  Signals can be interpreted as composed of a rapidly varying component
modulated by a slower varying envelope. Identifying this envelope is an
essential operation in signal processing, with applications in areas ranging
from seismology to medicine. Conventional envelope detection approaches based
on classic methods tend to lack generality, however, and need to be tailored to
each specific application in order to yield reasonable results. Taking
inspiration from geometric concepts, most notably the theory of alpha-shapes,
we introduce a general-purpose library to efficiently extract the envelope of
arbitrary signals.


  Numerical simulation of ultrasonic wave propagation provides an efficient
tool for crack identification in structures, while it requires a high
resolution and expensive time calculation cost in both time integration and
spatial discretization. Wavelet finite element model provides a highorder
finite element model and gives a higher accuracy on spatial discretization,
B-Spline wavelet interval (BSWI) has been proved to be one of the most commonly
used wavelet finite element model with the advantage of getting the same
accuracy but with fewer element so that the calculation cost is much lower than
traditional finite element method and other high-order element methods. Precise
Integration Method provides a higher resolution in time integration and has
been proved to be a stable time integration method with a much lower cut-off
error for same and even smaller time step. In this paper, a wavelet finite
element model combined with precise integration method is presented for the
numerical simulation of ultrasonic wave propagation and crack identification in
1D structures. Firstly, the wavelet finite element based on BSWI is constructed
for rod and beam structures. Then Precise Integrated Method is introduced with
application for the wave propagation in 1D structures. Finally, numerical
examples of ultrasonic wave propagation in rod and beam structures are
conducted for verification. Moreover, crack identification in both rod and beam
structures are studied based on the new model.


  The Hamiltonian of optical fields in a nonlinear dispersive fiber is studied.
Quantum field fluctuations are spontaneously created close to an optical event
horizon through the analog Hawking effect. The simplest model is considered for
an optical black-hole laser, where the Hawking radiation is produced and
amplified inside a cavity formed by two horizons: a black hole and a white
hole. It is found that resonant Hawking radiation originates from a discrete
set of instabilities and tunnels out of the horizons. Finally, the numerical
results are compared with the resonance and instability conditions and a
phenomenological model is developed to give a clear physical picture.


  Using the daily Mount Wilson Doppler velocity data during 1986-1994 (solar
cycle 22), we studied the short-term variations of the order of a few days to a
month time scales in the solar differential rotation coefficients A-bar, B-bar
and C-bar. We found that a ~9-day periodicity is statistically highly
significant in the variations of C-bar at the maximum of solar cycle 22. A
similar periodicity is found in the variations of B-bar during the descending
phase of the cycle 22 with significant on > 99.9% confidence level. At this
cycle maximum, a 30-40 day periodicity is found to be dominant among the
variations in B-bar, and this periodicity is found in A-bar during almost
throughout the period 1986-1994.The ~9-day periodicity in the variation of the
differential rotation approximately matches with the known quasi 10-day
periodicity in the total solar irradiance (TSI) variability. Hence, we
speculate that there exists a relationship between the differential rotation
and TSI variability. We suggest that the 9-10 day periodicities of the
differential rotation and TSI have a relationship with the production and the
emergence rates of the large-scale solar magnetic flux.


  Let K be an imaginary quadratic field with discriminant -D, and x the
Dirichlet character corresponding to the extension K/Q. Let m=2n or 2n+1 with n
a positive integer. Let f be a primitive form of weight 2k+1 and level D with
Neben character x, or a primitive form of weight 2k for SL(2,Z) according as
m=2n, or m=2n+1. For such an f let I(m,f) be the lift of f to the space of
Hermitian modular forms of degree m constructed by Ikeda. We then give an
explicit formula of the Koecher-Maass series L(s,I(m,f)) of I(m,f). This is a
generalization of [Y. Mizuno, Manuscripta Math. 119(2006), 175-216].


  In this article, we discuss a novel education approach to control theory in
undergraduate engineering programs. In particular, we elaborate on the
inclusion of an introductory course on process control during the first years
of the program, to appear right after the students undergo basic calculus and
physics courses. Our novel teaching proposal comprises debating the basic
elements of control theory without requiring any background on advanced
mathematical frameworks from the part of the students. The methodology
addresses, conceptually, the majority of the steps required for the analysis
and design of simple control systems. Herein, we thoroughly detail this
educational guideline, as well as tools that can be used in the classroom.
Furthermore, we propose a cheap test-bench kit and an open-source numerical
simulator that can be used to carry out experiments during the proposed course.
Most importantly, we also assess on how the Introduction to process control
course has affected the undergraduate program on Control and Automation
Engineering at Universidade Federal de Santa Catarina (UFSC, Brazil).
Specifically, we debate the outcomes of implementing our education approach at
UFSC from 2016 to 2023, considering students' rates of success in other control
courses and perspectives on how the chair helped them throughout the course of
their program. Based on randomised interviews, we indicate that our educational
approach has had good teaching-learning results: students tend to be more
motivated for other control-related subjects, while exhibiting higher rates of
success.


  During its commissioning phase in 2020, the Spectrometer/Telescope for
Imaging X-rays (STIX) on board the Solar Orbiter spacecraft observed 69
microflares. The two most significant events from this set (of GOES class B2
and B6) were observed on-disk from the spacecraft as well as from Earth and
analysed in terms of the spatial, temporal, and spectral characteristics.
  We complement the observations from the STIX instrument with EUV imagery from
SDO/AIA and GOES soft X-ray data by adding imaging and plasma diagnostics over
different temperature ranges for a detailed microflare case study that is
focussed on energy release and transport.
  Spectral fitting of the STIX data shows clear nonthermal emission for both
microflares studied here. The deduced plasma parameters from DEM reconstruction
as well as spectral fitting roughly agree with the values in the literature for
microflares as do the nonthermal fit parameters from STIX. The observed Neupert
effects and impulsive and gradual phases indicate that both events covered in
this study are consistent with the standard chromospheric evaporation flare
scenario. For the B6 event on 7 June 2020, this interpretation is further
supported by the temporal evolution seen in the DEM profiles of the flare
ribbons and loops. For this event, we also find that accelerated electrons can
roughly account for the required thermal energy. The 6 June 2020 event
demonstrates that STIX can detect nonthermal emission for GOES class B2 events
that is nonetheless smaller than the background rate level. We demonstrate for
the first time how detailed multi-instrument studies of solar flares can be
performed with STIX.


  A new kind of Lagrangian diagnostic family is proposed and a specific form of
it is suggested for characterizing mixing: the maximal extent of a trajectory
(MET). It enables the detection of coherent structures and their dynamics in
two- (and potentially three-) dimensional unsteady flows in both bounded and
open domains. Its computation is much easier than all other Lagrangian
diagnostics known to us and provides new insights regarding the mixing
properties on both short and long time scales and on both spatial plots and
distribution diagrams. We demonstrate its applicability to two dimensional
flows using two toy models and a data set of surface currents from the
Mediterranean Sea.


  AGINAO builds its cognitive engine by applying self-programming techniques to
create a hierarchy of interconnected codelets - the tiny pieces of code
executed on a virtual machine. These basic processing units are evaluated for
their applicability and fitness with a notion of reward calculated from
self-information gain of binary partitioning of the codelet's input
state-space. This approach, however, is useless for the evaluation of
actuators. Instead, a model is proposed in which actuators are evaluated by
measuring the impact that an activation of an effector, and consequently the
feedback from the robot sensors, has on average reward received by the
processing units.


  A method for the calculations of the Gilbert damping parameter $\alpha$ is
presented, which based on the linear response formalism, has been implemented
within the fully relativistic Korringa-Kohn-Rostoker band structure method in
combination with the coherent potential approximation alloy theory. To account
for thermal displacements of atoms as a scattering mechanism, an alloy-analogy
model is introduced. This allows the determination of $\alpha$ for various
types of materials, such as elemental magnetic systems and ordered magnetic
compounds at finite temperature, as well as for disordered magnetic alloys at
$T = 0$ K and above. The effects of spin-orbit coupling, chemical and
temperature induced structural disorder are analyzed. Calculations have been
performed for the 3$d$ transition-metals bcc Fe, hcp Co, and fcc Ni, their
binary alloys bcc Fe$_{1-x}$Co$_{x}$, fcc Ni$_{1-x}$Fe$_x$, fcc
Ni$_{1-x}$Co$_x$ and bcc Fe$_{1-x}$V$_{x}$, and for 5d impurities in
transition-metal alloys. All results are in satisfying agreement with
experiment.


  The magnetization orientation of a nanoscale ferromagnet can be manipulated
using an electric current via the spin transfer effect. Time domain
measurements of nanopillar devices at low temperatures have directly shown that
magnetization dynamics and reversal occur coherently over a timescale of
nanoseconds. By adjusting the shape of a spin torque waveform over a timescale
comparable to the free precession period (100-400 ps), control of the
magnetization dynamics in nanopillar devices should be possible. Here we report
coherent control of the free layer magnetization in nanopillar devices using a
pair of current pulses as narrow as 30 ps with adjustable amplitudes and delay.
We show that the switching probability can be tuned over a broad range by
timing the current pulses with the underlying free-precession orbits, and that
the magnetization evolution remains coherent for more than 1 ns even at room
temperature. Furthermore, we can selectively induce transitions along
free-precession orbits and thereby manipulate the free magnetic moment motion.
We expect this technique will be adopted for further elucidating the dynamics
and dissipation processes in nanomagnets, and will provide an alternative for
spin torque driven spintronic devices, such as resonantly pumping microwave
oscillators, and ultimately, for efficient reversal of memory bits in magnetic
random access memory (MRAM).


  We investigate the spatial statistics of the energy eigenfunctions on large
quantum graphs. It has previously been conjectured that these should be
described by a Gaussian Random Wave Model, by analogy with quantum chaotic
systems, for which such a model was proposed by Berry in 1977. The
autocorrelation functions we calculate for an individual quantum graph exhibit
a universal component, which completely determines a Gaussian Random Wave
Model, and a system-dependent deviation. This deviation depends on the graph
only through its underlying classical dynamics. Classical criteria for quantum
universality to be met asymptotically in the large graph limit (i.e. for the
non-universal deviation to vanish) are then extracted. We use an exact field
theoretic expression in terms of a variant of a supersymmetric sigma model. A
saddle-point analysis of this expression leads to the estimates. In particular,
intensity correlations are used to discuss the possible equidistribution of the
energy eigenfunctions in the large graph limit. When equidistribution is
asymptotically realized, our theory predicts a rate of convergence that is a
significant refinement of previous estimates. The universal and
system-dependent components of intensity correlation functions are recovered by
means of an exact trace formula which we analyse in the diagonal approximation,
drawing in this way a parallel between the field theory and semiclassics. Our
results provide the first instance where an asymptotic Gaussian Random Wave
Model has been established microscopically for eigenfunctions in a system with
no disorder.


