently outperform several state-of-the-art optimization-based algorithms
in convergence speed and recovery error.


  In semiconductors, the T2* coherence time of a single confined spin is
limited either by the fluctuating magnetic environment (via the hyperfine
interaction), or by charge fluctuations (via the spin-orbit interaction). We
demonstrate that both limitations can be overcome simultaneously by using two
exchange-coupled electron spins that realize a single decoherence-avoiding
qubit. Using coherent population trapping, we generate a coherent superposition
of the singlet and triplet states of an optically active quantum-dot molecule,
and show that the corresponding T2* may exceed 200 nanoseconds.


  We study the dynamics near the central singularity in spherically symmetric
collapse of a massless scalar field toward Schwarzschild black hole formation.
The equations of motion take different simplified forms in the early and late
stages of the singularity curve. We report some fine structures of the analytic
solutions and universal features for the metric functions and matter near the
singularity.


  Underdoped cuprates exhibit a normal-state pseudogap, and their spins and
doped carriers tend to spatially separate into 1- or 2-D stripes. Some view
these as central to superconductivity, others as peripheral and merely
competing. Using La$_{2-x}$Sr$_x$Cu$_{1-y}$Zn$_y$O$_4$ we show that an oxygen
isotope effect in $T_c$ and in the superfluid density can be used to
distinguish between the roles of stripes and pseudogap and also to detect the
presence of impurity scattering. We conclude that stripes and pseudogap are
distinct, and both compete and coexist with superconductivity.


  The anomalous Nernst effect (ANE) gives rise to an electrical response
transverse to the magnetization and an applied temperature gradient in a
magnetic metal. A nanoscale temperature gradient can be generated by the use of
a laser beam applied to the apex of an atomic force microscope tip, thereby
allowing for spatially-resolved ANE measurements beyond the optical diffraction
limit. Such a method has been used previously to map in-plane magnetized
magnetic textures. However, the spatial distribution of the out-of-plane
temperature gradient, which is needed to fully interpret such an ANE-based
imaging, was not studied. We therefore use a well-known magnetic texture, a
magnetic vortex core, to demonstrate the reliability of the ANE method for the
imaging of magnetic domains with nanoscale resolution. Moreover, since the ANE
signal is directly proportional to the temperature gradient, we can also
consider the inverse problem and deduce information about the nanoscale
temperature distribution. Our results together with finite element modeling
indicate that besides the out-of-plane temperature gradients, there are even
larger in-plane temperature gradients. Thus we extend the ANE imaging to study
out-of-plane magnetization in a racetrack nano-wire by detecting the ANE signal
generated by in-plane temperature gradients. In all cases, a spatial resolution
of about 80 nm is obtained. These results are significant for the rapidly
growing field of thermo-electric imaging of antiferromagnetic spintronic device
structures.


  We discuss the evolution of the cluster temperature function (TF) in
different scenarios for structure formation. We use the commonly adopted
procedure of fitting the model parameters to the local TF data, finding the
best fit values and, most of all, the associated statistical errors. These
errors yield an uncertainty in the prediction of the TF evolution. We conclude
that, at the moment, observations of cluster temperatures at z<=0.5 could
provide only a weak test for $\Omega_0$.


  At which masses does the regime of globular clusters end and the one of dwarf
galaxies begin? And what separates these two classes of hot stellar systems?
  We examine to what extend very massive (>10^7 Mo) young star clusters are
similar to their lower mass counter parts and to which degree they resemble
other objects in their mass regime (dwarf--globular transition objects (DGTOs),
ultra compact dwarf galaxies (UCDs), galaxy nuclei).
  The comparison is performed by placing the recently observed very massive
young clusters onto known scaling relation defined by globular clusters (with
typical masses <10^6 Mo) and/or by hot stellar systems with sizes up to those
of giant galaxies.
  The very massive (>10^{6.5-7} Mo) young clusters seem to show a mass--radius
relation compatible with the one defined by hot stellar systems of galaxy mass.
This, in turn, can explain their location on the other scaling relations
investigated. It contrasts with the behaviour of the less massive young
clusters and of globular clusters, which do not exhibit any mass-radius
relation. However, the behaviour of the most massive clusters is similar to
that of most other objects in that mass regime (10^6-10^8 Mo).
  We show that the properties of young massive clusters are compatible with
other objects in the same mass regime such as DGTOs/UCDs. They present a
possible direct avenue of formation for those objects, which does not require
the transformation of a previously existing stellar system. Simulations and
observations support the possibility of the formation of such very massive
young clusters by early mergers of lower mass stellar clusters, which could
explain the emergence of a mass--radius relation.


  Veloce is an ultra-stable fibre-fed R4 echelle spectrograph for the 3.9 m
Anglo-Australian Telescope. The first channel to be commissioned, Veloce
'Rosso', utilises multiple low-cost design innovations to obtain Doppler
velocities for Sun-like and M-dwarf stars at <1 m/s precision. The spectrograph
has an asymmetric white-pupil format with a 100-mm beam diameter, delivering
R>75,000 spectra over a 580-950 nm range for the Rosso channel. Simultaneous
calibration is provided by a single-mode pulsed laser frequency comb in tandem
with a traditional arc lamp. A bundle of 19 object fibres provides a 2.4" field
of view for full sampling of stellar targets from the AAT site. Veloce is
housed in dual environmental enclosures that maintain positive air pressure at
a stability of +/-0.3 mbar, with a thermal stability of +/-0.01 K on the
optical bench. We present a technical overview and early performance data from
Australia's next major spectroscopic machine.


  We present an updated timing solution for the young, energetic pulsar PSR
B1509-58 based on 21.3 years of radio timing data and 7.6 years of X-ray timing
data. No glitches have occurred in this time span, in contrast to other
well-studied young pulsars, which show frequent glitches. We report a
measurement of the third frequency derivative of (-1.28+/-0.21)x10^(-31)
s^(-4). This value is 1.65 standard deviations from, i.e. consistent with, that
predicted by the simple constant magnetic dipole model of pulsar spin-down. We
measured the braking index to be n=2.839+/-0.003 and show that it varies by
1.5% over 21.3 yr due to contamination from timing noise. Results of a
low-resolution power spectral analysis of the significant noise apparent in the
data yield a spectral index of alpha=-4.6+/-1.0 for the red noise component.


  A novel technique for measuring the mass of the top quark that uses only the
kinematic properties of its charged decay products is presented. Top quark pair
events with final states with one or two charged leptons and hadronic jets are
selected from the data set of 8 TeV proton-proton collisions, corresponding to
an integrated luminosity of 19.7 inverse femtobarns. By reconstructing
secondary vertices inside the selected jets and computing the invariant mass of
the system formed by the secondary vertex and an isolated lepton, an observable
is constructed that is sensitive to the top quark mass that is expected to be
robust against the energy scale of hadronic jets. The main theoretical
systematic uncertainties, concerning the modeling of the fragmentation and
hadronization of b quarks and the reconstruction of secondary vertices from the
decays of b hadrons, are studied. A top quark mass of 173.68 +/- 0.20 (stat)
+1.58 -0.97 (syst) GeV is measured. The overall systematic uncertainty is
dominated by the uncertainty in the b quark fragmentation and the modeling of
kinematic properties of the top quark.


  We present the general forms of piece-wise functions on partitioned domains
satisfying an intrinsic $C^0$ or $C^1$ continuity across the sub-domain
boundaries. These general forms are constructed based on a strategy stemming
from the theory of functional connections, and we refer to partitioned domains
endowed with these general forms as functionally connected elements (FCE). We
further present a method, incorporating functionally connected elements and a
least squares collocation approach, for solving boundary and initial value
problems. This method exhibits a spectral-like accuracy, with the free
functions involved in the FCE form represented by polynomial bases or by
non-polynomial bases of quasi-random sinusoidal functions. The FCE method
offers a unique advantage over traditional element-based methods for boundary
value problems involving relative boundary conditions. A number of linear and
nonlinear numerical examples in one and two dimensions are presented to
demonstrate the performance of the FCE method developed herein.


  With the advance in user-friendly and powerful video editing tools, anyone
can easily manipulate videos without leaving prominent visual traces.
Frame-rate up-conversion (FRUC), a representative temporal-domain operation,
increases the motion continuity of videos with a lower frame-rate and is used
by malicious counterfeiters in video tampering such as generating fake
frame-rate video without improving the quality or mixing temporally spliced
videos. FRUC is based on frame interpolation schemes and subtle artifacts that
remain in interpolated frames are often difficult to distinguish. Hence,
detecting such forgery traces is a critical issue in video forensics. This
paper proposes a frame-rate conversion detection network (FCDNet) that learns
forensic features caused by FRUC in an end-to-end fashion. The proposed network
uses a stack of consecutive frames as the input and effectively learns
interpolation artifacts using network blocks to learn spatiotemporal features.
This study is the first attempt to apply a neural network to the detection of
FRUC. Moreover, it can cover the following three types of frame interpolation
schemes: nearest neighbor interpolation, bilinear interpolation, and
motion-compensated interpolation. In contrast to existing methods that exploit
all frames to verify integrity, the proposed approach achieves a high detection
speed because it observes only six frames to test its authenticity. Extensive
experiments were conducted with conventional forensic methods and neural
networks for video forensic tasks to validate our research. The proposed
network achieved state-of-the-art performance in terms of detecting the
interpolated artifacts of FRUC. The experimental results also demonstrate that
our trained model is robust for an unseen dataset, unlearned frame-rate, and
unlearned quality factor.


