  The Photon Drag Effect (PDE) is a nonlinear process akin to optical
rectification in which the momentum of light is transferred to charged carriers
and converted to a DC voltage. Here, we experimentally demonstrate the
spin-polarized voltage, associated with the transference of light's spin
angular momenta to the linear momenta of charges, with visible-light
illumination on a nanovoid self-assembled plasmonic crystal surface. Numerical
calculations show that the gradient force, generally considered independent of
polarization, is responsible for the majority of the momentum transfer. The PDE
in this achiral system represents a distinct spin-orbit interaction that
produces asymmetric hotspots whose locations change with circular polarization
handedness. Our results significantly advance our understanding of the PDE and
demonstrate realistic potential for scalable plasmonic materials that utilize
PDE.


  Although modern face verification systems are accessible and accurate, they
are not always robust to pose variance and occlusions. Moreover, accurate
models require a large amount of data to train. We structure our experiments to
operate on small amounts of data obtained from an NGO that funds ophthalmic
surgeries. We set up our face verification task as that of verifying
pre-operation and post-operation images of a patient that undergoes ophthalmic
surgery, and as such the post-operation images have occlusions like an eye
patch. In this paper, we present a system that performs the face verification
task using one-shot learning. To this end, our paper uses deep convolutional
networks and compares different model architectures and loss functions. Our
best model achieves 85% test accuracy. During inference time, we also attempt
to detect image forgeries in addition to performing face verification. To
achieve this, we use Error Level Analysis. Finally, we propose an inference
pipeline that demonstrates how these techniques can be used to implement an
automated face verification and forgery detection system.


  Physics-based modeling and dynamic simulation of human eye movements has
significant implications for improving our understanding of the oculomotor
system and treating various visuomotor disorders. We introduce an open-source
biomechanical model of the human eye that can be used for kinematics and
dynamics analysis. This model is based on the passive pulley hypothesis,
constructed based on the data reported in literature regarding physiological
measurements of the human eye and made publicly available. The model is
implemented in OpenSim, which is an open-source framework for modeling and
simulation of musculoskeletal systems. The model incorporates an eye globe,
orbital suspension tissues and six extraocular muscles. The excitation and
activation patterns for a variety of targets can be calculated using the
proposed closed-loop fixation controller that drives the model to perform
saccadic movements in a forward dynamics manner. The controller minimizes the
error between the desired saccadic trajectory and the predicted movement.
Consequently, this model enables the investigation muscle activation patterns
during static fixation and analyze the dynamics of eye movements.


  The basis elements spanning the Sato Grassmannian element corresponding to
the KP $\tau$-function that serves as generating function for rationally
weighted Hurwitz numbers are shown to be Meijer $G$-functions. Using their
Mellin-Barnes integral representation the $\tau$-function, evaluated at the
trace invariants of an externally coupled matrix, is expressed as a matrix
integral. Using the Mellin-Barnes integral transform of an infinite product of
$\Gamma$ functions, a similar matrix integral representation is given for the
KP $\tau$-function that serves as generating function for quantum weighted
Hurwitz numbers.


  The outstanding properties of graphene have laid the foundation for exploring
graphene-like two-dimensional systems, commonly referred to as 2D-Xenes.
Amongst them, silicene is a front-runner owing to its compatibility with
current silicon fabrication technologies. Recent works on silicene have
unveiled its useful electronic and mechanical properties. The rapid
miniaturization of silicon devices and the useful electro-mechanical properties
of silicene necessitates the exploration for potential applications of silicene
flexible electronics in the nano electro-mechanical systems. Using a
theoretical model derived from the integration of \textit{ab-initio}
density-functional theory and quantum transport theory, we investigate the
piezoresistance effect of silicene in the nanoscale regime. Like graphene, we
obtain a small value of piezoresistance gauge factor of silicene, which is
sinusoidally dependent on the transport angle. The small gauge factor of
silicene is attributed to its robust Dirac cone and strain-independent valley
degeneracy. Based on the obtained results, we propose to use silicene as an
interconnect in flexible electronic devices and a reference piezoresistor in
strain sensors. This work will hence pave the way for exploring flexible
electronics applications in other 2D-Xene materials.


  The asymptotic dimension theory was founded by Gromov in the early 90s. In
this paper we give a survey of its recent history where we emphasize two of its
features: an analogy with the dimension theory of compact metric spaces and
applications to the theory of discrete groups.


  This short note is devoted to motivate and clarify the notion of sequential
walk introduced by the authors in a previous work. We also give some
applications of this concept.


  A lattice Boltzmann (LB) theory, analytical characteristic integral (ACI) LB
theory, is proposed in this paper. ACI LB theory takes Bhatnagar-Gross-Krook
(BGK) Boltzmann equation as the exact kinetic equation behind Navier-Stokes
continuum and momentum equations and constructs LB equation by rigorously
integrating BGK-Boltzmann equation along characteristics. It's a general
theory, supporting most existed LB equations including the standard lattice BGK
(LBGK) equation inherited from lattice-gas automata, whose theoretical
foundation had been questioned. ACI LB theory also indicates that the
characteristic parameter of LB equation is collision number, depicting the
particle-interacting intensity in the time span of LB equation, instead of
traditionally assumed relaxation time, and the over relaxation time problem is
merely a manifestation of temporal evolution of equilibrium distribution along
characteristics under high collision number, irrelevant to particle kinetics.
In ACI LB theory, the temporal evolution of equilibrium distribution along
characteristics is the determinant of LB method accuracy and we numerically
prove it.


  A search for supersymmetry or other new physics resulting in similar final
states is presented using a data sample of 4.73 inverse femtobarns of pp
collisions collected at sqrt(s)=7 TeV with the CMS detector at the LHC. Fully
hadronic final states are selected based on the variable MT2, an extension of
the transverse mass in events with two invisible particles. Two complementary
studies are performed. The first targets the region of parameter space with
medium to high squark and gluino masses, in which the signal can be separated
from the standard model backgrounds by a tight requirement on MT2. The second
is optimized to be sensitive to events with a light gluino and heavy squarks.
In this case, the MT2 requirement is relaxed, but a higher jet multiplicity and
at least one b-tagged jet are required. No significant excess of events over
the standard model expectations is observed. Exclusion limits are derived for
the parameter space of the constrained minimal supersymmetric extension of the
standard model, as well as on a variety of simplified model spectra.


  We study the effects of higher order transversal modes in a model of a
singly-resonant OPO, using both numerical solutions and mode expansions
including up to two radial modes. The numerical and two-mode solutions predict
lower threshold and higher conversion than the single-mode solution at negative
dispersion. Relative power in the zero order radial mode ranges from about 88%
at positive and small negative dispersion to 48% at larger negative dispersion,
with most of the higher mode content in the first mode, and less than 2% in
higher modes.


  We investigate in detail the flavor structure of the minimal 331 model and
its implications for several flavor changing neutral current (FCNC) processes.
In this model, where the weak SU(2)_L gauge group of the Standard Model is
extended to a SU(3)_L, the by far dominant new contributions come from an
additional neutral Z' gauge boson, that can transmit FCNCs at tree-level. At
the same time, electroweak precision observables receive new contributions only
at the loop level and do not constrain the model very strongly. In our
analysis, we take into account new CP violating effects that have been
neglected in earlier analyses, and account for a general flavor structure
without reference to a certain parameterization of the new mixing matrix. We
begin by studying the bounds obtained from quantities such as Delta M_K,
epsilon_K, Delta M_{d/s} as well as sin 2 beta|_{J/psi K_S}, and go on to
explore the implications for several clean rare decay channels, namely the
decays K+->pi+ nu nu, K_L -> pi0 nu nu, B_{d/s} -> mu+ mu- and K_L -> pi0 l+l-.
We find sizeable effects in all these decays, but the most interesting quantity
turns out to be the B_s - bar B_s mixing phase beta_s, as measured in the
mixing induced CP asymmetry of B_s -> J/psi phi, which can be large. In
general, we find effects in purely hadronic channels to be larger than in
(semi-)leptonic ones, due to a suppression of the Z'-lepton couplings.


  Much recent work on the cosmic microwave background (CMB) has focussed on the
angular power spectrum of temperature anisotropies and particularly on the
recovery of cosmological parameters from acoustic peaks in the power spectrum.
However, there is more that can conceivably be done with CMB measurements. Here
I briefly survey a few such ideas: cross-correlation with other cosmic
backgrounds as a probe of the density of the Universe; CMB polarization as a
gravitational-wave detector; secondary anisotropies and the ionization history
of the Universe; tests of alternative-gravity theories; polarization, the
Sunyaev-Zeldovich effect, and cosmic variance; and tests for a neutrino mass.