  In the first part of this paper, we present a study of the symmetry energy
($a_s$) and its slope parameter ($L$) for nuclear matter in the framework of
the Fermi liquid theory of Landau and Migdal. We derive an exact relation
between $a_s$ and $L$, which involves the nucleon effective masses and
three-particle Landau-Migdal parameters. We present simple estimates which
suggest that there are two main mechanisms to explain the empirical values of
$L$: The proton-neutron effective mass difference in isospin asymmetric matter
and the $\ell=0$ moment of the isovector in-medium three-particle scattering
amplitude. In the second part of this paper, we discuss the general structure
of three-particle interactions in nuclear matter in the framework of the Fermi
liquid theory. The connections to the Bethe-Brueckner-Goldstone theory and
other approaches are also discussed. We show explicitly how the first few terms
in the Faddeev series, together with medium induced three-particle
interactions, emerge naturally in the Fermi liquid theory.


  Linking Data initiatives have fostered the publication of large number of RDF
datasets in the Linked Open Data (LOD) cloud, as well as the development of
query processing infrastructures to access these data in a federated fashion.
However, different experimental studies have shown that availability of LOD
datasets cannot be always ensured, being RDF data replication required for
envisioning reliable federated query frameworks. Albeit enhancing data
availability, RDF data replication requires synchronization and conflict
resolution when replicas and source datasets are allowed to change data over
time, i.e., co-evolution management needs to be provided to ensure consistency.
In this paper, we tackle the problem of RDF data co-evolution and devise an
approach for conflict resolution during co-evolution of RDF datasets. Our
proposed approach is property-oriented and allows for exploiting semantics
about RDF properties during co-evolution management. The quality of our
approach is empirically evaluated in different scenarios on the DBpedia-live
dataset. Experimental results suggest that proposed proposed techniques have a
positive impact on the quality of data in source datasets and replicas.


  Recent observations by TESS revealed the existence of circumbinary planets in
the systems of TOI-1338 and TIC-172900988. The purpose of this work is to model
the planetary orbits in these two systems and study them under the perspective
of previous theoretical models. Each planet's distance from the barycenter
through time is simulated using n-body integrations and is compared with
outcomes from a semi-analytic, a geometric and a Keplerian-based approach.
Furthermore, we infer the most prominent frequencies of both planets' orbits
induced by the central binaries. We confirm that both systems appear to be
stable. Lastly, we examine the implications of an additional candidate planet
in TOI-1338 system finding that an extra, 48 M$_\oplus$ planet that has been
hinted from observations could be located at 0.8 AU without generating any
radical changes to the orbits of the other members of the system.


  We show that and how ultra-cold atoms in an accelerated two-band lattice are
a controlled realization of Landau--Zener--St\"uckelberg interferometry.


  Multisets are an intuitive extension of the traditional concept of sets that
allow repetition of elements, with the number of times each element appears
being understood as the respective multiplicity. Recent generalizations of
multisets to real-valued functions, accounting for possibly negative values,
have paved the way to a number of interesting implications and applications,
including respective implementations as electronic systems. The basic multiset
operations include the set complementation (sign change), intersection (minimum
between two values), union (maximum between two values), difference and sum
(identical to the algebraic counterparts). When applied to functions or
signals, the sign and conjoint sign functions are also required. Given that
signals are functions, it becomes possible to effectively translate the
multiset and multifunction operations to analog electronics, which is the
objective of the present work. It is proposed that effective multiset
operations capable of high performance self and cross-correlation can be
obtained with relative simplicity in either discrete or integrated circuits.
The problem of switching noise is also briefly discussed. The present results
have great potential for applications and related developments in analog and
digital electronics, as well as for pattern recognition, signal processing, and
deep learning.


  Semantic change detection concerns the task of identifying words whose
meaning has changed over time. The current state-of-the-art detects the level
of semantic change in a word by comparing its vector representation in two
distinct time periods, without considering its evolution through time. In this
work, we propose three variants of sequential models for detecting semantically
shifted words, effectively accounting for the changes in the word
representations over time, in a temporally sensitive manner. Through extensive
experimentation under various settings with both synthetic and real data we
showcase the importance of sequential modelling of word vectors through time
for detecting the words whose semantics have changed the most. Finally, we take
a step towards comparing different approaches in a quantitative manner,
demonstrating that the temporal modelling of word representations yields a
clear-cut advantage in performance.


  The numerical integration of the Benjamin and Benjamin--Ono equations are
considered. They are non-local partial differential equations involving the
Hilbert transform, and due to this, so far quite few structure-preserving
integrators have been proposed. In this paper, a new reformulation of the
equations is stated, and new structure-preserving discretizations are proposed
based on it. Numerical experiments confirm the effectiveness of the proposed
integrators.


  A new algorithm, termed subspace evolution and transfer (SET), is proposed
for solving the consistent matrix completion problem. In this setting, one is
given a subset of the entries of a low-rank matrix, and asked to find one
low-rank matrix consistent with the given observations. We show that this
problem can be solved by searching for a column space that matches the
observations. The corresponding algorithm consists of two parts -- subspace
evolution and subspace transfer. In the evolution part, we use a line search
procedure to refine the column space. However, line search is not guaranteed to
converge, as there may exist barriers along the search path that prevent the
algorithm from reaching a global optimum. To address this problem, in the
transfer part, we design mechanisms to detect barriers and transfer the
estimated column space from one side of the barrier to the another. The SET
algorithm exhibits excellent empirical performance for very low-rank matrices.


  We propose a new class of vector fields to construct a conserved charge in a
general field theory whose energy momentum tensor is covariantly conserved. We
show that there always exists such a vector field in a given field theory even
without global symmetry. We also argue that the conserved current constructed
from the (asymptotically) time-like vector field can be identified with the
entropy current of the system. As a piece of evidence we show that the
conserved charge defined therefrom satisfies the first law of thermodynamics
for an isotropic system with a suitable definition of temperature. We apply our
formulation to several gravitational systems such as the expanding universe,
Schwarzschild and BTZ black holes, and gravitational plane waves. We confirm
the conservation of the proposed entropy density under any homogeneous and
isotropic expansion of the universe, the precise reproduction of the
Bekenstein-Hawking entropy incorporating the first law of thermodynamics, and
the existence of gravitational plane wave carrying no charge, respectively. We
also comment on the energy conservation during gravitational collapse in simple
models.


  Graphics Processing Units (GPUs) are widely-used accelerators for
data-parallel applications. In many GPU applications, GPU memory bandwidth
bottlenecks performance, causing underutilization of GPU cores. Hence,
disabling many cores does not affect the performance of memory-bound workloads.
While simply power-gating unused GPU cores would save energy, prior works
attempt to better utilize GPU cores for other applications (ideally
compute-bound), which increases the GPU's total throughput.
  In this paper, we introduce Morpheus, a new hardware/software co-designed
technique to boost the performance of memory-bound applications. The key idea
of Morpheus is to exploit unused core resources to extend the GPU last level
cache (LLC) capacity. In Morpheus, each GPU core has two execution modes:
compute mode and cache mode. Cores in compute mode operate conventionally and
run application threads. However, for the cores in cache mode, Morpheus invokes
a software helper kernel that uses the cores' on-chip memories (i.e., register
file, shared memory, and L1) in a way that extends the LLC capacity for a
running memory-bound workload. Morpheus adds a controller to the GPU hardware
to forward LLC requests to either the conventional LLC (managed by hardware) or
the extended LLC (managed by the helper kernel). Our experimental results show
that Morpheus improves the performance and energy efficiency of a baseline GPU
architecture by an average of 39% and 58%, respectively, across several
memory-bound workloads. Morpheus' performance is within 3% of a GPU design that
has a quadruple-sized conventional LLC. Morpheus can thus contribute to
reducing the hardware dedicated to a conventional LLC by exploiting idle cores'
on-chip memory resources as additional cache capacity.


  We present an absorption line analysis of the Lyman limit system (LLS) at
z=3.55 in our Magellan/MIKE spectrum of PKS2000-330. Our analysis of the Lyman
limit and full HI Lyman series constrains the total HI column density of the
LLS (N_HI = 10^[18.0 +/- 0.25] cm^{-2} for b_HI >= 20 km/s) and also the N_HI
values of the velocity subsystems comprising the absorber. We measure ionic
column densities for metal-line transitions associated with the subsystems and
use these values to constrain the ionization state (>90% ionized) and relative
abundances of the gas. We find an order of magnitude dispersion in the
metallicities of the subsystems, marking the first detailed analysis of
metallicity variations in an optically thick absorber. The results indicate
that metals are not well mixed within the gas surrounding high $z$ galaxies.
Assuming a single-phase photoionization model, we also derive an N_H-weighted
metallicity, <[Si/H]> = -1.66 +/- 0.25, which matches the mean metallicity in
the neutral ISM in high z damped Lya systems (DLAs). Because the line density
of LLSs is ~10 times higher than the DLAs, we propose that the former dominate
the metal mass-density at z~3 and that these metals reside in the galaxy/IGM
interface. Considerations of a multi-phase model do not qualitatively change
these conclusions. Finally, we comment on an anomalously large O^0/Si^+ ratio
in the LLS that suggests an ionizing radiation field dominated by soft UV
sources (e.g. a starburst galaxy). Additional abundance analysis is performed
on the super-LLS systems at z=3.19.