  Graphene oxide (GO)-based resistive random access memory (RRAM) is one of the
most promising emerging non-volatile memories for flexible electronics because
of its simple structure and low fabrication cost. The reported switching
mechanism can be classified into either localized or bulk effect. The localized
effect is commonly observed in GO-RRAM with active electrode e.g. Cu and Al.
The switching mechanism includes metallic conduction filament evolution or
modification of interfacial resistance between GO layer and electrodes. On the
other hand, the bulk effect involves hybridization state change of the entire
GO layer and is typically observed in devices with inert electrode e.g. Pt and
Au. Numerous compact models have been proposed for RRAM that are based on
localized switching mechanism. However, compact modeling of GO-RRAM based on
bulk mechanism is still lacking. Thus, this paper presents a compact model for
GO-RRAM that relies on hybridization state modulation. The proposed model
associates the resistance switching mechanism with the electricaldriven
modification of sp2 clusters density in the switching layer. A SPICE model
incorporating the proposed compact model is developed for parameter
calibration. The simulated I-V characteristic exhibits strong correlation with
the experimental data. Hereby, we regard the proposed compact model as an
acceptable and close description of GO-RRAM operation that depends on the bulk
switching mechanism.


  Lensing of the CMB is now a well-developed probe of large-scale clustering
over a broad range of redshifts. By exploiting the non-Gaussian imprints of
lensing in the polarization of the CMB, the CORE mission can produce a clean
map of the lensing deflections over nearly the full-sky. The number of high-S/N
modes in this map will exceed current CMB lensing maps by a factor of 40, and
the measurement will be sample-variance limited on all scales where linear
theory is valid. Here, we summarise this mission product and discuss the
science that it will enable. For example, the summed mass of neutrinos will be
determined to an accuracy of 17 meV combining CORE lensing and CMB two-point
information with contemporaneous BAO measurements, three times smaller than the
minimum total mass allowed by neutrino oscillations. In the search for B-mode
polarization from primordial gravitational waves with CORE, lens-induced
B-modes will dominate over instrument noise, limiting constraints on the
gravitational wave power spectrum amplitude. With lensing reconstructed by
CORE, one can "delens" the observed polarization internally, reducing the
lensing B-mode power by 60%. This improves to 70% by combining lensing and CIB
measurements from CORE, reducing the error on the gravitational wave amplitude
by 2.5 compared to no delensing (in the null hypothesis). Lensing measurements
from CORE will allow calibration of the halo masses of the 40000 galaxy
clusters that it will find, with constraints dominated by the clean
polarization-based estimators. CORE can accurately remove Galactic emission
from CMB maps with its 19 frequency channels. We present initial findings that
show that residual Galactic foreground contamination will not be a significant
source of bias for lensing power spectrum measurements with CORE. [abridged]


  Linearizability is the de facto correctness criterion for concurrent data
structures. Unfortunately, linearizability imposes a performance penalty which
scales linearly in the number of contending threads. Quiescent consistency is
an alternative criterion which guarantees that a concurrent data structure
behaves correctly when accessed sequentially. Yet quiescent consistency says
very little about executions that have any contention.
  We define quantitative quiescent consistency (QQC), a relaxation of
linearizability where the degree of relaxation is proportional to the degree of
contention. When quiescent, no relaxation is allowed, and therefore QQC refines
quiescent consistency, unlike other proposed relaxations of linearizability. We
show that high performance counters and stacks designed to satisfy quiescent
consistency continue to satisfy QQC. The precise assumptions under which QQC
holds provides fresh insight on these structures. To demonstrate the robustness
of QQC, we provide three natural characterizations and prove compositionality.


  Style transfer aims to rewrite a source text in a different target style
while preserving its content. We propose a novel approach to this task that
leverages generic resources, and without using any task-specific parallel
(source-target) data outperforms existing unsupervised approaches on the two
most popular style transfer tasks: formality transfer and polarity swap. In
practice, we adopt a multi-step procedure which builds on a generic pre-trained
sequence-to-sequence model (BART). First, we strengthen the model's ability to
rewrite by further pre-training BART on both an existing collection of generic
paraphrases, as well as on synthetic pairs created using a general-purpose
lexical resource. Second, through an iterative back-translation approach, we
train two models, each in a transfer direction, so that they can provide each
other with synthetically generated pairs, dynamically in the training process.
Lastly, we let our best reresulting model generate static synthetic pairs to be
used in a supervised training regime. Besides methodology and state-of-the-art
results, a core contribution of this work is a reflection on the nature of the
two tasks we address, and how their differences are highlighted by their
response to our approach.


  Co-orbital planets have not yet been discovered, although they constitute a
frequent by-product of planetary formation and evolution models. This lack may
be due to observational biases, since the main detection methods are unable to
spot co-orbital companions when they are small or near the Lagrangian
equilibrium points. However, for a system with one known transiting planet
(with mass $m_1$), we can detect a co-orbital companion (with mass $m_2$) by
combining the time of mid-transit with the radial-velocity data of the star.
Here, we propose a simple method that allows the detection of co-orbital
companions, valid for eccentric orbits, that relies on a single parameter
$\alpha$, which is proportional to the mass ratio $m_2/m_1$. Therefore, when
$\alpha$ is statistically different from zero, we have a strong candidate to
harbour a co-orbital companion. We also discuss the relevance of false
positives generated by different planetary configurations.


  We survey the Si K edge structure in various absorbed Galactic low-mass X-ray
binaries (LMXBs) to study states of silicon in the inter- and circum-stellar
medium. The bulk of these LMXBs lie toward the Galactic bulge region and all
have column densities above $10^{22}$ cm$^{-2}$. The observations were
performed with the \emph{Chandra} High Energy Transmission Grating
Spectrometer. The Si K edge in all sources appears at an energy value of
1844$\pm$0.001 eV. The edge exhibits significant substructure which can be
described by a near edge absorption feature at 1849$\pm$0.002 eV and a far edge
absorption feature at 1865$\pm$0.002 eV. Both of these absorption features
appear variable with equivalent widths up to several m\AA. We can describe the
edge structure with several components: multiple edge functions, near edge
absorption excesses from silicates in dust form, signatures from X-ray
scattering optical depths, and a variable warm absorber from ionized atomic
silicon. The measured optical depths of the edges indicate much higher values
than expected from atomic silicon cross sections and ISM abundances, and appear
consistent with predictions from silicate X-ray absorption and scattering. A
comparison with models also indicates a preference for larger dust grain sizes.
In many cases we identify \sixiii\ resonance absorption and determine
ionization parameters between log $\xi$ = 1.8 and 2.8 and turbulent velocities
between 300 and 1000 \kms. This places the warm absorber in close vicinity of
the X-ray binaries. In some data we observe a weak edge at 1.840 keV,
potentially from a lesser contribution of neutral atomic silicon.


  The charmless decay processes of $X(3872)$ provide us a good platform to
study the nature and the decay mechanism of $X(3872)$. Based on a molecular
nature of $X(3872)$ as a $\bar{D}D^*$ bound state, we have investigated the
charmless decays $X(3872) \to VV$ and $VP$ via intermediate $D^*{\bar D} +c.c.$
meson loops, where $V$ and $P$ stand for light vector and pseudoscalar mesons,
respectively. We discuss three cases, i.e., pure neutral components
($\theta=0$), isospin singlet ($\theta=\pi/4$) and neutral components dominant
($\theta = \pi/6$), where $\theta$ is a phase angle describing the proportion
of neutral and charged constituents. The proportion of neutral and charged
constituent have an influence on the decay widths of $X(3872) \to VV$ and $VP$.
With the coupling constant of $X(3872)$ to the $\bar{D}D^*$ channel obtained
under the molecule ansatz of $X(3872)$ resonance, the predicted decay widths of
$X(3872)\rightarrow VV$ are about tens of keVs, while the decay width can reach
a few hundreds of keVs for $X(3872)\to VP$. The dependence of these ratios
between different decay modes of $X(3872)\to VV$ and $X(3872)\to VP$ to the
mixing angle $\theta$ is also investigated. It is expected that the theoretical
calculations here can be tested by future experiments.


