  For reliable millimeter-wave (mmWave) networks, this paper proposes
cooperative sensing with multi-camera operation in an image-to-decision
proactive handover framework that directly maps images to a handover decision.
In the framework, camera images are utilized to allow for the prediction of
blockage effects in a mmWave link, whereby a network controller triggers a
handover in a proactive fashion. Furthermore, direct mapping allows for the
scalability of the number of pedestrians. This paper experimentally
investigates the feasibility of adopting cooperative sensing with multiple
cameras that can compensate for one another's blind spots. The optimal mapping
is learned via deep reinforcement learning to resolve the high dimensionality
of images from multiple cameras. An evaluation based on experimentally obtained
images and received powers verifies that a mapping that enhances channel
capacity can be learned in a multi-camera operation. The results indicate that
our proposed framework with multi-camera operation outperforms a conventional
framework with single-camera operation in terms of the average capacity.


  We study the estimation of distance d between two wireless nodes by means of
their wideband channels to a third node, called observer. The motivating
principle is that the channel impulse responses are similar for small d and
drift apart when d increases. Following this idea we propose specific distance
estimators based on the differences of path delays of the extractable multipath
components. In particular, we derive such estimators for rich multipath
environments and various important cases: with and without clock
synchronization as well as errors on the extracted path delays (e.g. due to
limited bandwidth). The estimators readily support (and benefit from) the
presence of multiple observers. We present an error analysis and, using ray
tracing in an exemplary indoor environment, show that the estimators perform
well in realistic conditions. We describe possible localization applications of
the proposed scheme and highlight its major advantages: it requires neither
precise synchronization nor line-of-sight connection. This could make wireless
user tracking feasible in dynamic indoor settings.


  If cosmological cold dark matter (CDM) consists of light enough bosonic
particles that their phase-space density exceeds unity, they will comprise a
Bose-Einstein condensate (BEC). The nature of this BEC-CDM as a quantum fluid
may then distinguish it dynamically from the standard form of CDM involving a
collisionless gas of non-relativistic particles that interact purely
gravitationally. We summarize some of the dynamical properties of BEC-CDM that
may lead to observable signatures in galactic halos and present some of the
bounds on particle mass and self-interaction coupling strength that result from
a comparison with observed galaxies.


  The effect of the spatially varying spin current on a skyrmion is numerically
investigated. It is shown that an inhomogeneous current density induces an
elongation of the skyrmion. This elongation can be controlled using current
pulses of different strength and duration. Long current pulses lead to a
splitting that forms two replicas of the initial skyrmion while for short
pulses the elongated skyrmion relaxes back to its initial circular state
through rotation in the MHz-GHz frequency range. The frequency is dependent on
the strength of the damping coefficient.


  In the paper we study applications of integral transforms composition method
(ITCM) for obtaining transmutations via integral transforms. It is possible to
derive wide range of transmutation operators by this method. Classical integral
transforms are involved in the integral transforms composition method (ITCM) as
basic blocks, among them are Fourier, sine and cosine-Fourier, Hankel, Mellin,
Laplace and some generalized transforms. The ITCM and transmutations obtaining
by it are applied to deriving connection formulas for solutions of singular
differential equations and more simple non-singular ones. We consider
well-known classes of singular differential equations with Bessel operators,
such as classical and generalized Euler-Poisson-Darboux equation and the
generalized radiation problem of A.Weinstein. Methods of this paper are applied
to more general linear partial differential equations with Bessel operators,
such as multivariate Bessel-type equations, GASPT (Generalized Axially
Symmetric Potential Theory) equations of A.Weinstein, Bessel-type generalized
wave equations with variable coefficients,ultra B-hyperbolic equations and
others. So with many results and examples the main conclusion of this paper is
illustrated: the integral transforms composition method (ITCM) of constructing
transmutations is very important and effective tool also for obtaining
connection formulas and explicit representations of solutions to a wide class
of singular differential equations, including ones with Bessel operators.


  For generalized coordinate systems, the numerical values of vector and tensor
components do not generally equal the physical values, i.e., the values one
would measure with standard physical instruments. Hence, calculating physical
components from coordinate components is important for comparing experiment
with theory. Surprisingly, however, this calculational method is not widely
known among physicists, and is rarely taught in relativity courses, though it
is commonly employed in at least one other field (applied mechanics.) Different
derivations of this method, ranging from elementary to advanced level, are
presented. The result is then applied to clarify the oftentimes confusing issue
of whether or not the speed of light in non-inertial frames is equal to c.


  Mobile sensing has become a promising paradigm for mobile users to obtain
information by task crowdsourcing. However, due to the social preferences of
mobile users, the quality of sensing reports may be impacted by the underlying
social attributes and selfishness of individuals. Therefore, it is crucial to
consider the social impacts and trustworthiness of mobile users when selecting
task participants in mobile sensing. In this paper, we propose a Social Aware
Crowdsourcing with Reputation Management (SACRM) scheme to select the
well-suited participants and allocate the task rewards in mobile sensing.
Specifically, we consider the social attributes, task delay and reputation in
crowdsourcing and propose a participant selection scheme to choose the
well-suited participants for the sensing task under a fixed task budget. A
report assessment and rewarding scheme is also introduced to measure the
quality of the sensing reports and allocate the task rewards based the assessed
report quality. In addition, we develop a reputation management scheme to
evaluate the trustworthiness and cost performance ratio of mobile users for
participant selection. Theoretical analysis and extensive simulations
demonstrate that SACRM can efficiently improve the crowdsourcing utility and
effectively stimulate the participants to improve the quality of their sensing
reports.


  Detection of Alzheimer's Disease (AD) from neuroimaging data such as MRI
through machine learning have been a subject of intense research in recent
years. Recent success of deep learning in computer vision have progressed such
research further. However, common limitations with such algorithms are reliance
on a large number of training images, and requirement of careful optimization
of the architecture of deep networks. In this paper, we attempt solving these
issues with transfer learning, where state-of-the-art architectures such as VGG
and Inception are initialized with pre-trained weights from large benchmark
datasets consisting of natural images, and the fully-connected layer is
re-trained with only a small number of MRI images. We employ image entropy to
select the most informative slices for training. Through experimentation on the
OASIS MRI dataset, we show that with training size almost 10 times smaller than
the state-of-the-art, we reach comparable or even better performance than
current deep-learning based methods.


  In this paper we introduce the concept of characteristic number that are
proven to be useful in the study of the combinatorics of graph cohomology. We
claim that it is a good combinatorial counterpart for geometric Betti numbers.
We then use this concept and tools built along the way to study Hamiltonian GKM
manifolds whose moment maps are in general position. We prove some connectivity
properties of the their GKM graphs and show an upper bound of their second
Betti numbers, which allows us to conclude that these manifolds, in the case of
dimension 8 and 10, have non-decreasing even Betti numbers up to half
dimension.


  In this work, we calculate the $CP$-averaged branching ratios and the direct
$CP$-violating asymmetries of the quasi-two-body decays $B_{(s)} \to P (\rho
\to) \pi\pi$ by employing the perturbative QCD (PQCD) approach (here $P$ stands
for a light pseudoscalar meson $\pi, K, \eta$ or $\eta^{\prime}$). The vector
current time-like form factor $F_{\pi}$, which contains the final state
interactions between the pion pair in the resonant region associated with the
$P$-wave states $\rho(770)$ along with the two-pion distribution amplitudes,
are employed to describe the interactions between the $\rho$ and the pion pair
under the hypothesis of the conserved vector current. We found that (a) the
PQCD predictions for the branching ratios and the direct $CP$-violating
asymmetries for most considered $B_{(s)} \to P (\rho \to) \pi\pi$ decays agree
with currently available data within errors; (b) for ${\cal B}(B \to \pi^0
\rho^0 \to \pi^0(\pi^+ \pi^-)$, the PQCD prediction is much smaller than the
measured one; and (c) for $B^+ \to \pi^+(\rho^0\to)\pi^+ \pi^-$ decay mode, we
found a negative $CP$ asymmetry $(-27.5^{+3.0}_{-3.7})\%$, which agrees with
other theoretical predictions but different in sign from those as reported by
BaBar and LHCb Collaboration.


  We study the perception of the radiation phenomena of Hawking radiation and
Unruh effect by using two main tools: the Unruh-DeWitt detectors and the
effective temperature function (ETF), this last tool based on Bogoliubov
transformations. Using the Unruh-DeWitt detectors we find an adiabatic
expansion of the detection properties along linear trajectories with slowly
varying acceleration in Minkowski, which allows us to calculate the spectrum
detected, finding the thermal spectrum as the zeroth order contribution. Using
the ETF we study the perception of Hawking radiation by observers following
radial trajectories outside a Schwarzschild black hole. One of the most
important results is that, in general, free-falling observers crossing the
event horizon do detect some radiation, even when the field is in the Unruh
vacuum state, due to a Doppler blue-shift that diverges at the horizon. We give
a general expression for the ETF, which has a clear interpretation in terms of
well-known physical phenomena. We discuss which contribution to the perception
comes from the radiation emitted by the black hole, and which contribution is
due to the Unruh effect caused by the movement of the observer. We conclude
that the Unruh effect is not only due to the observer's proper acceleration and
cannot even be defined locally, but is due to the observer's acceleration with
respect to the asymptotic region. We apply the ETF to the analysis of different
physical situations, in particular to a possible buoyancy scenario near the
horizon due to Hawking radiation pressure. Finally, we propose a non-stationary
vacuum state, which we call pulsating vacuum, for the radiation field outside a
stellar object hovering closely to form an event horizon. In this vacuum state,
we get nearly Hawking radiation emitted by the object, while avoiding the known
problems of the information paradox and the trans-planckian problem.


  Since long neutron lifetimes measured with a beam of cold neutrons are
significantly different from lifetimes measured with ultracold neutrons bottled
in a trap. It is often speculated that this "neutron anomaly" is due to an
exotic dark neutron decay channel of unknown origin. We show that this
explanation of the neutron anomaly can be excluded with a high level of
confidence when use is made of new data on neutron decay parameters.
Furthermore, data from neutron decay now compare well with Ft data derived from
nuclear \b{eta} decays.