  We describe the wall and chamber structure of a special biserial algebra
whose module category is equivalent to the category of (middle) perverse
sheaves on the complex projective space $\mathbb{P}^n$. In particular, by the
well known classification of indecomposable modules for special biserial
algebras, we deduce that the algebra of interest is of finite representation
type and we provide an explicit description of the walls of the structure. By a
result of Bridgeland this wall and chamber structure coincides with the chamber
structure in an open subset of the space of stability conditions on the bounded
derived category of constructible sheaves on $\mathbb{P}^n$.


  Let $(R,\mathfrak{m})$ be a local Noetherian ring with residue field $k$.
While much is known about the generating sets of reductions of ideals of $R$ if
$k$ is infinite, the case in which $k$ is finite is less well understood. We
investigate the existence (or lack thereof) of proper reductions of an ideal of
$R$ and the number of generators needed for a reduction in the case $k$ is a
finite field. When $R$ is one-dimensional, we give a formula for the smallest
integer $n$ for which every ideal has an $n$-generated reduction. It follows
that in a one-dimensional local Noetherian ring every ideal has a principal
reduction if and only if the number of maximal ideals in the normalization of
the reduced quotient of $R$ is at most $|k|$. In higher dimensions, we show
that for any positive integer, there exists an ideal of $R$ that does not have
an $n$-generated reduction and that if $n \geq \dim R$ this ideal can be chosen
to be $\mathfrak{m}$-primary. In the case where $R$ is a two-dimensional
regular local ring, we construct an example of an integrally closed
$\mathfrak{m}$-primary ideal that does not have a $2$-generated reduction and
thus answer in the negative a question raised by Heinzer and Shannon.


  We present a novel method for direct detection and characterization of
exoplanets from space. This method uses four collecting telescopes, combined
with phase chopping and a spectrometer, with observations on only a few
baselines rather than on a continuously rotated baseline. Focusing on the
contiguous wavelength spectra of typical exoplanets, the (u, v) plane can be
simultaneously and uniformly filled by recording the spectrally resolved
signal. This concept allows us to perfectly remove speckles from reconstructed
images. For a target comprising a star and multiple planets, observations on
three baselines are sufficient to extract the position and spectrum of each
planet. Our simulations show that this new method allows us to detect an analog
Earth around a Sun-like star at 10 pc and to acquire its spectrum over the
wavelength range from 8 to 19 {\mu}m with a high spectral resolution of 100.
This method allows us to fully characterize an analog Earth and to similarly
characterize each planet in multi-planet systems.


  Over the last few years, the Sloan Digital Sky Survey (SDSS) has discovered
several hundred quasars with redshift between 4.0 and 6.4. Including the
effects of magnification bias, one expects a priori that an appreciable
fraction of these objects are gravitationally lensed. We have used the Advanced
Camera for Surveys on the Hubble Space Telescope to carry out a snapshot
imaging survey of high-redshift SDSS quasars to search for gravitationally
split lenses. This paper, the first in a series reporting the results of the
survey, describes snapshot observations of four quasars at z = 5.74, 5.82, 5.99
and 6.30, respectively. We find that none of these objects has a lensed
companion within 5 magnitudes with a separation larger than 0.3 arcseconds;
within 2.5 magnitudes, we can rule out companions within 0.1 arcseconds. Based
on the non-detection of strong lensing in these four systems, we constrain the
z~6 luminosity function to a slope of beta>-4.63 (3 sigma), assuming a break in
the quasar luminosity function at M_{1450}^*=-24.0. We discuss the implications
of this constraint on the ionizing background due to quasars in the early
universe. Given that these quasars are not highly magnified, estimates of the
masses of their central engines by the Eddington argument must be taken
seriously, possibly challenging models of black hole formation.


  Awfully idiosyncratic lecture notes from CMI summer school in arithmetic
geometry July 31-August 4, 2006.
  Does not include: rationality problems, techniques of the minimal model
problem and much of the rest.
  Includes: Lecture 0: geometry and arithmetic of curves
  Lecture 1: Kodaira dimension and properties, rational connectendess, Lang's
and Campana's conjectures.
  Lecture 2: Campana's program; Campana constellations framed in terms of
b-divisors, to allow for a definition of Kodaira dimension directly on the
base. A speculative notion of firmaments which may deserve further
investigation, especially the arithmetic side.
  Lecture 3: the minimal model program: very short discussion of
bend-and-break; even shorter discussion of finite generation and the existence
of flip.
  Lecture 4: Vojta's conjectures, Campana's conjectures, and ABC.


  Within a combined approach we investigate the main features of the production
of hyper-fragments in relativistic heavy-ion collisions. The formation of
hyperons is modelled within the UrQMD and HSD transport codes. To describe the
hyperon capture by nucleons and nuclear residues a coalescence of baryons (CB)
model was developed. We demonstrate that the origin of hypernuclei of various
masses can be explained by typical baryon interactions, and that it is similar
to processes leading to the production of conventional nuclei. At high beam
energies we predict a saturation of the yields of all hyper-fragments,
therefore, this kind of reactions can be studied with high yields even at the
accelerators of moderate relativistic energies.


  Covariance estimation is essential yet underdeveloped for analyzing
multivariate functional data. We propose a fast covariance estimation method
for multivariate sparse functional data using bivariate penalized splines. The
tensor-product B-spline formulation of the proposed method enables a simple
spectral decomposition of the associated covariance operator and explicit
expressions of the resulting eigenfunctions as linear combinations of B-spline
bases, thereby dramatically facilitating subsequent principal component
analysis. We derive a fast algorithm for selecting the smoothing parameters in
covariance smoothing using leave-one-subject-out cross-validation. The method
is evaluated with extensive numerical studies and applied to an Alzheimer's
disease study with multiple longitudinal outcomes.


  Metis is the CCNx 1.0 forwarder that implements the CCNx 1.0 Semantics and
Messages draft standards. This document describes how to use Metis and the
internal software architecture.


  With the emerging environment-aware applications, ubiquitous sensing is
expected to play a key role in future networks. In this paper, we study a
3-dimensional (3D) multi-target localization system where multiple intelligent
reflecting surfaces (IRSs) are applied to create virtual line-of-sight (LoS)
links that bypass the base station (BS) and targets. To fully unveil the
fundamental limit of IRS for sensing, we first study a single-target-single-IRS
case and propose a novel \textit{two-stage localization protocol} by
controlling the on/off state of IRS. To be specific, in the IRS-off stage, we
derive the Cram\'{e}r-Rao bound (CRB) of the azimuth/elevation
direction-of-arrival (DoA) of the BS-target link and design a DoA estimator
based on the MUSIC algorithm. In the IRS-on stage, the CRB of the
azimuth/elevation DoA of the IRS-target link is derived and a simple DoA
estimator based on the on-grid IRS beam scanning method is proposed.
Particularly, the impact of echo signals reflected by IRS from different paths
on sensing performance is analyzed. Moreover, we prove that the single-beam of
the IRS is not capable of sensing, but it can be achieved with
\textit{multi-beam}. Based on the two obtained DoAs, the 3D single-target
location is constructed. We then extend to the multi-target-multi-IRS case and
propose an \textit{IRS-adaptive sensing protocol} by controlling the on/off
state of multiple IRSs, and a multi-target localization algorithm is developed.
Simulation results demonstrate the effectiveness of our scheme and show that
sub-meter-level positioning accuracy can be achieved.


  The contemporary drug design process demands considerable time and resources
to develop each new compound entering the market. Generating small molecules is
a pivotal aspect of drug discovery, essential for developing innovative
pharmaceuticals. Uniqueness, validity, diversity, druglikeliness,
synthesizability, and solubility molecular pharmacokinetic properties, however,
are yet to be maximized. This work introduces several new generative
adversarial network models based on engineering integration of parametrized
quantum circuits into known molecular generative adversarial networks. The
introduced machine learning models incorporate a new multi-parameter reward
function grounded in reinforcement learning principles. Through extensive
experimentation on benchmark drug design datasets, QM9 and PC9, the introduced
models are shown to outperform scores achieved previously. Most prominently,
the new scores indicate an increase of up to 30% in the druglikeness
quantitative estimation. The new hybrid quantum machine learning algorithms, as
well as the achieved scores of pharmacokinetic properties, contribute to the
development of fast and accurate drug discovery processes.