  The reactive uptake of carbonyl-containing volatile organic compounds (cVOCs)
by aqueous atmospheric aerosols is a likely source of particulate organic
material. The aqueous-phase secondary organic products of some cVOCs are
surface-active. Therefore, cVOC uptake can lead to organic film formation at
the gas-aerosol interface and changes in aerosol surface tension. We examined
the chemical reactions of two abundant cVOCs, formaldehyde and acetaldehyde, in
water and aqueous ammonium sulfate (AS) solutions mimicking tropospheric
aerosols. Secondary organic products were identified using Aerosol Chemical
Ionization Mass Spectrometry (Aerosol-CIMS), and changes in surface tension
were monitored using pendant drop tensiometry. Hemiacetal oligomers and aldol
condensation products were identified using Aerosol-CIMS. Acetaldehyde
depresses surface tension to 65(\pm2) dyn/cm in pure water (a 10% surface
tension reduction from that of pure water) and 62(\pm1) dyn/cm in AS solutions
(a 20.6% reduction from that of a 3.1 M AS solution). Surface tension
depression by formaldehyde in pure water is negligible; in AS solutions, a 9%
reduction in surface tension is observed. Mixtures of these species were also
studied in combination with methylglyoxal in order to evaluate the influence of
cross-reactions on surface tension depression and product formation in these
systems. We find that surface tension depression in the solutions containing
mixed cVOCs exceeds that predicted by an additive model based on the
single-species isotherms.


  In this article we establish theory of semi-orthogonal Parseval wavelets
associated to generalized multiresolution analysis (GMRA) for the local field
of positive characteristics (LFPC). By employing the properties of translation
invariant spaces on the core space of GMRA we obtain a characterization of
semi-orthogonal Parseval wavelets in terms of consistency equation for LFPC. As
a consequence, we obtain a characterization of an orthonormal (multi)wavelet to
be associated with an MRA in terms of multiplicity function as well as
dimension function of a (multi)wavelet. Further, we provide characterizations
of Parseval scaling functions, scaling sets and bandlimited wavelets together
with a Shannon type multiwavelet for LFPC.


  In which is developed a new form of superselection sectors of topological
origin. By that it is meant a new investigation that includes several
extensions of the traditional framework of Doplicher, Haag and Roberts in local
quantum theories. At first we generalize the notion of representations of nets
of C*-algebras, then we provide a brand new view on selection criteria by
adopting one with a strong topological flavour. We prove that it is coherent
with the older point of view, hence a clue to a genuine extension. In this
light, we extend Roberts' cohomological analysis to the case where 1--cocycles
bear non trivial unitary representations of the fundamental group of the
spacetime, equivalently of its Cauchy surface in case of global hyperbolicity.
A crucial tool is a notion of group von Neumann algebras generated by the
1-cocycles evaluated on loops over fixed regions. One proves that these group
von Neumann algebras are localized at the bounded region where loops start and
end and to be factorial of finite type I. All that amounts to a new invariant,
in a topological sense, which can be defined as the dimension of the factor. We
prove that any 1-cocycle can be factorized into a part that contains only the
charge content and another where only the topological information is stored.
This second part resembles much what in literature are known as geometric
phases. Indeed, by the very geometrical origin of the 1-cocycles that we
discuss in the paper, they are essential tools in the theory of net bundles,
and the topological part is related to their holonomy content. At the end we
prove the existence of net representations.


  Superconducting quantum point contacts are known to possess two subgap states
per each propagating mode. In this note we compute the low-temperature
relaxation rate of the upper subgap state into the lower one with the emission
of an acoustic phonon. If the reflection in the contact is small, the
relaxation time may become much longer than the characteristic lifetime of a
bulk quasiparticle.


  In the usual optomechanical systems, the stability of the systems severely
limits those researches of the macroscopic quantum effects. We study an usual
cavity optomechanical system where the frequency of the optical mode is shaken
periodically. We find that, when the optical shaking frequency is large enough,
the shake of the optical mode can stabilize the system. That means we can study
the macroscopic quantum effects of the mechanical resonator even in the strong
coupling region where the standard optomechanical systems are always unstable.
As examples, we study the ground-state cooling of the mechanical resonator and
the entanglement between the optical and mechanical modes in the conventional
unstable region, and the results indicate that the final mean phonon number and
entanglement not only can be achieved but also can be modulated by the optical
shaking parameters. Our proposal provides a method to study the macroscopic
quantum effects even in conventional unstable region.


  This work presents an unsupervised approach for improving WordNet that builds
upon recent advances in document and sense representation via distributional
semantics. We apply our methods to construct Wordnets in French and Russian,
languages which both lack good manual constructions.1 These are evaluated on
two new 600-word test sets for word-to-synset matching and found to improve
greatly upon synset recall, outperforming the best automated Wordnets in
F-score. Our methods require very few linguistic resources, thus being
applicable for Wordnet construction in low-resources languages, and may further
be applied to sense clustering and other Wordnet improvements.


  We present a billboard-based free-viewpoint video synthesizing algorithm for
sports scenes that can robustly reconstruct and render a high-fidelity
billboard model for each object, including an occluded one, in each camera. Its
contributions are (1) applicable to a challenging shooting condition where a
high precision 3D model cannot be built because a small number of cameras
featuring wide-baseline are equipped; (2) capable of reproducing appearances of
occlusions, that is one of the most significant issues for billboard-based
approaches due to the ineffective detection of overlaps. To achieve
contributions above, the proposed method does not attempt to find a
high-quality 3D model but utilizes a raw 3D model that is obtained directly
from space carving. Although the model is insufficiently accurate for producing
an impressive visual effect, precise objects segmentation and occlusions
detection can be performed by back-projecting it onto each camera plane. The
billboard model of each object in each camera is rendered according to whether
it is occluded or not, and its location in the virtual stadium is determined
considering the location of its 3D model. We synthesized free-viewpoint videos
of two soccer sequences recorded by five cameras with the proposed and
state-of-art methods to demonstrate its performance.


  Recent years have seen increasing use of supervised learning methods for
segmentation tasks. However, the predictive performance of these algorithms
depends on the quality of labels. This problem is particularly pertinent in the
medical image domain, where both the annotation cost and inter-observer
variability are high. In a typical label acquisition process, different human
experts provide their estimates of the "true" segmentation labels under the
influence of their own biases and competence levels. Treating these noisy
labels blindly as the ground truth limits the performance that automatic
segmentation algorithms can achieve. In this work, we present a method for
jointly learning, from purely noisy observations alone, the reliability of
individual annotators and the true segmentation label distributions, using two
coupled CNNs. The separation of the two is achieved by encouraging the
estimated annotators to be maximally unreliable while achieving high fidelity
with the noisy training data. We first define a toy segmentation dataset based
on MNIST and study the properties of the proposed algorithm. We then
demonstrate the utility of the method on three public medical imaging
segmentation datasets with simulated (when necessary) and real diverse
annotations: 1) MSLSC (multiple-sclerosis lesions); 2) BraTS (brain tumours);
3) LIDC-IDRI (lung abnormalities). In all cases, our method outperforms
competing methods and relevant baselines particularly in cases where the number
of annotations is small and the amount of disagreement is large. The
experiments also show strong ability to capture the complex spatial
characteristics of annotators' mistakes.


  A supersymmetric model with four generations is proposed, in which the top
quark is approximately degenerate in mass with the $W^{\pm}$ gauge boson,
$m_t\simeq m_W$, leading to values of $R_b$ in better agreement with the
present experimental data than in the Standard Model. The model shares many of
the good features of the minimal supersymmetric extension of the Standard Model
(MSSM), such as the unification of gauge and Yukawa couplings at a common
high-energy scale. The model differs from the MSSM by re-interpreting the
Tevatron ``top-quark'' events as the production of the fourth generation quark
$t\pri$, which decays dominantly to $bW^+$. The top quark decays primarily into
supersymmetric particles, $t\rta\widetilde t\widetilde\chi^0_1$, with
$\widetilde t\rta c\widetilde\chi^0_1$, thereby evading previous searches.
Light supersymmetric particles are predicted to lie in the mass range between
25 and 70 GeV, which together with the fourth generation leptons provide a rich
spectrum of new physics which can be probed at LEP-2 and the Tevatron.


  Let $ S $ be a hyperbolic surface. We investigate the topology of the space
of all curves on $ S $ which start and end at given points in given directions,
and whose curvatures are constrained to lie in a given interval $
(\kappa_1,\kappa_2) $. Such a space falls into one of four qualitatively
distinct classes, according to whether $ (\kappa_1,\kappa_2) $ contains,
overlaps, is disjoint from, or contained in the interval $ [-1,1] $. Its
homotopy type is computed in the latter two cases. We also study the behavior
of these spaces under covering maps when $ S $ is arbitrary (not necessarily
hyperbolic nor orientable) and show that if $ S $ is compact then they are
always nonempty.


  We seek to augment a geometric network in the Euclidean plane with shortcuts
to minimize its continuous diameter, i.e., the largest network distance between
any two points on the augmented network. Unlike in the discrete setting where a
shortcut connects two vertices and the diameter is measured between vertices,
we take all points along the edges of the network into account when placing a
shortcut and when measuring distances in the augmented network.
  We study this network augmentation problem for paths and cycles. For paths,
we determine an optimal shortcut in linear time. For cycles, we show that a
single shortcut never decreases the continuous diameter and that two shortcuts
always suffice to reduce the continuous diameter. Furthermore, we characterize
optimal pairs of shortcuts for convex and non-convex cycles. Finally, we
develop a linear time algorithm that produces an optimal pair of shortcuts for
convex cycles. Apart from the algorithms, our results extend to rectifiable
curves.
  Our work reveals some of the underlying challenges that must be overcome when
addressing the discrete version of this network augmentation problem, where we
minimize the discrete diameter of a network with shortcuts that connect only
vertices.


  Aim: We aim to measure the LyC signal from a sample of sources in the Chandra
deep field south. We collect star-forming galaxies (SFGs) and active galactic
nuclei (AGN) with accurate spectroscopic redshifts, for which Hubble Space
Telescope (HST) coverage and multi-wavelength photometry are available. Method:
We selected a sample of about 200 sources at z~3. Taking advantage of HST
resolution, we applied a careful cleaning procedure and rejected sources
showing nearby clumps with different colours, which could be lower-z
interlopers. Our clean sample consisted of 86 SFGs (including 19 narrow-band
selected Lya emitters) and 8 AGN (including 6 detected in X-rays). We measured
the LyC flux from aperture photometry in four narrow-band filters covering
wavelengths below a 912 A rest frame (3.11<z<3.53). We estimated the ratio
between ionizing (LyC flux) and 1400 A non-ionizing emissions for AGN and
galaxies. Results: By running population synthesis models, we assume an average
intrinsic L(1400 A)/L(900 A) ratio of 5 as the representative value for our
sample. With this value and an average treatment of the lines of sight of the
inter-galactic medium, we estimate the LyC escape fraction relative to the
intrinsic value (fesc_rel(LyC)). We do not directly detect ionizing radiation
from any individual SFG, but we are able to set a 1(2)sigma upper limit of
fesc_rel(LyC)<12(24)%. This result is consistent with other non-detections
published in the literature. No meaningful limits can be calculated for the
sub-sample of Lya emitters. We obtain one significant direct detection for an
AGN at z=3.46, with fesc_rel(LyC) = (72+/-18)%. Conclusions: Our upper limit on
fescrel(LyC) implies that the SFGs studied here do not present either the
physical properties or the geometric conditions suitable for efficient
LyC-photon escape.