  In recent years, utilization of heterogeneous hardware other than small core
CPU such as GPU, FPGA or many core CPU is increasing. However, when using
heterogeneous hardware, barriers of technical skills such as OpenMP, CUDA and
OpenCL are high. Based on that, I have proposed environment-adaptive software
that enables automatic conversion, configuration, and high performance
operation of once written code, according to the hardware to be placed.
However, including existing technologies, there has been no research to
properly and automatically offload the mixed offloading destination environment
such as GPU, FPGA and many core CPU. In this paper, as a new element of
environment-adaptive software, I study a method for offloading applications
properly and automatically in the environment where the offloading destination
is mixed with GPU, FPGA and many core CPU. I evaluate the effectiveness of the
proposed method in multiple applications.


  High-quality two-qubit gate operations are crucial for scalable quantum
information processing. Often, the gate fidelity is compromised when the system
becomes more integrated. Therefore, a low-error-rate, easy-to-scale two-qubit
gate scheme is highly desirable. Here, we experimentally demonstrate a new
two-qubit gate scheme that exploits fixed-frequency qubits and a tunable
coupler in a superconducting quantum circuit. The scheme requires less control
lines, reduces crosstalk effect, simplifies calibration procedures, yet
produces a controlled-Z gate in 30ns with a high fidelity of 99.5%, derived
from the interleaved randomized benchmarking method. Error analysis shows that
gate errors are mostly coherence limited. Our demonstration paves the way for
large-scale implementation of high-fidelity quantum operations.


  Let $X$ be a Hyperk\"ahler manifold, and let $H$ be an ample divisor on $X$.
We give a lower bound in terms of the Beauville-Bogomolov form $q(H)$ for the
twisted cotangent bundle $\Omega_X \otimes H$ to be pseudoeffective. If $X$ is
deformation equivalent to the Hilbert scheme of a K3 surface the lower bound
can be written down explicitly and we study its optimality.


  We argue that fracture surfaces may exhibit anomalous dynamic scaling
properties akin to what occurs in some models of kinetic roughening. We
determine the complete scaling behavior of the local fluctuations of a brittle
fracture in a granite block from experimental data. We obtain a global
roughness exponent $\chi = 1.2$ which differs from the local one, $\chi_{loc} =
0.79$. Implications on fracture physics are discussed.


  The gravitational field is usually neglected in the calculation of atomic
energy levels as its effect is much weaker than the electromagnetic field, but
that is not the case for a particle orbiting a black hole. In this work, the
canonical quantization of a massive and massless particles under gravitational
field exerted by this tiny but very massive object, both neutral and charged,
is carried out. By using this method, a very rare exact result of the
particle's quantized energy can be discovered. The presence of a very strong
attractive field and also the horizon make the energy complex valued and force
the corresponding wave function to be a quasibound state. Moreover, by taking
the small scale limit, the system becomes a gravitational atom in the sense of
Hydrogenic atoms energy levels and its wave function can be rediscovered.
Moreover, analogous to electronic transitions, the transition of the particle
in this case emits a graviton which carries a unique fingerprint of the black
hole such as black hole's mass and charge.


  We use a boolean cellular automaton model to describe the diffusion limited
dynamics of the irreversible reaction A+A->A+S on a 1D lattice. We derive a set
of equations for the dynamics of the empty interval probabilities from which
explicit expressions for the particle concentration and the two-point
correlation can be obtained. It is shown that the long time dynamics is in
agreement with the off-lattice solution. The early time behavior, however,
predicts a slower decay of the concentration.


  We study the lattice artefacts of the Wilson Dirac operator for QCD with two
colors and fermions in the fundamental representation from the viewpoint of
chiral perturbation theory. These effects are studied with the help of the
following spectral observables: the level density of the Hermitian Wilson Dirac
operator, the distribution of chirality over the real eigenvalues, and the
chiral condensate for the quenched as well as for the unquenched theory. We
provide analytical expressions for all these quantities. Moreover we derive
constraints for the level density of the real eigenvalues of the non-Hermitian
Wilson Dirac operator and the number of additional real modes. The latter is a
good measure for the strength of lattice artefacts. All computations are
confirmed by Monte Carlo simulations of the corresponding random matrix theory
which agrees with chiral perturbation theory of two color QCD with Wilson
fermions.


  Context: Agile development methodologies in the software industry have
increased significantly over the past decade. Although one of the main aspects
of agile software development (ASD) is less documentation, there have always
been conflicting opinions about what to document in ASD. Objective: This study
aims to systematically identify what to document in ASD, which documentation
tools and methods are in use, and how those tools can overcome documentation
challenges. Method: We performed a systematic literature review of the studies
published between 2010 and June 2021 that discusses agile documentation. Then,
we systematically selected a pool of 74 studies using particular inclusion and
exclusion criteria. After that, we conducted a quantitative and qualitative
analysis using the data extracted from these studies. Results: We found nine
primary vital factors to add to agile documentation from our pool of studies.
Our analysis shows that agile practitioners have primarily developed their
documentation tools and methods focusing on these factors. The results suggest
that the tools and techniques in agile documentation are not in sync, and they
separately solve different challenges. Conclusions: Based on our results and
discussion, researchers and practitioners will better understand how current
agile documentation tools and practices perform. In addition, investigation of
the synchronization of these tools will be helpful in future research and
development.


  The results of the study of ultra-short pulse generation in continuous-wave
Kerr-lens mode-locked (KLM) solid-state lasers with semiconductor saturable
absorbers are presented. The issues of extremely short pulse generation are
addressed in the frames of the theory that accounts for the coherent nature of
the absorber-pulse interaction. We developed an analytical model that bases on
the coupled generalized Landau-Ginzburg laser equation and Bloch equations for
a coherent absorber. We showed, that in the absence of KLM semiconductor
absorber produces 2pi - non-sech-pulses of self-induced transparency, while the
KLM provides an extremely short sech-shaped pulse generation. 2pi- and
pi-sech-shaped solutions and variable-area chirped pulses have been found. It
was shown, that the presence of KLM removes the limitation on the minimal
modulation depth in absorber. An automudulational stability and self-starting
ability were analyzed, too.


  The presence of a white dwarf in a resolved binary system, such as Sirius,
provides an opportunity to combine dynamical information about the masses, from
astrometry and spectroscopy, with a gravitational red-shift measurement and
spectrophotometry of the white dwarf atmosphere to provide a test of
theoretical mass-radius relations of unprecedented accuracy. We demonstrated
this with the first Balmer line spectrum of Sirius B to be obtained free of
contamination from the primary, with STIS on HST. However, we also found an
unexplained discrepancy between the spectroscopic and gravitational red-shift
mass determinations. With the recovery of STIS, we have been able to revisit
our observations of Sirius B with an improved observation strategy designed to
reduce systematic errors on the gravitational red-shift measurement. We provide
a preliminary report on the refined precision of the Sirius B mass-radius
measurements and the extension of this technique to a larger sample of white
dwarfs in resolved binaries. Together these data can provide accurate mass and
radius determinations capable of testing the theoretical mass-radius relation
and distinguishing between possible structural models.


  Age of information (AoI) is gaining attention as a valuable performance
metric for many IoT systems, in which a large number of devices report
time-stamped updates to a central gateway. This is the case, for instance, of
remote sensing, monitoring, or tracking, with broad applications in the
industrial, vehicular, and environmental domain. In these settings, AoI
provides insights that are complementary to those offered by throughput or
latency, capturing the ability of the system to maintain an up-to-date view of
the status of each transmitting device. From this standpoint, while a good
understanding of the metric has been reached for point-to-point links,
relatively little attention has been devoted to the impact that link layer
solutions employed in IoT systems may have on AoI. In particular, no result is
available for modern random access protocols, which have recently emerged as
promising solutions to support massive machine-type communications. To start
addressing this gap we provide in this paper the first study of the AoI of a
scheme in this family, namely irregular repetition slotted ALOHA (IRSA). By
means of a Markovian analysis, we track the AoI evolution at the gateway, prove
that the process is ergodic, and derive a compact closed form expression for
its stationary distribution. Leaning on this, we compute exact formulations for
the average AoI and the age violation probability. The study reveals
non-trivial design trade-offs for IRSA and highlights the key role played by
the protocol operating frame size. Moreover, a comparison with the performance
of a simpler slotted ALOHA strategy highlights a remarkable potential for
modern random access schemes in terms of information freshness.


  Based on the hypothesis that the $X(3872)$ exotic hadron is a mixture of
$\chi_{c1}(2P)$ and other states and that its prompt hadroproduction
predominately proceeds via its $\chi_{c1}(2P)$ component, we calculate the
prompt-$X(3872)$ polarization at the CERN LHC through next-to-leading order in
$\alpha_s$ within the factorization formalism of nonrelativistic QCD, including
both the color-singlet $^3\!P_1^{[1]}$ and color-octet $^3\!S_1^{[8]}$ $c\bar
c$ Fock states. We also consider the polarization of the $J/\psi$ produced by
the subsequent $X(3872)$ decay. We predict that, under ATLAS, CMS, and LHCb
experimental conditions, the $X(3872)$ is largely longitudinally polarized,
while the $J/\psi$ is largely transversely polarized. We propose that the LHC
experiments perform such polarization measurements to pin down the nature of
the $X(3872)$ and other $X$, $Y$, $Z$ exotic states with non-zero spin.


  We study the behavior of very thin liquid films wetting homogeneous planar
and spherical substrates. In order to describe a simple fluid at very small
scales, we employ a classical density functional theory (DFT). Here, we model a
fluid with a local density approximation (LDA) for its hard-sphere contribution
and assume that the intermolecular attractive forces are long-range. In
particular, we first introduce the basic concept of DFT, and then present
computations for fluid films on planar and spherically symmetric walls. We
present equilibrium density profiles and adsorption isotherms. We also compare
our results to predictions from a sharp-interface approximation (SIA) and
suggest a piecewise function approximation (PFA), which assumes that the
density profile at the wall-liquid and the liquid-vapor interfaces varies
smoothly.