  We introduce a general model of resource allocation with customer choice. In
this model, there are multiple resources that are available over a finite
horizon. The resources are non-replenishable and perishable. Each unit of a
resource can be instantly made into one of several products. There are multiple
customer types arriving randomly over time. An assortment of products must be
offered to each arriving customer, depending on the type of the customer, the
time of arrival, and the remaining inventory. From this assortment, the
customer selects a product according to a general choice model. The selection
generates a product-dependent and customer-type-dependent reward. The objective
of the system is to maximize the total expected reward earned over the horizon.
  The above problem has a number of applications, including personalized
assortment optimization, revenue management of parallel flights, and web- and
mobile-based appointment scheduling. We derive online algorithms that are
asymptotically optimal and achieve the best constant relative performance
guarantees for this class of problems.


  Spectrum sharing, as an approach to significantly improve spectrum efficiency
in the era of 6th generation mobile networks (6G), has attracted extensive
attention. Radio Environment Map (REM) based low-complexity spectrum sharing is
widely studied where the spectrum occupancy measurement (SOM) is vital to
construct REM. The SOM in three-dimensional (3D) space is becoming increasingly
essential to support the spectrum sharing with space-air-ground integrated
network being a great momentum of 6G. In this paper, we analyze the performance
of 3D SOM to further study the tradeoff between accuracy and efficiency in 3D
SOM. We discover that the error of 3D SOM is related with the area of the
boundary surfaces of licensed networks, the number of discretized cubes, and
the length of the edge of 3D space. Moreover, we design a fast and accurate 3D
SOM algorithm that utilizes unmanned aerial vehicle (UAV) to measure the
spectrum occupancy considering the path planning of UAV, which improves the
measurement efficiency by requiring less measurement time and flight time of
the UAV for satisfactory performance. The theoretical results obtained in this
paper reveal the essential dependencies that describe the 3D SOM methodology,
and the proposed algorithm is beneficial to improve the efficiency of 3D SOM.
It is noted that the theoretical results and algorithm in this paper may
provide a guideline for more areas such as spectrum monitoring, spectrum
measurement, network measurement, planning, etc.


  The framework of distribution testing is currently ubiquitous in the field of
property testing. In this model, the input is a probability distribution
accessible via independently drawn samples from an oracle. The testing task is
to distinguish a distribution that satisfies some property from a distribution
that is far from satisfying it in the $\ell_1$ distance. The task of tolerant
testing imposes a further restriction, that distributions close to satisfying
the property are also accepted. This work focuses on the connection of the
sample complexities of non-tolerant ("traditional") testing of distributions
and tolerant testing thereof. When limiting our scope to label-invariant
(symmetric) properties of distribution, we prove that the gap is at most
quadratic. Conversely, the property of being the uniform distribution is indeed
known to have an almost-quadratic gap. When moving to general, not necessarily
label-invariant properties, the situation is more complicated, and we show some
partial results. We show that if a property requires the distributions to be
non-concentrated, then it cannot be non-tolerantly tested with $o(\sqrt{n})$
many samples, where $n$ denotes the universe size. Clearly, this implies at
most a quadratic gap, because a distribution can be learned (and hence
tolerantly tested against any property) using $\mathcal{O}(n)$ many samples.
Being non-concentrated is a strong requirement on the property, as we also
prove a close to linear lower bound against their tolerant tests. To provide
evidence for other general cases (where the properties are not necessarily
label-invariant), we show that if an input distribution is very concentrated,
in the sense that it is mostly supported on a subset of size $s$ of the
universe, then it can be learned using only $\mathcal{O}(s)$ many samples. The
learning procedure adapts to the input, and works without knowing $s$ in
advance.


  Generalized uncertainty principle puts forward the existence of the shortest
distances and/or maximum momentum at the Planck scale for consideration. In
this article, we investigate the solutions of a two-dimensional
Duffin-Kemmer-Petiau (DKP) oscillator within an external magnetic field in a
minimal length (ML) scale. First, we obtain the eigensolutions in ordinary
quantum mechanics. Then, we examine the DKP oscillator in the presence of an ML
for the spin-zero and spin-one sectors. We determine an energy eigenvalue
equation in both cases with the corresponding eigenfunctions in the
non-relativistic limit. We show that in the ordinary quantum mechanic limit,
where the ML correction vanishes, the energy eigenvalue equations become
identical with the habitual quantum mechanical ones. Finally, we employ the
Euler-Mclaurin summation formula and obtain the thermodynamic functions of the
DKP oscillator in the high-temperature scale.


  In previous papers, predictions of the new "Spatial Condensation (SC-)"
cosmological model were presented on the (1) foundations, (2) new source of
gravity, and (3) large-scale structure. In this paper predictions will include
new physical features that are due mostly to the postulated geometry of our
closed 3-D universe. Knowledge of the past universe is obtained from its many
types of radiation that travel to our instruments on great circles of our
expanding 3-sphere. Adding the fourth spatial dimension greatly increases our
understanding of the concepts of emission and reception distances of the
sources and 4-D trajectory of the radiation. In a closed expanding 3-D
universe, most of the radiation from a distant bright source at Ze can travel
halfway around the universe and be refocused as a "virtual source" at Zv ~1.5
where some of the re-diverging radiation arrives later to our instruments. With
the added fourth dimension, the SC-model makes some spectacular predictions for
these virtual sources. Indeed, the CBR becomes a re-focused "backside"
microwave radiation with its structure amplified in size and decreased in
luminosity by a factor ~ 1/350. "Viewed" in the optical from a direction
opposite the CBR, the same, but more evolved, structure at "virtual Zsame"
would certainly fix the geometry and size of our universe. Virtual sources are
also added radiation to the diffuse background of X-rays and infrared. The CBR
dipole suggests a preferred reference frame. Reflected light signals in a
non-accelerated frame show, in principle, the moving frame could be brought to
rest in the comoving frame.


  For a transcendental entire function $f$ of finite order in the
Eremenko-Lyubich class $\mathcal{B}$, we give conditions under which the
Lebesgue measure of the escaping set $\mathcal{I}(f)$ of $f$ is zero. This is
inspired by the recent work of Aspenberg and Bergweiler, in which they give
conditions on entire functions in the same class with escaping sets of positive
Lebesgue measure. We will construct an entire function in the Eremenko-Lyubich
class to show that the condition given by Aspenberg and Bergweiler is
essentially sharp. Furthermore, we adapt our idea of proof to the case of
infinite order entire functions. Under some restrictions to the growth of these
entire functions, we show that the escaping sets have zero Lebesgue measure.
This generalizes a result of Eremenko and Lyubich.


  A combinatorial approach to compressive sensing based on a deterministic
column replacement technique is proposed. Informally, it takes as input a
pattern matrix and ingredient measurement matrices, and results in a larger
measurement matrix by replacing elements of the pattern matrix with columns
from the ingredient matrices. This hierarchical technique yields great
flexibility in sparse signal recovery. Specifically, recovery for the resulting
measurement matrix does not depend on any fixed algorithm but rather on the
recovery scheme of each ingredient matrix. In this paper, we investigate
certain trade-offs for signal recovery, considering the computational
investment required. Coping with noise in signal recovery requires additional
conditions, both on the pattern matrix and on the ingredient measurement
matrices.


  Graph Neural Networks (GNNs) are efficient approaches to process
graph-structured data. Modelling long-distance node relations is essential for
GNN training and applications. However, conventional GNNs suffer from bad
performance in modelling long-distance node relations due to limited-layer
information propagation. Existing studies focus on building deep GNN
architectures, which face the over-smoothing issue and cannot model node
relations in particularly long distance. To address this issue, we propose to
model long-distance node relations by simply relying on shallow GNN
architectures with two solutions: (1) Implicitly modelling by learning to
predict node pair relations (2) Explicitly modelling by adding edges between
nodes that potentially have the same label. To combine our two solutions, we
propose a model-agnostic training framework named HighwayGraph, which overcomes
the challenge of insufficient labeled nodes by sampling node pairs from the
training set and adopting the self-training method. Extensive experimental
results show that our HighwayGraph achieves consistent and significant
improvements over four representative GNNs on three benchmark datasets.


  We present the first three-dimensional (3D), hydrodynamic simulations of the
core convection zone (CZ) and extended radiative zone spanning from 1% to 90%
of the stellar radius of an intermediate mass (3 $\mathrm{M}_\odot$) star. This
allows us to self-consistently follow the generation of internal gravity waves
(IGWs) at the convective boundary and their propagation to the surface. We find
that convection in the core is dominated by plumes. The frequency spectrum in
the CZ and that of IGW generation is a double power law as seen in previous
two-dimensional (2D) simulations. The spectrum is significantly flatter than
theoretical predictions using excitation through Reynolds stresses induced by
convective eddies alone. It is compatible with excitation through plume
penetration. An empirically determined distribution of plume frequencies
generally matches the one necessary to explain a large part of the observed
spectrum. We observe waves propagating in the radiation zone and excited
standing modes, which can be identified as gravity and fundamental modes. They
show similar frequencies and node patterns to those predicted by the stellar
oscillation code GYRE. The continuous part of the spectrum fulfills the IGW
dispersion relation. A spectrum of tangential velocity and temperature
fluctuations close to the surface is extracted, which are directly related to
observable brightness variations in stars. Unlike 2D simulations we do not see
the high frequencies associated with wave breaking, likely because these 3D
simulations are more heavily damped.