  A significant challenge for the control of a robotic lower extremity
rehabilitation exoskeleton is to ensure stability and robustness during
programmed tasks or motions, which is crucial for the safety of the
mobility-impaired user. Due to various levels of the user's disability, the
human-exoskeleton interaction forces and external perturbations are
unpredictable and could vary substantially and cause conventional motion
controllers to behave unreliably or the robot to fall down. In this work, we
propose a new, reinforcement learning-based, motion controller for a lower
extremity rehabilitation exoskeleton, aiming to perform collaborative squatting
exercises with efficiency, stability, and strong robustness. Unlike most
existing rehabilitation exoskeletons, our exoskeleton has ankle actuation on
both sagittal and front planes and is equipped with multiple foot force sensors
to estimate center of pressure (CoP), an important indicator of system balance.
This proposed motion controller takes advantage of the CoP information by
incorporating it in the state input of the control policy network and adding it
to the reward during the learning to maintain a well balanced system state
during motions. In addition, we use dynamics randomization and adversary force
perturbations including large human interaction forces during the training to
further improve control robustness. To evaluate the effectiveness of the
learning controller, we conduct numerical experiments with different settings
to demonstrate its remarkable ability on controlling the exoskeleton to
repetitively perform well balanced and robust squatting motions under strong
perturbations and realistic human interaction forces.


  Let $E$ be a locally compact separable metric space and $m$ be a positive
Radon measure on it. Given a nonnegative function $k$ defined on $E\times E$
off the diagonal whose anti-symmetric part is assumed to be less singular than
the symmetric part, we construct an associated regular lower bounded
semi-Dirichlet form $\eta$ on $L^2(E;m)$ producing a Hunt process $X^0$ on $E$
whose jump behaviours are governed by $k$. For an arbitrary open subset
$D\subset E$, we also construct a Hunt process $X^{D,0}$ on $D$ in an analogous
manner. When $D$ is relatively compact, we show that $X^{D,0}$ is censored in
the sense that it admits no killing inside $D$ and killed only when the path
approaches to the boundary. When $E$ is a $d$-dimensional Euclidean space and
$m$ is the Lebesgue measure, a typical example of $X^0$ is the stable-like
process that will be also identified with the solution of a martingale problem
up to an $\eta$-polar set of starting points. Approachability to the boundary
$\partial D$ in finite time of its censored process $X^{D,0}$ on a bounded open
subset $D$ will be examined in terms of the polarity of $\partial D$ for the
symmetric stable processes with indices that bound the variable exponent
$\alpha(x)$.


  Mediation analysis seeks to identify and quantify the paths by which an
exposure affects an outcome. Intermediate variables which are effected by the
exposure and which effect the outcome are known as mediators. There exists
extensive work on mediation analysis in the context of models with a single
mediator and continuous and binary outcomes. However these methods are often
not suitable for multi-omic data that include highly interconnected variables
measuring biological mechanisms and various types of outcome variables such as
censored survival responses. In this article, we develop a general framework
for causal mediation analysis with multiple exposures, multivariate mediators,
and continuous, binary, and survival responses. We estimate mediation effects
on several scales including the mean difference, odds ratio, and restricted
mean scale as appropriate for various outcome models. Our estimation method
avoids imposing constraints on model parameters such as the rare disease
assumption while accommodating continuous exposures. We evaluate the framework
and compare it to other methods in extensive simulation studies by assessing
bias, type I error and power at a range of sample sizes, disease prevalences,
and number of false mediators. Using Kidney Renal Clear Cell Carcinoma data
from The Cancer Genome Atlas, we identify proteins which mediate the effect of
metabolic gene expression on survival. Software for implementing this unified
framework is made available in an R package
(https://github.com/longjp/mediateR).


  We study the stellar kinematic properties and spatial distribution of the
association Cyg OB3 using precise astrometric data from Gaia DR2. All known O-
and B-type stars in Cyg OB3 region with positions, parallaxes and proper
motions available are included, comprising a total of 41 stars. The majority of
stars are found to be concentrated at a heliocentric distance of 2.0 +/- 0.3
kpc. The mean peculiar velocity of the sample after removing Galactic rotation
and solar motion is ~22 km/s, dominated by the velocity component towards the
Galactic center. The relative position and velocity of the black hole X-ray
binary Cyg X-1 with respect to the association suggest that Cyg OB3 is most
likely its parent association. The peculiar kinematic properties of some of the
stars are revealed and are suggestive of past stellar encounters. The sample
includes a previously known runaway star HD 227018, and its high peculiar
velocity of ~50 km/s is confirmed with Gaia. We estimated the velocities of
stars relative to the association and the star HD 225577 exhibits peculiar
velocity smaller than its velocity relative to the association. The star has
lower value of proper motion than the rest of the sample. The results suggest a
slowly expanding nature of the association, which is supported by the small
relative speeds <20 km/s with respect to the association for a majority of the
sample stars.


  Low-dimensional word vectors have long been used in a wide range of
applications in natural language processing. In this paper we shed light on
estimating query vectors in ad-hoc retrieval where a limited information is
available in the original query. Pseudo-relevance feedback (PRF) is a
well-known technique for updating query language models and expanding the
queries with a number of relevant terms. We formulate the query updating in
low-dimensional spaces first with rotating the query vector and then with
scaling. These consequential steps are embedded in a query-specific projection
matrix capturing both angle and scaling. In this paper we propose a new but not
the most effective technique necessarily for PRF in language modeling, based on
the query projection algorithm. We learn an embedded coefficient matrix for
each query, whose aim is to improve the vector representation of the query by
transforming it to a more reliable space, and then update the query language
model. The proposed embedded coefficient divergence minimization model (ECDMM)
takes top-ranked documents retrieved by the query and obtains a couple of
positive and negative sample sets; these samples are used for learning the
coefficient matrix which will be used for projecting the query vector and
updating the query language model using a softmax function. Experimental
results on several TREC and CLEF data sets in several languages demonstrate
effectiveness of ECDMM. The experimental results reveal that the new
formulation for the query works as well as state-of-the-art PRF techniques and
outperforms state-of-the-art PRF techniques in a TREC collection in terms of
MAP,P@5, and P@10 significantly.


  Super-resolution fluorescence microscopy, with a resolution beyond the
diffraction limit of light, has become an indispensable tool to directly
visualize biological structures in living cells at a nanometer-scale
resolution. Despite advances in high-density super-resolution fluorescent
techniques, existing methods still have bottlenecks, including extremely long
execution time, artificial thinning and thickening of structures, and lack of
ability to capture latent structures. Here we propose a novel deep learning
guided Bayesian inference approach, DLBI, for the time-series analysis of
high-density fluorescent images. Our method combines the strength of deep
learning and statistical inference, where deep learning captures the underlying
distribution of the fluorophores that are consistent with the observed
time-series fluorescent images by exploring local features and correlation
along time-axis, and statistical inference further refines the ultrastructure
extracted by deep learning and endues physical meaning to the final image.
Comprehensive experimental results on both real and simulated datasets
demonstrate that our method provides more accurate and realistic local patch
and large-field reconstruction than the state-of-the-art method, the 3B
analysis, while our method is more than two orders of magnitude faster. The
main program is available at https://github.com/lykaust15/DLBI


  We present a detailed study of the Orion B clouds (d~400 pc), imaged with the
PACS/SPIRE cameras at 70-500 $\mu$m by the Herschel Gould Belt survey (HGBS).
We release new high-res. maps of column density and dust temperature. In the
filamentary sub-regions NGC2023/2024, NGC2068/2071, and L1622, 1768 starless
dense cores were identified, ~28-45% of which are self-gravitating prestellar
cores. A total of 76 protostellar dense cores were also found. The typical
lifetime of the prestellar cores was found to be $t_{\rm
pre}=1.7_{-0.6}^{+0.8}$ Myr. The prestellar core mass function (CMF) peaks at
~0.5 $M_\odot$ and is consistent with a power law with log slope -1.27$\pm$0.24
at the high-mass end, compared to the Salpeter slope of -1.35. In this region,
we confirm the existence of a transition in prestellar core formation
efficiency (CFE) around a fiducial value A_V_bg~7 mag in background visual
extinction, similar to the trend observed with Herschel in other clouds. This
is not a sharp threshold, but a smooth transition between a regime with very
low prestellar CFE at A_V_bg<5 and a regime with higher, roughly constant CFE
at A_V_bg$\gtrsim$10. The total mass in the form of prestellar cores represents
only ~20% of the dense molecular cloud gas at A_V_bg$\gtrsim$7 mag. About
60-80% of the prestellar cores are closely associated with filaments, and this
fraction increases up to >90% when a more complete sample of filamentary
structures is considered. Interestingly, the median separation between nearest
core neighbors corresponds to the typical inner filament width of ~0.1 pc
commonly observed in nearby molecular clouds. Analysis of the CMF observed as a
function of background cloud column density shows that the most massive
prestellar cores are spatially segregated in the highest column density areas,
and suggests that both higher- and lower-mass prestellar cores may form in
denser filaments.