  In this series of lectures we give an introduction to the concept of
asymptotic symmetry analysis with a focus on asymptotically flat spacetimes in
2+1 dimensions. We explain general ideas of quantizing gauge theories and then
apply these ideas to gravity both in the metric as well as the Chern-Simons
formulations. This enables one to compute the asymptotic symmetries of given
gravitational configurations that in turn act as the basic underlying
symmetries of a possible dual quantum field theory in the context of
holography. We also briefly elaborate on the concept of "soft hair" excitations
of black holes in this context.


  Variational autoencoders (VAEs) are one of the powerful likelihood-based
generative models with applications in many domains. However, they struggle to
generate high-quality images, especially when samples are obtained from the
prior without any tempering. One explanation for VAEs' poor generative quality
is the prior hole problem: the prior distribution fails to match the aggregate
approximate posterior. Due to this mismatch, there exist areas in the latent
space with high density under the prior that do not correspond to any encoded
image. Samples from those areas are decoded to corrupted images. To tackle this
issue, we propose an energy-based prior defined by the product of a base prior
distribution and a reweighting factor, designed to bring the base closer to the
aggregate posterior. We train the reweighting factor by noise contrastive
estimation, and we generalize it to hierarchical VAEs with many latent variable
groups. Our experiments confirm that the proposed noise contrastive priors
improve the generative performance of state-of-the-art VAEs by a large margin
on the MNIST, CIFAR-10, CelebA 64, and CelebA HQ 256 datasets. Our method is
simple and can be applied to a wide variety of VAEs to improve the expressivity
of their prior distribution.


  The cross section for formation in $\gamma + p$ collisions of the recently
found hidden-charm pentaquark states $P_c(4380)$ and $P_c(4450)$ is discussed
and estimated. The studies of these resonances in photon beam experiments can
be complementary to those in the LHCb experiment setting, and may be more
advantageous for measurement of their additional decay channels. It is pointed
out that both the relative importance of such decays and the yield of the
resonances in the $\gamma + p$ collisions are sensitive to the internal
dynamics of the pentaquarks and can resolve between theoretical models.
Specific numerical estimates are discussed within a simple `baryocharmonium'
model, where the the observed $P_c$ resonances are composites of $J/\psi$ and
excited nucleon states with the quantum numbers of $N(1440)$ and $N(1520)$.


  We prove that externally definable sets in first order NIP theories have
honest definitions, giving a new proof of Shelah's expansion theorem. Also we
discuss a weak notion of stable embeddedness true in this context. Those
results are then used to prove a general theorem on dependent pairs, which in
particular answers a question of Baldwin and Benedikt on naming an
indiscernible sequence.


  For an edge-colored graph $G$, the minimum color degree of $G$ means the
minimum number of colors on edges which are adjacent to each vertex of $G$. We
prove that if $G$ is an edge-colored graph with minimum color degree at least
$5$ then $V(G)$ can be partitioned into two parts such that each part induces a
subgraph with minimum color degree at least $2$. We show this theorem by
proving a much stronger form. Moreover, we point out an important relationship
between our theorem and Bermond-Thomassen's conjecture in digraphs.


  IP eXchange or IPX is GSMA proposal for IP interconnection model which
supports multi services to offer end-to-end QoS, security, interoperability,
SLAs through a dedicated connection. There are some possible partnership
schemes between IPX providers such as peering mode, semi-hosted mode,
full-hosted mode, or combination between these modes. The implementation of the
schemes will be case-by-case basis with some considerations based on, but not
limited to, IPX Providers network asset, coverage, services, features offer,
commercial offer, and customers. For an IPX provider to become competitive in
IPX business and become a global IPX hub, some value added should be considered
such as cost efficiency and great network performance. To achieve it, an IPX
provider could implement some strategies such as build network sinergy between
them and partners to develop IPX Service as single offering, offer their
customers with bundled access network and services. An IPX provider should also
consider their existing customer-based that can be a benefit to their
bargaining position to other potential IPX provider partners to determine price
and business scheme for partnership.


  The problem of categorical data analysis in high dimensions is considered. A
discussion of the fundamental difficulties of probability modeling is provided,
and a solution to the derivation of high dimensional probability distributions
based on Bayesian learning of clique tree decomposition is presented. The main
contributions of this paper are an automated determination of the optimal
clique tree structure for probability modeling, the resulting derived
probability distribution, and a corresponding unified approach to clustering
and anomaly detection based on the probability distribution.


  We demonstrate coherent dual frequency-comb spectroscopy for detecting
variations in greenhouse gases. High signal-to-noise spectra are acquired
spanning 5990 to 6260 cm^-1 (1600 to 1670 nm) covering ~700 absorption features
from CO2, CH4, H2O, HDO, and 13CO2, across a 2-km open-air path. The
transmission of each frequency comb tooth is resolved, leading to spectra with
<1 kHz frequency accuracy, no instrument lineshape, and a 0.0033-cm^-1 point
spacing. The fitted path-averaged concentrations and temperature yield dry-air
mole fractions. These are compared with a point sensor under well-mixed
conditions to evaluate current absorption models for real atmospheres. In
heterogeneous conditions, time-resolved data demonstrate tracking of strong
variations in mole fractions. A precision of <1 ppm for CO2 and <3 ppb for CH4
is achieved in 5 minutes in this initial demonstration. Future portable systems
could support regional emissions monitoring and validation of the spectral
databases critical to global satellite-based trace gas monitoring.


  This paper presents a variational framework for dense diffeomorphic
atlas-mapping onto high-throughput histology stacks at the 20 um meso-scale.
The observed sections are modelled as Gaussian random fields conditioned on a
sequence of unknown section by section rigid motions and unknown diffeomorphic
transformation of a three-dimensional atlas. To regularize over the
high-dimensionality of our parameter space (which is a product space of the
rigid motion dimensions and the diffeomorphism dimensions), the histology
stacks are modelled as arising from a first order Sobolev space smoothness
prior. We show that the joint maximum a-posteriori, penalized-likelihood
estimator of our high dimensional parameter space emerges as a joint
optimization interleaving rigid motion estimation for histology restacking and
large deformation diffeomorphic metric mapping to atlas coordinates. We show
that joint optimization in this parameter space solves the classical curvature
non-identifiability of the histology stacking problem. The algorithms are
demonstrated on a collection of whole-brain histological image stacks from the
Mouse Brain Architecture Project.


  We develop a mesoscopic field theory for the collective nonequilibrium
dynamics of multicomponent mixtures of interacting active (i.e., motile) and
passive (i.e., nonmotile) colloidal particles with isometric shape in two
spatial dimensions. By a stability analysis of the field theory, we obtain
equations for the spinodal that describes the onset of a motility-induced
instability leading to cluster formation in such mixtures. The prediction for
the spinodal is found to be in good agreement with particle-resolved computer
simulations. Furthermore, we show that in active-passive mixtures the spinodal
instability can be of two different types. One type is associated with a
stationary bifurcation and occurs also in one-component active systems, whereas
the other type is associated with a Hopf bifurcation and can occur only in
active-passive mixtures. Remarkably, the Hopf bifurcation leads to moving
clusters. This explains recent results from simulations of active-passive
particle mixtures, where moving clusters and interfaces that are not seen in
the corresponding one-component systems have been observed.


  We present a review of a broad selection of nuclear matter equations of state
(EOSs) applicable in core-collapse supernova studies. The large variety of
nuclear matter properties, such as the symmetry energy, which are covered by
these EOSs leads to distinct outcomes in supernova simulations. Many of the
currently used EOS models can be ruled out by nuclear experiments, nuclear
many-body calculations, and observations of neutron stars. In particular the
two classical supernova EOS describe neutron matter poorly. Nevertheless, we
explore their impact in supernova simulations since they are commonly used in
astrophysics. They serve as extremely soft and stiff representative nuclear
models. The corresponding supernova simulations represent two extreme cases,
e.g., with respect to the protoneutron star (PNS) compactness and shock
evolution. Moreover, in multi-dimensional supernova simulations EOS differences
have a strong effect on the explosion dynamics. Because of the extreme
behaviors of the classical supernova EOSs we also include DD2, a relativistic
mean field EOS with density-dependent couplings, which is in satisfactory
agreement with many current nuclear and observational constraints. This is the
first time that DD2 is applied to supernova simulations and compared with the
classical supernova EOS. We find that the overall behaviour of the latter EOS
in supernova simulations lies in between the two extreme classical EOSs. As
pointed out in previous studies, we confirm the impact of the symmetry energy
on the electron fraction. Furthermore, we find that the symmetry energy becomes
less important during the post bounce evolution, where conversely the symmetric
part of the EOS becomes increasingly dominating, which is related to the high
temperatures obtained. Moreover, we study the possible impact of quark matter
at high densities and light nuclear clusters at low and intermediate dens


  We have observed Fermi polarons, dressed spin down impurities in a spin up
Fermi sea of ultracold atoms. The polaron manifests itself as a narrow peak in
the impurities' rf spectrum that emerges from a broad incoherent background. We
determine the polaron energy and the quasiparticle residue for various
interaction strengths around a Feshbach resonance. At a critical interaction,
we observe the transition from polaronic to molecular binding. Here, the
imbalanced Fermi liquid undergoes a phase transition into a Bose liquid
coexisting with a Fermi sea.


  We present an example of a 6-web W (6, 3, 2) of codimension two and of
maximum rank on a six-dimensional manifold which is not almost Grassmannizable.


  Brightness distribution of Gamma-Ray Bursts (GRBs) is studied in detail under
the assumption that GRB rate is related to cosmic star formation rate. The two
populations of the long- and short-duration bursts in the 4B BATSE catalog are
analyzed separately. Taking account of current uncertainties in the
observational estimate of star formation rate (SFR), we have tried various
models of the cosmic star formation history and we find that the SFR evolution
in $z$ = 0--1 is strongly constrained by the GRB distribution if the standard
candle approximation is valid. The strong SFR evolution by a factor of $\sim$
15 from $z$ = 0 to 1 inferred from UV observations is too steep to be
consistent with the GRB distribution for any distance scale of GRBs. Some
possibilities to reconcile this discrepancy are discussed, including the
intrinsic luminosity dispersion of GRBs and/or modification of star formation
history estimated by UV observations. We argue that SFR increase factor from
$z$ = 0 to 1 may be as low as about 4 if we choose different sets of
cosmological parameters and/or take account of the evolution of metallicity and
dust extinction in the UV data, and this would significantly remedy the
discrepancy.


