  We report the discovery of nearly coherent oscillations with a frequency of
567 Hz during type-I X-ray bursts from the X-ray transient and eclipsing binary
X 1658-298. If these oscillations are directly related to the neutron star
rotation then the spin period of the neutron star in X 1658-298 is 1.8 ms. The
oscillations can be present during the rise or decay phase of the bursts.
Oscillations during the decay phase of the bursts show an increase in the
frequency of 0.5 to 1 Hz. However, in one particular burst the oscillations
reappear at the end of the decay phase at about 571.5 Hz. This represents an
increase in oscillation frequency of about 5 Hz which is the largest frequency
change seen so far in a burst oscillation. It is unclear if such a large change
can be accommodated by present models used to explain the frequency evolution
of the oscillations. The oscillations at 571.5 Hz are unusually soft compared
to the oscillations found at 567 Hz. We also observed several bursts during
which the oscillations are detected at much lower significance or not at all.
Most of these bursts happen during periods of X-ray dipping behavior,
suggesting that the X-ray dipping might decrease the amplitude of the
oscillations (although several complications exist with this simple picture).
We discuss our discovery in the framework of the neutron star spin
interpretation.


  A facility based on a next-generation, high-flux D-D neutron generator has
been commissioned and it is now operational at the University of California,
Berkeley. The current generator design produces near monoenergetic 2.45 MeV
neutrons at outputs of 10^8 n/s. Calculations provided show that future
conditioning at higher currents and voltages will allow for a production rate
over 10^10 n/s. A significant problem encountered was beam-induced electron
backstreaming, that needed to be resolved to achieve meaningful beam currents.
Two methods of suppressing secondary electrons resulting from the deuterium
beam striking the target were tested: the application of static electric and
magnetic fields. Computational simulations of both techniques were done using a
finite element analysis in COMSOL Multiphysics. Experimental tests verified
these simulation results. The most reliable suppression was achieved via the
implementation of an electrostatic shroud with a voltage offset of -800 V
relative to the target.


  For the precision study at the ILC 250, measurement of $A_{LR}$ is important
as it can constrain SMEFT parameters. The current best measured $A_{LR}$ value
is $A_{LR} = 0.1514 \pm 0.0019\,(stat) \pm 0.0011\,(syst)$ which was measured
at the SLC, and a more precise value is required for the global fit for the new
physics search in TeV-scale. At the ILC, we can use the $e^+ e^- \to \gamma Z$
process to evaluate the $A_{LR}$. We performed a full simulation study of the
$e^+ e^- \to \gamma Z$ process at the center-of-mass energy of 250 GeV and
evaluated how much we can improve the precision of this observable. The
statistical error on $A_{LR}$ at the ILC 250 turned out to be $1.8 \times
10^{-4}$. Major source of the systematic error was error from the beam
polarization. As other sources of the systematic error, the uncorrelated parts
of error on the product of luminosity and selection efficiency for each
polarization combination contribute. Including those systematic errors, total
absolute error on $A_{LR}$ was estimated to be 0.00025, 8.8 times better
precision than that from the SLC (0.00219).


  We carry out a model-theoretic analysis of the Heisenberg algebra. To this
end, a geometric structure is associated to the Heisenberg algebra and is shown
to be a Zariski geometry. Furthermore, this Zariski geometry is shown to be
non-classical, in the sense that it is not interpretable in an algebraically
closed field. On assuming self-adjointness of the position and momentum
operators, one obtains a discrete substructure of which the original Zariski
geometry is seen as the complexification.


  The Gamma distribution is well-known and widely used in many signal
processing and communications applications. In this letter, a simple and
extremely efficient accept/reject algorithm is introduced for the generation of
independent random variables from a Gamma distribution with any shape parameter
\alpha >= 1. The proposed method uses another Gamma distribution with integer
\alpha_p <= \alpha, from which samples can be easily drawn, as proposal
function. For this reason, the new technique attains a higher acceptance rate
(AR) for \alpha >= 3 than all the methods currently available in the
literature, with AR tends to 1 as \alpha\ diverges.


  A new method for reducing metal artifacts in X-ray computed tomography (CT)
images is presented. It bases on the solution of a convex optimization problem
with inequality constraints on the sinogram, and total variation regularization
for the reconstructed image. The Chambolle-Pock algorithm is used to
numerically solve the discretized version of the optimization problem. As proof
of concept we present and discuss numerical results for synthetic data.


  We show that a Hitchin representation is determined by the spectral radii of
the images of simple, non-separating closed curves. As a consequence, we
classify isometries of the intersection function on Hitchin components of
dimension 3 and on the self-dual Hitchin components in all dimensions. As an
important tool in the proof, we establish a transversality result for positive
quadruples of flags.


  Based on the UrQMD model, we have investigated the influence of the symmetry
potential on the negatively and positively charged $\pi$ and $\Sigma$ hyperon
production ratios in heavy ion collisions at the SIS energies. We find that, in
addition to $\pi^-/\pi^+$ ratio, the $\Sigma^-/\Sigma^+$ ratio can be taken as
a sensitive probe for investigating the density dependence of the symmetry
potential of nuclear matter at high densities (1-4 times of normal baryon
density). This sensitivity of the symmetry potential to both the $\pi^-/\pi^+$
and $\Sigma^-/\Sigma^+$ ratios is found to depend strongly on the incident beam
energy. Furthermore, the $\Sigma^-/\Sigma^+$ ratio is shown to carry the
information about the isospin-dependent part of the $\Sigma$ hyperon
single-particle potential.


  We present a new approach for the simulation of Beyond Standard Model (BSM)
physics within the Herwig++ event generator. Our approach is more generic than
previous methods with the aim of minimising the effort of implementing further
new physics models. Spin correlations, which are important for BSM models due
to new heavy fermions and bosons, are discussed and their effects demonstrated
for the Minimal Supersymmetric Standard Model (MSSM) and Randall-Sundrum Model
using our new framework.


  Lesion detection is an important problem within medical imaging analysis.
Most previous work focuses on detecting and segmenting a specialized category
of lesions (e.g., lung nodules). However, in clinical practice, radiologists
are responsible for finding all possible types of anomalies. The task of
universal lesion detection (ULD) was proposed to address this challenge by
detecting a large variety of lesions from the whole body. There are multiple
heterogeneously labeled datasets with varying label completeness: DeepLesion,
the largest dataset of 32,735 annotated lesions of various types, but with even
more missing annotation instances; and several fully-labeled single-type lesion
datasets, such as LUNA for lung nodules and LiTS for liver tumors. In this
work, we propose a novel framework to leverage all these datasets together to
improve the performance of ULD. First, we learn a multi-head multi-task lesion
detector using all datasets and generate lesion proposals on DeepLesion.
Second, missing annotations in DeepLesion are retrieved by a new method of
embedding matching that exploits clinical prior knowledge. Last, we discover
suspicious but unannotated lesions using knowledge transfer from single-type
lesion detectors. In this way, reliable positive and negative regions are
obtained from partially-labeled and unlabeled images, which are effectively
utilized to train ULD. To assess the clinically realistic protocol of 3D
volumetric ULD, we fully annotated 1071 CT sub-volumes in DeepLesion. Our
method outperforms the current state-of-the-art approach by 29% in the metric
of average sensitivity.


  The x-vector based deep neural network (DNN) embedding systems have
demonstrated effectiveness for text-independent speaker verification. This
paper presents a multi-task learning architecture for training the speaker
embedding DNN with the primary task of classifying the target speakers, and the
auxiliary task of reconstructing the first- and higher-order statistics of the
original input utterance. The proposed training strategy aggregates both the
supervised and unsupervised learning into one framework to make the speaker
embeddings more discriminative and robust. Experiments are carried out using
the NIST SRE16 evaluation dataset and the VOiCES dataset. The results
demonstrate that our proposed method outperforms the original x-vector approach
with very low additional complexity added.


  ARTOS is all about creating, tuning, and applying object detection models
with just a few clicks. In particular, ARTOS facilitates learning of models for
visual object detection by eliminating the burden of having to collect and
annotate a large set of positive and negative samples manually and in addition
it implements a fast learning technique to reduce the time needed for the
learning step.
  A clean and friendly GUI guides the user through the process of model
creation, adaptation of learned models to different domains using in-situ
images, and object detection on both offline images and images from a video
stream. A library written in C++ provides the main functionality of ARTOS with
a C-style procedural interface, so that it can be easily integrated with any
other project.


  Despite their effective use in various fields, many aspects of neural
networks are poorly understood. One important way to investigate the
characteristics of neural networks is to explore the loss landscape. However,
most models produce a high-dimensional non-convex landscape which is difficult
to visualize. We discuss and extend existing visualization methods based on 1D-
and 2D slicing with a novel method that approximates the actual loss landscape
geometry by using charts with interpretable axes. Based on the assumption that
observations on small neural networks can generalize to more complex systems
and provide us with helpful insights, we focus on small models in the range of
a few dozen weights, which enables computationally cheap experiments and the
use of an interactive dashboard. We observe symmetries around the zero vector,
the influence of different layers on the global landscape, the different weight
sensitivities around a minimizer, and how gradient descent navigates high-loss
obstacles. The user study resulted in an average SUS (System Usability Scale)
score with suggestions for improvement and opened up a number of possible
application scenarios, such as autoencoders and ensemble networks.


  Water surfaces catalyze some organic reactions more effectively, making them
unique for 2D organic material synthesis. This report introduces a new
synthesis method via surfactant-monolayer-assisted interfacial synthesis on
water surfaces for ring-opening polymerization of pyrrole, producing distinct
polypyrrole derivatives with polyacetylene backbones and ionic substitutions.
The synthesis result in quasi 2D polyacetylene (q2DPA) film with enhanced
charge transport behavior. We employed time-of-flight photoconductivity (TOFP)
measurements using pulsed laser light of tunable wavelength for photoexcitation
of the charge carriers within the q2DPA film. The charge transport was measured
in the lateral direction as a function of external bias voltage ranging from 0
V to 200 V. We observed high electron mobility ({\mu}) of q2DPA reaching values
of 375 cm2 V-1 s-1 at bias voltage Vb = -20V and photon energy of 3.8 eV.


