  Currency is used almost everywhere to facilitate business. In most developing
countries, especially the ones in Africa, tangible notes are predominantly used
in everyday financial transactions. One of these countries, Ethiopia, is
believed to have one of the world highest rates of blindness (1.6%) and low
vision (3.7%). There are around 4 million visually impaired people; With 1.7
million people being in complete vision loss. Those people face a number of
challenges when they are in a bus station, in shopping centers, or anywhere
which requires the physical exchange of money. In this paper, we try to provide
a solution to this issue using AI/ML applications. We developed an Android and
IOS compatible mobile application with a model that achieved 98.9%
classification accuracy on our dataset. The application has a voice integrated
feature that tells the type of the scanned currency in Amharic, the working
language of Ethiopia. The application is developed to be easily accessible by
its users. It is build to reduce the burden of visually impaired people in
Ethiopia.


  The initial results of a millimeter (CO) survey of infrared-excess,
optically-selected quasars from the Palomar-Green (PG) Bright Quasar Survey
(BQS) with redshifts in the range 0.04 < z < 0.17 are presented. These
observations represent the first step towards establishing with a complete
sample whether or not quasi-stellar objects (QSOs) reside in molecular gas-rich
galaxies, as well as towards determining how the infrared and molecular gas
properties of QSOs compare with those of ultraluminous infrared galaxies
(ULIGs), which are a possible evolutionary precursor of QSOs. The sample
consists of QSOs having absolute blue magnitudes, M_B <~ -22.0, and infrared
excesses, L_IR (8-1000 um) /L_bbb (0.1-1.0 um) >0.36, where the contribution to
the bolometric luminosity of infrared thermal dust emission for all PG QSOs is
typically 20--40%. Six out of 10 of the QSOs observed are detected in the
CO(1-0) emission line; two detections confirm previous, less sensitive
detections of CO(1-0) in PG 1613+658 and PG 0838+770, and four additional QSOs
are detected for the first time (PG 1119+120, PG 1351+640, PG 1415+451, and PG
1440+356). These six detections, plus two previous detections of CO in IZw1 and
Mrk 1014, bring the total number of 0.04 < z < 0.17 infrared-excess PG QSOs
detected in CO to date to eight, and provide possible evidence that, in
addition to fueling star formation, molecular gas may also serve as a primary
source of fuel for QSO activity...


  A large number of sensors deployed in recent years in various setups and
their data is readily available in dedicated databases or in the cloud. Of
particular interest is real-time data processing and 3D visualization in
web-based user interfaces that facilitate spatial information understanding and
sharing, hence helping the decision making process for all the parties
involved. In this research, we provide a prototype system for near real-time,
continuous X3D-based visualization of processed sensor data for two significant
applications: thermal monitoring for residential/commercial buildings and
nitrogen cycle monitoring in water beds for aquaponics systems. As sensors are
sparsely placed, in each application, where they collect data for large periods
(of up to one year), we employ a Finite Differences Method and a Neural
Networks model to approximate data distribution in the entire volume.


  We prove that energy minimizing Yang-Mills connections on a compact
$G_{2}$-manifold has holonomy equal to $G_{2}$ are $G_{2}$-instantons, subject
to an extra condition on the curvature. Furthermore, we show that energy
minimizing connections on a compact Calabi-Yau $3$-fold has holonomy equal to
$SU(3)$ subject to a similar condition are holomorphic.


  Spontaneous photon emission in the Continuous Spontaneous Localization (CSL)
model is studied one more time. In the CSL model each particle interacts with a
noise field that induces the collapse of its wave function. As a consequence of
this interaction, when the particle is electrically charged, it radiates. As
discussed in [1], the formula for the emission rate, to first perturbative
order, contains two terms: One is proportional to the Fourier component of the
noise field at the same frequency as that of the emitted photon and one is
proportional to the zero Fourier component of the noise field. As discussed in
previous works, this second term seems unphysical. In [1], it was shown that
the unphysical term disappears when the noises is confined to a bounded region
and the final particle's state is a wave packet. Here we investigate the origin
of the unphysical term and why it vanishes according to the previous
prescription. For this purpose, the electrodynamic part of the equation of
motion is solved exactly while the part due to the noise is treated
perturbatively. We show that the unphysical term is connected to exponentially
decaying function of time which dies out in the large time limit, however,
approximates to 1 in the first perturbative order in the electromagnetic field.


  Based on chiral ring relations and anomalies, as described by Cachazo,
Douglas, Seiberg and Witten, we argue that the holomorphic effective action in
N=2 Yang-Mills theory can be understood as an integrated U(1) anomaly from a
purely field theory point of view. In particular, we show that the periods of
the Riemann surface arising from the generalized Konishi anomaly can be given a
physical interpretation without referring to special geometry. We also discuss
consequences for the multi-instanton calculus in N=2 Yang-Mills theory.


  Results of the most sophisticated measurements in coincidence of the angular
resolved K-shell photo- and Auger-electrons, and of two atomic ions produced by
dissociation of N2 molecule, are analyzed. Detection of photoelectrons at
certain angles allows separating the Auger decay processes of the 1{\sigma}g
and 1{\sigma}u core hole states. The Auger electron angular distributions for
each of these hole states are measured as a function of the kinetic energy
release of two atomic ions and are compared with the corresponding theoretical
angular distributions. From that comparison one can disentangle the
contributions of different repulsive doubly charged molecular ion states to the
Auger decay. Different kinetic energy release values are directly related to
the different internuclear distances. In this way one can trace experimentally
the behavior of the potential energy curves of dicationic final states inside
the Frank-Condon region. Presentation of the Auger electron angular
distributions as a function of kinetic energy release of two atomic ions opens
a new dimension in the study of Auger decay.


  A new formulation of MOND as a modified-potential theory of gravity is
propounded. In effect, the theory dictates that the MOND potential phi produced
by a mass distribution rho is a solution of the Poisson equation for the
modified source density rho*=-(1/4 pi G)divergence(g), where g=nu(|gN|/a0)gN,
and gN is the Newtonian acceleration field of rho. This makes phi simply the
scalar potential of the algebraic acceleration field g. The theory thus
involves solving only linear differential equations, with one nonlinear,
algebraic step. It is derivable from an action, satisfies all the usual
conservation laws, and gives the correct center-of-mass acceleration to
composite bodies. The theory is akin in some respects to the nonlinear Poisson
formulation of Bekenstein and Milgrom, but it is different from it, and is
obviously easier to apply. The two theories are shown to emerge as natural
modifications of a Palatini-type formulation of Newtonian gravity, and are
members in a larger class of bi-potential theories.


  Universal low-energy properties are studied for three identical bosons
confined in two dimensions. The short-range pair-wise interaction in the
low-energy limit is described by means of the boundary condition model. The
wave function is expanded in a set of eigenfunctions on the hypersphere and the
system of hyper-radial equations is used to obtain analytical and numerical
results. Within the framework of this method, exact analytical expressions are
derived for the eigenpotentials and the coupling terms of hyper-radial
equations. The derivation of the coupling terms is generally applicable to a
variety of three-body problems provided the interaction is described by the
boundary condition model. The asymptotic form of the total wave function at a
small and a large hyper-radius $\rho$ is studied and the universal logarithmic
dependence $\sim \ln^3 \rho$ in the vicinity of the triple-collision point is
derived. Precise three-body binding energies and the $2 + 1$ scattering length
are calculated.


  The equilibration of a finite Bose system is modelled using a gradient
expansion of the collision integral that leads to a nonlinear transport
equation. For constant transport coefficients, it is solved in closed form
through a nonlinear transformation. Using schematic initial conditions, the
exact solution and the equilibration time are derived and compared to the
corresponding case for fermions. Applications to the equilibration of the gluon
system created initially in relativistic heavy-ion collisions, and to cold
quantum gases are envisaged.


  Semantic communication is envisioned as a promising technique to break
through the Shannon limit. However, semantic inference and semantic error
correction have not been well studied. Moreover, error correction methods of
existing semantic communication frameworks are inexplicable and inflexible,
which limits the achievable performance. In this paper, to tackle this issue, a
knowledge graph is exploited to develop semantic communication systems. Two
cognitive semantic communication frameworks are proposed for the single-user
and multiple-user communication scenarios. Moreover, a simple, general, and
interpretable semantic alignment algorithm for semantic information detection
is proposed. Furthermore, an effective semantic correction algorithm is
proposed by mining the inference rule from the knowledge graph. Additionally,
the pre-trained model is fine-tuned to recover semantic information. For the
multi-user cognitive semantic communication system, a message recovery
algorithm is proposed to distinguish messages of different users by matching
the knowledge level between the source and the destination. Extensive
simulation results conducted on a public dataset demonstrate that our proposed
single-user and multi-user cognitive semantic communication systems are
superior to benchmark communication systems in terms of the data compression
rate and communication reliability. Finally, we present realistic single-user
and multi-user cognitive semantic communication systems results by building a
software-defined radio prototype system.


  Mobile learning (m-Learning) is considered to be one of the fastest growing
learning platforms. The immense interest in m-Learning is attributed to the
incredible rate of growth of mobile technology and its proliferation into every
aspect of modern life. Despite this, m-Learning has not experienced a similar
adoption rate in the education sector, chiefly higher education. Researchers
have attempted to explain this anomaly by conducting several studies in the
area. However, mostly the research in m-Learning is examined from the
perspective of the students and educators. In this research, it is contended
that there is a third important stakeholder group whose opinion is equally
important in determining the success of m-Learning: the university management.
Although diversified by nature, heads of departments, deans, and IT system
administrators are nevertheless considered members of any university
management. The results of the research show that university commitment to
m-Learning, university learning practices, and change management practices were
the factors critical to the success of m-Learning, from the university
management perspective.


  A new method of solving the Einstein-Friedmann dynamical equations of a
spatially homogeneous and isotropic universe is presented. The method is
applicable when the equation of state of the material content assumes the form
P=(g -1) rho, g = constant. The solution for the expansion factor is commonly
given only for g = 0, 1 and 4/3 when the curvature index K is 1 or -1. The
proposed procedure is valid for general g and K and it allows for ease of
derivation of the solutions. This alternative method is useful pedagogically to
introduce basic cosmology.