  We elucidate the dynamics of a thin spherical material shell with a
tangential pressure, using a new approach. This is both simpler than the
traditional method of extrinsic curvature junction conditions (which we also
employ), and suggests an expression for a `gravitational potential energy' of
the shell. Such a shell, if slowly spinning, can rotationally drag the inertial
frames within it through a finite angle as it collapses and rebounds from a
minimum radius. Rebounding `spherical' and cylindrical pulses of rotating
gravitational waves were studied previously. Here we calculate their angular
momentum and show that their rotational frame dragging is in agreement with
that of the rotating spherical shell and a rotating cylindrical dust shell.
This shows that Machian effects occur equally for material and analogous
`immaterial' sources.


  Deep Metric Learning (DML) is arguably one of the most influential lines of
research for learning visual similarities with many proposed approaches every
year. Although the field benefits from the rapid progress, the divergence in
training protocols, architectures, and parameter choices make an unbiased
comparison difficult. To provide a consistent reference point, we revisit the
most widely used DML objective functions and conduct a study of the crucial
parameter choices as well as the commonly neglected mini-batch sampling
process. Under consistent comparison, DML objectives show much higher
saturation than indicated by literature. Further based on our analysis, we
uncover a correlation between the embedding space density and compression to
the generalization performance of DML models. Exploiting these insights, we
propose a simple, yet effective, training regularization to reliably boost the
performance of ranking-based DML models on various standard benchmark datasets.
Code and a publicly accessible WandB-repo are available at
https://github.com/Confusezius/Revisiting_Deep_Metric_Learning_PyTorch.


  Let $G$ be a real Lie group, $\Lambda\subseteq G$ a lattice, and
$X=G/\Lambda$. We fix a probability measure $\mu$ on $G$ and consider the left
random walk induced on $X$. It is assumed that $\mu$ is aperiodic, has a finite
first moment, spans a semisimple algebraic group without compact factors, and
has two non mutually singular convolution powers. We show that for every
starting point $x\in X$, the $n$-th step distribution $\mu^n*\delta_{x}$ of the
walk weak-$\ast$ converges toward some homogeneous probability measure on $X$.


  We analyze the convergence of degenerate approximations to Green's function
of elliptic boundary value problems with high-contrast coefficients. It is
shown that the convergence is independent of the contrast if the error is
measured with respect to suitable norms. This lays ground to fast methods
(so-called hierarchical matrix approximations) which do not have to be adapted
to the coefficients.


  The earlier work of the author on Frequency estimation in three-phase power
systems ( that is included as the reference number 1) is expanded to the
distributed setting in order present a framework for the implementation of such
a frequency estimator in real-world power distribution networks. For rigor, the
mean and mean square performance of the distributed frequency estimator is
analysed. The performance of the developed algorithm is validated through
simulations on both synthetic data and real-world data recordings, where it is
shown to outperform standard linear and the recently introduced widely liner
frequency estimators.


  We prove that $\W_3$ is the gauge symmetry of the scale-invariant rigid
particle, whose action is given by the integrated extrinsic curvature of its
world line. This is achieved by showing that its equations of motion can be
written in terms of the Boussinesq operator. The $\W_3$ generators $T$ and $W$
then appear respectively as functions of the induced world line metric and the
extrinsic curvature. We also show how the equations of motion for the standard
relativistic particle arise from those of the rigid particle whenever it is
consistent to impose the ``zero-curvature gauge'', and how to rewrite them in
terms of the $\KdV$ operator. The relation between particle models and
integrable systems is further pursued in the case of the spinning particle,
whose equations of motion are closely related to the $\SKdV$ operator. We also
partially extend our analysis in the supersymmetric domain to the scale
invariant rigid particle by explicitly constructing a supercovariant version of
its action. Comment: This is an expanded version of hep-th/9406072 (to be
published in the Proceedings of the Workshop on the Geometry of Constrained
Dynamical Systems, held at the Isaac Newton Institute for Mathematical
Sciences, Cambridge, June 14-18, 1994.).


  Electrically charged systems bound by a strong gravitational force can
sustain a huge amount of electric charge (up to 10^20C) against Coulomb
repulsion. General relativistically such systems form a stable hydrostatic
configuration both in the non-rotating and rotating cases. Here we study the
effects of electric charge (electric energy density) on the spacetime outside a
rotating electrically charged system bound by a strong gravitational force. In
particular we investigate the effect of charge density on frame-dragging of
spacetime in the exterior region. Using the coupled Einstein-Maxwell equations
it is found that in the slow rotation approximation charge accumulations not
only acts like an additional mass, thus modifying the spherically symmetric
part of the spacetime, the electric charge also contributes directly to the
dragging of spacetime. A modified Lense-Thirring formula for the spacetime
frame dragging frequency is obtained.


  The ultrafast manipulation of quantum material has led to many novel and
significant discoveries. Among them, the light-induced transient
superconductivity in cuprates achieved by melting competing stripe orders
represents a highly appealing accomplishment. However, recent investigations
have shown that the notion of photoinduced superconductivity remains a topic of
controversy, and its elucidation solely through c-axis time-resolved terahertz
spectroscopy remains an arduous task. Here, we measure the in-plane and
out-of-plane transient terahertz responses simultaneously in the stripe-ordered
non-superconducting La$_{2-x}$Ba$_{x}$CuO$_4$ after near-infrared excitations.
We find that although a pump-induced reflectivity edge appears in the c-axis
reflectance spectrum, the reflectivity along the CuO$_2$ planes decreases
simultaneously, indicating an enhancement in the scattering rate of
quasiparticles. This in-plane transient response is clearly distinct from the
features associated with superconducting condensation. Therefore, we conclude
the out-of-plane transient responses cannot be explained by an equivalent of
Josephson tunneling. Notably, those pump-induced terahertz responses remain
consistent even when we vary the near-infrared optical pump wavelengths and
hole concentrations. Our results provide a critical evidence that transient
three-dimensional superconductivity cannot be induced by melting the competing
stripe orders with pump pulses whose photon energy is much higher than the
superconducting gap of cuprates.


  Recently, total variation (TV) based minimization algorithms have achieved
great success in compressive sensing (CS) recovery for natural images due to
its virtue of preserving edges. However, the use of TV is not able to recover
the fine details and textures, and often suffers from undesirable staircase
artifact. To reduce these effects, this letter presents an improved TV based
image CS recovery algorithm by introducing a new nonlocal regularization
constraint into CS optimization problem. The nonlocal regularization is built
on the well known nonlocal means (NLM) filtering and takes advantage of
self-similarity in images, which helps to suppress the staircase effect and
restore the fine details. Furthermore, an efficient augmented Lagrangian based
algorithm is developed to solve the above combined TV and nonlocal
regularization constrained problem. Experimental results demonstrate that the
proposed algorithm achieves significant performance improvements over the
state-of-the-art TV based algorithm in both PSNR and visual perception.


  We classify the countable homogeneous coloured multipartite graphs with any
finite number of parts. By Fraisse's Theorem this amounts to classifying the
families F of pairwise non-embeddable finite coloured multipartite graphs for
which the class Forb(F) of multipartite graphs which forbid these is an
amalgamation class. We show that once we understand such families F in the
quadripartite case, things do not become any more complicated for larger
numbers of parts.


  The development and use of large-scale quantum computers relies on
integrating quantum error-correcting (QEC) schemes into the quantum computing
pipeline. A fundamental part of the QEC protocol is the decoding of the
syndrome to identify a recovery operation with a high success rate. In this
work, we implement a decoder that finds the recovery operation with the highest
success probability by mapping the decoding problem to a spin system and using
Population Annealing to estimate the free energy of the different error
classes. We study the decoder performance on a 4.8.8 color code lattice under
different noise models, including code capacity with bit-flip and depolarizing
noise, and phenomenological noise, which considers noisy measurements, with
performance reaching near-optimal thresholds. This decoding algorithm can be
applied to a wide variety of stabilizer codes, including surface codes and
quantum low-density parity-check (qLDPC) codes.


  In the rapidly evolving landscape of computing disciplines, substantial
efforts are being dedicated to unraveling the sociotechnical implications of
generative AI (Gen AI). While existing research has manifested in various
forms, there remains a notable gap concerning the direct engagement of
knowledge workers in academia with Gen AI. We interviewed 18 knowledge workers,
including faculty and students, to investigate the social and technical
dimensions of Gen AI from their perspective. Our participants raised concerns
about the opacity of the data used to train Gen AI. This lack of transparency
makes it difficult to identify and address inaccurate, biased, and potentially
harmful, information generated by these models. Knowledge workers also
expressed worries about Gen AI undermining trust in the relationship between
instructor and student and discussed potential solutions, such as pedagogy
readiness, to mitigate them. Additionally, participants recognized Gen AI's
potential to democratize knowledge by accelerating the learning process and act
as an accessible research assistant. However, there were also concerns about
potential social and power imbalances stemming from unequal access to such
technologies. Our study offers insights into the concerns and hopes of
knowledge workers about the ethical use of Gen AI in educational settings and
beyond, with implications for navigating this new landscape.


  As a prototype of an evolution equation we consider the Schr\"odinger
equation i (d/dt) \Psi(t) = H \Psi(t), H = H_0 + V(x) for the Hilbert space
valued function \Psi(.) which describes the state of the system at time t in
space dimension at least 2. The kinetic energy operator H_0 may be propotional
to the Laplacian (nonrelativistic quantum mechanics),
  H_0 = \sqrt{-\Delta + m^2} (relativistic kinematics, Klein-Gordon equation),
the Dirac operator, or ..., while the potential V(x) tends to 0 suitably as |x|
to infinity.
  We present a geometrical approach to the inverse scattering problem. For
given scattering operator S we show uniqueness of the potential, we give
explicit limits of the high-energy behavior of the scattering operator, and we
give reconstruction formulas for the potential.
  Our mathematical proofs closely follow physical intuition. A key observation
is that at high energies translation of wave packets dominates over spreading
during the interaction time. Extensions of the method cover e.g. Schr\"odinger
operators with magnetic fields, multiparticle systems, and wave equations.