  Massive electrodynamics for London's superconductivity and Josephson effect
are derived. The propagation of massive boson inside a medium yields electric
phenomena that are reflected in the Josephson effect. Critical force, magnetic
field and temperature are found to be related to the critical current of the
junction. The mass of the boson depends only on the critical current of the
junction. The electromagnetic interaction between the Cooper pairs in the two
sides of the superconductor in the josephson junction is mediated by a massive
boson. The propagation of the electromagnetic waves mediated by the massive
bosons gives rise to the electric properties of the Josephson junction. Of
these properties are a quantized resistance of Hall type corresponding to a
non-quantized magnetic flux, and a quantized capacitance. A non zero magnetic
flux encompassing a magnetic charge is found to arise despite the fact that it
is not a priori assumed.


  Furthering the understanding of the catalytic mechanisms in the oxygen
reduction reaction (ORR) is critical to advancing and enabling fuel cell
technology. In this work, we use multimodal operando synchrotron X-ray
diffraction (XRD) and resonant elastic X-ray scattering (REXS) to investigate
the interplay between the structure and oxidation state of a Co-Mn spinel oxide
electrocatalyst, which has previously shown ORR activity that rivals Pt in
alkaline fuel cells. During cyclic voltammetry, the electrocatalyst exhibited a
reversible and rapid increase in tensile strain at low potentials, suggesting
robust structural reversibility and stability of Co-Mn oxide electrocatalysts
during normal fuel cell operating conditions. At low potential holds, exploring
the limit of structural stability, an irreversible tetragonal-to-cubic phase
transition was observed, which may be correlated to reduction in both Co and Mn
valence states. Meanwhile, joint density-functional theory (JDFT) calculations
provide insight into how reactive adsorbates induce strain in spinel oxide
nanoparticles. Through this work, strain and oxidation state changes that are
possible sources of degradation during the ORR in Co-Mn oxide electrocatalysts
are uncovered, and the unique capabilities of combining structural and chemical
characterization of electrocatalysts in multimodal operando X-ray studies are
demonstrated.


  We theoretically study the spectral properties of a pump-probe driven hybrid
spinning optomechanical ring resonator optically coupled with a two-level
quantum emitter (QE or qubit). Recently we have shown [arXiv:1810.03709] that
in the absence of the emitter the coupled cavity version of this setup is not
only capable of nonreciprocal light propagation but can also exhibit slow &
fast light propagation. In this work, we investigate in what ways the presence
of a single QE coupled with the optical whispering gallery modes of the
spinning optomechanical resonator can alter the probe light nonreciprocity.
Under the weak-excitation assumption and mean-field approximation, we find that
the interplay between the rotational/spinning Sagnac-effect and the qubit
coupling can lead to the enhancement both in the optomechanically induced
transparency (OMIT) peak value and in the width of the transparency window due
to the opening of qubit-assisted back reflection channel. However, compared to
the no-qubit case, we notice that such an enhancement comes at the cost of
degrading the group delay in probe light transmission by a factor of 1/2 for
clockwise rotary directions. The target applications of these results can be in
the areas of quantum circuitry and in non-reciprocal quantum communication
protocols where QEs are a key component.


  We study static vortex type solutions of pure gravity for $D \geq 4+1 $.
Non-singular vortex solutions can be obtained by considering periodic
Kaluza-Klein monopoles. We also show that away from the center of the vortices
the space is described by the gravitational instantons derived from minimal
surfaces.


  We present a simple characterization of equivalent Bayesian network
structures based on local transformations. The significance of the
characterization is twofold. First, we are able to easily prove several new
invariant properties of theoretical interest for equivalent structures. Second,
we use the characterization to derive an efficient algorithm that identifies
all of the compelled edges in a structure. Compelled edge identification is of
particular importance for learning Bayesian network structures from data
because these edges indicate causal relationships when certain assumptions
hold.


  The goals of Learning Analytics (LA) are manifold, among which helping
students to understand their academic progress and improving their learning
process, which are at the core of our work. To reach this goal, LA relies on
educational data: students' traces of activities on VLE, or academic,
socio-demographic information, information about teachers, pedagogical
resources, curricula, etc. The data sources that contain such information are
multiple and diverse. Data mining, specifically pattern mining, aims at
extracting valuable and understandable information from large datasets. In our
work, we assume that multiple educational data sources form a rich dataset that
can result in valuable patterns. Mining such data is thus a promising way to
reach the goal of helping students. However, heterogeneity and interdependency
within data lead to high computational complexity. We thus aim at designing low
complex pattern mining algorithms that mine multi-source data, taking into
consideration the dependency and heterogeneity among sources. The patterns
formed are meaningful and interpretable, they can thus be directly used for
students.


  The geometry and topology of the region in which a director field is embedded
impose limitations on the kind of supported orientational order. These
limitations manifest as compatibility conditions that relate the quantities
describing the director field to the geometry of the embedding space. For
example, in two dimensions (2D) the splay and bend fields suffice to determine
a director uniquely (up to rigid motions) and must comply with one relation
linear in the Gaussian curvature of the embedding manifold. In 3D there are
additional local fields describing the director, i.e. fields available to a
local observer residing within the material, and a number of distinct ways to
yield geometric frustration. So far it was unknown how many such local fields
are required to uniquely describe a 3D director field, nor what are the
compatibility relations they must satisfy. In this work, we address these
questions directly. We employ the method of moving frames to show that a
director field is fully determined by five local fields. These fields are shown
to be related to each other and to the curvature of the embedding space through
six differential relations. As an application of our method, we characterize
all uniform distortion director fields, i.e., directors for which all the local
characterizing fields are constant in space, in manifolds of constant
curvature. The classification of such phases has been recently provided for
directors in Euclidean space, where the textures correspond to foliations of
space by parallel congruent helices. For non-vanishing curvature, we show that
the pure twist phase is the only solution in positively curved space, while in
the hyperbolic space uniform distortion fields correspond to foliations of
space by (non-necessarily parallel) congruent helices. Further analysis is
expected to allow to also construct of new non-uniform director fields.


  We propose a gauged $U(1)_{B-L}$ extension of the standard model (SM) to
explain simultaneously the light neutrino masses and dark matter (DM). The
generation of neutrino masses occurs through a variant of type-II seesaw
mechanism in which one of the scalar triplets lies at the TeV scale yet have a
large dilepton coupling, which paves a path for probing this model at
colliders. The gauging of $U(1)_{B-L}$ symmetry in a type-II seesaw framework
introduces $B-L$ anomalies. Therefore we invoke three right handed neutrinos
$\nu_{R_{i}}$(i=1,2,3) with $B-L$ charges -4,-4,+5 to cancel the anomalies. We
further show that the lightest one among the three right handed neutrinos can
be a viable DM candidate. The stability of DM can be owed to a remnant $Z_2$
symmetry under which the right handed neutrinos are odd while all other
particles are even. We then discuss the constraints on the model parameters
from observed DM abundance and the search at direct detection experiments.


  We present a semi-analytical approach to the determination of the dynamic
properties of randomly branched polymers under the Rouse approximation. The
principle procedure is based on examining a spectrum of eigenvalues which
represents the average dynamic behavior of various structures. The calculated
spectra show that the eigenvalue distribution is random even within a single
structure which in turn produces a continuous spectrum of values for the entire
class. The auto-correlation functions for the radius of gyration squared were
calculated based on these spectra, which confirms that the dynamics is
non-exponential as earlier reported. A universal stretched exponent is also
found in this study.


  We study the time-resolved photoassociation of ultracold sodium in an optical
dipole trap. The photoassociation laser excites pairs of atoms to molecular
states of large total angular momentum at high intensities (above 20
kW/cm$^{2}$). Such transitions are generally suppressed at ultracold
temperatures by the centrifugal barriers for high partial waves. Time-resolved
ionization measurements reveal that the atoms are accelerated by the dipole
potential of the photoassociation beam. We change the collision energy by
varying the potential depth, and observe a strong variation of the
photoassociation rate. These results demonstrate the important role of light
forces in cw photoassociation at high intensities.


  We discuss the occurrence of oscillatory solutions which decay to 0 as
$s\to+\infty$ for a class of perturbed second order ordinary differential
equations. As opposed to other results in the recent literature, the
perturbation is as small as desired in terms of its improper integrals and it
is independent of the coefficients of the non-oscillatory unperturbed equation.
This class of equations reveals thus a new pathology in the theory of perturbed
oscillations.


  We consider a class of logarithmic Keller-Segel type systems modeling the
spatio-temporal behavior of either chemotactic cells or criminal activities in
spatial dimensions two and higher. Under certain assumptions on parameter
values and given functions, the existence of classical solutions is established
globally in time, provided that initial data are sufficiently regular. In
particular, we enlarge the range of chemotatic sensitivity $\chi$, compared to
known results, in case that spatial dimensions are between two and eight. In
addition, we provide new type of small initial data to obtain global classical
solution, which is also applicable to the urban crime model. We discuss
long-time asymptotic behaviors of solutions as well.


  We present a non-parametric method to estimate the discount curve from market
quotes based on the Moore-Penrose pseudoinverse. The discount curve reproduces
the market quotes perfectly, has maximal smoothness, and is given in
closed-form. The method is easy to implement and requires only basic linear
algebra operations. We provide a full theoretical framework as well as several
practical applications.


  We present a subtraction scheme for computing jet cross sections in
electron-positron annihilation at next-to-next-to-leading order accuracy in
perturbative QCD. In this first part we deal with the regularization of the
doubly-real contribution to the NNLO correction.


  Given the absence of directly detected dark matter (DM) as weakly interacting
massive particles, there is strong interest in the possibility that DM is an
ultra-light scalar field, here denoted as fuzzy DM. Ultra-diffuse galaxies,
with the sizes of giant galaxies and the luminosities of dwarf galaxies, have a
wide range of DM halo masses, thus providing new opportunities for exploring
the connections between galaxies and their DM halos. Following up on new
integral field unit spectroscopic observations and dynamics modeling of the
DM-dominated ultra-diffuse galaxy Dragonfly 44 in the outskirts of the Coma
Cluster, we present models of fuzzy DM constrained by the stellar dynamics of
this galaxy. We infer a scalar field mass of $\sim 3 \times 10^{-22}$ eV,
consistent with other constraints from galaxy dynamics but in tension with
constraints from Ly$\alpha$ forest power spectrum modeling. While we are unable
to statistically distinguish between fuzzy DM and normal cold DM models, we
find that the inferred properties of the fuzzy DM halo satisfy a number of
predictions for halos in a fuzzy DM cosmology. In particular, we find good
agreement with the predicted core size--halo mass relation and the predicted
transition radius between the quantum pressure-dominated inner region and the
outer halo region.