  We propose a general scheme for studying separably reducible properties in
metric spaces and then apply it to obtain separable determinacy of Lipschitz
property and the separable determinacy of slopes


  In this paper we perform in a manifestly $SO(n-1,1)$ [or, alternatively
$SO(n)$] covariant fashion, the canonical analysis of general relativity in $n$
dimensions written as a constrained $BF$ theory. Since the Lagrangian action of
the theory can be written in two classically equivalent ways, we analyze each
case separately. We show that for either action the canonical analysis can be
accomplished without introducing second-class constraints during the whole
process. Furthermore, in each case the resulting Hamiltonian formulation is the
same as the canonical formulation with only first-class constraints recently
obtained in M. Montesinos, R. Escobedo, J. Romero, and M. Celada, Phys. Rev. D
101, 024042 (2020) from the $n$-dimensional Palatini action.


  In knowledge bases such as Wikidata, it is possible to assert a large set of
properties for entities, ranging from generic ones such as name and place of
birth to highly profession-specific or background-specific ones such as
doctoral advisor or medical condition. Determining a preference or ranking in
this large set is a challenge in tasks such as prioritisation of edits or
natural-language generation. Most previous approaches to ranking knowledge base
properties are purely data-driven, that is, as we show, mistake frequency for
interestingness.
  In this work, we have developed a human-annotated dataset of 350 preference
judgments among pairs of knowledge base properties for fixed entities. From
this set, we isolate a subset of pairs for which humans show a high level of
agreement (87.5% on average). We show, however, that baseline and
state-of-the-art techniques achieve only 61.3% precision in predicting human
preferences for this subset.
  We then analyze what contributes to one property being rated as more
important than another one, and identify that at least three factors play a
role, namely (i) general frequency, (ii) applicability to similar entities and
(iii) semantic similarity between property and entity. We experimentally
analyze the contribution of each factor and show that a combination of
techniques addressing all the three factors achieves 74% precision on the task.
  The dataset is available at
www.kaggle.com/srazniewski/wikidatapropertyranking.


  Given any domain $X\subseteq \mathbb{R}^d$ and a probability measure $\rho$
on $X$, we study the problem of approximating in $L^2(X,\rho)$ a given function
$u:X\to\mathbb{R}$, using its noiseless pointwise evaluations at random
samples. For any given linear space $V\subset L^2(X,\rho)$ with dimension $n$,
previous works have shown that stable and optimally converging Weighted
Least-Squares (WLS) estimators can be constructed using $m$ random samples
distributed according to an auxiliary probability measure $\mu$ that depends on
$V$, with $m$ being linearly proportional to $n$ up to a logarithmic term. As a
first contribution, we present novel results on the stability and accuracy of
WLS estimators with a given approximation space, using random samples that are
more structured than those used in the previous analysis. As a second
contribution, we study approximation by WLS estimators in the adaptive setting.
For any sequence of nested spaces $(V_k)_{k} \subset L^2(X,\rho)$, we show that
a sequence of WLS estimators of $u$, one for each space $V_k$, can be
sequentially constructed such that: i) the estimators remain provably stable
with high probability and optimally converging in expectation, simultaneously
for all iterations from one to $k$, and ii) the overall number of samples
necessary to construct all the first $k$ estimators remains linearly
proportional to the dimension of $V_k$. We propose two sampling algorithms that
achieve this goal. The first one is a purely random algorithm that recycles
most of the samples from the previous iterations. The second algorithm recycles
all the samples from all the previous iterations. Such an achievement is made
possible by crucially exploiting the structure of the random samples. Finally
we develop numerical methods for the adaptive approximation of functions in
high dimension.


  Trace analysis can be a useful way to discover problems in a program under
test. Rather than writing a special purpose trace analysis tool, this paper
proposes that traces can usefully be analysed by checking them against a formal
model using a standard model-checker or else an animator for executable
specifications. These techniques are illustrated using a Travel Agent case
study implemented in J2EE. We added trace beans to this code that write trace
information to a database. The traces are then extracted and converted into a
form suitable for analysis by Spin, a popular model-checker, and Pro-B, a
model-checker and animator for the B notation. This illustrates the technique,
and also the fact that such a system can have a variety of models, in different
notations, that capture different features. These experiments have demonstrated
that model-based trace-checking is feasible. Future work is focussed on scaling
up the approach to larger systems by increasing the level of automation.


  State-of-the-art computations of the gravitational self-force (GSF) on
massive particles in black hole spacetimes involve numerical evolution of the
metric perturbation equations in the time-domain, which is computationally very
costly. We present here a new strategy, based on a frequency-domain treatment
of the perturbation equations, which offers considerable computational saving.
The essential ingredients of our method are (i) a Fourier-harmonic
decomposition of the Lorenz-gauge metric perturbation equations and a numerical
solution of the resulting coupled set of ordinary equations with suitable
boundary conditions; (ii) a generalized version of the method of extended
homogeneous solutions [Phys. Rev. D {\bf 78}, 084021 (2008)] used to circumvent
the Gibbs phenomenon that would otherwise hamper the convergence of the Fourier
mode-sum at the particle's location; and (iii) standard mode-sum
regularization, which finally yields the physical GSF as a sum over regularized
modal contributions. We present a working code that implements this strategy to
calculate the Lorenz-gauge GSF along eccentric geodesic orbits around a
Schwarzschild black hole. The code is far more efficient than existing
time-domain methods; the gain in computation speed (at a given precision) is
about an order of magnitude at an eccentricity of 0.2, and up to three orders
of magnitude for circular or nearly circular orbits. This increased efficiency
was crucial in enabling the recently reported calculation of the long-term
orbital evolution of an extreme mass ratio inspiral [Phys. Rev. D {\bf 85},
061501(R) (2012)]. Here we provide full technical details of our method to
complement the above report.


  A total of 628 pb-1 of data collected with the ALEPH detector at
centre-of-mass energies from 189 to 209 GeV is analysed in the search for gauge
mediated supersymmetry breaking (GMSB) topologies. In this framework, a novel
search for six-lepton final states when the stau is the next-to-lightest
supersymmetric particle (NLSP) and has negligible lifetime is performed. Other
possible signatures at LEP are studied and the ALEPH final results described
for two acoplanar photons, non-pointing single photons, acoplanar leptons,
large impact parameter leptons, detached slepton decay vertices, heavy stable
charged sleptons and multi-leptons plus missing energy final states. No
evidence is found for new phenomena, and lower limits on the masses of the
relevant supersymmetric particles are derived. A scan of a minimal GMSB
parameter space is performed and lower limits are set for the NLSP mass at 54
GeV and for the mass scale parameter Lambda at 10 TeV, independent of the NLSP
lifetime. Including the results from the neutral Higgs boson searches, a NLSP
mass limit of 77 GeV is obtained and values of Lambda up to 16 TeV are
excluded.


  In this paper, we present in-depth analysis of the condensation energy $E_c$
for a superconductor in a situation when superconductivity emerges out of a
non-Fermi liquid due to pairing mediated by a massless boson. This is the case
for electronic-mediated pairing near a quantum-critical point in a metal, for
pairing in SYK-type models, and for phonon-mediated pairing in the properly
defined limit, when the dressed Debye frequency vanishes. We consider a subset
of these quantum-critical models, in which the pairing in a channel with a
proper spatial symmetry is described by an effective $0+1$ dimensional model
with the effective dynamical interaction $V(\Omega_m) = {\bar
g}^\gamma/|\Omega_m|^\gamma$, where $\gamma$ is model-specific (the
$\gamma$-model). In previous papers, we argued that the pairing in the $\gamma$
model is qualitatively different from that in a Fermi liquid, and the gap
equation at $T=0$ has an infinite number of topologically distinct solutions,
$\Delta_n (\omega_m)$, where an integer $n$, running between $0$ and infinity,
is the number of zeros of $\Delta_n (\omega_m)$ on the positive Matsubara axis.
This gives rise to the set of extrema of $E_c$ at $E_{c,n}$, of which $E_{c,0}$
is the global minimum. The spectrum $E_{c,n}$ is discrete for a generic $\gamma
<2$, but becomes continuous at $\gamma = 2-0$. Here, we discuss in more detail
the profile of the condensation energy near each $E_{c,n}$ and the
transformation from a discrete to a continuous spectrum at $\gamma \to 2$. We
also discuss the free energy and the specific heat of the $\gamma$-model in the
normal state.