  The low luminosity of Uranus is still a puzzling phenomenon and has key
implications for the thermal and compositional gradients within the planet.
Recent studies have shown that planetary volatiles become ionically conducting
under conditions that are present in the ice giants. Rapidly growing electrical
conductivity with increasing depth would couple zonal flows to the background
magnetic field in the planets, inducing poloidal and toroidal field
perturbations $\mathbf{B}^{\omega} = \mathbf{B}^{\omega}_P +
\mathbf{B}^{\omega}_T$ via the $\omega$-effect. Toroidal perturbations
$\mathbf{B}^{\omega}_T$ are expected to diffuse downwards and produce poloidal
fields $\mathbf{B}^{\alpha}_P$ through turbulent convection via the
$\alpha$-effect, comparable in strength to those of the $\omega$-effect;
$\mathbf{B}^{\omega}_P$. To estimate the strength of poloidal field
perturbations for various Uranus models in the literature, we generate wind
decay profiles based on Ohmic dissipation constraints assuming an ionically
conducting H$_2$-He-H$_2$O interior. Due to the higher metallicities in outer
regions of hot Uranus models, zonal winds need to decay to $\sim$0.1% of their
surface values in the outer 1% of Uranus to admit decay solutions in the Ohmic
framework. Our estimates suggest that colder Uranus models could potentially
have poloidal field perturbations that reach up to $\mathcal{O}(0.1)$ of the
background magnetic field in the most extreme case. The possible existence of
poloidal field perturbations spatially correlated with Uranus' zonal flows
could be used to constrain Uranus' interior structure, and presents a further
case for the $\textit{in situ}$ exploration of Uranus.


  Isabelle is an interactive theorem prover that supports a variety of logics.
It represents rules as propositions (not as functions) and builds proofs by
combining rules. These operations constitute a meta-logic (or `logical
framework') in which the object-logics are formalized. Isabelle is now based on
higher-order logic -- a precise and well-understood foundation. Examples
illustrate use of this meta-logic to formalize logics and proofs. Axioms for
first-order logic are shown sound and complete. Backwards proof is formalized
by meta-reasoning about object-level entailment. Higher-order logic has several
practical advantages over other meta-logics. Many proof techniques are known,
such as Huet's higher-order unification procedure.


  We present Text2App -- a framework that allows users to create functional
Android applications from natural language specifications. The conventional
method of source code generation tries to generate source code directly, which
is impractical for creating complex software. We overcome this limitation by
transforming natural language into an abstract intermediate formal language
representing an application with a substantially smaller number of tokens. The
intermediate formal representation is then compiled into target source codes.
This abstraction of programming details allows seq2seq networks to learn
complex application structures with less overhead. In order to train sequence
models, we introduce a data synthesis method grounded in a human survey. We
demonstrate that Text2App generalizes well to unseen combination of app
components and it is capable of handling noisy natural language instructions.
We explore the possibility of creating applications from highly abstract
instructions by coupling our system with GPT-3 -- a large pretrained language
model. We perform an extensive human evaluation and identify the capabilities
and limitations of our system. The source code, a ready-to-run demo notebook,
and a demo video are publicly available at
\url{https://github.com/text2app/Text2App}.


  Low delay video transmission is becoming increasingly important. Delay
critical, video enabled applications range from teleoperation scenarios such as
controlling drones or telesurgery to autonomous control through computer vision
algorithms applied on real-time video. To judge the quality of the video
transmission in such a system, it is important to be able to precisely measure
the end-to-end (E2E) delay of the transmitted video. We present a
low-complexity system that automatically takes pairwise independent
measurements of E2E delay. The precision can be far below the millisecond
order, mainly limited by the sampling rate of the measurement system. In our
implementation, we achieve a precision of 0.5 milliseconds with a sampling rate
of 2kHz.


  Purely gravitational perturbations are considered in a thin rotating disk
composed of several gas and stellar components. The dispersion relation for the
axisymmetric density waves propagating through the disk is found and the
criterion for the local axisymmetric stability of the whole system is
formulated. In the appropriate limit of two-component gas we confirm the
findings of Jog & Solomon (1984) and extend consideration to the case when one
component is collisionless. Gravitational stability of the Galactic disk in the
Solar neighborhood based on the multicomponent instability condition is
explored using recent measurements of the stellar composition and kinematics in
the local Galactic disk obtained by Hipparcos satellite.


  We consider the effects of a non-vanishing strange-quark mass in the
determination of the full basis of dimension six matrix elements for $B_{s}$
mixing, in particular we get for the ratio of the $V-A$ Bag parameter in the
$B_s$ and $B_d$ system: $\overline{B}^s_{Q_1} / \overline{B}^d_{Q_1} =
0.987^{+0.007}_{-0.009}$. Combining these results with the most recent lattice
values for the ratio of decay constants $f_{B_s} / f_{B_d}$ we obtain the most
precise determination of the ratio $\xi = f_{B_s} \sqrt{\overline{B}^s_{Q_1}}/
f_{B_d} \sqrt{\overline{B}^d_{Q_1}} = 1.2014^{+0.0065}_{-0.0072}$ in agreement
with recent lattice determinations. We find $\Delta
M_s=(18.5_{-1.5}^{+1.2})\text{ps}^{-1}$ and $\Delta
M_d=(0.547_{-0.046}^{+0.035})\text{ps}^{-1}$ to be consistent with experiments
at below one sigma. Assuming the validity of the SM, our calculation can be
used to directly determine the ratio of CKM elements $|V_{td} / V_{ts} | =
0.2045^{+0.0012}_{-0.0013}$, which is compatible with the results from the CKM
fitting groups, but again more precise.


  We characterize homogeneous hypersurfaces in complex space forms which arise
as critical points of a higher order energy functional. As a consequence, we
obtain existence and non-existence results for $\mathbb{CP}^n$ and
$\mathbb{CH}^n$, respectively. Moreover, we study the stability of biharmonic
hypersurfaces and compute the normal index for a large family of solutions.


  We present spatially resolved stellar population age maps, average radial
profiles and gradients for the first 62 Active Galactic Nuclei (AGN) observed
with SDSS-IV MaNGA to study the effects of the active nuclei on the star
formation history of the host galaxies. These results, derived using the
STARLIGHT code, are compared with a control sample of non-active galaxies
matching the properties of the AGN hosts. We find that the fraction of young
stellar populations (SP) in high-luminosity AGN is higher in the inner ($R \leq
0.5\,R_e$) regions when compared with the control sample; low-luminosity AGN,
on the other hand, present very similar fractions of young stars to the control
sample hosts for the entire studied range ($1\,R_e$). The fraction of
intermediate age SP of the AGN hosts increases outwards, with a clear
enhancement when compared with the control sample. The inner region of the
galaxies (AGN and control galaxies) presents a dominant old SP, whose fraction
decreases outwards. We also compare our results (differences between AGN and
control galaxies) for the early and late-type hosts and find no significant
differences. In summary, our results suggest that the most luminous AGN seems
to have been triggered by a recent supply of gas that has also triggered recent
star formation ($t\,\leq\,40\,Myrs$) in the central region.


  Recent developments and widespread in wireless sensor network have led to
many routing protocols, many of these protocols consider the efficiency of
energy as the ultimate factor to maximize the WSN lifetime. The quality of
Service (QoS) requirements for different applications of wireless sensor
networks has posed additional challenges. Imaging and data transmission needs
both QoS aware routing and energy to ensure the efficient use of sensors. In
this paper, we propose an Efficient, Energy-Aware, Least Cost, (ECQSR) quality
of service routing protocol for sensor networks which can run efficiently with
best-effort traffic processing. The protocol aims to maximize the lifetime of
the network out of balancing energy consumption across multiple nodes, by using
the concept of service differentiation, finding lower cost by finding the
shortest path using nearest neighbor algorithm (NN), also put certain
constraints on the delay of the path for real-time data from where link cost
that captures energy nodes reserve, energy of the transmission, error rate and
other parameters. The results show that the proposed protocol improves the
network lifetime and low power consumption.