  The charge distribution induced by external fields in finite stacks of
graphene planes, or in semiinfinite graphite is considered. The interlayer
electronic hybridization is described by a nearest neighbor hopping term, and
the charge induced by the self consistent electrostatic potential is calculated
within linear response (RPA). The screening properties are determined by
contributions from inter- and intraband electronic transitions. In neutral
systems, only interband transitions contribute to the charge polarizability,
leading to insulating-like screening properties, and to oscillations in the
induced charge, with a period equal to the interlayer spacing. In doped
systems, we find a screening length equivalent to 2-3 graphene layers,
superimposed to significant charge oscillations.


  B-spline based orbital representations are widely used in Quantum Monte Carlo
(QMC) simulations of solids, historically taking as much as 50% of the total
run time. Random accesses to a large four-dimensional array make it challenging
to efficiently utilize caches and wide vector units of modern CPUs. We present
node-level optimizations of B-spline evaluations on multi/many-core shared
memory processors. To increase SIMD efficiency and bandwidth utilization, we
first apply data layout transformation from array-of-structures to
structure-of-arrays (SoA). Then by blocking SoA objects, we optimize cache
reuse and get sustained throughput for a range of problem sizes. We implement
efficient nested threading in B-spline orbital evaluation kernels, paving the
way towards enabling strong scaling of QMC simulations. These optimizations are
portable on four distinct cache-coherent architectures and result in up to 5.6x
performance enhancements on Intel Xeon Phi processor 7250P (KNL), 5.7x on Intel
Xeon Phi coprocessor 7120P, 10x on an Intel Xeon processor E5v4 CPU and 9.5x on
BlueGene/Q processor. Our nested threading implementation shows nearly ideal
parallel efficiency on KNL up to 16 threads. We employ roofline performance
analysis to model the impacts of our optimizations. This work combined with our
current efforts of optimizing other QMC kernels, result in greater than 4.5x
speedup of miniQMC on KNL.


  This paper reviews and summarizes the research results on fact-based fake
news from the perspectives of tasks and problems, algorithm strategies, and
datasets. First, the paper systematically explains the task definition and core
problems of fact-based fake news detection. Second, the paper summarizes the
existing detection methods based on the algorithm principles. Third, the paper
analyzes the classic and newly proposed datasets in the field, and summarizes
the experimental results on each dataset. Finally, the paper summarizes the
advantages and disadvantages of existing methods, proposes several challenges
that methods in this field may face, and looks forward to the next stage of
research. It is hoped that this paper will provide reference for subsequent
work in the field.


  We introduce two algorithms for nonconvex regularized finite sum
minimization, where typical Lipschitz differentiability assumptions are relaxed
to the notion of relative smoothness. The first one is a Bregman extension of
Finito/MISO, studied for fully nonconvex problems when the sampling is
randomized, or under convexity of the nonsmooth term when it is essentially
cyclic. The second algorithm is a low-memory variant, in the spirit of SVRG and
SARAH, that also allows for fully nonconvex formulations. Our analysis is made
remarkably simple by employing a Bregman Moreau envelope as Lyapunov function.
In the randomized case, linear convergence is established when the cost
function is strongly convex, yet with no convexity requirements on the
individual functions in the sum. For the essentially cyclic and low-memory
variants, global and linear convergence results are established when the cost
function satisfies the Kurdyka-\L ojasiewicz property.


  With the Wide Field Planetary Camera 2 (WFPC2) on the Hubble Space Telescope,
we have discovered in M4 (NGC 6121, C 1620-264) the first extensive sequence of
cooling white dwarfs seen in a globular cluster. Adopting a distance modulus of
(m-M)_V = 12.65 and a reddening of E(B-V) = 0.37, we show that the sequence,
which extends over 9 < M_U < 13, is comprised of white dwarfs of mass \sim 0.5
M_{\odot}. The total mass loss from the present turnoff to the white dwarf
sequence is 0.31 M_{\odot} and the intrinsic dispersion in the mean mass
appears to be < 0.05 M_{\odot}. Both the location of the white dwarf cooling
sequence in the cluster color-magnitude diagram and the cumulative luminosity
function attest to the basic correctness and completeness of the physics in
theoretical models for the upper three magnitudes of the observed white dwarf
cooling sequence. To test the theory in globular clusters at cooling ages
beyond \sim 3 \times 10^8 years will require deeper and more complete data.


  We analyse mobile-immobile transport of particles that switch between the
mobile and immobile phases with finite rates. Despite this seemingly simple
assumption of Poissonian switching we unveil a rich transport dynamics
including significant transient anomalous diffusion and non-Gaussian
displacement distributions. Our discussion is based on experimental parameters
for tau proteins in neuronal cells, but the results obtained here are expected
to be of relevance for a broad class of processes in complex systems.
Concretely, we obtain that when the mean binding time is significantly longer
than the mean mobile time, transient anomalous diffusion is observed at short
and intermediate time scales, with a strong dependence on the fraction of
initially mobile and immobile particles. We unveil a Laplace distribution of
particle displacements at relevant intermediate time scales. For any initial
fraction of mobile particles, the respective mean squared displacement displays
a plateau. Moreover, we demonstrate a short-time cubic time dependence of the
mean squared displacement for immobile tracers when initially all particles are
immobile.


  Adiabatic frequency tuning of finite-lifetime-nanocavity electromagnetic
modes affects also their quality-factor (Q). Perturbative Q change resulting
from (real) frequency tuning, is a controllable parameter. Here, the influence
of dielectric constant modulation (DCM) on cavity resonances is presented, by
first order perturbation analysis for a 3D cavity with radiation losses.
Semi-analytical expressions for DCM induced cavity mode frequency and Q changes
are derived. The obtained results are in good agreement with numerical
calculations.


  We study the shortcut Fr\'{e}chet distance, a natural variant of the
Fr\'{e}chet distance, that allows us to take shortcuts from and to any point
along one of the curves. The classic Fr\'echet distance is a bottle-neck
distance measure and hence quite sensitive to outliers. The shortcut
Fr\'{e}chet distance allows us to cut across outliers and hence produces
significantly more meaningful results when dealing with real world data.
Driemel and Har-Peled recently described approximation algorithms for the
restricted case where shortcuts have to start and end at input vertices. We
show that, in the general case, the problem of computing the shortcut
Fr\'{e}chet distance is NP-hard. This is the first hardness result for a
variant of the Fr\'{e}chet distance between two polygonal curves in the plane.
We also present two algorithms for the decision problem: a 3-approximation
algorithm for the general case and an exact algorithm for the vertex-restricted
case. Both algorithms run in O(n^3 log n) time.


  We characterize singularities of focal surfaces of wave fronts in terms of
differential geometric properties of the initial wave fronts. Moreover, we
study relationships between geometric properties of focal surfaces and
geometric invariants of the initial wave fronts.


  The emission characteristics of intense laser driven protons are controlled
using ultra-strong (of the order of 10^9 V/m) electrostatic fields varying on a
few ps timescale. The field structures are achieved by exploiting the high
potential of the target (reaching multi-MV during the laser interaction).
Suitably shaped targets result in a reduction in the proton beam divergence,
and hence an increase in proton flux while preserving the high beam quality.
The peak focusing power and its temporal variation are shown to depend on the
target characteristics, allowing for the collimation of the inherently highly
divergent beam and the design of achromatic electrostatic lenses.


  Instabilities of robot motion are caused by topological reasons. In this
paper we find a relation between the topological properties of a configuration
space (the structure of its cohomology algebra) and the character of
instabilities, which are unavoidable in any motion planning algorithm. More
specifically, let $X$ denote the space of all admissible configurations of a
mechanical system. A {\it motion planner} is given by a splitting $X\times X =
F_1\cup F_2\cup ... \cup F_k$ (where $F_1, ..., F_k$ are pairwise disjoint
ENRs, see below) and by continuous maps $s_j: F_j \to PX,$ such that $E\circ
s_j =1_{F_j}$. Here $PX$ denotes the space of all continuous paths in $X$
(admissible motions of the system) and $E: PX\to X\times X$ denotes the map
which assigns to a path the pair of its initial -- end points. Any motion
planner determines an algorithm of motion planning for the system. In this
paper we apply methods of algebraic topology to study the minimal number of
sets $F_j$ in any motion planner in $X$. We also introduce a new notion of {\it
order of instability} of a motion planner; it describes the number of
essentially distinct motions which may occur as a result of small perturbations
of the input data. We find the minimal order of instability, which may have
motion planners on a given configuration space $X$. We study a number of
specific problems: motion of a rigid body in $\R^3$, a robot arm, motion in
$\R^3$ in the presence of obstacles, and others.


  In this paper, we study the global regularity estimates in Lorentz spaces for
gradients of solutions to quasilinear elliptic equations with measure data of
the form \begin{eqnarray*} \left\{ \begin{array}{rcl} -{\rm div}(\mathcal{A}(x,
\nabla u))&=& \mu \quad \text{in} ~\Omega, u&=&0 \quad \text{on}~ \partial
\Omega, \end{array}\right. \end{eqnarray*} where $\mu$ is a finite signed Radon
measure in $\Omega$, $\Omega \subset \mathbb{R}^n$ is a bounded domain such
that its complement $\mathbb{R}^n\backslash\Omega$ is uniformly $p$-thick and
$\mathcal{A}$ is a Carath\'eodory vector valued function satisfying growth and
monotonicity conditions for the strongly singular case $1<p\leq
\frac{3n-2}{2n-1}$. Our result extends the earlier results \cite{55Ph0,Tran19}
to the strongly singular case $1<p\leq \frac{3n-2}{2n-1}$ and a recent result
\cite{HP} by considering rough conditions on the domain $\Omega$ and the
nonlinearity $\mathcal{A}$.