  The fermion Green function and spectral characteristics for the 2D Frohlich
model of superconductivity at static fluctuations in the phase of the order
parameter are calculated. The results demonstrate strongly non-Fermi-liquid
properties of the system at finite temperatures and relate with the pseudogap
behavior of high-$T_{c}$ superconductors at relatively small charge carrier
densities.


  This paper deals with generalized elliptic integrals and generalized modular
functions. Several new inequalities are given for these and related functions.


  Adversarial optimal transport has been proven useful as a mathematical
formulation to model resource allocation problems to maximize the efficiency of
transportation with an adversary, who modifies the data. It is often the case,
however, that only the adversary knows which nodes are malicious and which are
not. In this paper we formulate the problem of seeking adversarial optimal
transport into Bayesian games. We construct the concept of Bayesian equilibrium
and design a distributed algorithm that achieve those equilibria, making our
model applicable to large-scale networks. Keywords: game theory, crime control,
Markov games


  We study existence and multiplicity of positive radial solutions for a
coupled elliptic system in exterior domains where the nonlinearities depend on
the gradients and the boundary conditions are nonlocal. We use a non-standard
cone to establish existence of solutions by means of fixed point index theory.


  This paper is concerned with the factorization method with a single far-field
pattern to recover an arbitrary convex polygonal scatterer/source in linear
elasticity. The approach also applies to the compressional (resp. shear) part
of the far-field pattern excited by a single compressional (resp. shear) plane
wave. The one-wave factorization is based on the scattering data for a priori
given testing scatterers. It can be regarded as a domain-defined sampling
method and does not require forward solvers. We derive the spectral system of
the far-field operator for rigid disks and show that, using testing disks, the
one-wave factorization method can be justified independently of the classical
factorization method.


  Lower bound for ${\bar \rho}''(0)$, the second derivative of the spherically
averaged atomic electronic density at the nucleus, and upper bound for ${\bar
\rho}'''(0)$, the third derivative, are obtained respectively. It is shown
that, for the ground state, ${\bar \rho}''(0) \ge {10/3} Z^2 \rho(0)$ and
${\bar \rho}'''(0) \le -{14/3}Z^3 \rho(0)$ where $Z$ is the charge of the
nucleus, and $\rho(0)$ is the electron density at the nucleus. Tighter bounds
for ${\bar \rho}''(0)$ and ${\bar \rho}'''(0)$ are also reported which are
valid for both the ground state and excited states. Explicit illustration with
the example of one-electron atomic ions is given.


  XMM-Newton observed the soft gamma repeater SGR 1806-20 about two months
after its 2004 December 27 giant flare. A comparison with the previous
observations taken with the same instrument in 2003-2004 shows that the pulsed
fraction and the spin-down rate have significantly decreased and that the
spectrum slightly softened. These changes may indicate a global reconfiguration
of the neutron star magnetosphere. The spectral analysis confirms that the
presence of a blackbody component in addition to the power-law is required.
Since this additional component is consistent with being constant with respect
to the earlier observations, we explore the possibility of describing the
long-term spectral evolution as only due to the power-law variations. In this
case, the slope of the power-law does not significantly change and the spectral
softening following the giant flare is caused by the increase of the relative
contribution of the blackbody over the power-law component.


  The AMS02 experiment has published the periodic spectra of proton, helium and
helium isotopes across the majority of the 24 solar cycle. These precise data
exhibit temporal structures that correlate with solar modulation. In this
study, we utilize these data to probe three analytic solar modulation models,
including the force-field approximation, the convection-diffusion model and the
extended force-field approximation with a drift effect. We adopt a method that
eliminates the influence of interstellar cosmic ray spectra, and use the
Earth-observed spectra at time $t_1$ to predict those at time $t_2$. In order
to explore the rigidity-dependence of solar modulation models, we substitute
the conventional potential parameter $\phi$ with a modified parameter
$\phi'=\frac{R}{ k_2(R)}\phi$ for our analysis. Combining with the $\chi^2$
minimization method, the best-fit modulation parameter $\phi'$ can be
evaluated. First, we test the validity of a rigidity-independent $\phi'$ and
find that both the force-field approximation (FFA) and the extended force-field
approximation (EFFA) agree well with data near the solar minimum period.
However, all models significantly deviate from the data during the solar
maximum. Consequently, we assume a constant $\phi'(t_1)$ at solar minimum and
calculate $\Delta\phi'=\phi'(t_2)-\phi'(t_1)$ for each rigidity bin at time
$t_2$. It is found that $\Delta\phi'$ generally adheres to a linear-logarithm
relationship with rigidity at any given time. By adopting a linear-logarithm
formula of $\Delta\phi'$, we further discover that both the modified FFA and
EFFA can reconcile the observations during solar maxima. This suggests that at
solar maximum, the parameter $\phi'$, which correlates with the diffusion
pattern in the heliospheric magnetic fields, exhibits a rigidity dependence.


  Streaming automatic speech recognition (ASR) aims to emit each hypothesized
word as quickly and accurately as possible. However, emitting fast without
degrading quality, as measured by word error rate (WER), is highly challenging.
Existing approaches including Early and Late Penalties and Constrained
Alignments penalize emission delay by manipulating per-token or per-frame
probability prediction in sequence transducer models. While being successful in
reducing delay, these approaches suffer from significant accuracy regression
and also require additional word alignment information from an existing model.
In this work, we propose a sequence-level emission regularization method, named
FastEmit, that applies latency regularization directly on per-sequence
probability in training transducer models, and does not require any alignment.
We demonstrate that FastEmit is more suitable to the sequence-level
optimization of transducer models for streaming ASR by applying it on various
end-to-end streaming ASR networks including RNN-Transducer,
Transformer-Transducer, ConvNet-Transducer and Conformer-Transducer. We achieve
150-300 ms latency reduction with significantly better accuracy over previous
techniques on a Voice Search test set. FastEmit also improves streaming ASR
accuracy from 4.4%/8.9% to 3.1%/7.5% WER, meanwhile reduces 90th percentile
latency from 210 ms to only 30 ms on LibriSpeech.


  Automatic code generation is to generate the program code according to the
given natural language description. The current mainstream approach uses neural
networks to encode natural language descriptions, and output abstract syntax
trees (AST) at the decoder, then convert the AST into program code. While the
generated code largely conforms to specific syntax rules, two problems are
still ignored. One is missing program testing, an essential step in the process
of complete code implementation; the other is only focusing on the syntax
compliance of the generated code, while ignoring the more important program
functional requirements. The paper proposes a CodeGen-Test model, which adds
program testing steps and incorporates program testing information to
iteratively generate code that meets the functional requirements of the
program, thereby improving the quality of code generation. At the same time,
the paper proposes a new evaluation metric, test accuracy (Test-Acc), which
represents the proportion of passing program test in generated code. Different
from the previous evaluation metric, which only evaluates the quality of code
generation from the perspective of character similarity, the Test-Acc can
evaluate the quality of code generation from the Program functions. Moreover,
the paper evaluates the CodeGen-test model on a python data set "hearthstone
legend". The experimental results show the proposed method can effectively
improve the quality of generated code. Compared with the existing optimal
model, CodeGen-Test model improves the Bleu value by 0.2%, Rouge-L value by
0.3% and Test-Acc by 6%.


  Context: The earliest evolutionary stages of low-mass protostars are
characterised by hot and fast jets which remove angular momentum from the
circumstellar disk, thus allowing mass accretion onto the central object.
However, the launch mechanism is still being debated. Aims: We would like to
exploit high-angular (~ 0.8") resolution and high-sensitivity images to
investigate the origin of protostellar jets using typical molecular tracers of
shocked regions, such as SiO and SO. Methods: We mapped the inner 22" of the
NGC1333-IRAS2A protostar in SiO(5-4), SO(65-54), and the continuum emission at
1.4 mm using the IRAM Plateau de Bure interferometer in the framework of the
CALYPSO IRAM large program. Results: For the first time, we disentangle the
NGC1333-IRAS2A Class 0 object into a proto-binary system revealing two
protostars (MM1, MM2) separated by ~ 560 AU, each of them driving their own
jet, while past work considered a single protostar with a quadrupolar outflow.
We reveal (i) a clumpy, fast (up to |V-VLSR| > 50 km/s), and blueshifted jet
emerging from the brightest MM1 source, and (ii) a slower redshifted jet,
driven by MM2. Silicon monoxide emission is a powerful tracer of
high-excitation (Tkin > 100 K; n(H2) > 10^5 cm-3) jets close to the launching
region. At the highest velocities, SO appears to mimic SiO tracing the jets,
whereas at velocities close to the systemic one, SO is dominated by extended
emission, tracing the cavity opened by the jet. Conclusions: Both jets are
intrinsically monopolar, and intermittent in time. The dynamical time of the
SiO clumps is < 30-90 yr, indicating that one-sided ejections from protostars
can take place on these timescales.


  This paper considers a leader-following formation control problem for
heterogeneous, second-order, uncertain, input-affine, nonlinear multi-agent
systems modeled by a directed graph. A tunable, three-layer neural network (NN)
is proposed with an input layer, two hidden layers, and an output layer to
approximate an unknown nonlinearity. Unlike commonly used trial and error
efforts to select the number of neurons in a conventional NN, in this case an
\textit{a priori} knowledge allows one to set up the number of neurons in each
layer. The NN weights tuning laws are derived using the Lyapunov theory. The
leader-following and formation control problems are addressed by a robust
integral of the sign of the error (RISE) feedback and a NN-based control. The
RISE feedback term compensates for unknown leader dynamics and the unknown,
bounded disturbance in the agent error dynamics. The NN-based term compensates
for the unknown nonlinearity in the dynamics of multi-agent systems, and
semi-global asymptotic tracking results are rigorously proven using the
Lyapunov stability theory. The results of the paper are compared with two
previous results to evaluate the efficiency and performance of the proposed
method.