  An instance of the maximum mixed graph orientation problem consists of a
mixed graph and a collection of source-target vertex pairs. The objective is to
orient the undirected edges of the graph so as to maximize the number of pairs
that admit a directed source-target path. This problem has recently arisen in
the study of biological networks, and it also has applications in communication
networks.
  In this paper, we identify an interesting local-to-global orientation
property. This property enables us to modify the best known algorithms for
maximum mixed graph orientation and some of its special structured instances,
due to Elberfeld et al. (CPM '11), and obtain improved approximation ratios. We
further proceed by developing an algorithm that achieves an even better
approximation guarantee for the general setting of the problem. Finally, we
study several well-motivated variants of this orientation problem.


  Intermetallic compounds Zr7Ni10 and Hf7Ni10 have been studied by perturbed
angular correlation (PAC) spectroscopy considering the fact that Zr7Ni10 has
application as hydrogen storage material in fuel cell. In stoichiometric
Zr7Ni10, the phase Zr2Ni7 is found to be dominant (~38%) while a fraction of
~25% is found for the Zr7Ni10 phase at room temperature. In this compound, a
phase due to Zr8Ni21 (~10%) is found from room temperature up to 773 K but,
this is not found at 873 K and above. In the stoichiometric Hf7Ni10 sample, the
phase due to Hf7Ni10 is found as a minor phase (~22%) at room temperature. In
this system, no phase of Hf2Ni7 is observed but, a different phase due to HfNi3
is found to be dominant (~62%). It is found that the site fraction of Hf7Ni10
enhances with temperature at the expense of HfNi3 and this phase becomes
predominant (~57%) at 673 K and above. The change of phase fractions of HfNi3
and Hf7Ni10 with temperature is found to be reversible. The phase components in
Zr7Ni10 and Hf7Ni10 have been determined also from X-ray powder diffraction
(XRD) and transmission electron microscopy/selected area electron diffraction
(TEM/SAED) measurements. Ab-initio calculations using the all electron full
potential (linearized) augmented plane wave [FP-(L)APW] method, within the
framework of the density functional theory (DFT), have been performed to
determine the electric field gradients at the 181Ta impurity sites and
therefrom to assign the different components observed from PAC measurements.
Present experimental and calculated results of EFG support the Cmca space group
for both Zr7Ni10 and Hf7Ni10 compounds.


  Gastrointestinal diseases pose significant healthcare chall-enges as they
manifest in diverse ways and can lead to potential complications. Ensuring
precise and timely classification of these diseases is pivotal in guiding
treatment choices and enhancing patient outcomes. This paper introduces a novel
approach on classifying gastrointestinal diseases by leveraging cost-sensitive
pre-trained deep convolutional neural network (CNN) architectures with
supervised contrastive learning. Our approach enables the network to learn
representations that capture vital disease-related features, while also
considering the relationships of similarity between samples. To tackle the
challenges posed by imbalanced datasets and the cost-sensitive nature of
misclassification errors in healthcare, we incorporate cost-sensitive learning.
By assigning distinct costs to misclassifications based on the disease class,
we prioritize accurate classification of critical conditions. Furthermore, we
enhance the interpretability of our model by integrating gradient-based
techniques from explainable artificial intelligence (AI). This inclusion
provides valuable insights into the decision-making process of the network,
aiding in understanding the features that contribute to disease classification.
To assess the effectiveness of our proposed approach, we perform extensive
experiments on a comprehensive gastrointestinal disease dataset, such as the
Hyper-Kvasir dataset. Through thorough comparisons with existing works, we
demonstrate the strong classification accuracy, robustness and interpretability
of our model. We have made the implementation of our proposed approach publicly
available at
https://github.com/dibya404/Gastrointestinal-Disease-Classification-through-Explainable-and-Cost-Sensitive-DNN-with-SCL


  Merging supermassive black hole binaries produce low-frequency gravitational
waves, which pulsar timing experiments are searching for. Much of the current
theory is developed within the plane-wave formalism, and here we develop the
more general Fresnel formalism. We show that Fresnel corrections to
gravitational wave timing residual models allow novel measurements to be made,
such as direct measurements of the source distance from the timing residual
phase and frequency, as well as direct measurements of chirp mass from a
monochromatic source. Probing the Fresnel corrections in these models will
require future pulsar timing arrays with more distant pulsars across our Galaxy
(ideally at the distance of the Magellanic Clouds), timed with precisions less
than $100$ ns, with distance uncertainties reduced to the order of the
gravitational wavelength. We find that sources with chirp mass of order $10^9 \
\mathrm{M}_\odot$ and orbital frequency $\omega_0 > 10$ nHz are good candidates
for probing Fresnel corrections. With these conditions met, the measured source
distance uncertainty can be made less than 10 per cent of the distance to the
source for sources out to $\sim 100$ Mpc, source sky localization can be
reduced to sub-arcminute precision, and source volume localization can be made
to less than $1 \ \text{Mpc}^3$ for sources out to 1-Gpc distances.


  One can geometrically engineer supersymmetric field theories theories by
placing D-branes at or near singularities. The opposite process is described,
where one can reconstruct the singularities from quiver theories. The
description is in terms of a noncommutative quiver algebra which is constructed
from the quiver diagram and the superpotential. The center of this
noncommutative algebra is a commutative algebra, which is the ring of
holomorphic functions on a variety V. If certain algebraic conditions are met,
then the reverse geometric engineering produces V as the geometry that D-branes
probe. It is also argued that the identification of V is invariant under
Seiberg dualities.


  We present LM-GAN, an HDR sky model that generates photorealistic environment
maps with weathered skies. Our sky model retains the flexibility of traditional
parametric models and enables the reproduction of photorealistic all-weather
skies with visual diversity in cloud formations. This is achieved with flexible
and intuitive user controls for parameters, including sun position, sky color,
and atmospheric turbidity.
  Our method is trained directly from inputs fitted to real HDR skies, learning
both to preserve the input's illumination and correlate it to the real
reference's atmospheric components in an end-to-end manner. Our main
contributions are a generative model trained on both sky appearance and scene
rendering losses, as well as a novel sky-parameter fitting algorithm. We
demonstrate that our fitting algorithm surpasses existing approaches in both
accuracy and sky fidelity, and also provide quantitative and qualitative
analyses, demonstrating LM-GAN's ability to match parametric input to
photorealistic all-weather skies. The generated HDR environment maps are ready
to use in 3D rendering engines and can be applied to a wide range of
image-based lighting applications.


  The Thermodynamic Non-Equilibrium (TNE) effects in the coalescing process of
two initially static bubbles under thermal conditions are investigated by a
Discrete Boltzmann Model (DBM). The spatial distributions of the typical
none-quilibrium quantity, i.e., the Non-Organized Momentum Fluxes (NOMF) during
evolutions are investigated in detail. The density-weighted statistical method
is used to highlight the relationship between the TNE effects and the
morphological or kinetics characteristics of bubble coalescence. It is found
that the $xx$-component and $yy$-component of NOMF are anti-symmetrical; the
$xy$-component changes from an anti-symmetric internal and external double
quadrupole structure to an outer octupole structure during the coalescing
process. More importantly, the evolution of the averaged $xx$-component of NOMF
provides two characteristic instants, which divide the non-equilibrium process
into three stages. The first instant corresponds to the moment when the mean
coalescing speed gets the maximum and at this time the ratio of minor and major
axes is about $1/2$. The second instant corresponds to the moment when the
ratio of minor and major axes gets $1$ for the first time. It is interesting to
find that the three quantities, TNE intensity, acceleration of coalescence and
negative slope of boundary length, show a high degree of correlation and attain
their maxima simultaneously. Surface tension and heat conduction accelerate the
process of bubble coalescence while viscosity delays it. Both surface tension
and viscosity enhance the global non-equilibrium intensity, whereas heat
conduction restrains it. These TNE features and findings present some new
insights into the kinetics of bubble coalescence.


  The maximally symmetric D-branes of string theory on the non-simply connected
Lie group SU(n)/Z_d are analysed using conformal field theory methods, and
their charges are determined. Unlike the well understood case for simply
connected groups, the charge equations do not determine the charges uniquely,
and the charge group associated to these D-branes is therefore in general not
cyclic. The precise structure of the charge group depends on some number
theoretic properties of n, d, and the level of the underlying affine algebra k.
The examples of SO(3)=SU(2)/Z_2 and SU(3)/Z_3 are worked out in detail, and the
charge groups for SU(n)/Z_d at most levels k are determined explicitly.


  Combustion vehicle emissions contribute to poor air quality and release
greenhouse gases into the atmosphere, and vehicle pollution has been associated
with numerous adverse health effects. Roadways with extensive waiting and/or
passenger drop off, such as schools and hospital drop-off zones, can result in
high incidence and density of idling vehicles. This can produce micro-climates
of increased vehicle pollution. Thus, the detection of idling vehicles can be
helpful in monitoring and responding to unnecessary idling and be integrated
into real-time or off-line systems to address the resulting pollution. In this
paper we present a real-time, dynamic vehicle idling detection algorithm. The
proposed idle detection algorithm and notification rely on an algorithm to
detect these idling vehicles. The proposed method relies on a multi-sensor,
audio-visual, machine-learning workflow to detect idling vehicles visually
under three conditions: moving, static with the engine on, and static with the
engine off. The visual vehicle motion detector is built in the first stage, and
then a contrastive-learning-based latent space is trained for classifying
static vehicle engine sound. We test our system in real-time at a hospital
drop-off point in Salt Lake City. This in-situ dataset was collected and
annotated, and it includes vehicles of varying models and types. The
experiments show that the method can detect engine switching on or off
instantly and achieves 71.02 average precision (AP) for idle detections and
91.06 for engine off detections.


  Green and Tao famously proved in a 2008 paper that there are arithmetic
progressions of prime numbers of arbitrary lengths. Soon after, analogous
statements were proved by Tao for the ring of Gaussian integers and by L\^e for
the polynomial rings over finite fields. In 2020 this was extented to orders of
arbitrary number fields by Kai-Mimura-Munemasa-Seki-Yoshino. We settle the case
of the coordinate rings of affine curves over finite fields. The main
contribution of this paper is subtle choice of a polynomial subring of the
given ring which plays the role of $\mathbb Z$ in the number field case. This
choice and the proof of its pleasant properties eventually depend on the
Riemann-Roch formula.