  Given F a locally compact, non-discrete, non-archimedean field of
characteristic different from 2 and R an integral domain such that a
non-trivial smooth F-character with values in the multiplicative group of R
exists, we construct the (reduced) metaplectic group attached to R. We show
that it is in most cases a double cover of the symplectic group over F. Finally
we define a faithful infinite dimensional R-representation of the metaplectic
group analogue to the Weil representation in the complex case.


  Some new kinds of special curves called $\overset{\_}{\xi}$-helix,
$\overset{% \_}{\xi}_{1}$-helix, $\overset{\_}{\mu}$-helix,
$\overset{\_}{\nu}$-helix and $W_{k}$-Darboux helices $(k\in \left\{
{n,r,o}\right\} )$ in the Myller configuration $M(C,\overset{\_}{\xi },\pi )$
are defined and studied. The necessary and sufficient conditions for these
curves are obtained, also the axes of those helices are given and the
relationships between them are introduced.


  Face authentication usually utilizes deep learning models to verify users
with high recognition accuracy. However, face authentication systems are
vulnerable to various attacks that cheat the models by manipulating the digital
counterparts of human faces. So far, lots of liveness detection schemes have
been developed to prevent such attacks. Unfortunately, the attacker can still
bypass these schemes by constructing wide-ranging sophisticated attacks. We
study the security of existing face authentication services (e.g., Microsoft,
Amazon, and Face++) and typical liveness detection approaches. Particularly, we
develop a new type of attack, i.e., the low-cost 3D projection attack that
projects manipulated face videos on a 3D face model, which can easily evade
these face authentication services and liveness detection approaches. To this
end, we propose FaceLip, a novel liveness detection scheme for face
authentication, which utilizes unforgeable lip motion patterns built upon
well-designed acoustic signals to enable a strong security guarantee. The
unique lip motion patterns for each user are unforgeable because FaceLip
verifies the patterns by capturing and analyzing the acoustic signals that are
dynamically generated according to random challenges, which ensures that our
signals for liveness detection cannot be manipulated. Specially, we develop
robust algorithms for FaceLip to eliminate the impact of noisy signals in the
environment and thus can accurately infer the lip motions at larger distances.
We prototype FaceLip on off-the-shelf smartphones and conduct extensive
experiments under different settings. Our evaluation with 44 participants
validates the effectiveness and robustness of FaceLip.


  The Big Data is the most popular paradigm nowadays and it has almost no
untouched area. For instance, science, engineering, economics, business, social
science, and government. The Big Data are used to boost up the organization
performance using massive amount of dataset. The Data are assets of the
organization, and these data gives revenue to the organizations. Therefore, the
Big Data is spawning everywhere to enhance the organizations' revenue. Thus,
many new technologies emerging based on Big Data. In this paper, we present the
taxonomy of Big Data. Besides, we present in-depth insight on the Big Data
paradigm.


  We report a new kind of exceptional points in periodically driven system,
called Floquet $\pi$ exceptional points, whose eigenvectors rotate on Bloch
sphere and accumulate $\pi$ geometric phase in one time period. The merging of
two such kind exceptional points are constrained by their dynamical structure,
meaning two order-1/2 exceptional points with same dynamical structure can
merge to one order-1 one while those with opposite dynamical structure can not.
We show they exist in Floquet bipartite lattices, and the order-1 Floquet $\pi$
exceptional points appear at the phase transition point between quasimomentum
gap phases and quasienergy gap phases. The scattering properties around the
order-1 Floquet $\pi$ exceptional points is quite novel, which is perfect
transparency but detectable in reflection for one of two sides.


  In this paper, we propose a low-rank representation with symmetric constraint
(LRRSC) method for robust subspace clustering. Given a collection of data
points approximately drawn from multiple subspaces, the proposed technique can
simultaneously recover the dimension and members of each subspace. LRRSC
extends the original low-rank representation algorithm by integrating a
symmetric constraint into the low-rankness property of high-dimensional data
representation. The symmetric low-rank representation, which preserves the
subspace structures of high-dimensional data, guarantees weight consistency for
each pair of data points so that highly correlated data points of subspaces are
represented together. Moreover, it can be efficiently calculated by solving a
convex optimization problem. We provide a rigorous proof for minimizing the
nuclear-norm regularized least square problem with a symmetric constraint. The
affinity matrix for spectral clustering can be obtained by further exploiting
the angular information of the principal directions of the symmetric low-rank
representation. This is a critical step towards evaluating the memberships
between data points. Experimental results on benchmark databases demonstrate
the effectiveness and robustness of LRRSC compared with several
state-of-the-art subspace clustering algorithms.


  Mukai showed that projective models of Brill-Noether general polarized K3
surfaces of genus $6-10$ and $12$ are obtained as linear sections of projective
homogeneous varieties, and that their hyperplane sections are Brill-Noether
general curves. In general, the question, raised by Knutsen, and attributed to
Mukai, of whether the Brill-Noether generality of any polarized K3 surface
$(S,H)$ is equivalent to the Brill-Noether generality of smooth curves $C$ in
the linear system $|H|$, is still open. Using Lazarsfeld-Mukai bundle
techniques, we answer this question in the affirmative for polarized K3
surfaces of genus $\leq 19$, which provides a new and unified proof even in the
genera where Mukai models exist.


  The close relationship among the polynomial functions and Fibonacci numerical
sequences is shown in this paper. These numerical sequences are defined by the
recurrence equation $x_{k + n} = \displaystyle\sum_{j = 0}^{n-1}\alpha_j x_{k +
j}$, where $n$ is the polynomial degree and $\alpha$'s, the polynomial
coefficients. The arithmetic trapezoid resulting from the recurrence equations
is also shown. This trapezoid is nothing but a generalization of Pascal's
Triangle. Trapezoid is a convenient name because the form it appears does not
have the `upper end` of a usual triangle. This study shows that each polynomial
generates infinite sequences, and that each sequence generates only a single
arithmetic trapezoid.


  In this work, we show that, due to the alternating orientation of the spins
in the ground state of the artificial square spin ice, the influence of a set
of spins at a certain distance of a reference spin decreases faster than the
expected result for the long range dipolar interaction, justifying the use of
the nearest neighbor two dimensional square spin ice model as an effective
model. Using an extension of the model presented in ref. [Scientific Reports 5,
15875 (2015)], considering the influence of the eight nearest neighbors of each
spin on the lattice, we analyze the thermodynamics of the model and study the
monopoles and string densities dependence as a function of the temperature.


  Atmospheric neutrino-fluxes are calculated over the wide energy range from 30
MeV to 3,000 GeV for the study of neutrino-physics using the data from
underground neutrino-detectors. The atmospheric muon-flux at high altitude and
at sea level is studied to calibrate the neutrino-fluxes at low energies and
high energies respectively. The agreement of our calculation with observations
is satisfactory. The uncertainty of atmospheric neutrino-fluxes is also
studied.


  We present a prescription to calculate manifestly gauge invariant tree-level
helicity amplitudes for arbitrary scattering processes with off-shell
initial-state gluons within the kinematics of high-energy scattering. We show
that it is equivalent to Lipatov's effective action approach, and show its
computational potential through numerical calculations for scattering processes
with several particles in the final state.


  As an analogy of fully entangled fraction in the framework of entanglement
theory, we have introduced the notion of quantum coherence fraction
$C_{\mathcal{F}}$, which quantifies the closeness between a given state and the
set of maximally coherent states. By providing an alternative formulation of
the robustness of coherence $C_{\mathcal{R}}$, we have elucidated the
relationship between quantum coherence fraction and the normalized version of
$C_{\mathcal{R}}$ (i.e., $\overline{C}_{\mathcal{R}}$), where the role of
genuinely incoherent operations (GIO) is highlighted. Numerical simulation
shows that though as expected $C_{\mathcal{F}}$ is upper bounded by
$\overline{C}_{\mathcal{R}}$, $C_{\mathcal{F}}$ constitutes a good
approximation to $\overline{C}_{\mathcal{R}}$ especially in low-dimensional
Hilbert spaces. Even more intriguingly, we can analytically prove that
$C_{\mathcal{F}}$ is exactly equivalent to $\overline{C}_{\mathcal{R}}$ for
qubit and qutrit states. Moreover, some intuitive properties and implications
of $C_{\mathcal{F}}$ are also indicated.


  We analyze the general phenomenology of neutrinoless double beta decay in the
minimal left-right symmetric model. We study under which conditions a New
Physics dominated neutrinoless double beta decay signal can be expected in the
future experiments. We show that the correlation among the different
contributions to the process, which arises from the neutrino mass generation
mechanism, can play a crucial role. We have found that, if no fine tuned
cancellation is involved in the light active neutrino contribution, a New
Physics signal can be expected mainly from the $W_R-W_R$ channel. An
interesting exception is the $W_L-W_R$ channel which can give a dominant
contribution to the process if the right-handed neutrino spectrum is
hierarchical with $M_1\lesssim$ MeV and $M_2,M_3\gtrsim$ GeV. We also discuss
if a New Physics signal in neutrinoless double beta decay experiments is
compatible with the existence of a successful Dark Matter candidate in the
left-right symmetric models. It turns out that, although it is not a generic
feature of the theory, it is still possible to accommodate such a signal with a
KeV sterile neutrino as Dark matter.