  PSRJ 2032+4127 is only the second known gamma-ray binary where it is
confirmed that a young radio pulsar is in orbit around a Be-star. The
interaction of the pulsar wind with the mass outflow from the companion leads
to broad band emission from radio up to TeV energies. In the current paper we
present results of optical monitoring of the 2017 periastron passage with the
Nordic Optical Telescope. These observations are complemented by X-ray
(Swift/XRT, NuSTAR) and GeV (Fermi/LAT) monitoring. Joint analysis of the
evolution of the parameters of the Halpha line and the broadband (X-ray to TeV)
spectral shape allows us to propose a model linking the observed emission to
the interaction of the pulsar and Be-star winds under the assumption of the
inclined disc geometry. Our model allows the observed flux and spectral
evolution of the system to be explained in a self-consistent way.


  We use X^{s,b}-inspired spaces to prove a uniqueness result for Calderon's
problem in a Lipschitz domain under the assumption that the conductivity is
Lipschitz. For Lipschitz conductivities, we obtain uniqueness for
conductivities close to the identity in a suitable sense. We also prove
uniqueness for arbitrary C^1 conductivities.


  Most stochastic gradient descent algorithms can optimize neural networks that
are sub-differentiable in their parameters; however, this implies that the
neural network's activation function must exhibit a degree of continuity which
limits the neural network model's uniform approximation capacity to continuous
functions. This paper focuses on the case where the discontinuities arise from
distinct sub-patterns, each defined on different parts of the input space. We
propose a new discontinuous deep neural network model trainable via a decoupled
two-step procedure that avoids passing gradient updates through the network's
only and strategically placed, discontinuous unit. We provide approximation
guarantees for our architecture in the space of bounded continuous functions
and universal approximation guarantees in the space of piecewise continuous
functions which we introduced herein. We present a novel semi-supervised
two-step training procedure for our discontinuous deep learning model, tailored
to its structure, and we provide theoretical support for its effectiveness. The
performance of our model and trained with the propose procedure is evaluated
experimentally on both real-world financial datasets and synthetic datasets.


  Let A be a simple, sigma-unital, non-unital C*-algebra, with metrizable
tracial simplex T(A), which is projection-surjective and injective and has
strict comparison of positive elements by traces. Then the following are
equivalent: (i) A has quasicontinuous scale; (ii) The multiplier algebra M(A)
has strict comparison of positive elements by traces; (iii) The coronal algebra
M(A)/A is purely infinite; (iii') The quotient M(A)/Imin is purely infinite;
(iv) M(A) has finitely many ideals; (v) Imin=Ifin. If furthermore algebra of n
by n matrices of A is projection-surjective and injective for every n, then the
above conditions are equivalent to: (vi) the monoid V(M(A)) has finitely many
order ideals. Quasicontinuity of the scale is a notion introduced by Kucerovsky
and Perera that extends both the property of having finitely many extremal
traces and of having continuous scale. Projection-surjectivity and injectivity
permit to identify projections in M(A) that are not in A with lower
semicontinuous affine functions on T(A). Imin is the smallest ideal of M(A)
properly containing A, and Ifin is the ideal of of M(A) generated by the
positive elements with evaluation functions finite over the extremal boundary
of T(A).


  The search for extraterrestrial intelligence (SETI) is a scientific endeavor
which struggles with unique issues -- a strong indeterminacy in what data to
look for and when to do so. This has led to attempts at finding both
fundamental limits of the communication between extraterrestrial intelligence
and human civilizations, as well as benchmarks so as to predict what kinds of
signals we might most expect. Previous work has been formulated in terms of the
information-theoretic task of communication, but we instead argue it should be
viewed as a detection problem, specifically one-shot (asymmetric) hypothesis
testing. With this new interpretation, we develop fundamental limits as well as
provide simple examples of how to use this framework to analyze and benchmark
different possible signals from extraterrestrial civilizations. We show that
electromagnetic signaling for detection requires much less power than for
communication, that detection as a function of power can be non-linear, and
that much of the analysis in this framework may be addressed using
computationally efficient optimization problems, thereby demonstrating tools
for further inquiry.


  We have measured the moment $A_{LU}^{\sin\phi}$ corresponding to the
polarized electron beam-spin asymmetry in SIDIS. $A_{LU}^{\sin\phi}$ is a
twist-3 quantity providing information about quark-gluon correlations. Data
were taken with the CLAS Spectrometer at Jefferson Lab using a 5.498 GeV
longitudinally polarized electron beam and an unpolarized liquid hydrogen
target. All three pion channels ($\pi^+$, $\pi^0$ and $\pi^-$) were measured
simultaneously over a large range of kinematics within the virtuality range
$Q^2 \approx$ 1.0-4.5 GeV$^2$. The observable was measured with better than 1%
statistical precision over a large range of $z$, $P_T$, $x_B$, and $Q^{2}$,
which permits comparison with several reaction models. The discussed
measurements provide an upgrade in statistics over previous measurements, and
serve as the first evidence for the negative sign of the $\pi^{-}$ $\sin\phi$
moment.


  We present magnetoresistance measurements on large scale monolayer graphene
grown by chemical vapor deposition (CVD) on copper. The graphene layer was
transferred onto SiO2/Si via PMMA and thermal release tape for transport
measurements. The resulting centimeter-sized graphene samples were measured at
temperatures down to 30mK in a magnetic field. We observe a very sharp peak in
resistance at zero field, which is well fitted by weak localization theory. The
samples exhibit conductance fluctuations symmetric in field, which are
attributed to ensemble averaged conductance fluctuations due to large scale
inhomogeneities consistent with the grain boundaries of copper during the CVD
growth.


  Methods in Riemann-Finsler geometry are applied to investigate bi-Hamiltonian
structures and related mKdV hierarchies of soliton equations derived
geometrically from regular Lagrangians and flows of non-stretching curves in
tangent bundles. The total space geometry and nonholonomic flows of curves are
defined by Lagrangian semisprays inducing canonical nonlinear connections
(N-connections), Sasaki type metrics and linear connections. The simplest
examples of such geometries are given by tangent bundles on Riemannian
symmetric spaces $G/SO(n)$ provided with an N-connection structure and an
adapted metric, for which we elaborate a complete classification, and by
generalized Lagrange spaces with constant Hessian. In this approach,
bi-Hamiltonian structures are derived for geometric mechanical models and
(pseudo) Riemannian metrics in gravity. The results yield horizontal/ vertical
pairs of vector sine-Gordon equations and vector mKdV equations, with the
corresponding geometric curve flows in the hierarchies described in an explicit
form by nonholonomic wave maps and mKdV analogs of nonholonomic Schrodinger
maps on a tangent bundle.


  Acquiring multiple skills has commonly involved collecting a large number of
expert demonstrations per task or engineering custom reward functions. Recently
it has been shown that it is possible to acquire a diverse set of skills by
self-supervising control on top of human teleoperated play data. Play is rich
in state space coverage and a policy trained on this data can generalize to
specific tasks at test time outperforming policies trained on individual expert
task demonstrations. In this work, we explore the question of whether robots
can learn to play to autonomously generate play data that can ultimately
enhance performance. By training a behavioral cloning policy on a relatively
small quantity of human play, we autonomously generate a large quantity of
cloned play data that can be used as additional training. We demonstrate that a
general purpose goal-conditioned policy trained on this augmented dataset
substantially outperforms one trained only with the original human data on 18
difficult user-specified manipulation tasks in a simulated robotic tabletop
environment. A video example of a robot imitating human play can be seen here:
https://learning-to-play.github.io/videos/undirected_play1.mp4


  The controversies about the structure of the true ground state of
pseudorhombohedral compositions of Pb(ZrxTi1-x)O3 (PZT) are addressed using a
6% Sr2+ substituted sample with x=0.550. Sound velocity measurements reveal a
phase transition at Tc~279K. The temperature dependence of FWHM of (h00)pc
peaks and the unit cell volume also show anomalies around 279K even though
there is no indication of any change of space group in the synchrotron X-ray
powder diffraction (SXRD) patterns. The neutron powder diffraction patterns
reveal appearance of superlattice peaks below Tc~279K confirming the existence
of an antiferrodistortive phase transition. The Rietveld analysis of the room
temperature and low temperature SXRD data below Tc shows that the structure
corresponds to single monoclinic phase in the Cm space group while the analysis
of neutron powder diffraction data reveals that the structure of the ground
state phase below Tc corresponds to the Cc space group. Our analysis shows that
the structural models for the ground state phase based on R3c space group with
or without the coexistence of the room temperature monoclinic phase in the Cm
space group can be rejected.


  We propose an approach to approximately implement the variational coupled
cluster (VCC) theory on quantum computers, which struggles with exponential
scaling of computational costs on classical computers. To this end, we employ
expanding the exponential cluster operator using Chebyshev polynomials and
introduce two methods: the Chebyshev approximated VCC (C$^d$-VCC) and the
Hermitian-part Chebyshev approximated VCC (HC$^d$-VCC), where $d$ indicates the
maximum degree of the Chebyshev polynomials. The latter method decomposes the
cluster operator into anti-Hermitian and Hermitian parts, with the
anti-Hermitian part represented by the disentangled unitary coupled cluster
ansatz and the Hermitian part approximated using Chebyshev expansion. We
illustrate the implementation of the HC$^d$-VCC in a quantum circuit using the
quantum singular value transformation technique. Numerical simulations show
that the C$^d$-VCC rapidly converges to the exact VCC with increasing
truncation degree $d$, and the HC$^d$-VCC effectively reduces the Chebyshev
expansion error compared to the C$^d$-VCC. The HC$^d$-VCC method for realizing
non-unitary coupled cluster wave functions on quantum computers is expected to
be useful for initial state preparation on quantum computers and efficient
tomography of the quantum state for post-processing on classical computers
after quantum computations.