  Reaction networks are often used to model interacting species in fields such
as biochemistry and ecology. When the counts of the species are sufficiently
large, the dynamics of their concentrations are typically modeled via a system
of differential equations. However, when the counts of some species are small,
the dynamics of the counts are typically modeled stochastically via a discrete
state, continuous time Markov chain.
  A key quantity of interest for such models is the probability mass function
of the process at some fixed time. Since paths of such models are relatively
straightforward to simulate, we can estimate the probabilities by constructing
an empirical distribution. However, the support of the distribution is often
diffuse across a high-dimensional state space, where the dimension is equal to
the number of species. Therefore generating an accurate empirical distribution
can come with a large computational cost.
  We present a new Monte Carlo estimator that fundamentally improves on the
"classical" Monte Carlo estimator described above. It also preserves much of
classical Monte Carlo's simplicity. The idea is basically one of conditional
Monte Carlo. Our conditional Monte Carlo estimator has two parameters, and
their choice critically affects the performance of the algorithm. Hence, a key
contribution of the present work is that we demonstrate how to approximate
optimal values for these parameters in an efficient manner. Moreover, we
provide a central limit theorem for our estimator, which leads to approximate
confidence intervals for its error.


  Do diffusive non-Markovian stochastic Schr\"odinger equations (SSEs) for open
quantum systems have a physical interpretation? In a recent paper [Phys. Rev. A
66, 012108 (2002)] we investigated this question using the orthodox
interpretation of quantum mechanics. We found that the solution of a
non-Markovian SSE represents the state the system would be in at that time if a
measurement was performed on the environment at that time, and yielded a
particular result. However, the linking of solutions at different times to make
a trajectory is, we concluded, a fiction. In this paper we investigate this
question using the modal (hidden variable) interpretation of quantum mechanics.
We find that the noise function $z(t)$ appearing in the non-Markovian SSE can
be interpreted as a hidden variable for the environment. That is, some chosen
property (beable) of the environment has a definite value $z(t)$ even in the
absence of measurement on the environment. The non-Markovian SSE gives the
evolution of the state of the system ``conditioned'' on this environment hidden
variable. We present the theory for diffusive non-Markovian SSEs that have as
their Markovian limit SSEs corresponding to homodyne and heterodyne detection,
as well as one which has no Markovian limit.


  Identifying directions where extreme events occur is a major challenge in
multivariate extreme value analysis. In this paper, we use the concept of
sparse regular variation introduced by Meyer and Wintenberger (2021)} to infer
the tail dependence of a random vector X. This approach relies on the Euclidean
projection onto the simplex which better exhibits the sparsity structure of the
tail of X than the standard methods. Our procedure based on a rigorous
methodology aims at capturing clusters of extremal coordinates of X. It also
includes the identification of the threshold above which the values taken by X
are considered as extreme. We provide an efficient and scalable algorithm
called MUSCLE and apply it on numerical examples to highlight the relevance of
our findings. Finally we illustrate our approach with financial return data.


  The increase in discovered close binary central stars of planetary nebulae is
leading to a sufficiently large sample to begin to make broader conclusions
about the effect of close binary stars on common envelope evolution and
planetary nebula formation. Herein I review some of the recent results and
conclusions specifically relating close binary central stars to nebular
shaping, common envelope evolution off the red giant branch, and the total
binary fraction and double degenerate fraction of central stars. Finally, I use
parameters of known binary central stars to explore the relationship between
the proto-planetary nebula and planetary nebula stages, demonstrating that the
known proto-planetary nebulae are not the precursors of planetary nebulae with
close binary central~stars.


  Suicide is recognized as one of the most serious concerns in the modern
society. Suicide causes tragedy that affects countries, communities, and
families. There are many factors that lead to suicidal ideations. Early
detection of suicidal ideations can help to prevent suicide occurrence by
providing the victim with the required professional support, especially when
the victim does not recognize the danger of having suicidal ideations. As
technology usage has increased, people share and express their ideations
digitally via social media, chatbots, and other digital platforms. In this
paper, we proposed a novel, simple deep learning-based model to detect suicidal
ideations in digital content, mainly focusing on chatbots as the primary data
source. In addition, we provide a framework that employs the proposed suicide
detection integration with a chatbot-based support system.


  Random walks are basic diffusion processes on networks and have applications
in, for example, searching, navigation, ranking, and community detection.
Recent recognition of the importance of temporal aspects on networks spurred
studies of random walks on temporal networks. Here we theoretically study two
types of event-driven random walks on a stochastic temporal network model that
produces arbitrary distributions of interevent-times. In the so-called active
random walk, the interevent-time is reinitialized on all links upon each
movement of the walker. In the so-called passive random walk, the
interevent-time is only reinitialized on the link that has been used last time,
and it is a type of correlated random walk. We find that the steady state is
always the uniform density for the passive random walk. In contrast, for the
active random walk, it increases or decreases with the node's degree depending
on the distribution of interevent-times. The mean recurrence time of a node is
inversely proportional to the degree for both active and passive random walks.
Furthermore, the mean recurrence time does or does not depend on the
distribution of interevent-times for the active and passive random walks,
respectively.


  Let $S$ be a set of $n$ sites in the plane, so that every site $s \in S$ has
an associated radius $r_s > 0$. Let $\mathcal{D}(S)$ be the disk intersection
graph defined by $S$, i.e., the graph with vertex set $S$ and an edge between
two distinct sites $s, t \in S$ if and only if the disks with centers $s$, $t$
and radii $r_s$, $r_t$ intersect.Our goal is to design data structures that
maintain the connectivity structure of $\mathcal{D}(S)$ as sites are inserted
and/or deleted in $S$.


  The problem of the flux to a spherical trap in one and three dimensions, for
diffusing particles undergoing discrete-time jumps with a given radial
probability distribution, is solved in general, verifying the Smoluchowski-like
solution in which the effective trap radius is reduced by an amount
proportional to the jump length. This reduction in the effective trap radius
corresponds to the Milne extrapolation length.


  I present a set of long-term, direct, relativistic many-body computations of
model dense stellar clusters with up-to-date stellar-evolutionary, supernova
(SN), and remnant natal-kick models, including pair instability and pulsation
pair instability supernova (PSN and PPSN), using an updated version of NBODY7
N-body simulation program. The N-body model also includes stellar
evolution-based natal spins of BHs and treatments of binary black hole (BBH)
mergers based on numerical relativity. These, for the first time in a direct
N-body simulation, allow for second-generation BBH mergers. The set of 65
evolutionary models have initial masses $10^4M_\odot-10^5M_\odot$, sizes 1 pc-3
pc, metallicity $0.0001-0.02$, with the massive stars in primordial binaries
and they represent young massive clusters (YMC) and moderately massive open
clusters (OC). Such models produce dynamically-paired BBH mergers that agree
well with the observed masses, mass ratios, effective spin parameters, and
final spins of the LVC O1/O2 merger events, provided BHs are born with low or
no spin but spin up after undergoing a BBH merger or matter accretion onto it.
In particular, the distinctly higher mass, effective spin parameter, and final
spin of GW170729 merger event is naturally reproduced, as also the mass
asymmetry of the O3 event GW190412. The computed models produce massive,
$\sim100M_\odot$ BBH mergers with primary mass within the 'PSN gap' and also
yield mergers involving remnants in the 'mass gap'. They also suggest that YMCs
and OCs produce persistent, Local-Universe GW sources detectable by LISA. Such
clusters are also capable of producing eccentric LIGO-Virgo mergers.


  An observer at rest in a uniformly accelerated reference frame experiences a
parallel gravitational field, where the rays of light are formed as circular
arcs instead of being straight lines. We deduce how a sphere at rest in the
Rindler frame, and a freely falling sphere, will appear to an observer at rest
in the frame.


  We propose an efficient quantum repeater architecture with mesoscopic atomic
ensembles, where the Rydberg blockade is employed for deterministic local
entanglement generation, entanglement swapping and entanglement purification.
Compared with conventional atomic-ensemble-based quantum repeater, the
entanglement distribution rate is improved by up to two orders of magnitude
with the help of the deterministic Rydberg gate. This new quantum repeater
scheme is robust and fast, and thus opens up a new way for practical
long-distance quantum communication.


  The search of high-order periodic orbits has been typically restricted to
problems with symmetries that help to reduce the dimension of the search space.
Well-known examples include reversible maps with symmetry lines. The present
work proposes a new method to compute high-order periodic orbits in twist maps
without the use of symmetries. The method is a combination of the
parameterization method in Fourier space and a Newton-Gauss multiple shooting
scheme. The parameterization method has been successfully used in the past to
compute quasi-periodic invariant circles. However, this is the first time that
this method is used in the context of periodic orbits. Numerical examples are
presented showing the accuracy and efficiency of the proposed method. The
method is also applied to verify the renormalization prediction of the
residues' convergence at criticality (extensively studied in reversible maps)
in the relatively unexplored case of maps without symmetries.


  In this paper, we explore the possibility of detecting polar lows in C-band
SAR images by means of deep learning. Specifically, we introduce a novel
dataset consisting of Sentinel-1 images divided into two classes, representing
the presence and absence of a maritime mesocyclone, respectively. The dataset
is constructed using the ERA5 dataset as baseline and it consists of 2004
annotated images. To our knowledge, this is the first dataset of its kind to be
publicly released. The dataset is used to train a deep learning model to
classify the labeled images. Evaluated on an independent test set, the model
yields an F-1 score of 0.95, indicating that polar lows can be consistently
detected from SAR images. Interpretability techniques applied to the deep
learning model reveal that atmospheric fronts and cyclonic eyes are key
features in the classification. Moreover, experimental results show that the
model is accurate even if: (i) such features are significantly cropped due to
the limited swath width of the SAR, (ii) the features are partly covered by sea
ice and (iii) land is covering significant parts of the images. By evaluating
the model performance on multiple input image resolutions (pixel sizes of 500m,
1km and 2km), it is found that higher resolution yield the best performance.
This emphasises the potential of using high resolution sensors like SAR for
detecting polar lows, as compared to conventionally used sensors such as
scatterometers.