  We outline formal and physical similarities between the quantum dynamics of
open systems, and the mesoscopic description of classical systems affected by
weak noise. The main tool of our interest is the dissipative Wigner equation,
that, for suitable timescales, becomes analogous to the Fokker-Planck equation
describing classical advection and diffusion. This correspondence allows in
principle to surmise a finite resolution, other than the Planck scale, for the
quantized state space of the open system, particularly meaningful when the
latter underlies chaotic classical dynamics. We provide representative examples
of the quantum-stochastic parallel with noisy Hopf cycles and Van der Pol type
oscillators.


  Semileptonic B decays are studied on quenched anisotropic lattices using
Symanzik improved glue, NRQCD heavy quark and D234 light quark actions. We
employ constrained fits to extract ground state contributions to two- and
three-point correlators. Results for the B --> pi, l nubar decay form factors
are compared with previous lattice results. We find that our systematic errors
(excluding quenching errors) are dominated by chiral extrapolation
uncertainties.


  The goal of this numerical study is to get insight into singular solutions of
the two-dimensional (2D) Euler equations for non-smooth initial data, in
particular for vortex sheets. To this end high resolution computations of
vortex layers in 2D incompressible Euler flows are performed using the
characteristic mapping method (CMM). This semi-Lagrangian method evolves the
flow map using the gradient-augmented level set method (GALS). The semi-group
structure of the flow map allows its decomposition into sub-maps (each over a
finite time interval), and thus the precision can be controlled by choosing
appropriate remapping times. Composing the flow map yields exponential
resolution in linear time, a unique feature of CMM, and thus fine scale flow
structures can be resolved in great detail. Here the roll-up process of vortex
layers is studied varying the thickness of the layer showing its impact on the
growth of palinstrophy and possible blow up of absolute vorticity. The
curvature of the vortex sheet shows a singular-like behavior. The self-similar
structure of the vortex core is investigated in the vanishing thickness limit.
Conclusions on the non-uniqueness of weak solutions of 2D Euler for non-smooth
initial data are drawn and the presence of flow singularities is revealed
tracking them in the complex plane.


  A new supersymmetric grand unified model based on the gauge group
$SU(5)\times SU(5)$ is discussed. The model has the feature that the
conventional seesaw mechanism for neutrino masses is implemented using the
$(15, 1)+(1,\bar{15)}$ representation. This multiplet may have a better chance
of arising from level two compactification of superstring theories than the the
${bf \bar{126}}$ representation used in the SO(10) model. The model also
naturally suppresses all R-parity violating interactions.


  We reprove and generalize the result that the intersection cohomology groups
of a toric variety with coefficient in a nontrivial rank one local system
vanish. We prove a similar vanishing result for a certain class of varieties on
which a connected linear solvable group acts, including all spherical
varieties.


  Federated learning is a decentralized machine learning paradigm that allows
multiple clients to collaborate by leveraging local computational power and the
models transmission. This method reduces the costs and privacy concerns
associated with centralized machine learning methods while ensuring data
privacy by distributing training data across heterogeneous devices. On the
other hand, federated learning has the drawback of data leakage due to the lack
of privacy-preserving mechanisms employed during storage, transfer, and
sharing, thus posing significant risks to data owners and suppliers. Blockchain
technology has emerged as a promising technology for offering secure
data-sharing platforms in federated learning, especially in Industrial Internet
of Things (IIoT) settings. This survey aims to compare the performance and
security of various data privacy mechanisms adopted in blockchain-based
federated learning architectures. We conduct a systematic review of existing
literature on secure data-sharing platforms for federated learning provided by
blockchain technology, providing an in-depth overview of blockchain-based
federated learning, its essential components, and discussing its principles,
and potential applications. The primary contribution of this survey paper is to
identify critical research questions and propose potential directions for
future research in blockchain-based federated learning.


  Constraints to the parameters of inflation models are often derived assuming
some plausible range for the number--e.g., $N_k=46$ to $N_k=60$--of $e$-folds
of inflation that occurred between the time that our current observable
Universe exited the horizon and the end of inflation. However, that number is,
for any specific inflaton potential, related to an effective equation-of-state
parameter $w_{\mathrm{re}}$ and temperature $T_{\mathrm{re}}$, for reheating.
Although the physics of reheating is highly uncertain, there is a finite range
of reasonable values for $w_{\mathrm{re}}$. Here we show that by restricting
$w_{\mathrm{re}}$ to this range, more stringent constraints to inflation-model
parameters can be derived than those obtained from the usual procedure. To do
so, we focus in this work in particular on natural inflation and inflation with
a Higgs-like potential, and on power law models as limiting cases of those. As
one example, we show that the lower limit to the tensor-to-scalar ratio $r$,
derived from current measurements of the scalar spectral index, is about
20%-25% higher (depending on the model) with this procedure than with the usual
approach.


  We study the internal dynamics of bosonic atoms in an optical lattice. Within
the regime in which the atomic crystal is a Mott insulator with one atom per
well, the atoms behave as localized spins which interact according to some spin
Hamiltonian. The type of Hamiltonian (Heisenberg, Ising), and the sign of
interactions may be tuned by changing the properties of the optical lattice, or
applying external magnetic fields. When, on the other hand, the number of atoms
per lattice site is unknown, we can still use the bosons to perform general
quantum computation.


  We present results for SCET and bHQET matching coefficients and jet functions
in the large-$\beta_0$ limit. Our computations exactly predict all terms of the
form $\alpha_s^{n+1} n_f^n$ for any $n\geq 0$, and we find full agreement with
the coefficients computed in the full theory up to $\mathcal{O}(\alpha_s^4)$.
We obtain all-order closed expressions for the cusp and non-cusp anomalous
dimensions (which turn out to be unambiguous) as well as matrix elements (with
ambiguities) in this limit, which can be easily expanded to arbitrarily high
powers of $\alpha_s$ using recursive algorithms to obtain the corresponding
fixed-order coefficients. Examining the poles laying on the positive real axis
of the Borel-transform variable $u$ we quantify the perturbative convergence of
a series and estimate the size of non-perturbative corrections. We find a so
far unknown $u=1/2$ renormalon in the bHQET hard factor $H_m$ that affects the
normalization of the peak differential cross section for boosted top quark pair
production. For ambiguous series the so-called Borel sum is defined with the
principal value prescription. Furthermore, one can assign an ambiguity based on
the arbitrariness of avoiding the poles by contour deformation into the
positive or negative imaginary half-plane. Finally, we compute the relation
between the pole mass and four low-scale short distance masses in the
large-$\beta_0$ approximation (MSR, RS and two versions of the jet mass), work
out their $\mu$- and $R$-evolution in this limit, and study how their
implementation improves the convergence of the position-space bHQET jet
function, whose three-loop coefficient in full QCD is numerically estimated.


  his paper describes and analyzes the spatial spread of tuberculosis (TB) on
complex metapopulation, that is, networks of populations connected by migratory
flows whose configurations are described in terms of connectivity distribution
of nodes (patches) and the conditional probabilities of connections among
classes of nodes sharing the same degree. The migration and transmission
processes occur simultaneously. For uncorrelated networks under the assumption
of standard incidence transmission, we compute the disease-free equilibrium and
the basic reproduction number, and show that the disease-free equilibrium is
locally asymptotically stable. Moreover, for uncorrelated networks and under
assumption of simple mass action transmission, we give a necessary and
sufficient conditions for the instability of the disease-free equilibrium.
  The existence of endemic equilibria is also discussed. Finally, the
prevalence of the TB infection across the metapopulation as a function of the
path connectivity is studied using numerical simulations.