  From a long time series of high resolution (R=115,000) HARPS spectra and
simultaneous broad-band photometry, we report new evidence for magnetospheric
accretion as well as ejection processes in the nearly edge-on classical T Tauri
star AA Tau.
  AA Tau's light curve is modulated with a period of 8.22d. The recurrent
luminosity dips are due to the periodic occultation of the central star by the
magnetically-warped inner disk edge located at about 9 Rstar. Balmer line
profiles exhibit a clear rotational modulation of high-velocity redshifted
absorption components with a period of 8.22 days as well, with a maximum
strength when the main accretion funnel flow passes through the line of sight.
At the same time, the luminosity of the system decreases by about 1 mag,
indicative of circumstellar absorption of the stellar photosphere by the
magnetically-warped, corotating inner disk edge. The photospheric and HeI
radial velocities also exhibit periodic variations, and the veiling is
modulated by the appearance of the accretion shock at the bottom of the
accretion funnel. Diagnostics of hot winds and their temporal behaviour are
also presented.
  The peculiar geometry of the young AA Tau system (nearly edge-on) allows us
to uniquely probe the acretion-ejection region close to the star. We find that
most spectral and photometric diagnostics vary as expected from models of
magnetically-channelled accretion in young stars, with a large scale
magnetosphere tilted by 20 deg onto the star's spin axis. We also find evidence
for time variability of the magnetospheric accretion flow on a timescale of a
few rotational periods.


  In a recent paper, Mandelkern & Linzen (2024) - henceforth M&L - address the
question of whether language models' (LMs) words refer. Their argument draws
from the externalist tradition in philosophical semantics, which views
reference as the capacity of words to "achieve 'word-to-world' connections". In
the externalist framework, causally uninterrupted chains of usage, tracing
every occurrence of a name back to its bearer, guarantee that, for example,
'Peano' refers to the individual Peano (Kripke 1980). This account is
externalist both because words pick out referents 'out there' in the world, and
because what determines reference are coordinated linguistic actions by members
of a community, and not individual mental states. The "central question to
ask", for M&L, is whether LMs too belong to human linguistic communities, such
that words by LMs may also trace back causally to their bearers. Their answer
is a cautious "yes": inputs to LMs are linguistic "forms with particular
histories of referential use"; "those histories ground the referents of those
forms"; any occurrence of 'Peano' in LM outputs is as causally connected to the
individual Peano as any other occurrence of the same proper name in human
speech or text; therefore, occurrences of 'Peano' in LM outputs refer to Peano.
In this commentary, we first qualify M&L's claim as applying to a narrow class
of natural language expressions. Thus qualified, their claim is valid, and we
emphasise an additional motivation for that in Section 2. Next, we discuss the
actual scope of their claim, and we suggest that the way they formulate it may
lead to unwarranted generalisations about reference in LMs. Our critique is
likewise applicable to other externalist accounts of LMs (e.g., Lederman &
Mahowald 2024; Mollo & Milliere 2023). Lastly, we conclude with a comment on
the status of LMs as members of human linguistic communities.


  In this paper, we first propose a new iterative algorithm, called the K-sets+
algorithm for clustering data points in a semi-metric space, where the distance
measure does not necessarily satisfy the triangular inequality. We show that
the K-sets+ algorithm converges in a finite number of iterations and it retains
the same performance guarantee as the K-sets algorithm for clustering data
points in a metric space. We then extend the applicability of the K-sets+
algorithm from data points in a semi-metric space to data points that only have
a symmetric similarity measure. Such an extension leads to great reduction of
computational complexity. In particular, for an n * n similarity matrix with m
nonzero elements in the matrix, the computational complexity of the K-sets+
algorithm is O((Kn + m)I), where I is the number of iterations. The memory
complexity to achieve that computational complexity is O(Kn + m). As such, both
the computational complexity and the memory complexity are linear in n when the
n * n similarity matrix is sparse, i.e., m = O(n). We also conduct various
experiments to show the effectiveness of the K-sets+ algorithm by using a
synthetic dataset from the stochastic block model and a real network from the
WonderNetwork website.


  Studies of deuterated isotopologues of complex organic molecules can provide
important constraints on their origin in regions of star formation. In
particular, the abundances of deuterated species are very sensitive to the
physical conditions in the environment where they form. Due to the low
temperatures in regions of star formation, these isotopologues are enhanced to
significant levels, making detections of multiply-deuterated species possible.
However, for complex organic species, only the multiply-deuterated variants of
methanol and methyl cyanide have been reported so far. The aim of this paper is
to initiate the characterisation of multiply-deuterated variants of complex
organic species with the first detection of doubly-deuterated methyl formate,
CHD2OCHO. We use ALMA observations from the Protostellar Interferometric Line
Survey (PILS) of the protostellar binary IRAS 16293-2422, in the spectral range
of 329.1 GHz to 362.9 GHz. We report the first detection of doubly-deuterated
methyl formate CHD2OCHO in the ISM. The D/H ratio of CHD2OCHO is found to be
2-3 times higher than the D/H ratio of CH2DOCHO for both sources, similar to
the results for formaldehyde from the same dataset. The observations are
compared to a gas-grain chemical network coupled to a dynamical physical model,
tracing the evolution of a molecular cloud until the end of the Class 0
protostellar stage. The overall D/H ratio enhancements found in the
observations are of the same order of magnitude as the predictions from the
model for the early stages of Class 0 protostars. However, the higher D/H ratio
of CHD2OCHO compared to the D/H ratio of CH2DOCHO is still not predicted by the
model. This suggests that a mechanism is enhancing the D/H ratio of singly- and
doubly-deuterated methyl formate that is not in the model, e.g. mechanisms for
H-D substitutions.


  We consider the numbers arising in the problem of normal ordering of
expressions in canonical boson creation and annihilation operators. We treat a
general form of a boson string which is shown to be associated with
generalizations of Stirling and Bell numbers. The recurrence relations and
closed-form expressions (Dobiski-type formulas) are obtained for these
quantities by both algebraic and combinatorial methods. By extensive use of
methods of combinatorial analysis we prove the equivalence of the
aforementioned problem to the enumeration of special families of graphs. This
link provides a combinatorial interpretation of the numbers arising in this
normal ordering problem.


  We report extensive high-resolution spectroscopic observations and V-band
differential photometry of the slightly eccentric 7.02-day detached eclipsing
binary V501 Mon (A6m+F0), which we use to determine its absolute dimensions to
high precision (0.3% for the masses and 1.8% for the radii, or better). The
absolute masses, radii, and temperatures are M(A) = 1.6455 +/- 0.0043 M(Sun),
R(A) = 1.888 +/- 0.029 R(Sun), and T(A) = 7510 +/- 100 K for the primary, and
M(B) = 1.4588 +/- 0.0025 M(Sun), R(B) = 1.592 +/- 0.028 R(Sun), and T(B) = 7000
+/- 90 K for the secondary. Apsidal motion has been detected, to which General
Relativity contributes approximately 70%. The primary star is found to be a
metallic-line A star. A detailed chemical analysis of the disentangled spectra
yields abundances for more than a dozen elements in each star. Based on the
secondary, the system metallicity is near solar: [Fe/H] = +0.01 +/- 0.06.
Lithium is detected in the secondary but not in the primary. A comparison with
current stellar evolution models shows a good match to the measured properties
at an age of about 1.1 Gyr.


  Like natural complex systems such as the Earth's climate or a living cell,
semiconductor lithography systems are characterized by nonlinear dynamics
across more than a dozen orders of magnitude in space and time. Thousands of
sensors measure relevant process variables at appropriate sampling rates, to
provide time series as primary sources for system diagnostics. However,
high-dimensionality, non-linearity and non-stationarity of data remain a major
challenge to effectively diagnose rare or new system issues by merely using
model-based approaches. To reduce the causal search space, we validate an
algorithm that applies transfer entropy to obtain a weighted directed graph
from a system's multivariate time series and graph eigenvector centrality to
identify the system's most influential parameters. The results suggest that
this approach robustly identifies the true influential sources in a complex
system, even when its information transfer network includes redundant edges.


  In the note, the Euler scaling is used to study a certain scenario of
potential Type II blowups of axisymmetric solutions to the Navier-Stokes
equations.


  In this paper we establish uniqueness theorems for the noncommutative residue
and the canonical trace on pseudodifferential operators on noncommutative tori
of arbitrary dimension. The former is the unique trace up to constant multiple
on integer order pseudodifferential operators.The latter is the unique trace up
to constant multiple on non-integer order pseudodifferential operators. This
improves previous uniqueness results by Fathizadeh-Khalkhali, Fathizadeh-Wong,
and L\'evy-Neira-Paycha.


  We prove that, for any smooth and projective scheme $X$ over a field $k$ of
char. $0$, the set of maps from Spec $k$ to $X$ in the $\mathbf{A}^1$-homotopy
category of schemes $\mathcal{H}_{\mathbf{A}^1}(k)$ is in bijection with the
quotient of $X(k)$ by $R$-equivalence, and is a birational invariant of $X$.
This is achieved by establishing a precise relation between the localization of
the category of smooth $k$-schemes by birational maps and the category
$\mathcal{H}_{\mathbf{A}^1}(k)$, and by applying results of the second named
author and R. Sujatha on birational invariants. This gives a new proof of
results obtained by A. Asok and F. Morel.


  It is shown that spin-orbit interaction leads to drastic changes in wave
patterns generated by a flow of two-component Bose-Einstein condensate (BEC)
past an obstacle. The combined Rashba and Dresselhaus spin-orbit interaction
affects in different ways two types of excitations---density and polarization
waves---which can propagate in a two-component BEC. We show that the density
and polarization "ship wave" patterns rotate in opposite directions around the
axis located at the obstacle position and the angle of rotation depends on the
strength of spin-orbit interaction. This rotation is accompanied by narrowing
of the Mach cone. The influence of spin-orbit coupling on density solitons and
polarization breathers is studied numerically.


  This paper introduces a collection of scaling methods for generating
$2N$-point DCT-II approximations based on $N$-point low-complexity
transformations. Such scaling is based on the Hou recursive matrix
factorization of the exact $2N$-point DCT-II matrix. Encompassing the widely
employed Jridi-Alfalou-Meher scaling method, the proposed techniques are shown
to produce DCT-II approximations that outperform the transforms resulting from
the JAM scaling method according to total error energy and mean squared error.
Orthogonality conditions are derived and an extensive error analysis based on
statistical simulation demonstrates the good performance of the introduced
scaling methods. A hardware implementation is also provided demonstrating the
competitiveness of the proposed methods when compared to the JAM scaling
method.