  Data storytelling (DS) is rapidly gaining attention as an approach that
integrates data, visuals, and narratives to create data stories that can help a
particular audience to comprehend the key messages underscored by the data with
enhanced efficiency and effectiveness. It has been posited that DS can be
especially advantageous for audiences with limited visualisation literacy, by
presenting the data clearly and concisely. However, empirical studies
confirming whether data stories indeed provide these benefits over conventional
data visualisations are scarce. To bridge this gap, we conducted a study with
103 participants to determine whether DS indeed improve both efficiency and
effectiveness in tasks related to information retrieval and insights
comprehension. Our findings suggest that data stories do improve the efficiency
of comprehension tasks, as well as the effectiveness of comprehension tasks
that involve a single insight compared with conventional visualisations.
Interestingly, these benefits were not associated with participants'
visualisation literacy.


  The locations of supernovae in the local stellar and gaseous environment in
galaxies contain important clues to their progenitor stars. Access to this
information, however, has been hampered by the limited resolution achieved by
ground-based observations. High spatial resolution Hubble Space Telescope (HST)
images of galaxy fields in which supernovae had been observed can improve the
situation considerably. We have examined the immediate environments of a few
dozen supernovae using archival post-refurbishment HST images. Although our
analysis is limited due to signal-to-noise ratio and filter bandpass
considerations, the images allow us for the first time to resolve individual
stars in, and to derive detailed color-magnitude diagrams for, several
environments. We are able to place more rigorous constraints on the masses of
these supernovae. A search was made for late-time emission from supernovae in
the archival images, and for the progenitor stars in presupernova images of the
host galaxies. We have detected SN 1986J in NGC 891 and, possibly, SN 1981K in
NGC 4258. We have also identified the progenitor of the Type IIn SN 1997bs in
NGC 3627. By removing younger resolved stars in the environments of SNe Ia, we
can measure the colors of the unresolved stellar background and attribute these
colors generally to an older, redder population. HST images ``accidentally''
caught the Type Ia SN 1994D in NGC 4526 shortly after its outburst; we measure
its brightness. Finally, we add to the statistical inferences that can be made
from studying the association of SNe with recent star-forming regions.


  Firstly we prove that the Voronoi formula of Miller-Schmid type applies to
automorphic forms on GL(3) for the congruence subgroup $\Gamma_0(N)$, when the
conductor of the additive character in the formula is a multiple of $N$. As an
application, we produce a result about the functional equation of $L$-function
of the automorphic form on GL(3) twisted by Dirichlet characters. Secondly we
prove that a similar formula applies to automorphic forms on GL(3) for the
congruence subgroup $\Gamma_0(N)$, when the conductor of the additive character
in the formula is coprime with $N$.


  Neural Network movement controllers promise a variety of advantages over
conventional control methods, however, they are not widely adopted due to their
inability to produce reliably precise movements. This research explores a
bilateral neural network architecture as a control system for motor tasks. We
aimed to achieve hemispheric specialisation similar to what is observed in
humans across different tasks; the dominant system (usually the right hand,
left hemisphere) excels at tasks involving coordination and efficiency of
movement, and the non-dominant system performs better at tasks requiring
positional stability. Specialisation was achieved by training the hemispheres
with different loss functions tailored to the expected behaviour of the
respective hemispheres. We compared bilateral models with and without
specialised hemispheres, with and without inter-hemispheric connectivity
(representing the biological Corpus Callosum), and unilateral models with and
without specialisation. The models were trained and tested on two tasks common
in the human motor control literature: the random reach task, suited to the
dominant system, a model with better coordination, and the hold position task,
suited to the non-dominant system, a model with more stable movement. Each
system outperformed the non-preferred system in its preferred task. For both
tasks, a bilateral model outperformed the non-preferred hand and was as good or
better than the preferred hand. The results suggest that the hemispheres could
collaborate on tasks or work independently to their strengths. This study
provides ideas for how a biologically inspired bilateral architecture could be
exploited for industrial motor control.


  The quantum entanglement for the two electrons in the excited states of the
helium-like atom/ions is investigated using the two-electron wave functions
constructed by the B-spline basis. As a measure of the spatial
(electron-electron orbital) entanglement, the von Neumann entropy and linear
entropy of the reduced density matrix are calculated for the 1s2s 1,3S excited
states for systems with some selected Z values from Z=2 to Z=100. Results for
the helium atom are compared with other available calculations. We have also
investigated the entropies for these excited states when the nucleus charge is
reduced from Z=2 to Z=1. At such a critical charge, all the singly-excited
states of this system become unbound, and the linear entropies and the von
Neumann entropies for the excited states are approaching 1/2 and 1,
respectively, the limits for the entropies when one electron is bound to the
nucleus, and the other being free.


  We prove in some cases a formula for the Greenberg-Benois
$\mathcal{L}$-invariant of the spin, standard and adjoint Galois
representations associated with Siegel-Hilbert modular forms. In order to
simplify the calculation, we give a new definition of the
$\mathcal{L}$-invariant for a Galois representation $V$ of a number field
$F\neq \mathbb{Q}$; we also check that it is compatible with Benois' definition
for $\mathrm{Ind}_F^{\mathbb{Q}}(V)$.


  Social networks represent nowadays in many contexts the main source of
information transmission and the way opinions and actions are influenced. For
instance, generic advertisements are way less powerful than suggestions from
our contacts. However, this process hugely depends on the influence of people
who disseminate these suggestions. Therefore modern marketing often involves
paying some targeted users, or influencers, for advertising products or ideas.
Finding the set of nodes in a social network that lead to the highest
information spread -- the so-called Influence Maximization (IM) problem -- is
therefore a pressing question and as such it has recently attracted a great
research interest. In particular, several approaches based on Evolutionary
Algorithms (EAs) have been proposed, although they are known to scale poorly
with the graph size. In this paper, we tackle this limitation in two ways.
Firstly, we use approximate fitness functions to speed up the EA. Secondly, we
include into the EA various graph-aware mechanisms, such as smart
initialization, custom mutations and node filtering, to facilitate the EA
convergence. Our experiments show that the proposed modifications allow to
obtain a relevant runtime gain and also improve, in some cases, the spread
results.


  We consider the one-dimensional nonlinear Klein-Gordon equation with a double
power focusing-defocusing nonlinearity
  \begin{equation*}
  \partial_{t}^{2}u-\partial_{x}^{2}u+u-|u|^{p-1}u+|u|^{q-1}u=0,\quad
\mbox{on}\ [0,\infty)\times \mathbb{R},
  \end{equation*}
  with $1<q<p<\infty$. The main result states the stability in the energy space
$H^{1}(\mathbb{R})\times L^{2}(\mathbb{R})$ of the sums of decoupled solitary
waves with different speeds, up to the natural instabilities. The proof is
inspired by the techniques developed for the generalized Korteweg-de Vries
equation and the nonlinear Schr\"odinger equation in a similar context by
Martel, Merle and Tsai [14,15]. However, the adaptation of this strategy to a
wave-type equation requires the introduction of a new energy functional adapted
to the Lorentz transform.


  We show that any normal toric variety over a rank one valuation ring admits
an equivariant open embedding in a normal toric variety which is proper over
the valuation ring, after a base-change by a finite extension of valuation
rings. If the value group $\Gamma$ is discrete or divisible then no base-change
is needed. We give explicit examples which show that existing methods do not
produce such normal equivariant completions. Our approach is combinatorial and
proceeds by showing that $\Gamma$-admissible fans admit $\Gamma$-admissible
completions. In order to show this we prove a combinatorial analog of
noetherian reduction which we believe will be of independent interest.


  We revisit the problem of computing the boundary density profile of a droplet
of two-dimensional one-component plasma (2D OCP) with logarithmic interaction
between particles in a confining harmonic potential. At a sufficiently low
temperature but still in the liquid phase, the density exhibits oscillations as
a function of the distance to the boundary of the droplet. We obtain the
density profile numerically using Monte-Carlo simulations of the 2D OCP. We
argue that the decay and period of those oscillations can be explained within a
picture of the Wigner crystallization near the boundary, where the crystal is
gradually melted with the increasing distance to the boundary.


  In order to establish whether the unstable r-modes in a rotating neutron star
provide a detectable source of gravitational waves, we need to understand the
details of the many dissipative processes that tend to counteract the
instability. It has been established that the bulk viscosity due to exotic
particles, like hyperons, may be particularly important in this respect.
However, the effects of hyperon superfluidity have so far not been fully
accounted for. While the associated suppression of the reaction rates that give
rise to the bulk viscosity has been estimated, superfluid aspects of the fluid
dynamics have not been considered. In this paper we determine the r-mode
instability window for a neutron star with a $\Sigma^{-}$ hyperon core, using
the appropriate multifluid formalism including, for the first time, the effect
of the "superfluid" bulk viscosity coefficients. We demonstrate that, even
though the extra terms may increase the bulk viscosity damping somewhat, their
presence does not affect the qualitative features of the r-mode instability
window.


  From the open boundary t-J model, an impurity model is constructed in which
magnetic impurities of arbitrary spins are coupled to the edges of the strongly
correlated electron system. The boundary R matrices are given explicitly. The
interaction parameters between magnetic impurities and electrons are related to
the potentials of the impurities to preserve the integrability of the system.
The Hamiltonian of the impurity model is diagonalized exactly. The integral
equations of the ground state are derived and the ground state properties are
discussed in details. We discuss also the string solutions of the Bethe ansatz
equations, which describe the bound states of the charges and spins. By
minimizing the thermodynamic potential we get the thermodynamic Bethe ansatz
equations. The finite size correction of the free energy contributed by the
magnetic impurities is obtained explicitly. The properties of the system at
some special limits are discussed and the boundary bound states are obtained.


  Black phosphorus (bP) is a crystalline material that can be seen as ordered
stackings of two-dimensional layers, which lead to outstanding anisotropic
physical properties. The knowledge of its pressure-temperature (P-T) phase
diagram, and in particular, the slope and location of its melting curve is
fundamental for better understanding the synthesis and stability conditions of
this important material. Despite several experimental studies, important
uncertainties remain in the determination of this melting curve. Here we report
accurate melting points measurements, using in situ high-temperature and
high-pressure high-resolution synchrotron x-ray diffraction. In particular, we
have employed an original and accurate pressure and temperature metrology based
on the unique anisotropic P-T response of bP, that we used as sensor for the
simultaneous determination of pressure and temperature up to 5 GPa and 1700 K.
We confirmed the existence of and located a solid-liquid-liquid triple point at
the intersection of the low- and high-pressure melting curves. Finally, we have
characterized the irreversibility of the transformation in the low-pressure
regime below 1 GPa, as the low-density liquid does not crystallize back to bP
but into red phosphorus on temperature quenching.