  In robust optimization, the uncertainty set is used to model all possible
outcomes of uncertain parameters. In the classic setting, one assumes that this
set is provided by the decision maker based on the data available to her. Only
recently it has been recognized that the process of building useful uncertainty
sets is in itself a challenging task that requires mathematical support.
  In this paper, we propose an approach to go beyond the classic setting, by
assuming multiple uncertainty sets to be prepared, each with a weight showing
the degree of belief that the set is a "true" model of uncertainty. We consider
theoretical aspects of this approach and show that it is as easy to model as
the classic setting. In an extensive computational study using a shortest path
problem based on real-world data, we auto-tune uncertainty sets to the
available data, and show that with regard to out-sample performance, the
combination of multiple sets can give better results than each set on its own.


  We have attempted to analyse all the available data taken by XMM-Newton as it
slews between targets. This slew survey, the resultant source catalogue and the
analysis procedures used are described in an accompanying paper. In this letter
we present the initial science results from the survey. To date, detailed
source-searching has been performed in three X-ray bands (soft, hard and total)
in the EPIC-pn 0.2-12 keV band over ~6300 sq.degrees (~15% of the sky), and of
order 4000 X-ray sources have been detected (~55% of which have IDs). A great
variety of sources are seen, including AGN, galaxies, clusters and groups,
active stars, SNRs, low- and high-mass XRBs and white dwarfs. In particular, as
this survey constitutes the deepest ever hard-band 2-12 keV all-sky survey, a
large number of hard sources are detected. Furthermore, the great sensitivity
and low-background of the EPIC-pn camera are especially suited to emission from
extended sources, and interesting spatial structure is observed in many
supernova remnants and clusters of galaxies. The instrument is very adept at
mapping large areas of the X-ray sky. Also, as the slew survey is well matched
to the ROSAT all-sky survey, long-term variability studies are possible, and a
number of extremely variable X-ray sources, some possibly due to the tidal
disruption of stars by central supermassive black holes, have been discovered.


  Biological vision adopts a coarse-to-fine information processing pathway,
from initial visual detection and binding of salient features of a visual
scene, to the enhanced and preferential processing given relevant stimuli. On
the contrary, CNNs employ a fine-to-coarse processing, moving from local,
edge-detecting filters to more global ones extracting abstract representations
of the input. In this paper we reverse the feature extraction part of standard
bottom-up architectures and turn them upside-down: We propose top-down
networks. Our proposed coarse-to-fine pathway, by blurring higher frequency
information and restoring it only at later stages, offers a line of defence
against adversarial attacks that introduce high frequency noise. Moreover,
since we increase image resolution with depth, the high resolution of the
feature map in the final convolutional layer contributes to the explainability
of the network's decision making process. This favors object-driven decisions
over context driven ones, and thus provides better localized class activation
maps. This paper offers empirical evidence for the applicability of the
top-down resolution processing to various existing architectures on multiple
visual tasks.


  In this paper we present our imaging observations on the CO(7-6) line and its
underlying continuum emission of the young submillimeter galaxy LESS 073 at
redshift 4.755, using the Atacama Large Millimeter/submillimeter Array (ALMA).
At the achieved resolution of
$\sim$$1^{\prime\prime}.2\times0^{\prime\prime}.9$ ($8\times6$~kpc$^2$), the
CO(7-6) emission is largely unresolved (with a deconvolved size of
$1^{\prime\prime}.1(\pm0^{\prime\prime}.5) \times
0^{\prime\prime}.9(\pm0^{\prime\prime}.8)$), and the continuum emission is
totally unresolved. The CO(7-6) line emission has an integrated flux of
$0.86\pm0.08$~Jy km/s, and a line width of $343\pm40$ km/s. The continuum
emission has a flux density of 0.51 mJy. By fitting the observed far-infrared
(FIR) spectral energy distribution of LESS 073 with a single-temperature
modified blackbody function, we obtained a dust temperature $T_{\rm
dust}=57.6\pm3.5$ K, 60-to-100 $\mu$m flux density ratio
$f_{60}/f_{100}=0.86\pm0.08$, and total infrared luminosity $L_{\rm
IR}=(5.8\pm0.9) \times 10^{12}~L_\odot$. The SED-fit-based $f_{60}/f_{100}$ is
consistent with those estimated from various line ratios as advocated by our
earlier work, indicating that those proposed line-ratio-based method can be
used to practically derive $f_{60}/f_{100}$ for high-$z$ sources. The total
molecular gas mass of LESS 073 is $(3.3\pm1.7) \times10^{10}~M_\odot$, and the
inferred gas depletion time is about 43 Myr.


  Experimental data on the number of neutrons born in the heavy water targets
of the large neutrino detectors are used to set the limit on the proton
life-time independently on decay mode through the reaction d -> n+?. The best
up-to-date limit tau_p > 4 10^23 yr with 95% C.L. is derived from the
measurements with D_2O target (mass 267 kg) installed near the Bugey reactor.
This value can be improved by six orders of magnitude with future data
accumulated with the SNO detector containing 1000 t of D_2O.


  Introduced by Kodama and Williams, Bruhat interval polytopes are generalized
permutohedra closely connected to the study of torus orbit closures and total
positivity in Schubert varieties. We show that the 1-skeleton posets of these
polytopes are lattices and classify when the polytopes are simple, thereby
resolving open problems and conjectures of Fraser, of Lee--Masuda, and of
Lee--Masuda--Park. In particular, we classify when generic torus orbit closures
in Schubert varieties are smooth.


  In this paper, we prove that almost every translation of $\mathbb{T}^2$
admits a symbolic coding which has linear complexity $2n+1$. The partitions are
constructed with Rauzy fractals associated with sequences of substitutions,
which are produced by a particular extended continued fraction algorithm in
projective dimension $2$. More generally, in dimension $d\geq 1$, we study
extended measured continued fraction algorithms, which associate to each
direction a subshift generated by substitutions, called $S$-adic subshift. We
give some conditions which imply the existence, for almost every direction, of
a translation of the torus $\mathbb{T}^d$ and a nice generating partition, such
that the associated coding is a conjugacy with the subshift.


  RGB-Infrared (IR) person re-identification is an important and challenging
task due to large cross-modality variations between RGB and IR images. Most
conventional approaches aim to bridge the cross-modality gap with feature
alignment by feature representation learning. Different from existing methods,
in this paper, we propose a novel and end-to-end Alignment Generative
Adversarial Network (AlignGAN) for the RGB-IR RE-ID task. The proposed model
enjoys several merits. First, it can exploit pixel alignment and feature
alignment jointly. To the best of our knowledge, this is the first work to
model the two alignment strategies jointly for the RGB-IR RE-ID problem.
Second, the proposed model consists of a pixel generator, a feature generator,
and a joint discriminator. By playing a min-max game among the three
components, our model is able to not only alleviate the cross-modality and
intra-modality variations but also learn identity-consistent features.
Extensive experimental results on two standard benchmarks demonstrate that the
proposed model performs favorably against state-of-the-art methods. Especially,
on SYSU-MM01 dataset, our model can achieve an absolute gain of 15.4% and 12.9%
in terms of Rank-1 and mAP.


  Dust extinction and stellar confusion by the Milky Way reduce the efficiency
of detecting galaxies at low Galactic latitudes, creating the so-called Zone of
Avoidance. This stands as a stumbling block in charting the distribution of
galaxies and cosmic flow fields, and therewith our understanding of the local
dynamics in the Universe (CMB dipole, convergence radius of bulk flows). For
instance, ZoA galaxies are generally excluded from the whole-sky Tully-Fisher
Surveys ($|b| \leq 5^\circ$) even if catalogued. We show here that by
fine-tuning the near-infrared TF relation, there is no reason not to extend
peculiar velocity surveys deeper into the ZoA. Accurate axial ratios ($b/a$)
are crucial to both the TF sample selection and the resulting TF distances. We
simulate the effect of dust extinction on the geometrical properties of
galaxies. As expected, galaxies appear rounder with increasing obscuration
level, even affecting existing TF samples. We derive correction models and
demonstrate that we can reliably reproduce the intrinsic axial ratio from the
observed value up to extinction level of about $A_J\simeq3$ mag ($A_V\sim11$
mag), we also recover a fair fraction of galaxies that otherwise would fall out
of an uncorrected inclination limited galaxy sample. We present a
re-calibration of the 2MTF relation in the NIR $J$, $H$, and $K_s$-bands for
isophotal rather than total magnitudes, using their same calibration sample.
Both TF relations exhibit similar scatter at high Galactic latitudes. However,
the isophotal TF relation results in a significant improvement in the scatter
for galaxies in the ZoA, and low surface brightness galaxies in general,
because isophotal apertures are more robust in the face of significant stellar
confusion.


  We introduce a Bayesian solution for the problem in forensic speaker
recognition, where there may be very little background material for estimating
score calibration parameters. We work within the Bayesian paradigm of evidence
reporting and develop a principled probabilistic treatment of the problem,
which results in a Bayesian likelihood-ratio as the vehicle for reporting
weight of evidence. We show in contrast, that reporting a likelihood-ratio
distribution does not solve this problem. Our solution is experimentally
exercised on a simulated forensic scenario, using NIST SRE'12 scores, which
demonstrates a clear advantage for the proposed method compared to the
traditional plugin calibration recipe.


  We study the coupled surface and grain boundary motion in a bicrystal in the
context of the "quarter loop" geometry. Two types of physics motions are
involved in this model: motion by mean curvature and motion by surface
diffusion. The goal is finding a formulation that can describe the coupled
motion and has good numerical behavior when discretized. Two formulations are
proposed in this paper. One of them is given by a mixed order parabolic system
and the other is given by Partial Differential Algebraic Equations. The
parabolic formulation constitutes several parabolic equations which model the
two normal direction motions separately. The performance of this formulation is
good for a short time simulation. It performs even better by adding an extra
term to adjust the tangential velocity of grid points. The PDAE formulation
preserves the scaled arc length property and performs much better with no need
to add an adjusting term. Both formulations are proven to be well-posed in a
simpler setting and are solved by finite difference methods.


  Using computer simulations of two charged colloidal spheres with their
counterions in a hard sphere solvent, we show that the granular nature of the
solvent significantly influences the effective colloidal interaction. For
divalent counterions, the total effective force can become attractive generated
by counterion hydration, while for monovalent counterions the forces are
repulsive and well-described by a solvent-induced colloidal charge
renormalization. Both effects are not contained in the traditional "primitive"
approaches but can be accounted for in a solvent-averaged primitive model.