  The recent spreading of coronavirus made many countries impose restrictions
in order to control its dangerous effect on the citizens. We developed a
theoretical dynamical model based on compartmental SIR system with additional
adjustment taken from Flow network and Markov chain frameworks to illustrate
developments and trends based on publicly available data. Based on this Model,
code in R was written and fed by stamped publicly available data from
authorized governmental websites in Spain and in the Nederlands, to compare
trends. Our results show that the 'peak' of infection is already behind us in
both countries, but also demonstrate that there is a danger of rebound of a
spread. It is obvious that measures imposed are giving the results, but we
should be precarious of near future practices and developments since the
majority of population will still be without immunity.


  Stochastic gradient Markov chain Monte Carlo (SG-MCMC) methods are Bayesian
analogs to popular stochastic optimization methods; however, this connection is
not well studied. We explore this relationship by applying simulated annealing
to an SGMCMC algorithm. Furthermore, we extend recent SG-MCMC methods with two
key components: i) adaptive preconditioners (as in ADAgrad or RMSprop), and ii)
adaptive element-wise momentum weights. The zero-temperature limit gives a
novel stochastic optimization method with adaptive element-wise momentum
weights, while conventional optimization methods only have a shared, static
momentum weight. Under certain assumptions, our theoretical analysis suggests
the proposed simulated annealing approach converges close to the global optima.
Experiments on several deep neural network models show state-of-the-art results
compared to related stochastic optimization algorithms.


  Since Press and Dyson's ingenious discovery of ZD (zero-determinant) strategy
in the repeated Prisoner's Dilemma game, several studies have confirmed the
existence of ZD strategy in repeated multiplayer social dilemmas. However, few
researches study the evolutionary performance of multiplayer ZD strategies,
especially from a theoretical perspective. Here, we use a newly proposed
state-clustering method to theoretically analyze the evolutionary dynamics of
two representative ZD strategies: generous ZD strategies and extortionate ZD
strategies. Apart from the competitions between the two strategies and some
classical strategies, we consider two new settings for multiplayer ZD
strategies: competitions in the whole ZD strategy space and competitions in the
space of all memory-1 strategies. Besides, we investigate the influence of
level of generosity and extortion on the evolutionary dynamics of generous and
extortionate ZD, which was commonly ignored in previous studies. Theoretical
results show players with limited generosity are at an advantageous place and
extortioners extorting more severely hold their ground more readily. Our
results may provide new insights into better understanding the evolutionary
dynamics of ZD strategies in repeated multiplayer games.


  COMPASS is a high-energy physics experiment operating on the M2 beam line at
the SPS at CERN. Using high energy muon and hadron beams the experiment covers
broad range of physics aspects in the field of the hadron structure and
spectroscopy. One of the important objectives of the COMPASS experiment is the
exploration of transverse spin structure of the nucleon via study of spin
(in)dependent azimuthal asymmetries with semi-inclusive deep inelastic
scattering (SIDIS) processes and starting from 2014 also with Drell-Yan (DY)
reactions. Experimental results obtained by COMPASS for azimuthal effects in
SIDIS play an important role in the general understanding of the
three-dimensional nature of the nucleon. Giving access to the entire "twist-2"
set of transverse momentum dependent (TMD) parton distribution functions (PDFs)
and fragmentation functions (FFs) COMPASS data trigger constant theoretical
interest and are being widely used in phenomenological analyses and global data
fits. In particular, unique x-$Q^{2}$-z-pT multidimensional results for
transverse spin asymmetries recently obtained by COMPASS will serve as a direct
and unprecedented input for TMD $Q^{2}$-evolution related studies, one of the
hottest topics in the field of spin-physics. In addition, measurement of the
Sivers and all other azimuthal effects in polarized Drell-Yan at COMPASS will
reveal another side of the spin-puzzle providing a link between SIDIS and
Drell-Yan branches. This will be a unique possibility to test universality and
key-features of TMD PDFs using essentially the same experimental setup and
exploring the same kinematical domain. In this review main focus will be given
to the very recent results obtained by the collaboration for multi-dimensional
transverse spin asymmetries and to the physics aspects of COMPASS polarized
Drell-Yan program.


  Asteroseismology, i.e. the study of the internal structures of stars via
their global oscillations, is a valuable tool to obtain stellar parameters such
as mass, radius, surface gravity and mean density. These parameters can be
obtained using certain scaling relations which are based on an asymptotic
approximation. Usually the observed oscillation parameters are assumed to
follow these scaling relations. Recently, it has been questioned whether this
is a valid approach, i.e., whether the order of the observed oscillation modes
are high enough to be approximated with an asymptotic theory. In this work we
use stellar models to investigate whether the differences between observable
oscillation parameters and their asymptotic estimates are indeed significant.
We compute the asymptotic values directly from the stellar models and derive
the observable values from adiabatic pulsation calculations of the same models.
We find that the extent to which the atmosphere is included in the models is a
key parameter. Considering a larger extension of the atmosphere beyond the
photosphere reduces the difference between the asymptotic and observable values
of the large frequency separation. Therefore, we conclude that the currently
suggested discrepancies in the scaling relations might have been overestimated.
Hence, based on the results presented here we believe that the suggestions of
Mosser et al. (2013) should not be followed without careful consideration.


  We investigate the optical conductivity in the Mott insulating phase of the
one-dimensional extended Hubbard model with alternating hopping terms
(dimerization) at quarter band filling. Optical spectra are calculated for the
various parameter regimes using the dynamical density-matrix renormalization
group method. The study of limiting cases allows us to explain the various
structures found numerically in the optical conductivity of this model. Our
calculations show that the dimerization and the nearest-neighbor repulsion
determine the main features of the spectrum. The on-site repulsion plays only a
secondary role. We discuss the consequences of our results for the theory of
the optical conductivity in the Bechgaard salts.


  A hypothesis is presented that non-separability of degrees of freedom is the
fundamental property underlying consciousness in physical systems. The amount
of consciousness in a system is determined by the extent of non-separability
and the number of degrees of freedom involved. Non-interacting and feedforward
systems have zero consciousness, whereas most systems of interacting particles
appear to have low non-separability and consciousness. By contrast, brain
circuits exhibit high complexity and weak but tightly coordinated interactions,
which appear to support high non-separability and therefore high amount of
consciousness. The hypothesis applies to both classical and quantum cases, and
we highlight the formalism employing the Wigner function (which in the
classical limit becomes the Liouville density function) as a potentially
fruitful framework for characterizing non-separability and, thus, the amount of
consciousness in a system. The hypothesis appears to be consistent with both
the Integrated Information Theory and the Orchestrated Objective Reduction
Theory and may help reconcile the two. It offers a natural explanation for the
physical properties underlying the amount of consciousness and points to
methods of estimating the amount of non-separability as promising ways of
characterizing the amount of consciousness.


  Perturbative QCD is the appropriate tool to describe many important
properties of the inclusive observables measured at electron-proton (or ion)
colliders, such as the energy dependence of the total cross sections in
well-chosen kinematical regions. This is because the electron may effectively
be replaced by its cloud of photons, whose virtualities provide a hard scale
that enables perturbative expansions.
  At hadron colliders instead, there is no hard scale in the initial state.
Therefore, the observables one may compute perturbatively involve the
production of jets, and thus belong to a quite different class of observables.
  However, it turns out that there is a formal relation between production
processes and total cross sections, enabling one to apply calculations of the
latter to the former. We review this relation, and present our recent proof
that it holds at next-to-leading order (in the BFKL sense).


  Despite significant progress in synthesizing several new molecules and many
promising single device demonstrations, wide range acceptance of molecular
electronics as an alternative to CMOS technology has been stalled not only by
controversial theories of a molecular device`s operation, for example the
switching mechanism, but also by our inability to reproducibly fabricate large
arrays of devices. In this paper, we investigate the role of Casimir force as
one of the potential source of a wide range of discrepancies in the reported
electrical characteristics and high rate of device shorting in molecular
electronic switching junctions fabricated by sandwiching a molecular monolayer
between a pair of planar metal electrode.


  For effective human-robot collaboration, it is crucial for robots to
understand requests from users and ask reasonable follow-up questions when
there are ambiguities. While comprehending the users' object descriptions in
the requests, existing studies have focused on this challenge for limited
object categories that can be detected or localized with existing object
detection and localization modules. On the other hand, in the wild, it is
impossible to limit the object categories that can be encountered during the
interaction. To understand described objects and resolve ambiguities in the
wild, for the first time, we suggest a method by leveraging explainability. Our
method focuses on the active regions of a scene to find the described objects
without putting the previous constraints on object categories and natural
language instructions. We evaluate our method in varied real-world images and
observe that the regions suggested by our method can help resolve ambiguities.
When we compare our method with a state-of-the-art baseline, we show that our
method performs better in scenes with ambiguous objects which cannot be
recognized by existing object detectors.


  We study a series of one-dimensional discrete-time quantum-walk models
labeled by half integers $j=1/2, 1, 3/2, ...$, introduced by Miyazaki {\it et
al.}, each of which the walker's wave function has $2j+1$ components and
hopping range at each time step is $2j$. In long-time limit the density
functions of pseudovelocity-distributions are generally given by superposition
of appropriately scaled Konno's density function. Since Konno's density
function has a finite open support and it diverges at the boundaries of
support, limit distribution of pseudovelocities in the $(2j+1)$-component model
can have $2j+1$ pikes, when $2j+1$ is even. When $j$ becomes very large,
however, we found that these pikes vanish and a universal and monotone convex
structure appears around the origin in limit distributions. We discuss a
possible route from quantum walks to classical diffusion associated with the $j
\to \infty$ limit.


  Image inpainting refers to the task of generating a complete, natural image
based on a partially revealed reference image. Recently, many research
interests have been focused on addressing this problem using fixed diffusion
models. These approaches typically directly replace the revealed region of the
intermediate or final generated images with that of the reference image or its
variants. However, since the unrevealed regions are not directly modified to
match the context, it results in incoherence between revealed and unrevealed
regions. To address the incoherence problem, a small number of methods
introduce a rigorous Bayesian framework, but they tend to introduce mismatches
between the generated and the reference images due to the approximation errors
in computing the posterior distributions. In this paper, we propose COPAINT,
which can coherently inpaint the whole image without introducing mismatches.
COPAINT also uses the Bayesian framework to jointly modify both revealed and
unrevealed regions, but approximates the posterior distribution in a way that
allows the errors to gradually drop to zero throughout the denoising steps,
thus strongly penalizing any mismatches with the reference image. Our
experiments verify that COPAINT can outperform the existing diffusion-based
methods under both objective and subjective metrics. The codes are available at
https://github.com/UCSB-NLP-Chang/CoPaint/.