  We present an exploration of weak lensing by large-scale structure in the
linear regime, using the third-year (T0003) CFHTLS Wide data release. Our
results place tight constraints on the scaling of the amplitude of the matter
power spectrum sigma_8 with the matter density Omega_m. Spanning 57 square
degrees to i'_AB = 24.5 over three independent fields, the unprecedented
contiguous area of this survey permits high signal-to-noise measurements of
two-point shear statistics from 1 arcmin to 4 degrees. Understanding systematic
errors in our analysis is vital in interpreting the results. We therefore
demonstrate the percent-level accuracy of our method using STEP simulations, an
E/B-mode decomposition of the data, and the star-galaxy cross correlation
function. We also present a thorough analysis of the galaxy redshift
distribution using redshift data from the CFHTLS T0003 Deep fields that probe
the same spatial regions as the Wide fields. We find sigma_8(Omega_m/0.25)^0.64
= 0.785+-0.043 using the aperture-mass statistic for the full range of angular
scales for an assumed flat cosmology, in excellent agreement with WMAP3
constraints. The largest physical scale probed by our analysis is 85 Mpc,
assuming a mean redshift of lenses of 0.5 and a LCDM cosmology. This allows for
the first time to constrain cosmology using only cosmic shear measurements in
the linear regime. Using only angular scales theta> 85 arcmin, we find
sigma_8(Omega_m/0.25)_lin^0.53 = 0.837+-0.084, which agree with the results
from our full analysis. Combining our results with data from WMAP3, we find
Omega_m=0.248+-0.019 and sigma_8 = 0.771+-0.029.


  Particle production by slow-changing gravitational fields is usually
described using quantum field theory in curved spacetime. Calculations require
a definition of the vacuum state, which can be given using the adiabatic (WKB)
approximation. I investigate the best attainable precision of the resulting
approximate definition of the particle number. The standard WKB ansatz yields a
divergent asymptotic series in the adiabatic parameter. I derive a novel
formula for the optimal number of terms in that series and demonstrate that the
error of the optimally truncated WKB series is exponentially small. This
precision is still insufficient to describe particle production from vacuum,
which is typically also exponentially small. An adequately precise
approximation can be found by improving the WKB ansatz through perturbation
theory. I show quantitatively that the fundamentally unavoidable imprecision in
the definition of particle number in a time-dependent background is equal to
the particle production expected to occur during that epoch. The results are
illustrated by analytic and numerical examples.


  A number of computer vision tasks exploit a succinct representation of the
visual content in the form of sets of local features. Given an input image,
feature extraction algorithms identify a set of keypoints and assign to each of
them a description vector, based on the characteristics of the visual content
surrounding the interest point. Several tasks might require local features to
be extracted from a video sequence, on a frame-by-frame basis. Although
temporal downsampling has been proven to be an effective solution for mobile
augmented reality and visual search, high temporal resolution is a key
requirement for time-critical applications such as object tracking, event
recognition, pedestrian detection, surveillance. In recent years, more and more
computationally efficient visual feature detectors and decriptors have been
proposed. Nonetheless, such approaches are tailored to still images. In this
paper we propose a fast keypoint detection algorithm for video sequences, that
exploits the temporal coherence of the sequence of keypoints. According to the
proposed method, each frame is preprocessed so as to identify the parts of the
input frame for which keypoint detection and description need to be performed.
Our experiments show that it is possible to achieve a reduction in
computational time of up to 40%, without significantly affecting the task
accuracy.


  High-resolution single crystal neutron diffraction measurements are presented
probing the magnetostructural response to uniaxial pressure in the iron
pnictide parent system BaFe2As2. Scattering data reveal a strain-activated,
anisotropic broadening of nuclear Bragg reflections, which increases upon
cooling below the resolvable onset of global orthorhombicity. This anisotropy
in lattice coherence continues to diverge until a lower temperature scale---the
first-order onset of antiferromagnetism---is reached. Our data suggest that
antiferromagnetism and strong magnetoelastic coupling drive the
strain-activated lattice response in this material and that the development of
anisotropic lattice coherence under strain is the physical origin for the
anomalous nematic anisotropy in this compound.


  We report the first detection of the ISW effect in wavelet space, at scales
in the sky around 7 degrees with a significance of around 3.3 sigma, by
cross-correlating the WMAP first-year data and the NRAO VLA Sky Survey (NVSS).
In addition, we present a detailed comparison among the capabilities of three
different techniques for two different objectives: to detect the ISW and to put
constraints in the nature of the dark energy. The three studied techniques are:
the cross-angular power spectrum (CAPS, harmonic space), the correlation
function (CCF, real space) and the covariance of the Spherical Mexican Hat
Wavelet (SMHW) coefficients (CSMHW, wavelet space). We prove that the CSMHW is
expected to provide a higher detection of the ISW effect for a certain scale.
This prediction has been corroborated by the analysis of the data. The SMHW
analysis shows that the cross-correlation signal is caused neither by
systematic effects nor foreground contamination. However, by taking into
account the information encoded in all the multipoles/scales/angles, the CAPS
provides slightly better constraints than the SMHW in the cosmological
parameters that define the nature of the dark energy. The limits provided by
the CCF are wider than for the other two methods. Two different cases have been
studied: 1) a flat Lambda-CDM universe and 2) a flat universe with an equation
of state parameter different from -1. In the first case, the CAPS provides (for
a bias value of b = 1.6) 0.59 < Lambda density < 0.84 (at 1 sigma CL).
Moreover, the CAPS rejects the range Lambda density < 0.1 at 3.5 sigma, which
is the highest detection of the dark energy reported up to date. In the second
case, the CAPS gives 0.50 < dark energy density < 0.82 and -1.16 < w < 0.43 (at
1 sigma CL).


  In arithmetic and algebraic geometry, superspecial (s.sp.\ for short) curves
are one of the most important objects to be studied, with applications to
cryptography and coding theory. If $g \geq 4$, it is not even known whether
there exists such a curve of genus $g$ in general characteristic $p > 0$, and
in the case of $g=4$, several computational approaches to search for those
curves have been proposed. In the genus-$4$ hyperelliptic case, Kudo-Harashita
proposed a generic algorithm to enumerate all s.sp.\ curves, and recently
Ohashi-Kudo-Harashita presented an algorithm specific to the case where
automorphism group contains the Klein 4-group. In this paper, we propose an
algorithm with complexity $\tilde{O}(p^4)$ in theory but $\tilde{O}(p^3)$ in
practice to enumerate s.sp.\ hyperelliptic curves of genus 4 with automorphism
group containing the cyclic group of order $6$. By executing the algorithm over
Magma, we enumerate those curves for $p$ up to $1000$. We also succeeded in
finding a s.sp.\ hyperelliptic curve of genus $4$ in every $p$ with $p \equiv 2
\pmod{3}$. As a theoretical result, we classify hyperelliptic curves of genus
$4$ in terms of automorphism groups in the appendix.


  We derive formulas to compute mean number of worms in a newly Helminth
infected population before secondary infections are started (population is
closed). We have proved the two types of growth functions arise in this process
as measurable functions.


  In this short paper, I introduce an elementary method for exactly evaluating
the definite integrals $\, \int_0^{\pi}{\ln{(\sin{\theta})}\,d\theta}$,
$\int_0^{\pi/2}{\ln{(\sin{\theta})}\,d\theta}$,
$\int_0^{\pi/2}{\ln{(\cos{\theta})}\,d\theta}$, and
$\int_0^{\pi/2}{\ln{(\tan{\theta})}\,d\theta} \,$ in finite terms. The method
consists in to manipulate the sums obtained from the logarithm of certain
products of trigonometric functions at rational multiples of $\pi$, putting
them in the form of Riemann sums. As this method does not involve any search
for primitives, it represents a good alternative to more involved integration
techniques. As a bonus, I show how to apply the method for easily evaluating
$\,\int_0^1{\ln{\Gamma(x)} \, d x}$.


  We propose that a specific spatial configuration of lattice sites that
energetically favor {\it 3+} or {\it 4+} Mn ions in moderately doped manganites
constitutes approximately a spatially random two-energy-level system. Such an
effect results in a mechanism of metal-insulator transitions that appears to be
different from both the Anderson transition and the Mott-Hubbard transition.
Correspondingly, a disordered Kondo lattice model is put forward, whose
dynamical mean-field solution agrees reasonably with experiments.


  We studied roles of the magnetic field on the gas dynamics in the Galactic
bulge by a three-dimensional global magnetohydrodynamical simulation data,
particularly focusing on vertical flows that are ubiquitously excited by
magnetic activity. In local regions where the magnetic filed is stronger, it is
frequently seen that fast down-flows slide along inclined magnetic field lines
that are associated with buoyantly rising magnetic loops. The vertical velocity
of these down-flows reaches ~ 100 km s$^{-1}$ near the foot-point of the loops
by the gravitational acceleration toward the Galactic plane. The two footpoints
of rising magnetic loops are generally located at different radial locations
and the field lines are deformed by the differential rotation. The angular
momentum is transported along the field lines, and the radial force balance
breaks down. As a result, a fast downflow is often observed only at the one
footpoint located at the inner radial position. The fast downflow compresses
the gas to form a dense region near the footpoint, which will be important in
star formation afterward. Furthermore, the horizontal components of the
velocity are also fast near the foot-point because the down-flow is accelerated
along the magnetic sliding slope. As a result, the high-velocity flow creates
various characteristic features in a simulated position-velocity diagram,
depending on the viewing angle.


  Rotating domain wall based sensors that have recently been developed are
based on a segmented looping geometry. In order to determine the crucial
pinning of domain walls in this special geometry, we investigate the depinning
under different angles of an applied magnetic field and obtain the angular
dependence of the depinning field of the domain walls. Due to the geometry, the
depinning field not only exhibits a 180$^\circ$-periodicity but a more complex
dependence on the angle. The depinning field depends on two different angles
associated with the initial state and the segmented geometry of the corner. We
find that depending on the angle of the applied field two different switching
processes occur and we can reproduce the angular dependence using a simple
model calculation.