  The problem of audio-to-audio (A2A) style transfer involves replacing the
style features of the source audio with those from the target audio while
preserving the content related attributes of the source audio. In this paper,
we propose an efficient approach, termed as Zero-shot Emotion Style Transfer
(ZEST), that allows the transfer of emotional content present in the given
source audio with the one embedded in the target audio while retaining the
speaker and speech content from the source. The proposed system builds upon
decomposing speech into semantic tokens, speaker representations and emotion
embeddings. Using these factors, we propose a framework to reconstruct the
pitch contour of the given speech signal and train a decoder that reconstructs
the speech signal. The model is trained using a self-supervision based
reconstruction loss. During conversion, the emotion embedding is alone derived
from the target audio, while rest of the factors are derived from the source
audio. In our experiments, we show that, even without using parallel training
data or labels from the source or target audio, we illustrate zero shot emotion
transfer capabilities of the proposed ZEST model using objective and subjective
quality evaluations.


  Multilegged robots have the ability to perform stable locomotion on
relatively rough terrain. However, the complexity of legged robots over wheeled
or tracked robots make them difficult to control. This paper presents OpenSHC
(Open-source Syropod High-level Controller), a versatile high-level controller
{capable of generating gaits and poses for quasi-static multilegged robots,
both simulated and with real hardware implementations. With full Robot
Operating System (ROS) integration, the controller can be quickly deployed on
robots with different actuators and sensor payloads}. The flexibility of
OpenSHC is demonstrated on the 30 degrees of freedom hexapod Bullet, analysing
the energetic performance of various leg configurations, kinematic arrangements
and gaits over different locomotion speeds. With OpenSHC being easily
configured to different physical and locomotion specifications, a
hardware-based parameter space search for optimal locomotion parameters is
conducted. The experimental evaluation shows that the mammalian configuration
offers lower power consumption across a range of step frequencies; with the
insectoid configuration providing performance advantages at higher body
velocities and increased stability at low step frequencies. OpenSHC is
open-source and able to be configured for various number of joints and legs.


  The emergence of generative Large Language Models (LLMs) emphasizes the need
for accurate and efficient prompting approaches. LLMs are often applied in
Few-Shot Learning (FSL) contexts, where tasks are executed with minimal
training data. FSL has become popular in many Artificial Intelligence (AI)
subdomains, including AI for health. Rare diseases affect a small fraction of
the population. Rare disease identification from clinical notes inherently
requires FSL techniques due to limited data availability. Manual data
collection and annotation is both expensive and time-consuming. In this paper,
we propose Models-Vote Prompting (MVP), a flexible prompting approach for
improving the performance of LLM queries in FSL settings. MVP works by
prompting numerous LLMs to perform the same tasks and then conducting a
majority vote on the resulting outputs. This method achieves improved results
to any one model in the ensemble on one-shot rare disease identification and
classification tasks. We also release a novel rare disease dataset for FSL,
available to those who signed the MIMIC-IV Data Use Agreement (DUA).
Furthermore, in using MVP, each model is prompted multiple times, substantially
increasing the time needed for manual annotation, and to address this, we
assess the feasibility of using JSON for automating generative LLM evaluation.


  We perform a classification of all potential supersymmetric $R$-parity
violating signatures at the LHC to address the question: are existing bounds on
supersymmetric models robust, or are there still signatures not covered by
existing searches, allowing LHC-scale supersymmetry to be hiding? We analyze
all possible scenarios with one dominant RPV trilinear coupling at a time,
allowing for arbitrary LSPs and mass spectra. We consider direct production of
the LSP, as well as production via gauge-cascades, and find 6 different
experimental signatures for the $LL\bar E$-case, 6 for the $LQ\bar D$-case, and
5 for the $\bar U\bar D\bar D$-case; together these provide complete coverage
of the RPV-MSSM landscape. This set of signatures is confronted with the
existing searches by \texttt{ATLAS} and \texttt{CMS}. We find all signatures
have been covered at the LHC, although not at the sensitivity level needed to
probe the direct production of all LSP types. For the case of a dominant
$LL\bar E$-operator, we use \texttt{CheckMATE} to quantify the current lower
bounds on the supersymmetric masses and find the limits to be comparable to or
better than the $R$-parity conserving case. Our treatment can be easily
extended to scenarios with more than one non-zero RPV coupling.


  This paper studies a risk minimization problem with decision dependent data
distribution. The problem pertains to the performative prediction setting where
a trained model can affect the outcome that the model estimates. Such
dependency creates a feedback loop that influences the stability of
optimization algorithms such as stochastic gradient descent (SGD). We present
the first study on performative prediction with smooth but possibly non-convex
loss. We analyze a greedy deployment scheme with SGD (SGD-GD). Note that in the
literature, SGD-GD is often studied with strongly convex loss. We first propose
the definition of stationary performative stable (SPS) solutions through
relaxing the popular performative stable condition. We then prove that SGD-GD
converges to a biased SPS solution in expectation. We consider two conditions
of sensitivity on the distribution shifts: (i) the sensitivity is characterized
by Wasserstein-1 distance and the loss is Lipschitz w.r.t.~data samples, or
(ii) the sensitivity is characterized by $\chi^2$-divergence and the loss is
bounded. In both conditions, the bias levels are proportional to stochastic
gradient's variance and sensitivity level. Our analysis is extended to a lazy
deployment scheme where models are deployed once per several SGD updates, and
we show that it converges to a bias-free SPS solution. Numerical experiments
corroborate our theories.


  Flow-Imaging Microscopy (FIM) is commonly used in both academia and industry
to characterize subvisible particles (those $\le 25 \mu m$ in size) in protein
therapeutics. Pharmaceutical companies are required to record vast volumes of
FIM data on protein therapeutic products, but are only mandated under US FDA
regulations (i.e., USP $\big \langle 788 \big \rangle$) to control the number
of particles exceeding $10$ and $25 \mu m$ in delivered products. Hence, a vast
amount of digital images are available to analyze. Current state-of-the-art
methods rely on a relatively low-dimensional list of "morphological features"
to characterize particles, but these methods ignore an enormous amount of
information encoded in the existing large digital image repositories. Deep
Convolutional Neural Networks (CNNs or "ConvNets") have demonstrated the
ability to extract predictive information from raw macroscopic image data
without requiring the selection or specification of "morphological features" in
a variety of tasks. However, the heterogeneity, polydispersity of protein
therapeutics, and optical phenomena associated with subvisible FIM particle
measurements introduce new challenges regarding the application of CNNs to FIM
image analysis. In this article, we demonstrate a supervised learning technique
leveraging CNNs to extract information from raw images in order to predict the
process conditions or stress states (freeze-thaw, mechanical shaking, etc.)
that produced a variety of different protein images. We demonstrate that our
new classifier (in combination with a sample "image pooling" strategy) can
obtain nearly perfect predictions using as few as 20 FIM images from a given
protein formulation in a variety of scenarios of relevance to protein
therapeutics quality control and process monitoring.


  Jet models of Event Horizon Telescope (EHT) data should also conform to the
observed jet profiles just downstream. This study evaluates conformance of
models of black hole jets to images of the innermost jet of M87. This is a
basic test that should be passed before using them to perform a physical
interpretation of EHT data. Recent 86 GHz Very Long Baseline Interferometry
observations of M87 have revealed the morphology and size of the jet near its
source ($<65$\,M, or 0.06 lt-yrs after correcting for line of sight to the jet,
where $M$ is the black hole mass in geometrized units) for the first time.
Current transverse resolution indicates that this region is dominated by flux
emanating from the edge of the jet. The observed inner jet profiles are
compared to all existing published synthetic radio images constructed from
"state of the art" 3-D numerical simulations of the black hole accretion system
in M87. Despite efforts to produce the characteristic wide, edge dominated jet,
these models are too narrow (by a factor of $\sim2$) in the region 0.06 - 0.32
lt-yrs from the source, even though the jets (spine and/or sheath) in the image
plane might appear conformant farther downstream. Furthermore, the synthetic
radio images are not edge dominated 0.06 - 0.32 lt-yrs from the source, but
spine dominated. Analyses that implement these models as physical diagnostics
of EHT visibility amplitudes are therefore suspect. Thus, these inner jet
characteristics are important considerations before applying simulations to the
EHT data.


  We determine the quantization condition for the energy levels of two
interacting particles in a finite box in a ``moving frame'', i.e. one in which
the total momentum of pions is non-zero. This condition is valid up to
corrections which fall exponentially withe the box size, and holds only below
the inelastic threshold. It is derived using field theoretic methods, using a
generalization of previous summation formulae relating sums and integrals over
momenta. The result agrees with that obtained earlier by Rummakainen and
Gottlieb using a relativistic quantum mechanical approach. Technically, we
expand the finite-volume four-point Green function in terms of the
infinite-volume Bethe-Salpeter kernel, and determine the position of the poles.
The final result is written in terms of the two-pion scattering phase shift.
Our result can be used to facilitate the determination of the scattering phase
shift, and can be used to generalize the Lellouch-L\"uscher formula relating
finite-volume two-particle matrix elements to those in infinite volume.


  A rigorous proof is presented of the boundedness of the entanglement entropy
of a block of spins for the ground state of the one-dimensional quantum Ising
model with sufficiently strong transverse field. This is proved by a refinement
of the arguments in the earlier work by the same authors (J. Statist. Phys. 131
(2008) 305-339). The proof is geometrical, and utilises a transformation to a
model of classical probability called the continuum random-cluster model. Our
method of proof is fairly robust, and applies also to certain disordered
systems.


  We derive a feasible criterion for the bias-optimal selection of the tuning
parameters involved in estimating the integrated volatility of the spot
volatility via the simple realized estimator by Barndorff-Nielsen and Veraart
(2009). Our analytic results are obtained assuming that the spot volatility is
a continuous mean-reverting process and that consecutive local windows for
estimating the spot volatility are allowed to overlap in a finite sample
setting. Moreover, our analytic results support some optimal selections of
tuning parameters prescribed in the literature, based on numerical evidence.
Interestingly, it emerges that window-overlapping is crucial for optimizing the
finite-sample bias of volatility-of-volatility estimates.