  The Event Horizon Telescope (EHT), a global very long baseline interferometry
array operating at millimetre wavelengths, is spatially resolving the immediate
environments of black holes for the first time. The current observations of the
Galactic center black hole, Sagittarius A* (Sgr A*), and M87 have been
interpreted in terms of either geometric models (e.g., a symmetric Gaussian) or
detailed calculations of the appearance of black hole accretion flows. The
former are not physically motivated, while the latter are subject to large
systematic uncertainties. Motivated by the dominant relativistic effects of
Doppler beaming and gravitational lensing in many calculations, we propose a
geometric crescent model for black hole images. We show that this simple model
provides an excellent statistical description of the existing EHT data of Sgr
A* and M87, superior to other geometric models for Sgr A*. It also
qualitatively matches physically predicted models, bridging accretion theory
and observation. Based on our results, we make predictions for the
detectability of the black hole shadow, a signature of strong gravity, in
future observations.


  In this paper, we explore how to use topological tools to compare dimension
reduction methods. We first make a brief overview of some of the methods often
used dimension reduction such as Isometric Feature Mapping, Laplacian
Eigenmaps, Fast Independent Component Analysis, Kernel Ridge Regression,
t-distributed Stochastic Neighbor Embedding. We then give a brief overview of
some topological notions used in topological data analysis, such as, barcodes,
persistent homology, and Wasserstein distance. Theoretically, these methods
applied on a data set can be interpreted differently. From EEG data embedded
into a manifold of high dimension, we apply these methods and we compare them
across persistent homologies of dimension 0, 1, and 2, that is, across
connected components, tunnels and holes, shells around voids or cavities. We
find that from three dimension clouds of points, it is not clear how distinct
from each other the methods are, but Wasserstein and Bottleneck distances,
topological tests of hypothesis, and various methods show that the methods
qualitatively and significantly differ across homologies.


  In this paper, we study noncommutative surface singularities arising from
orders. The singularities we study are mild in the sense that they have finite
representation type or, equivalently, are log terminal in the sense of the Mori
minimal model program for orders [CI05]. These were classified independently by
Artin (in terms of ramification data) and Reiten-Van den Bergh (in terms of
their AR-quivers). The first main goal of this paper is to connect these two
classifications, by going through the finite subgroups $G \subset
\mathrm{GL}_2$, explicitly computing $H^2(G,k^*)$, and then matching these up
with Artin's list of ramification data and Reiten-Van den Bergh's AR-quivers.
This provides a semi-independent proof of their classifications and extends the
study of canonical orders in [CHI09] to the case of log terminal orders. A
secondary goal of this paper is to study noncommutative analogues of plane
curves which arise as follows. Let $B = k_{\zeta} [[ x,y ]]$ be the skew power
series ring where $\zeta$ is a root of unity, or more generally a terminal
order over a complete local ring. We consider rings of the form $A = B/(f)$
where $f \in Z(B)$ which we interpret to be the ring of functions on a
noncommutative plane curve. We classify those noncommutative plane curves which
are of finite representation type and compute their AR-quivers.


  This volume represents the proceedings of With or Without Permission:
Site-Specific Augmented Reality for Social Justice CHI 2024 workshop.


  We present a theory for interpreting the sodium lines detected in
transmission spectra of exoplanetary atmospheres. Previous analyses employed
the isothermal approximation and dealt only with the transit radius. By
recognising the absorption depth and the transit radius as being independent
observables, we develop a theory for jointly interpreting both quantities,
which allows us to infer the temperatures and number densities associated with
the sodium lines. We are able to treat a non-isothermal situation with a
constant temperature gradient. Our novel diagnostics take the form of
simple-to-use algebraic formulae and require measurements of the transit radii
(and their corresponding absorption depths) at line center and in the line wing
for both sodium lines. We apply our diagnostics to the HARPS data of HD
189733b, confirm the upper atmospheric heating reported by Huitson et al.
(2012), derive a temperature gradient of $0.4376 \pm 0.0154$ K km$^{-1}$ and
find densities $\sim 1$ to $10^4$ cm$^{-3}$.


  I propose an iterative expectation maximization algorithm for reconstructing
a quantum optical ensemble from a set of balanced homodyne measurements
performed on an optical state. The algorithm applies directly to the acquired
data, bypassing the intermediate step of calculating marginal distributions.
The advantages of the new method are made manifest by comparing it with the
traditional inverse Radon transformation technique.


  Photonic signal processing is essential in the optical communication and
optical computing. Numerous photonic signal processors have been proposed, but
most of them exhibit limited reconfigurability and automaticity. A feature of
fully automatic implementation and intelligent response is highly desirable for
the multipurpose photonic signal processors. Here, we report and experimentally
demonstrate a fully self-learning and reconfigurable photonic signal processor
based on an optical neural network chip. The proposed photonic signal processor
is capable of performing various functions including multichannel optical
switching, optical multiple-input-multiple-output descrambler and tunable
optical filter. All the functions are achieved by complete self-learning. Our
demonstration suggests great potential for chip-scale fully programmable
optical signal processing with artificial intelligence.


  We examine several resummation methods for computing higher order corrections
to the finite temperature effective potential, in the context of a scalar
$\phi^4$ theory. We show by explicit calculation to four loops that dressing
the propagator, not the vertex, of the one-loop tadpole correctly counts
``daisy'' and ``super-daisy'' diagrams.


  We estimate from below by geometric data the eigenvalues of the periodic
Sturm-Liouville operator $- 4 d^2/ds^2 + \kappa^2 (s)$ with potential given by
the curvature of a closed curve.


  Agents' judgment depends on perception and previous knowledge. Assuming that
previous knowledge depends on perception, we can say that judgment depends on
perception. So, if judgment depends on perception, can agents judge that they
have the same perception? In few words, this is the addressed paradox through
this document. While illustrating on the paradox, it's found that to reach
agreement in communication, it's not necessary for parties to have the same
perception however the necessity is to have perception correspondence. The
attempted solution to this paradox reveals a potential uncertainty in judging
the matter thus supporting the skeptical view of the problem. Moreover,
relating perception to intelligence, the same uncertainty is inherited by
judging the level of intelligence of an agent compared to others not
necessarily from the same kind (e.g. machine intelligence compared to human
intelligence). Using a proposed simple mathematical model for perception and
action, a tool is developed to construct scenarios, and the problem is
addressed mathematically such that conclusions are drawn systematically based
on mathematically defined properties. When it comes to formalization,
philosophical arguments and views become more visible and explicit.


  For a Lie ring $L$ over the ring of integers, we compare its lower central
series $\{\gamma_n(L)\}_{n\geq 1}$ and its dimension series
$\{\delta_n(L)\}_{n\geq 1}$ defined by setting $\delta_n(L)= L\cap
\varpi^n(L)$, where $\varpi(L)$ is the augmentation ideal of the universal
enveloping algebra of $L$. While $\gamma_n(L)\subseteq\delta_n(L)$ for all
$n\geq 1$, the two series can differ. In this paper it is proved that if $L$ is
a metabelian Lie ring, then $2\delta_n(L)\subseteq\gamma_n(L)$, and
$[\delta_n(L),\,L]=\gamma_{n+1}(L)$, for all $n\geq 1$.


  Physics-based simulation of mesh based domains remains a challenging task.
State-of-the-art techniques can produce realistic results but require expert
knowledge. A major bottleneck in many approaches is the step of integrating a
potential energy in order to compute velocities or displacements. Recently,
learning based method for physics-based simulation have sparked interest with
graph based approaches being a promising research direction. One of the
challenges for these methods is to generate models that are mesh independent
and generalize to different material properties. Moreover, the model should
also be able to react to unforeseen external forces like ubiquitous collisions.
Our contribution is based on a simple observation: evaluating forces is
computationally relatively cheap for traditional simulation methods and can be
computed in parallel in contrast to their integration. If we learn how a system
reacts to forces in general, irrespective of their origin, we can learn an
integrator that can predict state changes due to the total forces with high
generalization power. We effectively factor out the physical model behind
resulting forces by relying on an opaque force module. We demonstrate that this
idea leads to a learnable module that can be trained on basic internal forces
of small mesh patches and generalizes to different mesh typologies,
resolutions, material parameters and unseen forces like collisions at inference
time. Our proposed paradigm is general and can be used to model a variety of
physical phenomena. We focus our exposition on the detail enhancement of coarse
clothing geometry which has many applications including computer games, virtual
reality and virtual try-on.


  This paper addresses the problem of cross-modal musical piece identification
and retrieval: finding the appropriate recording(s) from a database given a
sheet music query, and vice versa, working directly with audio and scanned
sheet music images. The fundamental approach to this is to learn a cross-modal
embedding space with a suitable similarity structure for audio and sheet image
snippets, using a deep neural network, and identifying candidate pieces by
cross-modal near neighbour search in this space. However, this method is
oblivious of temporal aspects of music. In this paper, we introduce two
strategies that address this shortcoming. First, we present a strategy that
aligns sequences of embeddings learned from sheet music scans and audio
snippets. A series of experiments on whole piece and fragment-level retrieval
on 24 hours worth of classical piano recordings demonstrates significant
improvement. Second, we show that the retrieval can be further improved by
introducing an attention mechanism to the embedding learning model that reduces
the effects of tempo variations in music. To conclude, we assess the
scalability of our method and discuss potential measures to make it suitable
for truly large-scale applications.