  We report the fabrication and characterization of an alternative design for a
superconducting quantum interference proximity transistor (SQUIPT) based on a
normal metal (N) probe. The absence of direct Josephson coupling between the
proximized metal nanowire and the N probe allows us to observe the full
modulation of the wire density of states around zero voltage and current
\textit{via} the application of an external magnetic field. This results into a
drastic suppression of power dissipation which can be as low as a few $\sim
10^{-17}$ W. In this context the interferometer allows an improvement of up to
four orders of magnitude with respect to earlier SQUIPT designs, and makes it
ideal for extra-low power cryogenic applications. In addition, the N-SQUIPT has
been recently predicted to be the enabling candidate for the implementation of
coherent caloritronic devices based on proximity effect.


  In this paper, we propose an improved version of an agglomerative
hierarchical clustering algorithm that performs disjoint community detection in
large-scale complex networks. The improved algorithm is achieved after
replacing the local structural similarity used in the original algorithm, with
the recently proposed Dynamic Structural Similarity. Additionally, the improved
algorithm is extended to detect fuzzy and crisp overlapping community
structure. The extended algorithm leverages the disjoint community structure
generated by itself and the dynamic structural similarity measures, to compute
a proposed membership probability function that defines the fuzzy communities.
Moreover, an experimental evaluation is performed on reference benchmark graphs
in order to compare the proposed algorithms with the state-of-the-art.


  We analyze the probabilistic variance of a solution of Liouville's equation
for curvature, given suitable bounds on the Gaussian curvature. The related
systolic geometry was recently studied by Horowitz, Katz, and Katz, where we
obtained a strengthening of Loewner's torus inequality containing a "defect
term", similar to Bonnesen's strengthening of the isoperimetric inequality.
Here the analogous isosystolic defect term depends on the metric and "measures"
its deviation from being flat. Namely, the defect is the variance of the
function f which appears as the conformal factor expressing the metric on the
torus as f^2(x,y)(dx^2+dy^2), in terms of the flat unit-area metric in its
conformal class. A key tool turns out to be the computational formula for
probabilistic variance, which is a kind of a sharpened version of the
Cauchy-Schwartz inequality.


  Optimization algorithms and large language models (LLMs) enhance
decision-making in dynamic environments by integrating artificial intelligence
with traditional techniques. LLMs, with extensive domain knowledge, facilitate
intelligent modeling and strategic decision-making in optimization, while
optimization algorithms refine LLM architectures and output quality. This
synergy offers novel approaches for advancing general AI, addressing both the
computational challenges of complex problems and the application of LLMs in
practical scenarios. This review outlines the progress and potential of
combining LLMs with optimization algorithms, providing insights for future
research directions.


  We present a neutron spin echo study (NSE) of the nanosecond dynamics of
polyethylene glycol (PEG) functionalised nanosized gold particles dissolved in
D$_2$O at two temperatures and two different PEG molecular weights. The
analysis of the NSE data was performed by applying a Bayesian approach to the
description of time correlation function decays in terms of exponential terms,
recently proved to be theoretically rigorous. This approach, which addresses in
a direct way the fundamental issue of model choice in any dynamical analysis,
provides here a guide to the most statistically supported way to follow the
decay of the Intermediate Scattering Functions I(Q, t) by basing on statistical
grounds the choice of the number of terms required for the description of the
nanosecond dynamics of the studied systems. Then, the presented analysis avoids
from the start resorting to a pre-selected framework and can be considered as
model free. By comparing the results of PEG coated nanoparticles with those
obtained in PEG2000 solutions, we were able to disentangle the translational
diffusion of the nanoparticles from the internal dynamics of the polymer
grafted to them, and to show that the polymer corona relaxation follows a pure
exponential decay in agreement with the behavior predicted by coarse grained
molecular dynamics simulations and theoretical models. This methodology has one
further advantage: in the presence of a complex dynamical scenario I(Q,t) is
often described in terms of the Kohlrausch-Williams-Watts function that can
implicitly represent a distribution of relaxation times. By choosing to
describe the I(Q,t) as a sum of exponential functions and with the support of
the Bayesian approach, we can explicitly determine when a finer-structure
analysis of the dynamical complexity of the system exists according to the
available data without the risk of overparametrisation.


  The structure of an interior dipole magnetic field of neutron stars in $f(R)$
gravity is considered. For this purpose, the perturbative approaches are used
when both the deviations from general relativity and the deformations of
spherically symmetric configurations associated with the presence of the
magnetic field are assumed to be small. Solutions are constructed which
describe relativistic, spherically symmetric configurations consisting of a
gravitating magnetized perfect fluid modeled by a realistic equation of state.
Comparing configurations from general relativity and modified gravity, we
reveal possible differences in the structure of the magnetic field which occur
in considering neutron stars in modified gravity.


  It is well-known, that for separation of variables in the eigenvalue problem,
the corresponding operator should be represented as a sum of operators
depending on single variables. In the case of the Fokker--Planck equations, the
separation of variables is possible under essentially weaker conditions.


  Logic program transformation by the unfold/fold method ad- vocates the
writing of correct logic programs via the application of some rules to a naive
program. This work focuses on how to overcome subgoal- introduction
difficulties in synthesizing efficient sorting algorithms from an naive sorting
algorithm, through logic program transformation and abductive reasoning.


  Gravitational lensing in a modified gravity (MOG) is derived and shown to
describe lensing without postulating dark matter. The recent data for merging
clusters identified with the interacting cluster 1E0657-56 is shown to be
consistent with a weak lensing construction based on MOG without exotic dark
matter.


  We develop a theory of macroscopic resonant tunneling of flux in a
double-well potential in the presence of realistic flux noise with significant
low-frequency component. The rate of incoherent flux tunneling between the
wells exhibits resonant peaks, the shape and position of which reflect
qualitative features of the noise, and can thus serve as a diagnostic tool for
studying the low-frequency flux noise in SQUID qubits. We show, in particular,
that the noise-induced renormalization of the first resonant peak provides
direct information on the temperature of the noise source and the strength of
its quantum component.


  A modified generalized Chaplygin gas (MGCG) is considered as the unified dark
matter-dark energy revisited. The character of MGCG is endued with the dual
role, which behaves as matter at early times and as an quiessence dark energy
at late times. The equation of state for MGCG is
$p=-\alpha\rho/(1+\alpha)-\vartheta(z)\rho^{-\alpha}/(1+\alpha) $, where
$\vartheta(z)=-[\rho_{0c}(1+z)^{3}]^{(1+\alpha)}(1-\Omega_{0B})^{\alpha}\{\alpha\Omega_{0DM}+
\Omega_{0DE}[\omega_{DE}+\alpha(1+\omega_{DE})](1+z)^{3\omega_{DE}(1+\alpha)}\}$.
Some cosmological quantities, such as the densities of different components of
the universe $\Omega_{i}$ ($i$ respectively denotes baryons, dark matter and
dark energy) and the deceleration parameter $q$, are obtained. The present
deceleration parameter $q_{0}$, the transition redshift $z_{T}$ and the
redshift $z_{eq}$, which describes the epoch when the densities in dark matter
and dark energy are equal, are also calculated. To distinguish MGCG from
others, we then apply the Statefinder diagnostic. Later on, the parameters
($\alpha$ and $\omega_{DE}$) of MGCG are constrained by combination of the
sound speed $c^{2}_{s}$, the age of the universe $t_{0}$, the growth factor $m$
and the bias parameter $b$. It yields
$\alpha=-3.07^{+5.66}_{-4.98}\times10^{-2}$ and
$\omega_{DE}=-1.05^{+0.06}_{-0.11}$. Through the analysis of the growth of
density perturbations for MGCG, it is found that the energy will transfer from
dark matter to dark energy which reach equal at $z_{eq}\sim 0.48$ and the
density fluctuations start deviating from the linear behavior at $z\sim 0.25$
caused by the dominance of dark energy.


  At nanohertz frequencies gravitational waves (GWs) cause variations in
time-of-arrival of pulsar signals potentially measurable via precision timing
observations. Here we compute very-low-frequency GW sensitivity constrained by
instrumental, propagation, and other noises fundamentally limiting pulsar
timing observations. Reaching expected GW signal strengths will require
estimation and removal of $\simeq$99% of time-of-arrival fluctuations caused by
typical interstellar plasma turbulence and a reduction of white rms timing
noise to $\sim$100 nsec or less. If these were achieved, single-pulsar
signal-to-noise ratio (SNR) = 1 sensitivity is then limited by the best current
terrestrial time standards at $h_{rms} \sim$2 $\times 10^{-16}$ [f/(1
cycle/year)]$^{-1/2}$ for $f < 3 \times 10^{-8}$ Hz, where f is Fourier
frequency and a bandwidth of 1 cycle/(10 years) is assumed. This sensitivity
envelope may be optimistic in that it assumes negligible intrinsic pulsar
rotational noise, perfect time transfer from time standard to observatory, and
stable pulse profiles. Nonetheless it can be compared to predicted signal
levels for a broadband astrophysical GW background from supermassive black hole
binaries. Such a background is comparable to timekeeping-noise only for
frequencies lower than about 1 cycle/(10 years), indicating that reliable
detections will require substantial improvements in signal-to-noise ratio
through pulsar array signal processing.


  We consider discrete-time Markov chains and study large deviations of the
pair empirical occupation measure, which is useful to compute fluctuations of
pure-additive and jump-type observables. We provide an exact expression for the
finite-time moment generating function, which is split in cycles and paths
contributions, and scaled cumulant generating function of the pair empirical
occupation measure via a graph-combinatorial approach. The expression obtained
allows us to give a physical interpretation of interaction and entropic terms,
and of the Lagrange multipliers, and may serve as a starting point for
sub-leading asymptotics. We illustrate the use of the method for a simple
two-state Markov chain.


  We have observed that a rotating liquid soap film generates electricity when
placed between two non-contact electrodes with a sufficiently large potential
difference. In our experiments suspended liquid film (water + soap film) is
formed on the surface of a circular frame, which is forced to rotate in the
$x-y$ horizontal plane by a motor. This system is located at the center of two
capacitor-like vertical plates to apply an external electric voltage difference
in the $x-$direction. The produced electric current is collected from the
liquid film using two conducting electrodes that are separated in the
$y-$direction. We previously reported that a liquid film in an external
electric field rotates when an electric current passes through it, naming it
the liquid film motor (LFM). In this paper we report a novel technique, in
which a similar device can be used as an electric generator, converting the
rotating mechanical energy to electrical energy. The liquid film electric
generator (LFEG) is in stark contrast to the LFM, both of which could be
designed similarly in very small scales like micro scales with different
applications. Although the device is comparable to commercial electric motors
or electric generators, there is a significant difference in their working
principles. Usually in an electric motor or generator the magnetic field causes
the driving force, while in a LFM or LFEG the Coulomb force is the driving
force. This fact is also interesting from the Bio-science point of view and
brings a similarity to bio motors. Here we have investigated the electrical
characteristics of such a generator for the first time experimentally and
modelled the phenomenon with electroconvection governing equations. A numerical
simulation is performed using the local approximation for the charge-potential
relation and results are in qualitative agreement with experiments.