  Semi-implicit variational inference (SIVI) greatly enriches the
expressiveness of variational families by considering implicit variational
distributions defined in a hierarchical manner. However, due to the intractable
densities of variational distributions, current SIVI approaches often use
surrogate evidence lower bounds (ELBOs) or employ expensive inner-loop MCMC
runs for unbiased ELBOs for training. In this paper, we propose SIVI-SM, a new
method for SIVI based on an alternative training objective via score matching.
Leveraging the hierarchical structure of semi-implicit variational families,
the score matching objective allows a minimax formulation where the intractable
variational densities can be naturally handled with denoising score matching.
We show that SIVI-SM closely matches the accuracy of MCMC and outperforms
ELBO-based SIVI methods in a variety of Bayesian inference tasks.


  Empirical risk minimization (ERM) is the workhorse of machine learning,
whether for classification and regression or for off-policy policy learning,
but its model-agnostic guarantees can fail when we use adaptively collected
data, such as the result of running a contextual bandit algorithm. We study a
generic importance sampling weighted ERM algorithm for using adaptively
collected data to minimize the average of a loss function over a hypothesis
class and provide first-of-their-kind generalization guarantees and fast
convergence rates. Our results are based on a new maximal inequality that
carefully leverages the importance sampling structure to obtain rates with the
right dependence on the exploration rate in the data. For regression, we
provide fast rates that leverage the strong convexity of squared-error loss.
For policy learning, we provide rate-optimal regret guarantees that close an
open gap in the existing literature whenever exploration decays to zero, as is
the case for bandit-collected data. An empirical investigation validates our
theory.


  The coincidence problems and other dynamical features of dark energy are
studied in cosmological models with variable cosmological parameters and in
models with the composite dark energy. It is found that many of the problems
usually considered to be cosmological coincidences can be explained or
significantly alleviated in the aforementioned models.


  The United States Department of Agriculture's National Agricultural
Statistics Service (NASS) conducts the June Agricultural Survey (JAS) annually.
Substantial misclassification occurs during the pre-screening process and from
field-estimating farm status for non-response and inaccessible records,
resulting in a biased estimate of the number of US farms from the JAS. Here the
Annual Land Utilization Survey (ALUS) is proposed as a follow-on survey to the
JAS to adjust the estimates of the number of US farms and other important
variables. A three-phase survey design-based estimator is developed for the
JAS-ALUS with non-response adjustment for the second phase (ALUS). A
design-unbiased estimator of the variance is provided in explicit form.


  We study the $L_{\infty}$-approximation of $d$-variate functions from Hilbert
spaces via linear functionals as information. It is a common phenomenon in
tractability studies that unweighted problems (with each dimension being
equally important) suffer from the curse of dimensionality in the deterministic
setting, that is, the number $n(\varepsilon,d)$ of information needed in order
to solve a problem to within a given accuracy $\varepsilon > 0$ grows
exponentially in $d$. We show that for certain approximation problems in
periodic tensor product spaces, in particular Korobov spaces with smoothness $r
> 1/2$, switching to the randomized setting can break the curse of
dimensionality, now having polynomial tractability, namely $n(\varepsilon,d)
\preceq \varepsilon^{-2} \, d \, (1 + \log d)$. Similar benefits of Monte Carlo
methods in terms of tractability have only been known for integration problems
so far.


  The Einstein-Maxwell fields of rotating stationary sources are represented by
the SU(2,1) spinor potential $\Psi_A$ satisfying \[ \nabla \cdot [\Theta
^{-1}(\Psi_A\nabla \Psi_B-\Psi_B\nabla \Psi_A)]=-2\Theta ^{-2}\vec{C}\cdot
(\Psi_A\nabla \Psi_B-\Psi_B\nabla \Psi_A) \] where $\Theta =\Psi ^{\dagger
}\cdot \Psi $ is the SU(2,1) norm of $\Psi $% . The Ernst potentials are
expressed in terms of the spinor potential by $% {\cal E}=\frac{\Psi_1-\Psi
_2}{\Psi_1+\Psi_2}$, $\Phi =\frac{\Psi_3}{% \Psi_1+\Psi_2}$ . The group
invariant vector $\vec{C}=-2i\func{Im}\{\Psi ^{\dagger}\cdot \nabla \Psi \}$ is
generated exclusively by the rotation of the source, hence it is appropriate to
refer to $\vec{C}$ as the {\em swirl} of the field. Static fields have no
swirl.
  The fields with no swirl are a class generalizing the equilibrium ($| e| =m$)
class of Einstein-Maxwell fields. We obtain the integrability conditions and a
highly symmetrical set of field equations for this class, as well as exact
solutions and an open research problem.


  Upcoming facilities such as the Herschel Space Observatory or ALMA will
deliver a wealth of molecular line observations of young stellar objects
(YSOs). Based on line fluxes, chemical abundances can then be estimated by
radiative transfer calculations. To derive physical properties from abundances,
the chemical network needs to be modeled and fitted to the observations. This
modeling process is however computationally exceedingly demanding, particularly
if in addition to density and temperature, far UV (FUV) irradiation, X-rays,
and multi-dimensional geometry have to be considered.
  We develop a fast tool, suitable for various applications of chemical
modeling in YSOs. A grid of the chemical composition of the gas having a
density, temperature, FUV irradiation and X-ray flux is pre-calculated as a
function of time. A specific interpolation approach is developed to reduce the
database to a feasible size. Published models of AFGL 2591 are used to verify
the accuracy of the method. A second benchmark test is carried out for FUV
sensitive molecules. The novel method for chemical modeling is more than
250,000 times faster than direct modeling and agrees within a mean factor of
1.35. The tool is distributed for public use.
  In the course of devloping the method, the chemical evolution is explored: We
find that X-ray chemistry in envelopes of YSOs can be reproduced by means of an
enhanced cosmic-ray ionization rate. We further find that the abundance of CH+
in low-density gas with high ionization can be enhanced by the recombination of
doubly ionized carbon (C++) and suggest a new value for the initial abundance
of the main sulphur carrier in the hot-core.


  The SKA era is set to revolutionize our understanding of neutral hydrogen
(HI) in individual galaxies out to redshifts of z~0.8; and in the z > 6
intergalactic medium through the detection and imaging of cosmic reionization.
Direct HI number density constraints will, nonetheless, remain relatively weak
out to cosmic noon (z~2) - the epoch of peak star formation and black hole
accretion - and beyond. However, as was demonstrated from the 1990s with
molecular line observations, this can be overcome by utilising the natural
amplification afforded by strong gravitational lensing, which results in an
effective increase in integration time by the square of the total magnification
(\mu^2) for an unresolved source. Here we outline how a dedicated lensed HI
survey will leverage MeerKAT's high sensitivity, frequency coverage, large
instantaneous bandwidth, and high dynamic range imaging to enable a lasting
legacy of high-redshift HI emission detections well into the SKA era. This
survey will not only provide high-impact, rapid-turnaround MeerKAT science
commissioning results, but also unveil Milky Way-like systems towards cosmic
noon which is not possible with any other SKA precursors/pathfinders. An
ambitious lensed HI survey will therefore make a significant impact from
MeerKAT commissioning all the way through to the full SKA era, and provide a
more complete picture of the HI history of the Universe.


  Let $M$ be a compact connected K\"ahler manifold and let ${\E}_{l-1}$ be the
smallest term in the Harder-Narasimhan filtration of its tangent bundle. Let
$G$ be an affine algebraic reductive group over $\C$. We prove the following
result: If $M$ satisfies the condition that $\deg (T/{\E}_{l-1}) \geq 0$, then
a holomorphic principal $G$-bundle $P$ on $M$ admitting a compatible
holomorphic connection is semistable. Moreover, if $\deg (T/{\E}_{l-1}) >0$,
then such a bundle $P$ actually admits a compatible flat $G$-connection.


  This work is part of a multi-wavelength program to study the effects of
X-ray/UV/optical stellar radiation on the chemistry of the circumbinary disk
around the young high-eccentricity binary DQ Tau. ALMA observations for
near/around December 5, 2021 periastron were postponed due to bad weather, but
supporting Swift-XRT-UVOT TOO observations were successful. These Swift
observations along with previous X-ray-optical-mm data show that DQ Tau keeps
exhibiting powerful flares near periastron, offering a unique laboratory for
studies of flare effects on the gas-phase ion chemistry in protoplanetary
disks.


  The user-centric cooperative transmission provides a compelling way to
alleviate frequent handovers caused by an ever-increasing number of randomly
deployed base stations (BSs) in ultra-dense networks (UDNs). This paper
proposes a new user-centric cooperative transmissions-based handover scheme,
i.e., the group-cell handover (GCHO) scheme, with the aim of reducing the
handover rate in UDNs. In the proposed scheme, the boundary of the cooperating
cluster depends on the distance among the user equipment (UE) and cooperating
BSs. The new scheme captures the dynamicity and irregularity of the cooperating
cluster topology resulting from randomly distributed BSs. Based on
stochastic-geometry tools where BSs locations are modeled as the Poison point
process (PPP), we derive an analytical expression of the handover rate for the
UE with an arbitrary movement trajectory. Furthermore, a GCHO skipping (GCHO-S)
scheme is proposed to minimize the handover cost, i.e., the percentage of time
wasted in handover signaling in user-centric cooperative transmissions
scenarios. The numerical results show that the GCHO scheme decreases the
handover rate by 42.3% and 72.7% compared with the traditional single BS
association and fixed-region cooperative network topology handover approaches,
respectively. Moreover, under the same group-cell size and constant velocity,
the GCHO-S scheme diminishes the handover cost by 50% against the GCHO scheme.