  A magnetic power spectral analysis is performed on 53 solar active regions,
observed from August 2011 to July 2012. Magnetic field data obtained from the
Helioseismic and Magnetic Imager, inverted as Active Region Patches, are used
to study the evolution of the magnetic power index as each region rotates
across the solar disk. Active regions are classified based on the number, and
sizes, of solar flares they produce, in order to study the relationship between
flare productivity and the magnetic power index. The choice of window size and
inertial range plays a key role in determining the correct magnetic power
index. The overall distribution of magnetic power indices has a range of
$1.0-2.5$. Flare-quiet regions peak at a value of 1.6, however flare-productive
regions peak at a value of 2.2. Overall, the histogram of the distribution of
power indices of flare-productive active regions is well separated from
flare-quiet active regions. Only 12\% of flare-quiet regions exhibit an index
greater than 2, whereas 90\% of flare-productive regions exhibit an index
greater than 2. Flare-quiet regions exhibit a high temporal variance (i.e, the
index fluctuates between high and low values), whereas flare-productive regions
maintain an index greater than 2 for several days. This shows the importance of
including the temporal evolution of active regions in flare prediction studies,
and highlights the potential of a 2-3 day prediction window for space weather
applications.


  The Moyal *-deformed noncommutative version of Burgers' equation is
considered. Using the *-analog of the Cole-Hopf transformation, the
linearization of the model in terms of the linear heat equation is found.
Noncommutative q-deformations of shock soliton solutions and their interaction
are described


  The radio source 3C84, in NGC1275, has a two sided structure on parsec
scales. The northern feature, presumed to be associated with a jet moving away
from the Earth, shows strong evidence for free-free absorption. The ionized gas
responsible for that absorption would be a source of detectable stimulated
recombination line emission for a wide range of physical conditions. The VLBA
has been used to search for the H65$\alpha$ hydrogen recombination line. The
line is only expected to be seen against the northern feature which contains a
small fraction of the total radio flux density. This spatial discrimination
significantly aids the search for a weak line. No line was seen, with upper
limits of roughly 15% of the continuum over a velocity range of 1486 km/s with
resolutions up to 6.6 km/s. In the absence of a strong radiation field, this
would imply that the free-free absorbing gas has a wide velocity width, is
moving rapidly relative to the systemic velocity, or is concentrated in a thin,
high density structure. All of these possibilities are reasonably likely close
to an AGN. However, in the intense radiation environment of the AGN, even
considering only the radiation we actually observe passing through the
free-free absorbing gas, the non-detection is probably assured by a combination
of saturation and radiation damping.


  In the present paper, non-singular Morse-Smale flows on closed orientable
3-manifolds under the assumption that among the periodic orbits of the flow
there is only one saddle one and it is twisted are considered. An exhaustive
description of the topology of such manifolds is obtained. Namely, it has been
established that any manifold admitting such flows is either a lens space, or a
connected sum of a lens space with a projective space, or Seifert manifolds
with base homeomorphic to sphere and three singular fibers. Since the latter
are simple manifolds, the result obtained refutes the result that among simple
manifolds, the considered flows admit only lens spaces.


  Supersymmetric quantum Hall liquids are constructed on a noncommutative
superplane.
  We explore a supersymmetric formalism of the Landau problem. In the lowest
Landau level, there appear spin-less bosonic states and spin-1/2 down fermionic
states, which exhibit a super-chiral property. It is shown the Laughlin
wavefunction and topological excitations have their superpartners. Similarities
between supersymmetric quantum Hall systems and bilayer quantum Hall systems
are discussed.


  The accretion onto the black hole in the system HDE 226868/Cygnus X-1 is
powered by the strong line driven stellar wind of the O-type donor star. We
study the X-ray properties of the stellar wind in the hard state of Cyg X-1 as
determined with data from the Chandra High Energy Transmission Gratings. Large
density and temperature inhomogeneities are present in the wind, with a
fraction of the wind consisting of clumps of matter with higher density and
lower temperature embedded in a photoionized gas. Absorption dips observed in
the light curve are believed to be caused by these clumps. This work
concentrates on the non-dip spectra as a function of orbital phase. The spectra
show lines of H-like and He-like ions of S, Si, Na, Mg, Al and highly ionized
Fe (Fe xvii-Fe xxiv). We measure velocity shifts, column densities, and thermal
broadening of the line series. The excellent quality of these five observations
allows us to investigate the orbital phase dependence of these parameters. We
show that the absorber is located close to the black hole. Doppler shifted
lines point at a complex wind structure in this region, while emission lines
seen in some observations are from a denser medium than the absorber. The
observed line profiles are phase dependent. Their shapes vary from pure,
symmetric absorption at the superior conjunction to P Cygni profiles at the
inferior conjunction of the black hole.


  Any program that is designed to accomplish certain objectives, needs to
establish program level controls pertaining to the overall goal. A critical
aspect that determines the success of a program is the quality of the controls
and their effectiveness in accomplishing the goal. Traditional Control Maturity
Models primarily focus on the efficiency, management, and optimization of
controls, while only indirectly measuring control effectiveness which neglects
an essential aspect of control efficacy. In this paper, we highlight the
ineffectiveness of these models, outline an adaptable program controls
framework, and provide an approach to define measurable attributes (metrics)
that enable a zero-defect program. To the best of our knowledge, we believe
this is the first paper that provides a structured approach to defining a
controls measurement framework and creation of effectiveness metrics that can
be adopted by a variety of program use cases.


  We have examined a topology of 21 public transport networks in Poland. Our
data exhibit several universal features in considered systems when they are
analyzed from the point of view of evolving networks. Depending on the assumed
definition of a network topology the degree distribution can follow a power law
p(k) ~ k^(-\gamma) or can be described by an exponential function p(k)
\~exp(-\alpha k). In the first case one observes that mean distances between
two nodes are a linear function of logarithms of their degrees product.


  I describe the experimental determination of the CKM angle beta from
measurements of the decay time separation delta t between B0 mesons produced as
B Bbar pairs in e+e- annihilation. The current results from leading and
non-leading decay modes are presented and compared.


  In this paper we introduce a method to obtain algebraic information using
arithmetic one in the study of tori and their principal homogeneous spaces. In
particular, using some results of the authors with Tingyu Lee, we determine the
unramified Brauer groups of some norm one tori, and their torsors.


  We try to identify the light hadron world as the magnetic picture of QCD. We
take both phenomenological and theoretical approaches to this hypothesis, and
find that the interpretation seems to show interesting consistencies. In
particular, one can identify the rho and omega mesons as the magnetic gauge
bosons, and the Higgs mechanism for them provides a dual picture of the color
confinement.


  We present the design, implementation and detailed experimental
characterization of two-dimensional Magneto-optical traps (MOT) of bosonic
$^{23}$Na and $^{39}$K atoms for loading the cold atomic mixture in a
dual-species 3DMOT with a large number of atoms. We report our various
measurements pertaining to the characterisation of the two 2D$^+$MOTs via the
capture rate in the 3DMOT and also present the optimised parameters for the
best performance of the system of the cold atomic mixture. In the optimised
condition, we capture more than $3 \times 10^{10}$ $^{39}$K atoms and $5.8
\times 10^8$ $^{23}$Na atoms in the 3DMOT simultaneously from the individual
2D$^+$MOTs with the capture rate of $5 \times 10^{10}$ atoms/sec and $3.5
\times 10^8$ atoms/sec for $^{39}$K and $^{23}$Na, respectively. We also
demonstrate improvements of more than a factor of 5 in the capture rate into
the 3DMOT from the cold atomic sources when a relatively high-power
ultra-violet light is used to cause light-induced atomic desorption (LIAD) in
the 2D$^+$MOT glass cells. The cold atomic mixture would be useful for further
experiments on Quantum simulation with ultra-cold quantum mixtures in optical
potentials.


  An extension of $k$-algebras $B \subset A$ is said to have depth one if there
exists a positive integer $n$ such that $ A$ is a direct summand of $ B^n$ in
$_B\mtr{Mod}_B$. Depth one extensions of semisimple algebras are completely
characterized in terms of their centers. For extensions of semisimple Hopf
algebras our results are similar to those obtained for finite group algebra
extensions in \cite{BKone}.


  We have investigated quantum critical behavior in the doped two-leg extended
Hubbard ladder, by using a weak-coupling bosonization method. In the ground
state, the dominant fluctuation changes from the conventional d-wave-like
superconducting (SCd) state into density-wave states, with increasing
nearest-neighbor repulsions and/or decreasing doping rate. The competition
between the SCd state and the charge-density-wave state coexisting with the
p-density-wave state becomes noticeable on the critical point, at which the gap
for magnetic excitations vanishes. Based on the Majorana-fermion description of
the effective theory, we calculate the temperature dependence of the magnetic
response such as the spin susceptibility and the NMR relaxation rate, which
exhibit unusual properties due to two kinds of spin excitation modes. On the
quantum critical point, the spin susceptibility shows paramagnetic behavior
with logarithmic corrections and the NMR relaxation rate also exhibits
anomalous power-law behavior. We discuss the commensurability effect due to the
umklapp scattering and relevance to the two-leg ladder compounds
Sr_{14-x}Ca_xCu_{24}O_{41}.


  In this paper, we present a strictly negative imaginary state feedback
control methodology for relative degree two negative imaginary systems such as
flexible structures with collocated sensors and actuators. We show that by
augmenting a nominal model with a destabilising PID controller, we can apply
state feedback control to the system, resulting in a strictly negative
imaginary nominal closed loop system with a prescribed degree of stability.
Moreover, the overall system is guaranteed to be internally stable in the face
of unmodelled spillover dynamics.


  This article investigates the problem of estimating stellar atmospheric
parameters from spectra. Feature extraction is a key procedure in estimating
stellar parameters automatically. We propose a scheme for spectral feature
extraction and atmospheric parameter estimation using the following three
procedures: firstly, learn a set of basic structure elements (BSE) from stellar
spectra using an autoencoder; secondly, extract representative features from
stellar spectra based on the learned BSEs through some procedures of
convolution and pooling; thirdly, estimate stellar parameters ($T_{eff}$,
log$~g$, [Fe/H]) using a back-propagation (BP) network. The proposed scheme has
been evaluated on both real spectra from Sloan Digital Sky Survey (SDSS)/Sloan
Extension for Galactic Understanding and Exploration (SEGUE) and synthetic
spectra calculated from Kurucz's new opacity distribution function (NEWODF)
models. The best mean absolute errors (MAEs) are 0.0060 dex for log$~T_{eff}$,
0.1978 dex for log$~g$ and 0.1770 dex for [Fe/H] for the real spectra and
0.0004 dex for log$~T_{eff}$, 0.0145 dex for log$~g$ and 0.0070 dex for [Fe/H]
for the synthetic spectra.