  In weakly nonlinear systems, the main effect of cubic nonlinearity on wave
propagation is an amplitude-dependent correction of the dispersion relation.
This phenomenon can manifest either as a frequency shift or as a wavenumber
shift depending on whether the excitation is prescribed as a initial condition
or as a boundary condition, respectively. Several models have been proposed to
capture the frequency shifts observed when the system is subjected to harmonic
initial excitations. However, these models are not compatible with harmonic
boundary excitations, which represent the conditions encountered in most
practical applications. To overcome this limitation, we present a multiple
scales framework to analytically capture the wavenumber shift experienced by
dispersion relation of nonlinear monatomic chains under harmonic boundary
excitations. We demonstrate that the wavenumber shifts result in an unusual
dispersion correction effect, which we term wavenumber-space band clipping. We
then extend the framework to locally-resonant periodic structures to explore
the implications of this phenomenon on bandgap tunability. We show that the
tuning capability is available if the cubic nonlinearity is deployed in the
internal springs supporting the resonators.


  Planet formation is sensitive to the conditions in protoplanetary disks, for
which scaling laws as a function of stellar mass are known. We aim to test
whether the observed population of planets around low-mass stars can be
explained by these trends, or if separate formation channels are needed.
  We address this question by confronting a state-of-the-art planet population
synthesis model with a sample of planets around M dwarfs observed by the HARPS
and CARMENES radial velocity (RV) surveys. To account for detection biases, we
performed injection and retrieval experiments on the actual RV data to produce
synthetic observations of planets that we simulated following the core
accretion paradigm.
  These simulations robustly yield the previously reported high occurrence of
rocky planets around M dwarfs and generally agree with their planetary mass
function. In contrast, our simulations cannot reproduce a population of giant
planets around stars less massive than 0.5 solar masses. This potentially
indicates an alternative formation channel for giant planets around the least
massive stars that cannot be explained with current core accretion theories. We
further find a stellar mass dependency in the detection rate of short-period
planets. A lack of close-in planets around the earlier-type stars ($M_\star
\gtrsim 0.4\, M_\odot$) in our sample remains unexplained by our model and
indicates dissimilar planet migration barriers in disks of different spectral
subtypes.
  Both discrepancies can be attributed to gaps in our understanding of planet
migration in nascent M dwarf systems. They underline the different conditions
around young stars of different spectral subtypes, and the importance of taking
these differences into account when studying planet formation.


  A novel and readily understandable derivation of the Golden Rule of time
dependent perturbation theory is presented. The derivation is based on
adiabatic turning on of the perturbation as used, for instance, in some formal
developments of scattering theory. Energy conservation is expressed in terms of
an intuitively and physically appealing Lorentzian line shape rather than the
artificial, oscillatory sin(x)=x type line shape that appears in conventional
derivations. The conditions for the derivation's validity are compactly and
conveniently expressed in the frequency/energy domain rather than in the usual
time domain. The derivation also highlights how, along with energy
conservation, the transition rate faithfully and instantaneously follows the
variations in the square of the perturbing potential as one may expect in the
adiabatic limit. In the first instance, the adiabatic turning on is achieved,
as usual, by a single exponential time variation. But we demonstrate that the
instantaneous following of the square of the perturbing potential by the
transition rate is more general and that one can derive the Golden Rule for a
general slowly varying time dependent perturbation. This allows one to derive
generalisations of the simple decay law, originally derived in the classic
paper by Weisskopf and Wigner; a tutorial exposition of the essence of this
classic work is provided. The Oppenheimer method for applying the Golden rule
to problems, such as the electric field ionisation of atoms, in which the
perturbing potential can also create the final states, is reviewed. No use of
an energy gap condition is needed to derive our results on adiabatic behaviour
in contrast to the origianl derivations of the adiabatic theorem in quantum
mechanics.


  The fundamentals of near infrared spectroscopy (NIRS) are reviewed. Among the
major factors controlling the cerebral blood flow (CBF), the effect of PaCO2 is
peculiar in that it violates autoregulatory CBF mechanisms and allows to
explore the full range of the CBF. A simple physical model, with a four
parameter formula, relating the CBF to PaCO2 is presented. It can be used to
transform the fits of one animal to the fits of another one. It enable the use
of rats data as monkeys data simply by rescaling the PaCO2 values and the CBF
data. Controlled breathing can change the PaCO2. Experiments on human subjects
relating the PaCO2 to rSO2, measured with brain oximeters, are presented. A
simple model relating the mean blood pressure to CBF is worked out.


  Although stars accrete mass throughout the first few Myr of their lives, the
physical mechanism that drives disk accretion in the T Tauri phase is
uncertain, and diagnostics that probe the nature of disk accretion have been
elusive, particularly in the planet formation region of the disk. Here we
explore whether an accretion process such as the magnetorotational instability
could be detected through its "heat signature", the energy it deposits in the
disk atmosphere. To examine this possibility, we investigate the impact of
accretion-related mechanical heating and energetic stellar irradiation (FUV and
X-rays) on the thermal-chemical properties of disk atmospheres at planet
formation distances. We find that stellar FUV irradiation (Lyman alpha and
continuum), through its role in heating and photodissociation, affects much of
the upper warm (400-2000 K) molecular layer of the atmosphere, and the
properties of the layer are generally in good agreement with the observed
molecular emission features of disks at UV, near-infrared, and mid-infrared
wavelengths. At the same time, the effect of FUV irradiation is restricted to
the upper molecular layer of the disk, even when irradiation by Ly alpha is
included. The region immediately below the FUV-heated layer is potentially
dominated by accretion-related mechanical heating. As cooler (90-400 K) CO,
water, and other molecules are potential diagnostics of the mechanically-heated
layer, emission line studies of these diagnostics might be used to search for
evidence of the magnetorotational instability in action.


  In this paper, we introduce a complete family of parametrized
quasi-probability distributions in phase space and their corresponding Weyl
quantization maps with the aim to generalize the recently developed Wigner-Weyl
formalism within the Loop Quantum Cosmology program (LQC). In particular, we
intend to define those quasi-distributions for states valued on the Bohr
compactification of the real line in such a way that they are labeled by a
parameter that accounts for the ordering ambiguity corresponding to
non-commutative quantum operators. Hence, we notice that the projections of the
parametrized quasi-probability distributions result in marginal probability
densities which are invariant under any ordering prescription. We also note
that, in opposition to the standard Schr\"odinger representation, for an
arbitrary character the quasi-distributions determine a positive function
independently of the ordering. Further, by judiciously implementing a
parametric-ordered Weyl quantization map for LQG, we are able to recover in a
simple manner the relevant cases of the standard, anti-standard, and Weyl
symmetric orderings, respectively. We expect that our results may serve to
analyze several fundamental aspects within the LQC program, in special those
related to coherence, squeezed states, and the convergence of operators, as
extensively analyzed in the quantum optics and in the quantum information
frameworks.


  We discuss the past and future of set theory, axiom systems and independence
results. We deal in particular with cardinal arithmetic.


  The structure of the neutron rich sodium isotopes 31,32,33Na was investigated
by means of in-beam gammaray spectroscopy following one-neutron knockout and
inelastic scattering of radioactive beams provided by the RIKEN Radioactive Ion
Beam Factory. The secondary beams were selected and separated by the fragment
separator BigRIPS and incident at ~240 meV/u on a natural carbon (secondary)
target, which was surrounded by the DALI2 array to detect coincident
de-excitation gammarays. Scattered particles were identified by the
spectrometer ZeroDegree. In 31Na, a new decay gammaray was observed in
coincidence with the known (5/2+)-> 3/2(+) transition, while for 32,33Na
excited states are reported for the first time. From a comparison to
state-of-the-art shell model calculations it is concluded that the newly
observed excited state in 31Na belongs to a rotational band formed by a 2p2h
intruder configuration within the "Island of Inversion".


  In this paper, we study the role of degree mixing in the naming game. It is
found that consensus can be accelerated on disassortative networks. We provide
a qualitative explanation of this phenomenon based on clusters statistics.
Compared with assortative mixing, disassortative mixing can promote the merging
of different clusters, thus resulting in a shorter convergence time. Other
quantities, including the evolutions of the success rate, the number of total
words and the number of different words, are also studied.


  Erythropoiesis is a mechanism for the production of red blood cells by
cellular differentiation. It is based on amplification steps due to an
interplay between renewal and differentiation in the successive cell
compartments from stem cells to red blood cells. We will study this mechanism
with a stochastic point of view to explain unexpected fluctuations on the red
blood cell numbers, as surprisingly observed by biologists and medical doctors
in a rest erythropoiesis. We consider three compartments: stem cells,
progenitors and red blood cells. The dynamics of each cell type is
characterized by its division rate and by the renewal and differentiation
probabilities at each division event. We model the global population dynamics
by a three-dimensional stochastic decomposable branching process. We show that
the amplification mechanism is given by the inverse of the small difference
between the differentiation and renewal probabilities. Introducing a parameter
$K$ which scales simultaneously the size of the first component, the
differentiation and renewal probabilities and the red blood cell death rate, we
describe the asymptotic behavior of the process for large $K$. We show that
each compartment has its own size scale and its own time scale. Focussing on
the third component, we prove that the red blood cell population size,
conveniently renormalized (in time and size), is expanded in an usual way
inducing large fluctuations. The proofs are based on a fine study of the
different scales involved in the model and on the use of different convergence
and average techniques in the proofs.