  The goal of this study is to explore emerging trends in cloud computing
technology that can support an economic and social change. We apply the methods
of entity linking, which links word strings to entities from a knowledge base,
to extract main keywords in cloud computing from accumulated publications from
2004 to 2021. Results suggest that in cloud computing research, Internet of
things has an accelerated technological and scientific growth compared to the
other topics. Other critical research fields that support the evolution of
cloud computing are mathematical optimization and virtual machine. These
findings reveal a technological competition between Cloud systems
infrastructure, hardware development side, and computing and software
development to play the main role in technological evolution of Cloud
Computing. Moreover, this study shows that technological development of virtual
machines and computing device can be of critical importance to foster an
economic and technological change in many sectors. However, the implementation
of cloud computing has to be supported by skill development, organizational
change, and adopter engagement, to foster the management and the diffusion of
cloud technologies and the exploitation of cloud-based infrastructures for
competitive advantage of firms in fast-changing markets. This study can provide
main information to extend the knowledge having theoretical implications to
explain characteristics of the evolution of science and technology in this
field of research and practical implications of innovation management for the
appropriate allocation of resources towards new technological trajectories in
cloud computing having a potential of growth and beneficial impact in society.


  A red hole is "just like a black hole" except it lacks an event horizon and a
singularity. As a result, a red hole emits much more energy than a black hole
during a collapse or accretion event. We consider how a red hole solution can
solve the "energy crisis" and power extremely energetic gamma ray bursts and
hypernovae.


  Caching at mobile devices, accompanied by device-to-device (D2D)
communications, is one promising technique to accommodate the exponentially
increasing mobile data traffic. While most previous works ignored user
mobility, there are some recent works taking it into account. However, the
duration of user contact times has been ignored, making it difficult to
explicitly characterize the effect of mobility. In this paper, we adopt the
alternating renewal process to model the duration of both the contact and
inter-contact times, and investigate how the caching performance is affected by
mobility. The data offloading ratio, i.e., the proportion of requested data
that can be delivered via D2D links, is taken as the performance metric. We
first approximate the distribution of the communication time for a given user
by beta distribution through moment matching. With this approximation, an
accurate expression of the data offloading ratio is derived. For the
homogeneous case where the average contact and inter-contact times of different
user pairs are identical, we prove that the data offloading ratio increases
with the user moving speed, assuming that the transmission rate remains the
same. Simulation results are provided to show the accuracy of the approximate
result, and also validate the effect of user mobility.


  Let $R$ be a finite commutative ring. We prove that a MacWilliams type
relation between the m-spotty weight enumerators of a linear code over $R$ and
its dual hold, if and only if, $R$ is a Frobenius (equivalently,
Quasi-Frobenius) ring, if and only if, the number of maximal ideals and minimal
ideals of $R$ are the same, if and only if, for every linear code $C$ over $R$,
the dual of the dual $C$ is $C$ itself. Also as an intermediate step, we
present a new and simpler proof for the commutative case of Wood's theorem
which states that $R$ has a generating character if and only if $R$ is a
Frobenius ring.


  In this paper, we present a new construction for strong separating hash
families by using hypergraphs and obtain some optimal separating hash families.
  We also improve some previously known bounds of separating hash families.


  The decays $D^0\to d\bar u\,e^+\nu\to a^-_0(980)\, e^+\nu\to\pi^-\eta\,
e^+\nu$ and $D^+\to d\bar d\,e^+\nu\to a^0_0(980)\, e^+\nu\to\pi^0\eta\,
e^+\nu$ (and the charge conjugated ones) is the direct probe of the two-quark
components in the $a^\pm_0(980)$ and $a^0_0(980)$ wave functions. Recent BESIII
experiment is the first step in experimental study of these decays. We present
a possible variant of $\eta\pi$ invariant mass distribution when $a_0(980)$ has
no $q\bar q$ component at all.


  We verify a conjecture of Lutwak, Yang, Zhang about the equality case in the
Orlicz-Petty projection inequality, and provide an essentially optimal
stability version.


  Hadronic spectral densities are important quantities whose non-perturbative
knowledge allows for calculating phenomenologically relevant observables, such
as inclusive hadronic cross-sections and non-leptonic decay-rates. The
extraction of spectral densities from lattice correlators is a notoriously
difficult problem because lattice simulations are performed in Euclidean time
and lattice data are unavoidably affected by statistical and systematic
uncertainties. In this paper we present a new method for extracting hadronic
spectral densities from lattice correlators. The method allows for choosing a
smearing function at the beginning of the procedure and it provides results for
the spectral densities smeared with this function together with reliable
estimates of the associated uncertainties. The same smearing function can be
used in the analysis of correlators obtained on different volumes, such that
the infinite volume limit can be studied in a consistent way. While the method
is described by using the language of lattice simulations, in reality it is
completely general and can profitably be used to cope with inverse problems
arising in different fields of research.


  The square and rectangular shape of the pixels in the digital images for
sensing and display purposes introduces several inaccuracies in the
representation of digital images. The major disadvantage of square pixel shapes
is the inability to accurately capture and display the details in the objects
having variable orientations to edges, shapes and regions. This effect can be
observed by the inaccurate representation of diagonal edges in low resolution
square pixel images. This paper explores a less investigated idea of using
variable shaped pixels for improving visual quality of image scans without
increasing the square pixel resolution. The proposed adaptive filtering
technique reports an improvement in image PSNR.


  We give a proof of the celebrated stability theorem of Perelman stating that
for a noncollapsing sequence $X_i$ of Alexandrov spaces with curvature bounded
below Gromov-Hausdorff converging to a compact Alexandrov space $X$, $X_i$ is
homeomorphic to $X$ for all large $i$.


  A quantum interference mechanism of the stripe phase instability in quasi
one-dimensional (1D) repulsive electron system is proposed. The leading
spin-charge coupling term in Landau functional is derived microscopically. It
is shown that away from half filling, periodic lattice potential causes
cooperative condensation of the spin and charge superlattices, which constitute
a 1D analogue of the experimentally observed quasi 2D structures in lanthanum
cuprates and nickelates. Renormalization group analysis qualitatively supports
the Hartree-Fock picture.


  Directional point-contact spectroscopy measurements were performed for the
first time in state-of-the-art MgB_2 single crystals. The selective suppression
of the superconductivity in the "pi" band by means of a suitable magnetic field
allowed separating the partial contribution of each band to the total
point-contact conductance. By fitting the partial conductance curves
sigma_sigma(V) and sigma_pi(V), we got an independent determination of the two
gaps, Delta_sigma and Delta_pi, with a strong reduction of the experimental
uncertainty. Their temperature dependence was found to agree well with the
predictions of the two-band models for MgB_2.


  Time-resolved terahertz quenching studies of the magnetoexcitonic
photoluminescence from GaAs/AlGaAs quantum wells are performed. A microscopic
theory is developed to analyze the experiments. Detailed experiment-theory
comparisons reveal a remarkable magnetic-field controllability of the Coulomb
and terahertz interactions in the excitonic system.


  We build upon the intriguing possibility that the recently reported nano-Hz
gravitational wave signal by Pulsar Timing Array (PTA) experiments is sourced
by a strong first-order phase transition from a nearly conformal dark sector.
The phase transition has to be strongly supercooled to explain the signal
amplitude, while the critical temperature has to be in the $\cal{O}$(GeV)
range, as dictated by the peak frequency of the gravitational wave spectrum.
However, the resulting strong supercooling exponentially dilutes away any
pre-existing baryon asymmetry and dark matter, calling for a new paradigm of
their productions. We then develop a mechanism of cold darkogenesis that
generates a dark asymmetry during the phase transition from the textured dark
$SU(2)_{\rm D}$ Higgs field. This dark asymmetry is transferred to the visible
sector via neutron portal interactions, resulting in the observed baryon
asymmetry. Furthermore, the mechanism naturally leads to the correct abundance
of asymmetric dark matter, with self-interaction of the scale that is of the
right order to solve the diversity problem in galactic rotation curves.
Collider searches for mono-jets and dark matter direct detection experiments
can dictate the viability of the model.


  Hollands and Wald's technique based on *-algebras of Wick products of field
operators is strightforwardly generalized to define the stress-energy tensor
operator in curved globally hyperbolic spacetimes. In particular, the locality
and covariance requirement is generalized to Wick products of differentiated
quantum fields. The proposed stress-energy tensor operator is conserved and
reduces to the classical form if field operators are replaced by classical
fields satisfying the equation of motion. The definition is based on the
existence of convenient counterterms given by certain local Wick products of
differentiated fields. They are independent from the arbitrary length scale
(and any quantum state) and they classically vanish on solutions of field
equation. The averaged stress-energy tensor with respect to Hadamard quantum
states can be obtained by an improved point-splitting renormalization procedure
which makes use of the nonambiguous part of the Hadamard parametrix only that
is completely determined by the local geometry and the parameters which appear
in the Klein-Gordon operator. The averaged stress-energy tensor also coincides
with that found by employing the local $\zeta$-function approach.


  This lecture, directed to an broad audience including non-specialists,
presents a short review of the problem of strong CP symmetry maintenance. The
problem is defined and the possible solutions briefly reviewed. I discuss the
way in which Roberto Peccei and I came up with one solution, generally known as
Peccei-Quinn symmetry.


  With 4.5 million hours of English speech from 10 different sources across 120
countries and models of up to 10 billion parameters, we explore the frontiers
of scale for automatic speech recognition. We propose data selection techniques
to efficiently scale training data to find the most valuable samples in massive
datasets. To efficiently scale model sizes, we leverage various optimizations
such as sparse transducer loss and model sharding. By training 1-10B parameter
universal English ASR models, we push the limits of speech recognition
performance across many domains. Furthermore, our models learn powerful speech
representations with zero and few-shot capabilities on novel domains and styles
of speech, exceeding previous results across multiple in-house and public
benchmarks. For speakers with disorders due to brain damage, our best zero-shot
and few-shot models achieve 22% and 60% relative improvement on the AphasiaBank
test set, respectively, while realizing the best performance on public social
media videos. Furthermore, the same universal model reaches equivalent
performance with 500x less in-domain data on the SPGISpeech financial-domain
dataset.


  We propose new approximate alternating projection methods, based on
randomized sketching, for the low-rank nonnegative matrix approximation
problem: find a low-rank approximation of a nonnegative matrix that is
nonnegative, but whose factors can be arbitrary. We calculate the computational
complexities of the proposed methods and evaluate their performance in
numerical experiments. The comparison with the known deterministic alternating
projection methods shows that the randomized approaches are faster and exhibit
similar convergence properties.