  A search for excited quarks is performed using the full ep data sample
collected by the H1 experiment at HERA, corresponding to a total integrated
luminosity of 475 pb^-1. The electroweak decays of excited quarks q* -> q
gamma, q* -> q Z and q* -> q W with subsequent hadronic or leptonic decays of
the W and Z bosons are considered. No evidence for first generation excited
quark production is found. Mass dependent exclusion limits on q* production
cross sections and on the ratio f/Lambda of the coupling to the compositeness
scale are derived within gauge mediated models. These limits extend the
excluded region compared to previous excited quark searches.


  Student commitment towards a learning recommendation is not separable from
their understanding of the reasons it was recommended to them; and their
ability to modify it based on that understanding. Among explainability
approaches, chatbots offer the potential to engage the student in a
conversation, similar to a discussion with a peer or a mentor. The capabilities
of chatbots, however, are still not sufficient to replace a human mentor,
despite the advancements of generative AI (GenAI) and large language models
(LLM). Therefore, we propose an approach to utilize chatbots as mediators of
the conversation and sources of limited and controlled generation of
explanations, to harvest the potential of LLMs while reducing their potential
risks at the same time. The proposed LLM-based chatbot supports students in
understanding learning-paths recommendations. We use a knowledge graph (KG) as
a human-curated source of information, to regulate the LLM's output through
defining its prompt's context. A group chat approach is developed to connect
students with human mentors, either on demand or in cases that exceed the
chatbot's pre-defined tasks. We evaluate the chatbot with a user study, to
provide a proof-of-concept and highlight the potential requirements and
limitations of utilizing chatbots in conversational explainability.


  We present an in-depth study of masses and decays of excited scalar and
pseudoscalar $\bar{q}q$ states in the Extended Linear Sigma Model (eLSM). The
model also contains ground-state scalar, pseudoscalar, vector and axial-vector
mesons. The main objective is to study the consequences of the hypothesis that
the $f_0(1790)$ resonance, observed a decade ago by the BES Collaboration and
recently by LHCb, represents an excited scalar quarkonium. In addition we also
analyse the possibility that the new $a_0(1950)$ resonance, observed recently
by BABAR, may also be an excited scalar state. Both hypotheses receive
justification in our approach although there appears to be some tension between
the simultaneous interpretation of $f_0(1790)$/$a_0(1950)$ and pseudoscalar
mesons $\eta(1295)$, $\pi(1300)$, $\eta(1440)$ and $K(1460)$ as excited
$\bar{q}q$ states.


  We develop a theory of the conductance of superconductor/normal
metal/superconductor junctions in the case where the superconducting order
parameter has d-wave symmetry. At low temperature the conductance is
proportional to the square root of the inelastic electron relaxation time in
the bulk of the superconductor. As a result it turns out to be much larger than
the conductance of the normal part of the junction.


  In this paper, a pragmatic semantic communication framework that enables
effective goal-oriented information sharing between two-intelligent agents is
proposed. In particular, semantics is defined as the causal state that
encapsulates the fundamental causal relationships and dependencies among
different features extracted from data. The proposed framework leverages the
emerging concept in machine learning (ML) called theory of mind (ToM). It
employs a dynamic two-level (wireless and semantic) feedback mechanism to
continuously fine-tune neural network components at the transmitter. Thanks to
the ToM, the transmitter mimics the actual mental state of the receiver's
reasoning neural network operating semantic interpretation. Then, the estimated
mental state at the receiver is dynamically updated thanks to the proposed
dynamic two-level feedback mechanism. At the lower level, conventional channel
quality metrics are used to optimize the channel encoding process based on the
wireless communication channel's quality, ensuring an efficient mapping of
semantic representations to a finite constellation. Additionally, a semantic
feedback level is introduced, providing information on the receiver's perceived
semantic effectiveness with minimal overhead. Numerical evaluations demonstrate
the framework's ability to achieve efficient communication with a reduced
amount of bits while maintaining the same semantics, outperforming conventional
systems that do not exploit the ToM-based reasoning.


  We prove that the double layer potential operator and the gradient of the
single layer potential operator are L_2 bounded for general second order
divergence form systems. As compared to earlier results, our proof shows that
the bounds for the layer potentials are independent of well posedness for the
Dirichlet problem and of De Giorgi-Nash local estimates. The layer potential
operators are shown to depend holomorphically on the coefficient matrix A\in
L_\infty, showing uniqueness of the extension of the operators beyond singular
integrals. More precisely, we use functional calculus of differential operators
with non-smooth coefficients to represent the layer potential operators as
bounded Hilbert space operators. In the presence of Moser local bounds, in
particular for real scalar equations and systems that are small perturbations
of real scalar equations, these operators are shown to be the usual singular
integrals. Our proof gives a new construction of fundamental solutions to
divergence form systems, valid also in dimension 2.


  The effect of rarefaction acceleration on the propagation dynamics and
structure of relativistically hot jets is studied through relativistic
hydrodynamic simulations. We emphasize the nonlinear interaction of rarefaction
waves excited at the interface between a cylindrical jet and the surrounding
medium. From simplified one-dimensional models with radial jet structure, we
find that a decrease in the relativistic pressure due to the interacting
rarefaction waves in the central zone of the jet transiently yields a more
powerful boost of the bulk jet than that expected from single rarefaction
acceleration. This leads to a cyclic in-situ energy conversion between thermal
and bulk kinetic energies which induces radial oscillating motion of the jet.
The oscillation timescale is characterized by the initial pressure ratio of the
jet to the ambient medium, and follows a simple scaling relation $\tau_{\rm
oscillation} \propto (P_{\rm jet,0}/P_{\rm amb,0})^{1/2}$. It is confirmed from
extended two-dimensional simulations that this radial oscillating motion in the
one-dimensional system manifests as modulation of the structure of the jet in a
more realistic situation where a relativistically hot jet propagates through an
ambient medium. It is found that when the ambient medium has a power law
pressure distribution, the size of the reconfinement region along the
propagation direction of the jet in the modulation structure $\lambda$ evolves
according to a self-similar relation $\lambda \propto t^{\alpha/2}$ where
$\alpha$ is the power-law index of the pressure distribution.


  Gaussian Boson sampling (GBS) plays a crucially important role in
demonstrating quantum advantage. As a major imperfection, the limited
connectivity of the linear optical network weakens the quantum advantage result
in recent experiments. Here we present a faster classical algorithm to simulate
the GBS process with limited connectivity. In this work, we introduce an
enhanced classical algorithm for simulating GBS processes with limited
connectivity. It computes the loop Hafnian of an $n \times n$ symmetric matrix
with bandwidth $w$ in $O(nw2^w)$ time which is better than the previous fastest
algorithm which runs in $O(nw^2 2^w)$ time. This classical algorithm is helpful
on clarifying how limited connectivity affects the computational complexity of
GBS and tightening the boundary of quantum advantage in the GBS problem.


  Reflection and transmission as a function of temperature have been measured
on a single crystal of the magnetoelectric ferrimagnetic compound
Cu$_{2}$OSeO$_{3}$ utilizing light spanning the far infrared to the visible
portions of the electromagnetic spectrum. The complex dielectric function and
optical properties were obtained via Kramers-Kronig analysis and by fits to a
Drude-Lortentz model. The fits of the infrared phonons show a magnetodielectric
effect near the transition temperature ($T_{c}\sim 60$~K). Assignments to
strong far infrared phonon modes have been made, especially those exhibiting
anomalous behavior around the transition temperature.


  The design, construction and operation of a Compton back-scattering laser
polarimeter at the HERA storage ring at DESY are described. The device measures
the longitudinal polarization of the electron beam between the spin rotators at
the HERMES experiment with a fractional systematic uncertainty of 1.6%. A
measurement of the beam polarization to an absolute statistical precision of
0.01 requires typically one minute when the device is operated in the
multi-photon mode. The polarimeter also measures the polarization of each
individual electron bunch to an absolute statistical precision of 0.06 in
approximately five minutes. It was found that colliding and non-colliding
bunches can have substantially different polarizations. This information is
important to the collider experiments H1 and ZEUS for their future
longitudinally polarized electron program because those experiments use the
colliding bunches only.


  The physics of the Mott transition in the anodic region of NiO Resistance
Random Access Memory (RRAM) is discussed from the Hubbard model. The Hubbard
approximation is examined in details and it is shown that the Wannier functions
in the definition of Hubbard U should not be replaced by atomic s-functions
when it comes to the metallic side of the transition. The corresponding
effective Hubbard U is subject to variations, which may also be understood by
introducing an effective permittivity of the solid as an ansatz. Furthermore,
the transition could be demonstrated in the Brinkman-Rice picture. Finally, the
anodic characteristics of such transition show that it is a local Mott
transition. Therefore, the unipolar switching NiO RRAM can still have
asymmetric I-V curves when a capping layer is inserted, which is explained
qualitatively by quantum mechanics.


  We introduce the notion of Demazure descent data on a triangulated category C
and define the descent category for such data. We illustrate the definition by
our basic example. Let G be a reductive algebraic group with a Borel subgroup
B. Demazure functors form Demazure descent data on the derived category of
Rep(B) and the descent category is equivalent to the derived category of
Rep(G).


  An efficient two-layer coding method using the histogram packing technique
with the backward compatibility to the legacy JPEG is proposed in this paper.
The JPEG XT, which is the international standard to compress HDR images, adopts
two-layer coding scheme for backward compatibility to the legacy JPEG. However,
this two-layer coding structure does not give better lossless performance than
the other existing single-layer coding methods for HDR images. Moreover, the
JPEG XT has problems on determination of the lossless coding parameters;
Finding appropriate combination of the parameter values is necessary to achieve
good lossless performance. The histogram sparseness of HDR images is discussed
and it is pointed out that the histogram packing technique considering the
sparseness is able to improve the performance of lossless compression for HDR
images and a novel two-layer coding with the histogram packing technique is
proposed. The experimental results demonstrate that not only the proposed
method has a better lossless compression performance than that of the JPEG XT,
but also there is no need to determine image-dependent parameter values for
good compression performance in spite of having the backward compatibility to
the well known legacy JPEG standard.