  In this paper we compute spaces of chiral operators in general
two-dimensional (0,2) nonlinear sigma models, both in theories twistable to the
A/2 or B/2 model, as well as in non-twistable theories, and apply them to check
recent duality conjectures. The fact that in a nonlinear sigma model, the Fock
vacuum can act as a section of a line bundle on the target space plays a
crucial role in our (0,2) computations, so we begin with a review of this
property. We also take this opportunity to show how even in (2,2) theories, the
Fock vacuum encodes in this way choices of target space spin structures, and
discuss how such choices enter the A and B model topological field theories. We
then compute chiral operators in general (0,2) nonlinear sigma models, and
apply them to test the recent Gadde-Gukov-Putrov triality proposal, which says
that certain triples of (0,2) GLSMs should RG flow to nontrivial IR fixed
points. We find that different UV theories in the same proposed universality
class do not necessarily have the same space of chiral operators -- but, the
mismatched operators do not contribute to elliptic genera and are in
non-integrable representations of the proposed IR affine symmetry groups,
suggesting that the mismatched states become massive along RG flow. We find
this state matching in examples not only of different geometric phases of the
same GLSMs, but also in phases of different GLSMs, indirectly verifying the
triality proposal, and giving a clean demonstration that (0,2) chiral rings are
not topologically protected. We also check proposals for enhanced IR affine E_6
symmetries in one such model, verifying that (matching) chiral states in phases
of corresponding GLSMs transform as 27s, 27^*s.


  Artificial intelligence (AI) in radiology has made great strides in recent
years, but many hurdles remain. Overfitting and lack of generalizability
represent important ongoing challenges hindering accurate and dependable
clinical deployment. If AI algorithms can avoid overfitting and achieve true
generalizability, they can go from the research realm to the forefront of
clinical work. Recently, small data AI approaches such as deep neuroevolution
(DNE) have avoided overfitting small training sets. We seek to address both
overfitting and generalizability by applying DNE to a virtually pooled data set
consisting of images from various institutions. Our use case is classifying
neuroblastoma brain metastases on MRI. Neuroblastoma is well-suited for our
goals because it is a rare cancer. Hence, studying this pediatric disease
requires a small data approach. As a tertiary care center, the neuroblastoma
images in our local Picture Archiving and Communication System (PACS) are
largely from outside institutions. These multi-institutional images provide a
heterogeneous data set that can simulate real world clinical deployment. As in
prior DNE work, we used a small training set, consisting of 30 normal and 30
metastasis-containing post-contrast MRI brain scans, with 37% outside images.
The testing set was enriched with 83% outside images. DNE converged to a
testing set accuracy of 97%. Hence, the algorithm was able to predict image
class with near-perfect accuracy on a testing set that simulates real-world
data. Hence, the work described here represents a considerable contribution
toward clinically feasible AI.


  The almost disjointness numbers associated to the quotients determined by the
transfinite products of the ideal of finite sets are investigated. A
$\mathrm{ZFC}$ lower bound involving the minimum of the classical almost
disjointness and splitting numbers is proved for these characteristics. En
route, it is shown that the splitting numbers associated to these quotients are
all equal to the classical splitting number. Finally, it is proved to be
consistent that the almost disjointness numbers associated to these quotients
are all equal to the second uncountable cardinal while the bounding number is
the first uncountable cardinal. Several open problems are considered.


  Algebraic structures involving both multiplications and comultiplications
(such as, e.g., bialgebras or Hopf algebras) can be encoded using PROPs
(categories with PROducts and Permutations) of Adams and MacLane. To encode
such structures on objects of a braided monoidal category, we need PROBs
(braided analogs of PROPs). Colored PROBs correspond to multi-sorted
structures.
  In particular, we have a colored PROB B governing non-negatively graded
bialgebras in braided categories. As a category, B splits into blocks B_n
according to the grading. We relate B_n with the category P_n of perverse
sheaves on the n-th symmetric product of the complex line, smooth with respect
to the natural stratification by multiplicities. More precisely, we show that
P_n is equivalent to the category of functors from B_n to vector spaces. This
gives a natural quiver description of P_n.


  Humans can leverage hierarchical structures to split a task into sub-tasks
and solve problems efficiently. Both imitation and reinforcement learning or a
combination of them with hierarchical structures have been proven to be an
efficient way for robots to learn complex tasks with sparse rewards. However,
in the previous work of hierarchical imitation and reinforcement learning, the
tested environments are in relatively simple 2D games, and the action spaces
are discrete. Furthermore, many imitation learning works focusing on improving
the policies learned from the expert polices that are hard-coded or trained by
reinforcement learning algorithms, rather than human experts. In the scenarios
of human-robot interaction, humans can be required to provide demonstrations to
teach the robot, so it is crucial to improve the learning efficiency to reduce
expert efforts, and know human's perception about the learning/training
process. In this project, we explored different imitation learning algorithms
and designed active learning algorithms upon the hierarchical imitation and
reinforcement learning framework we have developed. We performed an experiment
where five participants were asked to guide a randomly initialized agent to a
random goal in a maze. Our experimental results showed that using DAgger and
reward-based active learning method can achieve better performance while saving
more human efforts physically and mentally during the training process.


  We introduce the Hyperbolic Higgs, a novel solution to the little hierarchy
problem that features Standard Model neutral scalar top partners. At one-loop
order, the protection from ultraviolet sensitivity is due to an accidental
non-compact symmetry of the Higgs potential that emerges in the infrared. Once
the general features of the effective description are detailed, a completion
that relies on a five dimensional supersymmetric framework is provided. Novel
phenomenology is compared and contrasted with the Twin Higgs scenario.


  We give a direct proof of a result due to Karasev (2008), Karasev-Matschke
(2014) and Schnider-Sober\'on (2023). Given $m+1$ Borel probability measures on
the space of affine hyperplanes in a real vector space $V$ of dimension $m+1$,
there exist a line $L$ through the origin in $V$ and a point $v\in L$ such that
at least half of the hyperplanes, as counted by any of the measures, meet or
are parallel to each of the two closed rays in $L$ meeting at $v$.


  The structure of a social network is fundamentally related to the interests
of its members. People assort spontaneously based on the topics that are
relevant to them, forming social groups that revolve around different subjects.
Online social media are also favorable ecosystems for the formation of topical
communities centered on matters that are not commonly taken up by the general
public because of the embarrassment, discomfort, or shock they may cause. Those
are communities that depict or discuss what are usually referred to as deviant
behaviors, conducts that are commonly considered inappropriate because they are
somehow violative of society's norms or moral standards that are shared among
the majority of the members of society. Pornography consumption, drug use,
excessive drinking, illegal hunting, eating disorders, or any self-harming or
addictive practice are all examples of deviant behaviors.


  In recent work, Renaud, Venaille, and Bouchet (RVB) revisit the equilibrium
statistical mechanics theory of the shallow water equations, within a
microcanonical approach, focusing on a more careful treatment of the energy
partition between inertial gravity wave and eddy motions in the equilibrium
state, and deriving joint probability distributions for the corresponding
dynamical degrees of freedom. The authors derive a Liouville theorem that
determines the underlying phase space statistical measure, but then, through
some physical arguments, actually compute the equilibrium statistics using a
measure that \emph{violates} this theorem. Here, using a more convenient, but
essentially equivalent, grand canonical approach, the full statistical theory
consistent with the Liouville theorem is derived. The results reveal several
significant differences from the previous results: (1) The microscale wave
motions lead to a strongly fluctuating thermodynamics, including long-ranged
correlations, in contrast to the mean-field-like behavior found by RVB. The
final effective model is equivalent to that of an elastic membrane with a
nonlinear wave-renormalized surface tension. (2) Even when a mean field
approximation is made, a rather more complex joint probability distribution is
revealed. Alternative physical arguments fully support the consistency of the
results. Of course, the true fluid final steady state relies on dissipative
processes not included in the shallow water equations, such as wave breaking
and viscous effects, but it is argued that the current theory provides a more
mathematically consistent starting point for future work aimed at assessing
their impacts.