  We reformulate the coupled set of continuum equations for the renormalized
gluon and ghost propagators in QCD, such that the multiplicative
renormalizability of the solutions is manifest, independently of the specific
form of full vertices and renormalization constants. In the Landau gauge, the
equations are free of renormalization constants, and the renormalization point
dependence enters only through the renormalized coupling and the renormalized
propagator functions. The structure of the equations enables us to devise novel
truncations with solutions that are multiplicatively renormalizable and agree
with the leading order perturbative results. We show that, for infrared power
law behaved propagators, the leading infrared behavior of the gluon equation is
not solely determined by the ghost loop, as concluded in previous studies, but
that the gluon loop, the three-gluon loop, the four-gluon loop, and even
massless quarks also contribute to the infrared analysis. In our new Landau
gauge truncation, the combination of gluon and ghost loop contributions seems
to reject infrared power law solutions, but massless quark loops illustrate how
additional contributions to the gluon vacuum polarization could reinstate these
solutions. Moreover, a schematic study of the three-gluon and four-gluon loops
shows that they too need to be considered in more detail before a definite
conclusion about the existence of infrared power behaved gluon and ghost
propagators can be reached.


  We will develop simple relations between the arc-lengths of a pair of
geodesics that share common end-points. The two geodesics differ only by the
requirement that one is constrained to lie in a subspace of the parent
manifold. We will present two applications of our results. In the first example
we explore the convergence of Gaussian curvature estimates on a simple
triangular mesh. The second example demonstrates an improved error estimate for
the area of a Schwarz lantern.


  In the context of un-oriented open string theories, we identify quivers
whereby a Majorana mass for the neutron is indirectly generated by exotic
instantons. We discuss two classes of (Susy) Standard Model like quivers,
depending on the embedding of SU(2)_W in the Chan-Paton group. In both cases,
the main mechanism involves a vector-like pair mixing through a
non-perturbative mass term. We also discuss possible relations between the
phenomenology of Neutron-Antineutron oscillations and LHC physics in these
models. In particular, a vector-like pair of color-triplet scalars or
color-triplet fermions could be directly detected at LHC, compatibly with
n-\bar{n} limits. Finally we briefly comment on Pati-Salam extensions of our
models.


  A plasma scenario with negative triangularity (NT) shaping is achieved on
MAST-U for the first time. While edge localized modes (ELMs) are eventually
suppressed as the triangularity is decreased below $\delta$ < -0.06, an
extended period of H-mode operation with Type-III ELMs is sustained at less
negative $\delta$ even through access to the second stability region for ideal
ballooning modes is closed. This documents a qualitative difference from the
ELM-free access conditions documented in NT scenarios on conventional aspect
ratio machines. The electron temperature at the pedestal top drops across the
transition to ELM-free operation, but a steady rise in core temperature as
$\delta$ is decreased allows for similar normalized beta in the ELM-free NT and
H-mode positive triangularity shapes.


  As the first attempt to classify $\tau$-tilting finite two-point algebras, we
have determined the $\tau$-tilting finiteness for minimal wild two-point
algebras and some tame two-point algebras.


  With the advent of quantum key distribution (QKD) systems, perfect (i.e.
information-theoretic) security can now be achieved for distribution of a
cryptographic key. QKD systems and similar protocols use classical
error-correcting codes for both error correction (for the honest parties to
correct errors) and privacy amplification (to make an eavesdropper fully
ignorant). From a coding perspective, a good model that corresponds to such a
setting is the wire tap channel introduced by Wyner in 1975. In this paper, we
study fundamental limits and coding methods for wire tap channels. We provide
an alternative view of the proof for secrecy capacity of wire tap channels and
show how capacity achieving codes can be used to achieve the secrecy capacity
for any wiretap channel. We also consider binary erasure channel and binary
symmetric channel special cases for the wiretap channel and propose specific
practical codes. In some cases our designs achieve the secrecy capacity and in
others the codes provide security at rates below secrecy capacity. For the
special case of a noiseless main channel and binary erasure channel, we
consider encoder and decoder design for codes achieving secrecy on the wiretap
channel; we show that it is possible to construct linear-time decodable secrecy
codes based on LDPC codes that achieve secrecy.


  The second part of the theory for the multicomponent nonisothermal nucleation
is presented. The solution of the kinetic equation already derived in the first
part is given with the help of the Chapman-Enskog procedure. At first the
relaxation stage is considered. The special choice of the relaxation operator
allows to refuse from the special small parameter usually required in the
nucleation problems. The special procedure allows to estimate the tails of the
approximations appeared in the reccurent procedures. The final formulas for
corrections allows to reduce the problem to the ordinary Fokker-Planck equation
in the nulticomponent case.


  We derive a coupled set of equations that describe the non-equilibrium
evolution of cumulants of critical fluctuations for space-time trajectories on
the cross-over side of the QCD phase diagram. In particular, novel expressions
are obtained for the non-equilibrium evolution of non-Gaussian Skewness and
Kurtosis cumulants. Utilizing a simple model of the space-time evolution of a
heavy- ion collision, we demonstrate that, depending on the relaxation rate of
critical fluctuations, Skewness and Kurtosis can differ significantly in
magnitude as well as in sign from equilibrium expectations. Memory effects are
important and shown to persist even for trajectories that skirt the edge of the
critical regime. We use phenomenologically motivated parameterizations of
freeze-out curves, and of the beam energy dependence of the net baryon chemical
potential, to explore the implications of our model study for the critical
point search in heavy-ion collisions.


  Large extra dimensions, of size of order of TeV^{-1} ~= 10^{-16} cm, arise
naturally in the context of supersymmetry breaking in string theory, while
strings at a TeV scale offer a solution to the gauge hierarchy problem, as an
alternative to softly broken supersymmetry or technicolor. In this short
review, we present consistent perturbative realizations of string theories with
large volume compactifications and low string tensions, and discuss their main
physical implications.


  Decentralized federated learning (DFL) enables clients (e.g., hospitals and
banks) to jointly train machine learning models without a central orchestration
server. In each global training round, each client trains a local model on its
own training data and then they exchange local models for aggregation. In this
work, we propose SelfishAttack, a new family of attacks to DFL. In
SelfishAttack, a set of selfish clients aim to achieve competitive advantages
over the remaining non-selfish ones, i.e., the final learnt local models of the
selfish clients are more accurate than those of the non-selfish ones. Towards
this goal, the selfish clients send carefully crafted local models to each
remaining non-selfish one in each global training round. We formulate finding
such local models as an optimization problem and propose methods to solve it
when DFL uses different aggregation rules. Theoretically, we show that our
methods find the optimal solutions to the optimization problem. Empirically, we
show that SelfishAttack successfully increases the accuracy gap (i.e.,
competitive advantage) between the final learnt local models of selfish clients
and those of non-selfish ones. Moreover, SelfishAttack achieves larger accuracy
gaps than poisoning attacks when extended to increase competitive advantages.


  A hybrid encryption scheme is a public-key encryption system that consists of
a public-key part called the key encapsulation mechanism (KEM), and a
(symmetric) secret-key part called data encapsulation mechanism (DEM): the
public-key part is used to generate a shared secret key between two parties,
and the symmetric key part is used to encrypt the message using the generated
key. Hybrid encryption schemes are widely used for secure communication over
the Internet. In this paper, we initiate the study of hybrid encryption in
preprocessing model which assumes access to initial correlated variables by all
parties (including the eavesdropper). We define information-theoretic KEM
(iKEM) that, together with a (computationally) secure DEM, results in a hybrid
encryption scheme in preprocessing model. We define the security of each
building block, and prove a composition theorem that guarantees (computational)
qe-chosen plaintext (CPA) security of the hybrid encryption system if the iKEM
and the DEM satisfy qe-chosen encapculation attack and one-time security,
respectively. We show that iKEM can be realized by a one-way SKA (OW-SKA)
protocol with a revised security definition. Using an OW-SKA that satisfies
this revised definition of security effectively allows the secret key that is
generated by the OW-SKA to be used with a one-time symmetric key encryption
system such as XORing a pseudorandom string with the message, and provide
qe-CPA security for the hybrid encryption system.We discuss our results and
directions for future work.