  Here we address the hot Jupiter (hJ) pile-up at 0.05 AU around young
solar-type stars observed in stellar radial velocity surveys, the hJ longterm
orbital stability in the presence of stellar tides, and the hJ occurrence rate
of 1.2 (+-0.38)% in one framework. We calculate the combined torques on the
planet from the stellar dynamical tide and from the protoplanetary disk in the
type II migration regime. We model a 2D nonisothermal viscous disk
parameterized to reproduce the minimum-mass solar nebula and simulate an inner
disk cavity at various radial positions near the star. We choose stellar
rotation periods according to observations of young star clusters. The planet
is on a circular orbit in the disk midplane and in the star's equatorial plane.
We show that the torques can add up to zero beyond the corotation radius around
young stars and stop inward migration. Monte Carlo simulations predict hot
Jupiter survival rates between ~3% (alpha disk viscosity of 1e-1) and 15%
(alpha = 1e-3). Once the protoplanetary disk has been fully accreted, the
surviving hJs are pushed outward from their tidal migration barrier and pile up
near 0.05 AU, as we demonstrate using a numerical implementation of a stellar
dynamical tide model. Orbital decay is negligible on a one-billion-year
timescale due to the contraction of the highly dissipative convective envelopes
in young Sun-like stars. We find that the higher pile-up efficiency around
metal-rich stars can at least partly explain the observed positive correlation
between stellar metallicity and hJ occurrence. Combined with the observed hJ
occurrence rate, our results for the survival rate imply that <8 % (alpha =
1e-3) to <43 % (alpha = 1e-1) of sun-like stars initially encounter an inward
migrating hJ. This reconciles models and observations of young spinning stars
with the observed hJ pile up and hJ occurrence rates.


  We describe a method to calculate the electronic properties of an insulator
under an applied electric field. It is based on the minimization of an electric
enthalpy functional with respect to the orbitals, which behave as Wannier
functions under crystal translations, but are not necessarily orthogonal. This
paper extends the approach of Nunes and Vanderbilt (NV) [Phys. Rev. Lett. 73,
712 (1994)], who demonstrated that a Wannier function representation can be
used to study insulating crystals in the presence of a finite electric field.
According to a study by Fern\'{a}ndez et al. [Phys. Rev. B. 58, R7480 (1998)],
first-principles implementations of the NV approach suffer from the impact of
the localization constraint on the orthogonal wave functions, what affects the
accuracy of the physical results. We show that because non-orthogonal
generalized Wannier functions can be more localized than their orthogonal
counterparts, the error due to localization constraints is reduced, thus
improving the accuracy of the calculated physical quantities.


  We find a new example of an asymptotically $AdS_5 \times S^5$ geometry which
has an entanglement shadow: that is, a region of spacetime which no
Ryu-Takayanagi minimal surface enters. Our example is a particular case of the
supersymmetric LLM geometries. Our results illustrate how minimal surfaces,
which holographically geometrize entanglement entropy, can fail to probe the
whole of spacetime, posing a challenge for attempts to directly reconstruct
holographic geometries from the entanglement entropies of the dual field
theory. We also comment on the relation to previous investigations of minimal
surfaces localised in the $S^5$ factor of AdS$_5 \times S^5$.


  Efforts to understand the microscopic origin of superconductivity in the
cuprates are dependent on knowledge of the normal state. The Hall number in the
low temperature, high field limit $n_{\rm H}(0)$ has a particular significance
because within conventional transport theory it is simply related to the number
of charge carriers, and so its evolution with doping gives crucial information
about the nature of the charge transport. Here we report a study of the high
field Hall coefficient of the single-layer cuprates
Tl$_2$Ba$_2$CuO$_{6+\delta}$ (Tl2201) and (Pb/La) doped
Bi$_2$Sr$_2$CuO$_{6+\delta}$ (Bi2201) which shows how $n_{\rm H}(0)$ evolves in
the overdoped, so-called strange metal, regime of cuprates. We find that
$n_{\rm H}(0)$ increases smoothly from $p$ to $1+p$, where $p$ is the number of
holes doped into the parent insulating state, over a wide range of doping. The
evolution of $n_{\rm H}$ correlates with the emergence of the anomalous
linear-in-$T$ term in the low-$T$ in-plane resistivity. The results could
suggest that quasiparticle decoherence extends to dopings well beyond the
pseudogap regime.


  Uplift modeling is an emerging machine learning approach for estimating the
treatment effect at an individual or subgroup level. It can be used for
optimizing the performance of interventions such as marketing campaigns and
product designs. Uplift modeling can be used to estimate which users are likely
to benefit from a treatment and then prioritize delivering or promoting the
preferred experience to those users. An important but so far neglected use case
for uplift modeling is an experiment with multiple treatment groups that have
different costs, such as for example when different communication channels and
promotion types are tested simultaneously. In this paper, we extend standard
uplift models to support multiple treatment groups with different costs. We
evaluate the performance of the proposed models using both synthetic and real
data. We also describe a production implementation of the approach.


  In this paper we show the existence of ground-state solutions for the
energy-critical NLS perturbed with subcritical terms when the space dimension
$d\geq4$. However in dimension three, we show that when the perturbation is
small enough, then such solution does not exist. For the evolution equation, we
show the existence of finite time blow up of solutions with radially symmetric
data with energy below the one of the ground state.


  By modelling the expansion of a cloud of electrons and positrons with the
temperature 400 keV that propagates at the mean speed 0.9c ($c:$ speed of
light) through an initially unmagnetized electron-proton plasma with a
particle-in-cell (PIC) simulation, we find a mechanism that collimates the pair
cloud into a jet. A filamentation instability develops between the protons at
rest and the moving positrons. Its magnetic field collimates the positrons and
drives an electrostatic shock into the electron-proton plasma. The magnetic
field acts as a discontinuity that separates the protons of the shocked ambient
plasma, known as the outer cocoon, from the jet's interior region. The outer
cocoon expands at the speed 0.15c along the jet axis and at 0.03c
perpendicularly to it. The filamentation instability converts the jet's
directed flow energy into magnetic energy in the inner cocoon. The magnetic
discontinuity cannot separate the ambient electrons from the jet electrons.
Both species rapidly mix and become indistinguishable. The spatial distribution
of the positive charge carriers is in agreement with the distributions of the
ambient material and the jet material predicted by a hydrodynamic model apart
from a dilute positronic outflow that is accelerated by the electromagnetic
field at the jet's head.


  Strong approximations of uniform transport processes to the standard Brownian
motion rely on the Skorokhod embedding of random walk with centered double
exponential increments. In this note we make such an embedding explicit by
means of a Poissonian scheme, which both simplifies classic constructions of
strong approximations of uniform transport processes (Griego et al. (1971)) and
improves their rate of strong convergence (Gorostiza et al. (1980)). We
finalise by providing an extension regarding the embedding of a random walk
with asymmetric double exponential increments.


  We consider the problem of measuring the margin of robust feasibility of
solutions to a system of nonlinear equations. We study the special case of a
system of quadratic equations, which shows up in many practical applications
such as the power grid and other infrastructure networks. This problem is a
generalization of quadratically constrained quadratic programming (QCQP), which
is NP-Hard in the general setting. We develop approaches based on topological
degree theory to estimate bounds on the robustness margin of such systems. Our
methods use tools from convex analysis and optimization theory to cast the
problems of checking the conditions for robust feasibility as a nonlinear
optimization problem. We then develop inner bound and outer bound procedures
for this optimization problem, which could be solved efficiently to derive
lower and upper bounds, respectively, for the margin of robust feasibility. We
evaluate our approach numerically on standard instances taken from the MATPOWER
and NESTA databases of AC power flow equations that describe the steady state
of the power grid. The results demonstrate that our approach can produce tight
lower and upper bounds on the margin of robust feasibility for such instances.


  We discuss an optimal investment, consumption and insurance problem of a wage
earner under inflation. Assume a wage earner investing in a real money account
and three asset prices, namely: a real zero coupon bond, the inflation-linked
real money account and a risky share described by jump-diffusion processes.
Using the theory of quadratic-exponential backward stochastic differential
equation (BSDE) with jumps approach, we derive the optimal strategy for the two
typical utilities (exponential and power) and the value function is
characterized as a solution of BSDE with jumps. Finally, we derive the explicit
solutions for the optimal investment in both cases of exponential and power
utility functions for a diffusion case.


  Forming planets around young, fast-rotating solar-like stars are exposed to
an intense X-ray/extreme ultraviolet radiation field and strongly magnetized
stellar winds, as a consequence of the high magnetic activity of these stars.
Under these conditions, Earth-like exoplanets may experience a rapid loss of
their primordial hydrogen atmospheres, resulting in atmosphere-less rocky
obstacles for the stellar winds. The interaction of stellar winds with those
planets leads to the formation of potentially observable structures due to the
formation of large-scale magnetic field and density disturbances in the
vicinity of these planets, such as bow shocks, induced magnetospheres and
comet-like tails. In this work, we study the interaction between the stellar
winds of active, fast-rotating solar-like stars in the superfast-magnetosonic
regime with Earth-like, unmagnetized, tenuous atmosphere, planetary obstacles
through numerical 3D simulations using the PLUTO magnetohydrodynamical code.
The properties of AB Doradus, a nearby young star with a small rotation period
(0.51 days) and a strong flaring activity, have been used to parameterize this
early wind state. Bow shock and induced magnetosphere formation are
characterized through the alfv\'enic Mach number MA of the wind, for different
stellar wind configurations. Large bow shocks, up to an extension of ~7.0
planetary radii are found for low-MA winds. The general increase of density,
temperature and magnetic field in these large-scale structures formed around
planets may result in potentially detectable spectral signatures.


  A novel topological insulator with tunable edge states, called quantum
spin-quantum anomalous Hall (QSQAH) insulator, is predicted in a
heterostructure of a hydrogenated Sb (SbH) monolayer on a LaFeO3 substrate by
using ab initio methods. The substrate induces a drastic staggered exchange
field in the SbH film, which plays an important role to generate the QSQAH
effect. A topologically nontrivial band gap (up to 35 meV) is opened by Rashba
spin-orbit coupling, which can be enlarged by strain and electric field. To
understand the underlying physical mechanism of the QSQAH effect, a
tight-binding model based on px and py orbitals is constructed. With the model,
the exotic behaviors of the edge states in the heterostructure are
investigated. Dissipationless chiral charge edge states related to one valley
are found to emerge along the both sides of the sample, while low-dissipation
spin edge states related to the other valley flow only along one side of the
sample. These edge states can be tuned flexibly by polarization-sensitive
photoluminescence controls and/or chemical edge modifications. Such flexible
manipulations of the charge, spin, and valley degrees of freedom provide a
promising route towards applications in electronics, spintronics, and
valleytronics.