  Coherence resonance (CR), stochastic synchronization (SS), and
spike-timing-dependent plasticity (STDP) are ubiquitous dynamical processes in
biological neural networks. Whether there exists an optimal network and STDP
configuration at which CR and SS are both pronounced is a fundamental question
of interest that is still elusive. We expect such a configuration to enable the
brain to make synergistic and optimal use of these phenomena to process
information efficiently. This paper considers a small-world network of
excitable Hodgkin-Huxley neurons driven by channel noise and STDP with an
asymmetric Hebbian time window. Numerical results indicate specific network
topology and STDP parameter intervals in which CR and SS can be simultaneously
enhanced. Our results imply that an optimally tuned inherent background noise,
STDP rule, and network topology can play a constructive role in enhancing both
the time precision of firing and the synchronization in neural systems.


  We consider percolation and jamming transitions for particulate systems
exposed to compression. For the systems built of particles interacting by
purely repulsive forces in addition to friction and viscous damping, it is
found that these transitions are influenced by a number of effects, and in
particular by the compression rate. In a quasi-static limit, we find that for
the considered type of interaction between the particles, percolation and
jamming transitions coincide. For cohesive systems, however, or for any system
exposed to even slow dynamics, the differences between the considered
transitions are found and quantified.


  Denoising, detrending, deconvolution: usual restoration tasks, traditionally
decoupled. Coupled formulations entail complex ill-posed inverse problems. We
propose PENDANTSS for joint trend removal and blind deconvolution of sparse
peak-like signals. It blends a parsimonious prior with the hypothesis that
smooth trend and noise can somewhat be separated by low-pass filtering. We
combine the generalized pseudo-norm ratio SOOT/SPOQ sparse penalties
$\ell_p/\ell_q$ with the BEADS ternary assisted source separation algorithm.
This results in a both convergent and efficient tool, with a novel Trust-Region
block alternating variable metric forward-backward approach. It outperforms
comparable methods, when applied to typically peaked analytical chemistry
signals. Reproducible code is provided:
https://github.com/paulzhengfr/PENDANTSS.


  Recent developments of the two MC-generators SPHINX and PEPSI are discussed.
In SPHINX the process of polarized photo production was included to simulate
the potential of a polarized HERA to measure the photon structure function. In
PEPSI the CC polarized cross sections on tree level have been added together
with the electroweak corrections to simulate their effect on CC signals
proposed for a polarized HERA.


  Force on proton vortices in superfluid and superconducting matter of neutron
stars is calculated at vanishing stellar temperature. Both longitudinal
(dissipative) and transverse (Lorentz-type) components of the force are derived
in a coherent way and compared in detail with the corresponding expressions
available in the literature. This allows us to resolve a controversy about the
form of the Lorentz-type force component acting on proton vortices. The
calculated force is a key ingredient in magnetohydrodynamics of superconducting
neutron stars and is important for modeling the evolution of stellar magnetic
field.


  This report describes the design of a $\gamma\gamma$ Higgs factory in which
62.8 GeV electron beams collide with 1 keV X-ray free electron laser (XFEL)
beams to produce colliding beams of 62.5 GeV photons. The Higgs boson
production rate is 34,000 Higgs bosons per $10^7$ second year, roughly the same
as the ILC Higgs rate. The electron accelerator is based on cold copper
distributed coupling (C$^3$) accelerator technology. The 0.7 J pulse energy of
the XFEL represents a 300-fold increase over the pulse energy of current soft
x-ray FEL's. Design challenges are discussed, along with the R\&D to address
them, including demonstrators.


  Chiral twisting of the molecular orientation within the layer of a smectic-A
liquid crystal has been investigated using circular dichroism spectroscopy. The
results indicate that a rotation of the layers away from the alignment
direction is induced by the surface electroclinic effect. This leads to an
interfacial region where the molecular director twists from the alignment
direction until it reaches the layer normal direction. A theory is presented to
explain the observed field and temperature dependence of the circular
dichroism.


  We present the possibility of spin-dependent Kapitza-Dirac scattering based
on a two-photon interaction only. The interaction scheme is inspired from a
Compton scattering process, for which we explicitly show the mathematical
correspondence to the spin-dynamics of an electron diffraction process in a
standing light wave. The spin effect has the advantage that it already appears
in a Bragg scattering setup with arbitrary low field amplitudes, for which we
have estimated the diffraction count rate in a realistic experimental setup at
available X-ray free-electron laser facilities.


  We propose a Bayesian approach for both medical inquiry and disease
inference, the two major phases in differential diagnosis. Unlike previous work
that simulates data from given probabilities and uses ML algorithms on them, we
directly use the Quick Medical Reference (QMR) belief network, and apply
Bayesian inference in the inference phase and Bayesian experimental design in
the inquiry phase. Moreover, we improve the inquiry phase by extending the
Bayesian experimental design framework from one-step search to multi-step
search. Our approach has some practical advantages as it is interpretable, free
of costly training, and able to adapt to new changes without any additional
effort. Our experiments show that our approach achieves new state-of-the-art
results on two simulated datasets, SymCAT and HPO, and competitive results on
two diagnosis dialogue datasets, Muzhi and Dxy.


  We present an observational study of 22 broad absorption line quasars (BAL
QSOs) at $3\lesssim z \lesssim5$ based on optical/near-IR spectroscopy, aiming
to investigate quasar winds and their effects. The near-IR spectroscopy covers
the \hb\ and/or \mgii\ broad emission lines (BELs) for these quasars, allowing
us to estimate their central black hole (BH) masses in a robust way. We found
that our BAL QSOs on average do not have a higher Eddington ratio than that
from non-BAL QSOs matched in redshift and/or luminosity. In a subset consisting
of seven strong BAL QSOs possessing sub-relativistic BAL outflows, we see the
prevalence of large \civ-BEL blueshift ($\sim$3100 km s$^{-1}$) and weak \oiii\
emission (particularly the narrow \oiii$\lambda$5007 component), indicative of
nuclear outflows affecting the narrow emission-line (NEL) regions. In another
subset consisting of thirteen BAL QSOs having simultaneous observations of
\mgii\ and \hb, we found a strong correlation between 3000~\AA\ and 5000~\AA\
monochromatic luminosity, consistent with that from non-BAL QSOs matched in
redshift and luminosity; however, there is no correlation between \mgii\ and
\hb\ in FWHM, likely due to nuclear outflows influencing the BEL regions. Our
spectroscopic investigations offer strong evidence that the presence of nuclear
outflows plays an important role in shaping the BEL/NEL regions of these
quasars and possibly, regulating the growth of central supermassive black holes
(SMBHs). We propose that BEL blueshift and BAL could be different
manifestations of the same outflow system viewed at different sightlines and/or
phases.


  A kicking sequence of the atom optics kicked rotor at quantum resonance can
be interpreted as a quantum random walk in momentum space. We show how to steer
such a random walk by applying a random sequence of intensities and phases of
the kicking lattice chosen according to a probability distribution. This
distribution converts on average into the final momentum distribution of the
kicked atoms. In particular, it is shown that a power-law distribution for the
kicking strengths results in a L\'evy walk in momentum space and in a power-law
with the same exponent in the averaged momentum distribution. Furthermore, we
investigate the stability of our predictions in the context of a realistic
experiment with Bose-Einstein condensates.


  This volume contains the papers presented at the 6th Membrane Computing and
Biologically Inspired Process Calculi (MeCBIC 2012), a satellite workshop of
the 23rd International Conference on Concurrency Theory (CONCUR) held on 8th
September 2012 in Newcastle upon Tyne, UK.


  We investigate various search strategies for light vector boson $X$ in
$\mathcal{O}(10)~{\rm MeV}$ mass range using $J/\Psi$ associated channels at
BESIII and Belle II: (i) $J/\Psi \to \eta_c X$ with $10^{10} J/\Psi$s at
BESIII, (ii) $J/\Psi (\eta_c +X) +\ell \bar{\ell}$ production at Belle~II, and
(iii) $J/\Psi +X$ with the displaced vertex in $X\to e^+e^-$ decay are analyzed
and the future sensitivities at Belle II with 50 ${\rm ab}^{-1}$ luminosity are
comprehensively studied. By requiring the displaced vertex to be within the
beam pipe, the third method results in nearly background-free analysis, and the
vector boson-electron coupling and the vector boson mass can be probed in the
unprecedented range, $10^{-4}\leq |\varepsilon_e| \leq 10^{-3}$ and $9~{\rm
MeV}\leq m_X\leq 100 {\rm MeV}$ with 50 ${\rm ab}^{-1}$ at Belle II. This
covers the favored signal region of $^8{\rm Be}^*$ anomaly recently reported by
Atomki experiment with $m_X \simeq 17~{\rm MeV}$.


  This paper describes a novel dataset consisting of sentences with semantic
similarity annotations. The data originate from the journalistic domain in the
Czech language. We describe the process of collecting and annotating the data
in detail. The dataset contains 138,556 human annotations divided into train
and test sets. In total, 485 journalism students participated in the creation
process. To increase the reliability of the test set, we compute the annotation
as an average of 9 individual annotations. We evaluate the quality of the
dataset by measuring inter and intra annotation annotators' agreements. Beside
agreement numbers, we provide detailed statistics of the collected dataset. We
conclude our paper with a baseline experiment of building a system for
predicting the semantic similarity of sentences. Due to the massive number of
training annotations (116 956), the model can perform significantly better than
an average annotator (0,92 versus 0,86 of Person's correlation coefficients).