  Attaining a high degree of user controllability in visual generation often
requires intricate, fine-grained inputs like layouts. However, such inputs
impose a substantial burden on users when compared to simple text inputs. To
address the issue, we study how Large Language Models (LLMs) can serve as
visual planners by generating layouts from text conditions, and thus
collaborate with visual generative models. We propose LayoutGPT, a method to
compose in-context visual demonstrations in style sheet language to enhance the
visual planning skills of LLMs. LayoutGPT can generate plausible layouts in
multiple domains, ranging from 2D images to 3D indoor scenes. LayoutGPT also
shows superior performance in converting challenging language concepts like
numerical and spatial relations to layout arrangements for faithful
text-to-image generation. When combined with a downstream image generation
model, LayoutGPT outperforms text-to-image models/systems by 20-40% and
achieves comparable performance as human users in designing visual layouts for
numerical and spatial correctness. Lastly, LayoutGPT achieves comparable
performance to supervised methods in 3D indoor scene synthesis, demonstrating
its effectiveness and potential in multiple visual domains.


  The processing and material properties of commercial organic semiconductors,
for e.g. fullerenes is largely controlled by their precise arrangements,
specially intermolecular symmetries, distances and orientations, more
specifically, molecular polarisabilities. These supramolecular parameters
heavily influence their electronic structure, thereby determining molecular
photophysics and therefore dictating their usability as n-type semiconductors.
In this article we evaluate van der Waals potentials of a fullerene dimer model
system using two approaches: a) Density Functional Theory and, b) Macroscopic
Quantum Electrodynamics, which is particularly suited for describing long-range
van der Waals interactions. Essentially, we determine and explain the model
symmetry, distance and rotational dependencies on binding energies and spectral
changes. The resultant spectral tuning is compared using both methods showing
correspondence within the constraints placed by the different model
assumptions. We envision that the application of macroscopic methods and
structure/property relationships laid forward in this article will find use in
fundamental supramolecular electronics.


  The blind quantum computation (BQC) protocol allows for privacy-preserving
remote quantum computations. In this paper, we introduce a remote quantum error
correction code preparation protocol for BQC using a cluster state and analyze
its blindness in the measurement-based quantum computation model. Our protocol
requires fewer quantum resources than previous methods, as it only needs weak
coherent pulses, eliminating the need for quantum memory and limited quantum
computing. The results of our theoretical analysis and simulations show that
our protocol requires fewer quantum resources compared to non-coding methods
with the same qubit error rate.


  In the scenario with four quark generations, we perform a fit using
flavor-physics data and determine the allowed values -- preferred central
values and errors -- of all of the elements of the 4X4 quark mixing matrix. In
addition to the direct measurements of some of the elements, we include in the
fit the present measurements of several flavor-changing observables in the K
and B systems that have small hadronic uncertainties, and also consider the
constraints from the vertex corrections to Z -> b bbar. The values taken for
the masses of the fourth-generation quarks are consistent with the measurements
of the oblique parameters and perturbativity of the Yukawa couplings. We find
that |{\tilde V}_{tb}| >= 0.98 at 3sigma, so that a fourth generation cannot
account for any large deviation of |{\tilde V}_{tb}| from unity. The fit also
indicates that all the new-physics parameters are consistent with zero, and the
mixing of the fourth generation with the other three is constrained to be very
small: we obtain |{\tilde V}_{ub'}| < 0.06, |{\tilde V}_{cb'}| < 0.027, and
|{\tilde V}_{tb'}| < 0.31 at 3sigma. Still, this does allow for the possibility
of new-physics signals in Bd, Bs and rare K decays.


  This paper is dedicated to the classical Hadamard formula for asymptotics of
eigenvalues of the Dirichlet-Laplacian under perturbations of the boundary. We
prove that the Hadamard formula still holds for $C^1$-domains with
$C^1$-perturbations. We also derive an optimal estimate for the remainder term
in the $C^{1,\alpha}$-case. Furthermore, if the boundary is merely Lipschitz,
we show that the Hadamard formula is not valid.


  We significantly reduce the cost of factoring integers and computing discrete
logarithms in finite fields on a quantum computer by combining techniques from
Shor 1994, Griffiths-Niu 1996, Zalka 2006, Fowler 2012, Eker{\aa}-H{\aa}stad
2017, Eker{\aa} 2017, Eker{\aa} 2018, Gidney-Fowler 2019, Gidney 2019. We
estimate the approximate cost of our construction using plausible physical
assumptions for large-scale superconducting qubit platforms: a planar grid of
qubits with nearest-neighbor connectivity, a characteristic physical gate error
rate of $10^{-3}$, a surface code cycle time of 1 microsecond, and a reaction
time of 10 microseconds. We account for factors that are normally ignored such
as noise, the need to make repeated attempts, and the spacetime layout of the
computation. When factoring 2048 bit RSA integers, our construction's spacetime
volume is a hundredfold less than comparable estimates from earlier works (Van
Meter et al. 2009, Jones et al. 2010, Fowler et al. 2012, Gheorghiu et al.
2019). In the abstract circuit model (which ignores overheads from
distillation, routing, and error correction) our construction uses $3 n + 0.002
n \lg n$ logical qubits, $0.3 n^3 + 0.0005 n^3 \lg n$ Toffolis, and $500 n^2 +
n^2 \lg n$ measurement depth to factor $n$-bit RSA integers. We quantify the
cryptographic implications of our work, both for RSA and for schemes based on
the DLP in finite fields.


  A reaction-diffusion equation with power nonlinearity formulated either on
the half-line or on the finite interval with nonzero boundary conditions is
shown to be locally well-posed in the sense of Hadamard for data in Sobolev
spaces. The result is established via a contraction mapping argument, taking
advantage of a novel approach that utilizes the formula produced by the unified
transform method of Fokas for the forced linear heat equation to obtain linear
estimates analogous to those previously derived for the nonlinear
Schr\"odinger, Korteweg-de Vries and "good" Boussinesq equations. Thus, the
present work extends the recently introduced "unified transform method approach
to well-posedness" from dispersive equations to diffusive ones.


  The effect of spatial inhomogeneity on the properties of a two-dimensional
non-centrosymmetric superconductor in an in-plane magnetic field is
investigated, as it can be realized in LaAlO_3-SrTiO_3 interfaces. We
demonstrate that the spatial variation of Rashba spin-orbit coupling (RSOC)
yields a local magnetic flux pattern due to the field-induced inhomogeneous
helical phase. For sufficiently strong fields, vortices can nucleate at
inhomogeneities of the RSOC.


  This paper aims to clarify the nature of a surprising ordered phase recently
reported in biased Bernal bilayer graphene that occurs at the phase boundary
between the isospin-polarized and unpolarized phases. Strong nonlinearity of
transport at abnormally small currents, with $dI/dV$ vs. $I$ sharply rising and
then falling back, is typical for a charge/spin-density-wave state (CDW or SDW)
sliding transport. Here, however, it is observed at an isospin-order phase
boundary, prompting a question about the CDW/SDW mechanism and its relation to
the quantum critical point. We argue that the observed phase diagram cannot be
understood within a standard weak-coupling picture. Rather, it points to a
mechanism that relies on an effective interaction enhancement at a quantum
critical point. We develop a detailed strong-coupling framework accounting for
the soft collective modes that explain these observations.


  We review the present status of CP violation in the standard model.
Subsequently we make an excursion in the future in order to see what we could
expect in this field in this and the next decade. We present various strategies
for the determination of the CKM parameters and divide the decays into four
classes with respect to theoretical uncertainties. We emphasize that the
definitive tests of the Kobayashi-Maskawa picture of CP violation will come
through a {\it simultaneous} study of CP asymmetries in $B_{d,s}^o$ decays, the
rare decays $K^+ \to \pi^+\nu \bar\nu$ and $K_L \to \pi^o\nu\bar\nu$, and
$x_d/x_s$. We illustrate how the measurements of the CP asymmetries in
$B^0_{d,s}$-decays together with a measurement of $Br(K_L\to
\pi^\circ\nu\bar\nu)$ or $Br(\kpnn)$ and the known value of $\mid V_{us}\mid $
can determine {\it all} elements of the Cabibbo-Kobayashi-Maskawa matrix
essentially without any hadronic uncertainties.


  Oxygen-rich Asymptotic Giant Branch (AGB) stars can be intense emitters of
SiO ($v$=1 and 2, J=1$\rightarrow$0) and H$_2$O maser lines at 43 and 22 GHz,
respectively. VLBI observations of the maser emission provide a unique tool to
probe the innermost layers of the circumstellar envelopes in AGB stars.
Nevertheless, the difficulties in achieving astrometrically aligned \water\ and
$v$=1 and $v$=2 SiO maser maps have traditionally limited the physical
constraints that can be placed on the SiO maser pumping mechanism. We present
phase referenced simultaneous spectral-line VLBI images for the SiO $v$=1 and
$v$=2, J=1$\rightarrow$0, and H$_2$O maser emission around the AGB star R\,LMi,
obtained from the Korean VLBI Network (KVN). The simultaneous multi-channel
receivers of the KVN offer great possibilities for astrometry in the frequency
domain. With this facility we have produced images with bona-fide absolute
astrometric registration between high frequency maser transitions of different
species to provide the positions of the \water\ maser emission, and the centre
of the SiO maser emission, and hence reducing the uncertainty in the proper
motion for R\,LMi by an order of magnitude over that from Hipparcos. This is
the first successful demonstration of source frequency phase referencing for
mm-VLBI spectral-line observations and also where the ratio between the
frequencies is not an integer.