  We consider transformation maps on the space of states which are symmetries
in the sense of Wigner. Due to the convex nature of the space of states, the
set of these maps has a convex structure. We investigate the possibility of a
complete characterization of extreme maps of this convex body, to be able to
contribute to the classification of positive maps. Our study provides a variant
of Wigner's theorem originally proved for ray transformations in Hilbert
spaces.


  Recommender systems learn about user preferences over time, automatically
finding things of similar interest. This reduces the burden of creating
explicit queries. Recommender systems do, however, suffer from cold-start
problems where no initial information is available early on upon which to base
recommendations. Semantic knowledge structures, such as ontologies, can provide
valuable domain knowledge and user information. However, acquiring such
knowledge and keeping it up to date is not a trivial task and user interests
are particularly difficult to acquire and maintain. This paper investigates the
synergy between a web-based research paper recommender system and an ontology
containing information automatically extracted from departmental databases
available on the web. The ontology is used to address the recommender systems
cold-start problem. The recommender system addresses the ontology's
interest-acquisition problem. An empirical evaluation of this approach is
conducted and the performance of the integrated systems measured.


  Biological sequences may contain patterns that are signal important
biomolecular functions; a classical example is regulation of gene expression by
transcription factors that bind to specific patterns in genomic promoter
regions. In motif discovery we are given a set of sequences that share a common
motif and aim to identify not only the motif composition, but also the binding
sites in each sequence of the set. We present a Bayesian model that is an
extended version of the model adopted by the Gibbs motif sampler, and propose a
new centroid estimator that arises from a refined and meaningful loss function
for binding site inference. We discuss the main advantages of centroid
estimation for motif discovery, including computational convenience, and how
its principled derivation offers further insights about the posterior
distribution of binding site configurations. We also illustrate, using
simulated and real datasets, that the centroid estimator can differ from the
maximum a posteriori estimator.


  Skew density matrices can be diagonalized to yield probability
interpretation. The power-counting prediction of perturbative QCD is found
consistent with recent CEBAF data on $F_2(Q^2)/F_1(Q^2)$


  In this paper we investigate the growth rate of the number of all possible
paths in graphs with respect to their length in an exact analytical way. Apart
from the typical rates of growth, i.e. exponential or polynomial, we identify
conditions for a stretched exponential type of growth. This is made possible by
combining two or more graphs over the same alphabet, in order to obtain a
discrete dynamical system generated by a triangular map, which can also be
interpreted as a discrete non-autonomous system. Since the vertices and the
edges of a graph usually are used to depict the states and transitions between
states of a discrete dynamical system, the combination of two (or more) graphs
can be interpreted as the driving, or perturbation, of one system by another.


  An equivariantly gauge-fixed non-abelian gauge theory is a theory in which a
coset of the gauge group, not containing the maximal abelian subgroup, is gauge
fixed. Such theories are non-perturbatively well-defined. In a finite volume,
the equivariant BRST symmetry guarantees that expectation values of
gauge-invariant operators are equal to their values in the unfixed theory.
However, turning on a small breaking of this symmetry, and turning it off after
the thermodynamic limit has been taken, can in principle reveal new phases. In
this paper we use a combination of strong-coupling and mean-field techniques to
study an SU(2) Yang--Mills theory equivariantly gauge fixed to a U(1) subgroup.
We find evidence for the existence of a new phase in which two of the gluons
becomes massive while the third one stays massless, resembling the broken phase
of an SU(2) theory with an adjoint Higgs field. The difference is that here
this phase occurs in an asymptotically-free theory.


  The scientific community has been increasingly interested in harnessing the
power of deep learning to solve various domain challenges. However, despite the
effectiveness in building predictive models, fundamental challenges exist in
extracting actionable knowledge from deep neural networks due to their opaque
nature. In this work, we propose techniques for exploring the behavior of deep
learning models by injecting domain-specific actionable attributes as tunable
"knobs" in the analysis pipeline. By incorporating the domain knowledge in a
generative modeling framework, we are not only able to better understand the
behavior of these black-box models, but also provide scientists with actionable
insights that can potentially lead to fundamental discoveries.


  We study the generic NMSSM with the coupling \lambda S H_1 H_2 at the limit
of perturbativity, \lambda~0.7-0.8, and a moderate stop mass, m_{\tilde{t}} <
300 GeV. Respecting the LEP2 bounds and insisting on naturalness, we delimit
the allowed region of parameter space and we study the spectrum and
phenomenology of the relatively light new particles.


  We propose a method to protect the privacy of search engine users by
decomposing the queries using semantically \emph{related} and unrelated
\emph{distractor} terms. Instead of a single query, the search engine receives
multiple decomposed query terms. Next, we reconstruct the search results
relevant to the original query term by aggregating the search results retrieved
for the decomposed query terms. We show that the word embeddings learnt using a
distributed representation learning method can be used to find semantically
related and distractor query terms. We derive the relationship between the
\emph{obfuscity} achieved through the proposed query anonymisation method and
the \emph{reconstructability} of the original search results using the
decomposed queries. We analytically study the risk of discovering the search
engine users' information intents under the proposed query obfuscation method,
and empirically evaluate its robustness against clustering-based attacks. Our
experimental results show that the proposed method can accurately reconstruct
the search results for user queries, without compromising the privacy of the
search engine users.


  For $\Lambda$ a selfinjective algebra, and $Q$ a finite quiver without
oriented cycles, the algebra $\Lambda Q$ is a Gorenstein algebra and the
category ${\rm Gproj}\Lambda Q$ of Gorenstein-projective $\Lambda Q$-modules is
a Frobenius category. For a sink $v$ of $Q$, we define a functor $F(v) :
\underline{\rm Gproj}\Lambda Q\to \underline{\rm Gproj}\Lambda Q(v)$ between
the stable categories modulo projectives, where $Q(v)$ is obtained from $Q$ by
changing the direction of each arrow ending in $v$. The functor is given by an
explicit construction on the level of objects and homomorphisms. Our main
result states that $F(v)$ is an equivalence of categories. In the case where
the underlying graph of $Q$ is a tree, we deduce that the stable category
$\underline{\rm Gproj}\Lambda Q$ does not depend on the orientation of $Q$.
Moreover, if $Q$ is a quiver of type $\mathbb A_3$ and $\Lambda=k[T]/(T^n)$ the
bounded polynomial algebra, we use the symmetry of the octahedron in the
octahedral axiom to verify that the composition of twelve reflections yields
the identity on objects.


  One of the greatest data analysis challenges for the Laser Interferometer
Space Antenna (LISA) is the need to account for a large number of gravitational
wave signals from compact binary systems expected to be present in the data. We
introduce the basis of a Bayesian method that we believe can address this
challenge, and demonstrate its effectiveness on a simplified problem involving
one hundred synthetic sinusoidal signals in noise. We use a reversible jump
Markov chain Monte Carlo technique to infer simultaneously the number of
signals present, the parameters of each identified signal, and the noise level.
Our approach therefore tackles the detection and parameter estimation problems
simultaneously, without the need to evaluate formal model selection criteria,
such as the Akaike Information Criterion or explicit Bayes factors. The method
does not require a stopping criterion to determine the number of signals, and
produces results which compare very favorably with classical spectral
techniques.


  In this work we calculate the corrections to the amputated Green's functions
of 4-fermion operators, in 1-loop Lattice Perturbation theory. One of the novel
aspects of our calculations is that they are carried out to O(a^2) (a: lattice
spacing). We employ the Wilson/clover action for massless fermions (also
applicable for the twisted mass action in the chiral limit) and a family of
Symanzik improved actions for gluons. Our calculations have been carried out in
a general covariant gauge. Results have been obtained for several popular
choices of values for the Symanzik coefficients. While our Green's function
calculations regard any pointlike 4-fermion operators which do not mix with
lower dimension ones, we pay particular attention to DF=2 operators, both
Parity Conserving and Parity Violating (F: flavour). We compute the
perturbative renormalization constants for a complete basis of 4-fermion
operators and we study their mixing pattern. For some of the actions considered
here, even O(a^0) results did not exist in the literature to date. The
correction terms which we calculate are essential ingredients for minimizing
the lattice artifacts which are present in non-perturbative evaluations of
renormalization constants with the RI'-MOM method. Our perturbative results,
for the matrix elements of DF=2 operators and for the corresponding
renormalization matrices, depend on a large number of parameters: coupling
constant, number of colors, lattice spacing, external momentum, clover
parameter, Symanzik coefficients, gauge parameter. To make these results most
easily accessible, we have included them in the distribution package of this
paper, as an ASCII file named: 4-fermi.m; the file is best perused as
Mathematica input. The main results of this work have been applied to improve
non-perturbative estimates of the B_K-parameter in N_F=2 twisted mass lattice
QCD.


  Open-source software (OSS) plays a vital role in the modern software
ecosystem. However, the maintenance and sustainability of OSS projects can be
challenging. In this paper, we present the CrOSSD project, which aims to build
a database of OSS projects and measure their current project "health" status.
In the project, we will use both quantitative and qualitative metrics to
evaluate the health of OSS projects. The quantitative metrics will be gathered
through automated crawling of meta information such as the number of
contributors, commits and lines of code. Qualitative metrics will be gathered
for selected "critical" projects through manual analysis and automated tools,
including aspects such as sustainability, funding, community engagement and
adherence to security policies. The results of the analysis will be presented
on a user-friendly web platform, which will allow users to view the health of
individual OSS projects as well as the overall health of the OSS ecosystem.
With this approach, the CrOSSD project provides a comprehensive and up-to-date
view of the health of OSS projects, making it easier for developers,
maintainers and other stakeholders to understand the health of OSS projects and
make informed decisions about their use and maintenance.