  Possible layouts of superconducting dipoles for the main injector of High
Energy LHC (HE-LHC) are proposed on the basis of the experience matured with
ongoing R&D activities at the Italian National Institute of Nuclear Physics
(INFN), targeted at developing the technologies for high field fast cycled
superconducting magnets for the SIS300 synchrotron of FAIR. Two different
magnets are analysed: a) a 4 T dipole ramped up to 1.5 T/s, and b) a 6 T dipole
to be operated at lower ramp rates.


  Monocular 3D detection has drawn much attention from the community due to its
low cost and setup simplicity. It takes an RGB image as input and predicts 3D
boxes in the 3D space. The most challenging sub-task lies in the instance depth
estimation. Previous works usually use a direct estimation method. However, in
this paper we point out that the instance depth on the RGB image is
non-intuitive. It is coupled by visual depth clues and instance attribute
clues, making it hard to be directly learned in the network. Therefore, we
propose to reformulate the instance depth to the combination of the instance
visual surface depth (visual depth) and the instance attribute depth (attribute
depth). The visual depth is related to objects' appearances and positions on
the image. By contrast, the attribute depth relies on objects' inherent
attributes, which are invariant to the object affine transformation on the
image. Correspondingly, we decouple the 3D location uncertainty into visual
depth uncertainty and attribute depth uncertainty. By combining different types
of depths and associated uncertainties, we can obtain the final instance depth.
Furthermore, data augmentation in monocular 3D detection is usually limited due
to the physical nature, hindering the boost of performance. Based on the
proposed instance depth disentanglement strategy, we can alleviate this
problem. Evaluated on KITTI, our method achieves new state-of-the-art results,
and extensive ablation studies validate the effectiveness of each component in
our method. The codes are released at https://github.com/SPengLiang/DID-M3D.


  In this letter, we study the simultaneously transmitting and reflecting
reconfigurable intelligent surface (STAR-RIS) assisted unmanned aerial vehicle
(UAV) communications. Our goal is to maximize the sum rate of all users by
jointly optimizing the STAR-RIS's beamforming vectors, the UAV's trajectory and
power allocation. We decompose the formulated non-convex problem into three
subproblems and solve them alternately to obtain the solution. Simulations show
that: 1) the STAR-RIS achieves a higher sum rate than traditional RIS; 2) to
exploit the benefits of STAR-RIS, the UAV's trajectory is closer to STAR-RIS
than that of RIS; 3) the energy splitting for reflection and transmission
highly depends on the real-time trajectory of UAV.


  For the problem of the non-isentropic compressible Euler Equations coupled
with a nonlinear Poisson equation with the electric potential satisfying the
Dirichlet boundary condition in three spatial dimensions with a general free
boundary not restricting to a graph, we identify suitable stability conditions
on the electric potential and the pressure under which we obtain a priori
estimates on the Sobolev norms of the fluid and electric variables and bounds
for geometric quantities of free surface. The stability conditions in this case
for a general variable entropy are that the outer normal derivative of the
electric potential is positive on the free surface, whereas that on the
pressure is negative. In the isentropic case, the stability condition reduces
to a single one, the outer normal derivative of the difference of the enthalpy
and the electric potential is negative on the free surface. For the free
boundary problem of the non-isentropic compressible Euler equations with
variable entropy without coupling with the nonlinear Poisson equation, the
corresponding higher-order estimates are also obtained under the Taylor sign
condition. It is also found that one less derivative is needed to close the
energy estimates for the problem for the non-isentropic compressible Euler
Equations coupled with a nonlinear Poisson equation when the electric potential
satisfies the Dirichlet boundary condition under the stability conditions on
the electric potential and the pressure, compared with the problem of the
non-isentropic compressible Euler equations.


  Accurate estimation of output quantiles is crucial in many use cases, where
it is desired to model the range of possibility. Modeling target distribution
at arbitrary quantile levels and at arbitrary input attribute levels are
important to offer a comprehensive picture of the data, and requires the
quantile function to be expressive enough. The quantile function describing the
target distribution using quantile levels is critical for quantile regression.
Although various parametric forms for the distributions (that the quantile
function specifies) can be adopted, an everlasting problem is selecting the
most appropriate one that can properly approximate the data distributions. In
this paper, we propose a non-parametric and data-driven approach, Neural Spline
Search (NSS), to represent the observed data distribution without parametric
assumptions. NSS is flexible and expressive for modeling data distributions by
transforming the inputs with a series of monotonic spline regressions guided by
symbolic operators. We demonstrate that NSS outperforms previous methods on
synthetic, real-world regression and time-series forecasting tasks.


  The phase transition to the state of a phonon gas with pairwise correlations
of interacting phonons with opposite momenta is studies. A method for
describing such phonon systems within the framework of the self-consistent
field model is developed and their thermodynamic characteristics are
calculated. It is shown that a phonon gas with pair correlations can exist in a
state of unstable thermodynamic equilibrium. The possibility of experimental
observation of a solid in such a phase is discussed.


  We illustrate some tests which may shed light on physics beyond the Standard
Model. Some of them are especially sensitive to possible signals of new
physics.


  We study three different chiral Lagrangians that describe the two- and
three-body decays of an excited pseudoscalar glueball, $J^{PC}=0^{*-+}$, into
light mesons and charmonium states as well as into a scalar and pseudoscalar
glueball. We compute the decay channels for an excited pseudoscalar glueball
with a mass of $3.7$ GeV and consider a ground state pseudoscalar glueball of
mass $2.6$ GeV, following predictions from lattice QCD simulations. These
states and channels are in reach of the ongoing BESIII experiment and the PANDA
experiments at the upcoming FAIR facility experiment. We present the resulting
decay branching ratios with a parameter-free prediction.


  The decomposition of large unitary matrices into smaller ones is important,
because it provides ways to realization of classical and quantum information
processing schemes. Today, most of the methods use planar meshes of tunable
two-channel blocks, however, the schemes turn out to be sensitive to
fabrication errors. We study a novel decomposition method based on
multi-channel blocks. We have shown that the scheme is universal even when the
block`s transfer matrices are chosen at random, making it virtually insensitive
to errors. Moreover, the placement of the variable elements can be arbitrary,
so that the scheme is not bound to specific topologies. Our method can be
beneficial for large-scale implementations of unitary transformations by
techniques, which are not of wide proliferation today or yet to be developed.


  In this partly expository paper we discuss conditions for the global
injectivity of $C^2$ semi-algebraic local diffeomorphisms $f:\mathbb{R}^n \to
\mathbb{R}^n$. In case $n > 2$, we consider the foliations of $\mathbb{R}^n$
defined by the level sets of each $n-2$ projections of $f$, i.e., the maps
$\mathbb{R}^n \to \mathbb{R}^{n-2}$ obtained by deleting two coordinate
functions of $f$. It is known that if the set of non-proper points of $f$ has
codimension greater than or equal to $2$ and the leaves of the above-defined
foliations are simply connected, then $f$ is bijective. In this work we relate
this simply connectedness with the notion of locally trivial fibrations. Then
some computable regularity conditions at infinity ensuring such simply
connectedness are presented. Further, we provide an equivalent statement of the
Jacobian conjecture by using fibrations. By means of examples we prove that the
results presented here are different from a previous result based on a spectral
hypothesis. Our considerations are also applied to discuss the behaviour of
some conditions when $f$ is composed with linear isomorphisms: this is relevant
due to some misunderstandings appearing in the literature.


  The angular dependences of the spontaneous emission by hot electrons in
multivalley semiconductors are studied theoretically and experimentally using
$n$-Ge as an example. We demonstrate that the change in the scattering
mechanism caused by the growth of electron temperature can affect the angular
scattering dependence. In the case when the heating field is applied along the
symmetry axis of the crystal [for $n$-Ge it is the axis (1,0,0,)], the angular
dependence of the emission was observed experimentally for the first time, and
the corresponding theory is proposed. When electrons have identical
concentration and temperature in every valley, the angular dependence of
emission is shown to be related to the violation of symmetry of the energy
distribution of electrons (from the theoretical viewpoint, this effect means
going beyond the scope of the traditional diffusion approximation).


  For an analytic function f(z)=z+\sum_{n=2}^\infty a_n z^n satisfying the
inequality \sum_{n=2}^\infty n(n-1)|a_n|\leq \beta, sharp bound on $\beta$ is
determined so that $f$ is either starlike or convex of order $\alpha$. Several
other coefficient inequalities related to certain subclasses are also
investigated.