  The Gemini Planet Imager (GPI) has been designed for the direct detection and
characterization of exoplanets and circumstellar disks. GPI is equipped with a
dual channel polarimetry mode designed to take advantage of the inherently
polarized light scattered off circumstellar material to further suppress the
residual seeing halo left uncorrected by the adaptive optics. We explore how
recent advances in data reduction techniques reduce systematics and improve the
achievable contrast in polarimetry mode. In particular, we consider different
flux extraction techniques when constructing datacubes from raw data, division
by a polarized flat-field and a method for subtracting instrumental
polarization. Using observations of unpolarized standard stars we find that
GPI's instrumental polarization is consistent with being wavelength independent
within our errors. In addition, we provide polarimetry contrast curves that
demonstrate typical performance throughout the GPIES campaign.


  Pairing symmetry in oxypnictides, a new family of multiband high-Tc
superconductors, is partially imposed by the positions of multiple Fermi
pockets, which itself can give rise to new order parameters, such as s+,-
states or the state of dx^2-y^2 symmetry. Other pairing states may appear on
small pockets for long range interactions, but they are expected to be
sensitive to defects. We identify the competing antiferromagnetic order with
the triplet exciton transition in the semi- metallic background and discuss
whether its coexistence with superconductivity explains the doping dependence
of Tc.


  Interesting phenomena and problems arising from the coupling of large-scale
electromagnetic fields and spacetime curvature, are introduced and studied
within this thesis. From electromagnetic wave propagation in curved spacetime
to envisaging a gravito-electromagnetic equivalence on large scales; from
magnetic fields' cosmic evolution, and magnetised gravitational collapse in
astrophysical environments, to the interaction between electromagnetic and
gravitational radiation; the present research work explores some unique
characteristics and properties of the gravito-electromagnetic coexistence. Its
theoretical framework is generally provided by classical (Maxwellian)
electrodynamics in the (4-dimensional) Riemannian spacetime of General
Relativity. Chapter 1, dealing with the perspective of a
gravito-electromagnetic equivalence in a metric affine geometry (involving
torsion and non-metricity), forms an exception to the aforementioned general
framework. Regarding its structure, the manuscript consists of four chapters
divided in two parts. The first two chapters (forming Part I) are concerned
with the Maxwell field in curved, Riemannian (Chapter 2) and (generalised)
metric affine (Chapter 2), spacetime framework. Aspects of the Weyl-Maxwell
coupling (where the Weyl field refers to long-range curvature) are also
included in Chapter 2. The last two chapters (forming Part II) treat
magnetohydrodynamics in the general relativistic framework.


  Results of a survey of Galactic star-forming regions in the lines of methanol
8_{-1}-7_0E at 229.8 GHz, 3_{-2}-4_{-1}E at 230.0 GHz, 0_0-1_{-1}E at 108.9
GHz, and a series of methanol lines J_1-J_0E near 165 GHz are presented. Two
masers, DR 21(OH) and DR 21West, and two maser candidates, L 379IRS3 and NGC
6334I(N), as well as 16 thermal sources are found at 229.8 GHz. This is the
first detection of methanol masers at a wavelength as short as 1 mm. At 108.9
GHz, masers were found towards G345.01+1.79 and probably, towards M 8E. Thermal
emission is found towards 28 objects. Only thermal emission was found at 165
and 230.0 GHz (20 and 7 sources, respectively). The masers at 229.8 GHz belong
to class I, whereas those at 108.9 GHz belong to class II, according to the
classification by Menten (1991). The masers in DR 21(OH) and DR 21West can be
roughly fitted by models with the gas kinetic temperature of the order of 50K.
The detection of the 108.9 GHz masers towards G345.01+1.79 and M 8E may
indicate on a specific geometry of these objects. The combination of the
existence of the class II J_0-J_{-1}E masers towards W 3(OH), G345.01+1.79, W
48, and Cep A and our non-detection of the 3_{-2}-4_{-1}E and J_1-J_0E lines is
an evidence that the class II masers in these objects are pumped by the
radiation of hot dust rather than by that of UC HII-regions.


  Neural Radiance Field (NeRF) has recently emerged as a powerful
representation to synthesize photorealistic novel views. While showing
impressive performance, it relies on the availability of dense input views with
highly accurate camera poses, thus limiting its application in real-world
scenarios. In this work, we introduce Sparse Pose Adjusting Radiance Field
(SPARF), to address the challenge of novel-view synthesis given only few
wide-baseline input images (as low as 3) with noisy camera poses. Our approach
exploits multi-view geometry constraints in order to jointly learn the NeRF and
refine the camera poses. By relying on pixel matches extracted between the
input views, our multi-view correspondence objective enforces the optimized
scene and camera poses to converge to a global and geometrically accurate
solution. Our depth consistency loss further encourages the reconstructed scene
to be consistent from any viewpoint. Our approach sets a new state of the art
in the sparse-view regime on multiple challenging datasets.


  In this note we introduce the class of $\mathcal H$-groups (or Hall groups)
related to the class of $\mathcal B$-groups defined by Ph. Hall in 1950's.
Establishing some basic properties of Hall groups we use them to obtain results
concerning embeddings of abelian groups. In particular, we give an explicit
classification of all abelian groups that can occur as subgroups in
finitely-generated metabelian groups. Hall groups allow to give a negative
answer to the Baumslag's conjecture of 1990 on the cardinality of the set of
isomorphism classes for abelian subgroups in finitely generated metabelian
groups.


  A single unicast index coding problem (SUICP) with symmetric and consecutive
interference (SCI) has $K$ messages and $K$ receivers, the $k$th receiver $R_k$
wanting the $k$th message $x_k$ and having interference $\mathcal{I}_k=
\{x_{k-U-m},\dots,x_{k-m-2},x_{k-m-1}\}\cup\{x_{k+m+1},
x_{k+m+2},\dots,x_{k+m+D}\}$ and side-information $\mathcal{K}_k=(\mathcal{I}_k
\cup x_k)^c$. In this paper, we derive a lowerbound on the broadcast rate of
single unicast index coding problem with symmetric and consecutive interference
(SUICP(SCI)). In the SUICP(SCI), if $m=0$, we refer this as single unicast
index coding problem with symmetric and neighboring interference (SUICP(SNI)).
In our previous work\cite{VaR5}, we gave the construction of near-optimal
vector linear index codes for SUICP(SNI) with arbitrary $K,D,U$. In this paper,
we convert the SUICP(SCI) into SUICP(SNI) and give the construction of
near-optimal vector linear index codes for SUICP(SCI) with arbitrary $K,U,D$
and $m$. The constructed codes are independent of field size. The near-optimal
vector linear index codes of SUICP(SNI) is a special case of near-optimal
vector linear index codes constructed in this paper for SUICP(SCI) with $m=0$.
In our previous work\cite{VaR6}, we derived an upperbound on broadcast rate of
SUICP(SNI). In this paper, we give an upperbound on the broadcast rate of
SUICP(SCI) by using our earlier result on the upperbound on the broadcast rate
of SUICP(SNI). We derive the capacity of SUICP(SCI) for some special cases.


  In this paper, the Riemann problem for the pressureless Euler equations with
a discontinuous source term is considered. The delta shock wave solution is
obtained by combining the generalized Rankine-Hugoniot conditions together with
the method of characteristics for different situations, which reflects the
impact of the source term on the delta shock front. Moreover, during the
construction process of the Riemann solution, some interesting phenomena are
also observed, such as the disappearance of the delta shock wave and the
occurrence of the vacuum state, etc.


  In spectroscopy, it is conventional to treat pulses much stronger than the
linewidth as delta-functions. In NMR, this assumption leads to the prediction
that pi pulses do not refocus the dipolar coupling. However, NMR spin echo
measurements in dipolar solids defy these conventional expectations when more
than one pi pulse is used. Observed effects include a long tail in the CPMG
echo train for short delays between pi pulses, an even-odd asymmetry in the
echo amplitudes for long delays, an unusual fingerprint pattern for
intermediate delays, and a strong sensitivity to pi-pulse phase. Experiments
that set limits on possible extrinsic causes for the phenomena are reported. We
find that the action of the system's internal Hamiltonian during any real pulse
is sufficient to cause the effects. Exact numerical calculations, combined with
average Hamiltonian theory, identify novel terms that are sensitive to
parameters such as pulse phase, dipolar coupling, and system size.
Visualization of the entire density matrix shows a unique flow of quantum
coherence from non-observable to observable channels when applying repeated pi
pulses.


  Cancer patient diagnosis and prognosis is informed by assessment of
morphological properties observed in patient tissue. Pathologists normally
carry out this assessment, yet advances in computational image analysis provide
opportunities for quantitative assessment of tissue. A key aspect of that
quantitative assessment is the development of algorithms able to link image
data to patient survival. Here, we develop a point process methodology able to
describe patterns in cell distribution within cancerous tissue samples. In
particular, we consider the Palm intensities of two Neyman Scott point
processes, and a void process developed herein to reflect the spatial
patterning of the cells. An approximate-likelihood technique is taken in order
to fit point process models to patient data and the predictive performance of
each model is determined. We demonstrate that based solely on the spatial
arrangement of cells we are able to predict patient survival.


  A graph is k-linked if any k disjoint vertex-pairs can be joined by k
disjoint paths. We improve a lower bound on the linkedness of polytopes
slightly, which results in exact values for the minimal linkedness of 7-, 10-
and 13-dimensional polytopes.
  We analyze in detail linkedness of polytopes on at most (6d+7)/5 vertices. In
that case, a sharp lower bound on minimal linkedness is derived, and examples
meeting this lower bound are constructed. These examples contain a class of
examples due to Gallivan.


  Although various techniques have been proposed to generate adversarial
samples for white-box attacks on text, little attention has been paid to
black-box attacks, which are more realistic scenarios. In this paper, we
present a novel algorithm, DeepWordBug, to effectively generate small text
perturbations in a black-box setting that forces a deep-learning classifier to
misclassify a text input. We employ novel scoring strategies to identify the
critical tokens that, if modified, cause the classifier to make an incorrect
prediction. Simple character-level transformations are applied to the
highest-ranked tokens in order to minimize the edit distance of the
perturbation, yet change the original classification. We evaluated DeepWordBug
on eight real-world text datasets, including text classification, sentiment
analysis, and spam detection. We compare the result of DeepWordBug with two
baselines: Random (Black-box) and Gradient (White-box). Our experimental
results indicate that DeepWordBug reduces the prediction accuracy of current
state-of-the-art deep-learning models, including a decrease of 68\% on average
for a Word-LSTM model and 48\% on average for a Char-CNN model.