  We study the environmental dependence of color, stellar mass, and morphology
by comparing galaxies in a forming cluster to those in the field at z = 1:6
with Hubble Space Telescope near-infrared imaging in the CANDELS/UDS field. We
quantify the morphology of the galaxies using the effective radius, reff, and
S\'ersic index, n. In both the cluster and field, approximately half of the
bulge-dominated galaxies (n > 2) reside on the red sequence of the
color-magnitude diagram, and most disk-dominated galaxies (n < 2) have colors
expected for star-forming galaxies. There is weak evidence that cluster
galaxies have redder rest-frame U - B colors and higher stellar masses compared
to the field. Star-forming galaxies in both the cluster and field show no
significant differences in their morphologies. In contrast, there is evidence
that quiescent galaxies in the cluster have larger median effective radii and
smaller S\'ersic indices compared to the field with a significance of 2?. These
differences are most pronounced for galaxies at clustercentric distances 1 Mpc
< Rproj < 1.5 Mpc, which have low S\'ersic indices and possibly larger
effective radii, more consistent with star-forming galaxies at this epoch and
in contrast to other quiescent galaxies. We argue that star-forming galaxies
are processed under the influence of the cluster environment at distances
greater than the cluster-halo virial radius. Our results are consistent with
models where gas accretion onto these galaxies is suppressed from processes
associated with the cluster environment.


  The non-Markovian depolarizing channel is explored from the perspective of
understanding its non-Markovian behaviour as well as the occurrence of
singularities. The study brings together the various ways to identify and
quantify non-Markovianity. This includes dynamical techniques such as quantum
information backflow witness, BLP, RHP and HCLA measures. In addition,
geometrical visualization of non-Markovian effects is presented using the
variation in the volume of accessible states during dynamical evolution.
Further, a trajectory-based visualization of the dynamical map, of the
depolarizing channel, within the parameter space is presented. The trajectories
traced during evolution, demonstrate the loss of CP-divisibility and the
emergence of non-Markovianity under systematic variations of the system
parameters.


  The Bose Hubbard model (BHM) is an archetypal quantum lattice system
exhibiting a quantum phase transition between its superfluid (SF) and
Mott-insulator (MI) phase. Unlike in higher dimensions the phase diagram of the
BHM in one dimension possesses regions in which increasing the hopping
amplitude can result in a transition from MI to SF and then back to a MI. This
type of re-entrance is well known in classical systems like liquid crystals yet
its origin in quantum systems is still not well understood. Moreover, this
unusual re-entrant character of the BHM is not easily captured in approximate
analytical or numerical calculations. Here we study in detail the predictions
of three different and widely used approximations; a multi-site mean-field
decoupling, a finite-sized cluster calculation, and a real-space
renormalization group (RG) approach. It is found that mean-field calculations
do not reproduce re-entrance while finite-sized clusters display a precursor to
re-entrance. Here we show for the first time that RG does capture the
re-entrant feature and constitutes one of the simplest approximation able to do
so. The differing abilities of these approaches reveals the importance of
describing short-ranged correlations relevant to the kinetic energy of a MI in
a particle-number symmetric way.


  We report on the dynamics of photodegradation and subsequent recovery of
two-photon fluorescence in a dye-doped polymer. The energy dependence suggests
that photo-degradation is a linear process while recovery is entropic. Such
recovery could be useful to high-intensity devices such as two-photon
absorbers, which can be used in many applications.


  Deep Neural Networks (DNNs) have recently led to significant improvements in
many fields. However, DNNs are vulnerable to adversarial examples which are
samples with imperceptible perturbations while dramatically misleading the
DNNs. Moreover, adversarial examples can be used to perform an attack on
various kinds of DNN based systems, even if the adversary has no access to the
underlying model. Many defense methods have been proposed, such as obfuscating
gradients of the networks or detecting adversarial examples. However it is
proved out that these defense methods are not effective or cannot resist
secondary adversarial attacks. In this paper, we point out that steganalysis
can be applied to adversarial examples detection, and propose a method to
enhance steganalysis features by estimating the probability of modifications
caused by adversarial attacks. Experimental results show that the proposed
method can accurately detect adversarial examples. Moreover, secondary
adversarial attacks cannot be directly performed to our method because our
method is not based on a neural network but based on high-dimensional
artificial features and FLD (Fisher Linear Discriminant) ensemble.


  In the present work, a combined theoretical and experimental study on
Co$_{2}$PtGa Heusler alloy shows that it exhibits a martensite transition
around 1320 K with a small thermal hysteresis (10 K). Dynamical stability of
Co$_2$PtGa in the tetragonal phase has been established by the theoretically
calculated phonon dispersion curves. Magnetization measurements suggest that
this alloy is a ferromagnetic material with a saturation magnetic moment of
2.83 $\mu_B$/f.u. at 2 K, which is in excellent agreement with the value
obtained from \textit{ab-initio} calculations (2.87 $\mu_B$/f.u.). Our present
study demonstrates that Co$_{2}$PtGa is a promising material for high
temperature magnetic shape memory application.


  Using $1/N_C$ expansion and dispersion theory techniques, without relying on
any explicit resonance lagrangian, we generalize the KSRF relation beyond the
leading chiral order. Two sum rules for the low energy constants $L_2$, $L_3$
and a new relation between resonance couplings are derived. A rather detailed
examination to the new relation is also given.


  This paper presents Nana-HDR, a new non-attentive non-autoregressive model
with hybrid Transformer-based Dense-fuse encoder and RNN-based decoder for TTS.
It mainly consists of three parts: Firstly, a novel Dense-fuse encoder with
dense connections between basic Transformer blocks for coarse feature fusion
and a multi-head attention layer for fine feature fusion. Secondly, a
single-layer non-autoregressive RNN-based decoder. Thirdly, a duration
predictor instead of an attention model that connects the above hybrid encoder
and decoder. Experiments indicate that Nana-HDR gives full play to the
advantages of each component, such as strong text encoding ability of
Transformer-based encoder, stateful decoding without being bothered by exposure
bias and local information preference, and stable alignment provided by
duration predictor. Due to these advantages, Nana-HDR achieves competitive
performance in naturalness and robustness on two Mandarin corpora.


  We consider a lattice equation (Salerno model) combining onsite self-focusing
and intersite self-defocusing cubic terms, which may describe a Bose-Einstein
condensate of dipolar atoms trapped in a strong periodic potential. In the
continuum approximation, the model gives rise to solitons in a finite band of
frequencies, with sechlike solitons near one edge, and an exact peakon solution
at the other. A similar family of solitons is found in the discrete system,
including a peakon; beyond the peakon, the family continues in the form of
cuspons. Stability of the lattice solitons is explored through computation of
eigenvalues for small perturbations, and by direct simulations. A small part of
the family is unstable (in that case, the discrete solitons transform into
robust pulsonic excitations); both peakons and cuspons are stable. The
Vakhitov-Kolokolov criterion precisely explains the stability of regular
solitons and peakons, but does not apply to cuspons. In-phase and out-of-phase
bound states of solitons are also constructed. They exchange their stability at
a point where the bound solitons are peakons. Mobile solitons, composed of a
moving core and background, exist up to a critical value of the strength of the
self-defocusing intersite nonlinearity. Colliding solitons always merge into a
single pulse.


  Visibility of singlet-triplet qubit readout is reduced to almost zero in
large magnetic field gradients due to relaxation processes. Here we present a
new readout technique that is robust against relaxation and allows for
measurement when previously studied methods fail. This technique maps the qubit
onto spin states that are immune to relaxation using a spin dependent electron
tunneling process between the qubit and the lead. We probe this readout's
performance as a function of magnetic field gradient and applied magnetic
field, and optimize the pulse applied to the qubit through experiment and
simulation.


  Optical proximity correction (OPC) is a widely-used resolution enhancement
technique (RET) for printability optimization. Recently, rigorous numerical
optimization and fast machine learning are the research focus of OPC in both
academia and industry, each of which complements the other in terms of
robustness or efficiency. We inspect the pattern distribution on a design layer
and find that different sub-regions have different pattern complexity. Besides,
we also find that many patterns repetitively appear in the design layout, and
these patterns may possibly share optimized masks. We exploit these properties
and propose a self-adaptive OPC framework to improve efficiency. Firstly we
choose different OPC solvers adaptively for patterns of different complexity
from an extensible solver pool to reach a speed/accuracy co-optimization. Apart
from that, we prove the feasibility of reusing optimized masks for repeated
patterns and hence, build a graph-based dynamic pattern library reusing stored
masks to further speed up the OPC flow. Experimental results show that our
framework achieves substantial improvement in both performance and efficiency.


  The Bost-Connes Hecke C^*-algebra can be regarded as a direct limit of
subalgebras involving finite sets of primes. Each of these finite-prime
analogues of the Bost-Connes algebra is a crossed product by a semigroup N^F,
where F is finite. We describe composition series of ideals for these semigroup
crossed products in which the intermediate subquotients are finite direct sums
of classifiable AT-algebras. We then use similar techniques to identify
subquotients of the Bost-Connes algebra as classifiable AT-algebras.


  We report recent results and developments from our ongoing lattice studies of
$\mathcal N = 4$ supersymmetric Yang--Mills theory. These include a proof that
only a single fine-tuning needs to be performed, so long as the moduli space is
not lifted by nonperturbative effects. We extend our investigations of
supersymmetry restoration in the continuum limit by initiating Monte Carlo
renormalization group studies. We present additional numerical evidence that
the lattice theory does not suffer from a sign problem. Finally we study the
static potential, which we find to be Coulombic at both weak and strong
coupling. We compare the static potential Coulomb coefficients to perturbation
theory, including initial results for N=3 colors in addition to N=2.


  We introduce a class of graphs with coloured edges to encode subsystems of
the classical root systems, which in particular classify them up to
equivalence. We further use the graphs to describe root-kernel intersections,
as well as restrictions of root (sub)systems on such intersections,
generalising the regular part of a Cartan subalgebra. We also consider a slight
variation to encode the hyperplane arrangements only, showing there is a unique
noncrystallographic arrangement that arises. Finally, a variation of the main
definition leads to elementary classifications of closed and Levi root
subsystems.


  The past entropy is considered as an uncertainty measure for the past
lifetime distribution. Generating function approach to entropy become popular
in recent time as it generate several well-known entropy measures. In this
paper, we introduce the past entropy-generating function. We study certain
properties of this measure. It is shown that the past entropy-generating
function uniquely determines the distribution. Further, we present
characterizations for some lifetime models using the relationship between
reliability concepts and the past entropy-generating function.