  A classical result due to Deshouillers, Dress and Tenenbaum asserts that on
average the distribution of the divisors of the integers follows the arcsine
law. In this paper, we investigate the distribution of smooth divisors of the
integers, that is, those divisors which are free of large prime factors. We
show that on average these divisors are distributed according to a probability
law that we will describe.


  Recent large scale genome wide association analysis involves large scale
linear mixed models. Quantifying (co)-variance parameters in the mixed models
with a restricted maximum likelihood method results in a score function which
is the first derivative of a log-likelihood. To obtain a statistically
efficient estimate of the variance parameters, one needs to find the root of
the score function via the Newton method. Most elements of the Jacobian matrix
of the score involve a trace term of four parametric matrix-matrix
multiplications. It is computationally prohibitively for large scale data sets.
By a serial matrix transforms and an averaged information splitting technique,
an approximate Jacobian matrix can be obtained by splitting the average of the
Jacobian matrix and its expected value. In the approximated Jacobian, its
elements only involve Four matrix vector multiplications which can be
efficiently evaluated by solving sparse linear systems with the multi-frontal
factorization method.


  Low-resource automatic speech recognition (ASR) is challenging, as the
low-resource target language data cannot well train an ASR model. To solve this
issue, meta-learning formulates ASR for each source language into many small
ASR tasks and meta-learns a model initialization on all tasks from different
source languages to access fast adaptation on unseen target languages. However,
for different source languages, the quantity and difficulty vary greatly
because of their different data scales and diverse phonological systems, which
leads to task-quantity and task-difficulty imbalance issues and thus a failure
of multilingual meta-learning ASR (MML-ASR). In this work, we solve this
problem by developing a novel adversarial meta sampling (AMS) approach to
improve MML-ASR. When sampling tasks in MML-ASR, AMS adaptively determines the
task sampling probability for each source language. Specifically, for each
source language, if the query loss is large, it means that its tasks are not
well sampled to train ASR model in terms of its quantity and difficulty and
thus should be sampled more frequently for extra learning. Inspired by this
fact, we feed the historical task query loss of all source language domain into
a network to learn a task sampling policy for adversarially increasing the
current query loss of MML-ASR. Thus, the learnt task sampling policy can master
the learning situation of each language and thus predicts good task sampling
probability for each language for more effective learning. Finally, experiment
results on two multilingual datasets show significant performance improvement
when applying our AMS on MML-ASR, and also demonstrate the applicability of AMS
to other low-resource speech tasks and transfer learning ASR approaches.


  We estimate differential rapidity cross sections for $J/\Psi$, $\Psi(2S)$,
$\Upsilon(1S)$, $\Upsilon(2S)$, and $\Upsilon(3S)$ production via Pb-Pb
collisions at proton-proton energy $\equiv \sqrt{s_{pp}}$ =5.02 TeV. For the
$\Psi(2S)$, $\Upsilon(3S)$ states we use the mixed heavy quark hyrid theory,
with these states being approximately 50\% standard and 50\% hybrid charmonium,
bottomonium meson states. This is an extension of previous work on heavy quark
state production via Cu-Cu and Au-Au collisions at $\sqrt{s_{pp}}$=200 GeV.


  Observational tests of stellar and Galactic chemical evolution call for the
joint knowledge of a star's physical parameters, detailed element abundances,
and precise age. For cool main-sequence (MS) stars the abundances of many
elements can be measured from spectroscopy, but ages are very hard to
determine. The situation is different if the MS star has a white dwarf (WD)
companion and a known distance, as the age of such a binary system can then be
determined precisely from the photometric properties of the cooling WD. As a
pilot study for obtaining precise age determinations of field MS stars, we
identify nearly one hundred candidates for such wide binary systems: a faint WD
whose GPS1 proper motion matches that of a brighter MS star in Gaia/TGAS with a
good parallax ($\sigma_\varpi/\varpi\le 0.05$). We model the WD's multi-band
photometry with the BASE-9 code using this precise distance (assumed to be
common for the pair) and infer ages for each binary system. The resulting age
estimates are precise to $\le 10\%$ ($\le 20\%$) for $42$ ($67$) MS-WD systems.
Our analysis more than doubles the number of MS-WD systems with precise
distances known to date, and it boosts the number of such systems with precise
age determination by an order of magnitude. With the advent of the Gaia DR2
data, this approach will be applicable to a far larger sample, providing ages
for many MS stars (that can yield detailed abundances for over 20 elements),
especially in the age range 2 to 8\,\Gyr, where there are only few known star
clusters.


  Our aim in this article is to obtain the limit of counting function for the
Dirichlet eigenvalues involving the m-order logarithmic Laplacian in a bounded
Lipschitz domain and to derive also the lower bound.


  Multi-mode entangled coherent states are important resources for linear
optics quantum computation and teleportation. Here we introduce the generalized
balanced N-mode coherent states which recast in the multi-qudit case. The
necessary and sufficient condition for bi-separability of such balanced N-mode
coherent states is found. We particularly focus on pure and mixed multi-qubit
and multi-qutrit like states and examine the degree of bipartite as well as
tripartite entanglement using the concurrence measure. Unlike the N-qubit case,
it is shown that there are qutrit states violating monogamy inequality. Using
parity, displacement operator and beam splitters, we will propose a scheme for
generating balanced N-mode entangled coherent states for even number of terms
in superposition.


  Recent research has shown the possibility of using smartphones' sensors and
accessories to extract some behavioral attributes such as touch dynamics,
keystroke dynamics and gait recognition. These attributes are known as
behavioral biometrics and could be used to verify or identify users implicitly
and continuously on smartphones. The authentication systems that have been
built based on these behavioral biometric traits are known as active or
continuous authentication systems.
  This paper provides a review of the active authentication systems. We present
the components and the operating process of the active authentication systems
in general, followed by an overview of the state-of-the-art behavioral
biometric traits that used to develop an active authentication systems and
their evaluation on smartphones. We discuss the issues, strengths and
limitations that associated with each behavioral biometric trait. Also, we
introduce a comparative summary between them. Finally, challenges and open
research problems are presented in this research field.


  The "High school class for students with special abilities in physics" was
founded in Nis, Serbia (http://tesla.pmf.ni.ac.rs/f_odeljenje/) in 2003. The
basic aim of this project has been introducing a broadened curriculum of
physics, mathematics, computer science, as well as chemistry and biology. Now,
eight years after establishing of this specialized class, we present analyses
of the pupils' skills in solving rather problem oriented test, as PISA test,
and compare their results with the results of pupils who study under standard
curricula. Also, an external evaluation conducted more recently, shows that
Special physics class students performed higher on science knowledge test in
comparison with students from control groups (grammar school and special math
class students). Establishing of the Special physics class as an interesting
educational experiment and its development has been connected, in a sense, with
activities of the Southeastern European Network in Mathematical and Theoretical
Physics. We present the main achievements of the Network and their possible
impact to the students. We make conclusions and remarks that may be useful for
the future work that aims to increase pupils' intrinsic and instrumental
motivation for physics and sciences, as well as to increase the efficacy of
teaching physics and science.


  Some of the most successful statistical methods for obtaining distances of
planetary nebulae (PNe) are based on their apparent sizes and radio emission
intensities. These methods have the advantage of being "extinction-free" and
are especially suited to be applied to PNe situated at large distances. A
similar method, based on the mid-infrared (MIR) emission of PNe, would have the
advantage of being applicable to the large databases created after the various
all-sky or Galactic plane infrared surveys, such as IRAS, MSX, ISOGAL, GLIMPSE,
etc. In this work we propose a statistical method to calculate the distance of
PNe based on the apparent nebular radius and the MIR flux densities. We show
that the specific intensity between 8 and 21 micron is proportional to the
brightness temperature T_b at 5 GHz. Using MIR flux densities at 8, 12, 15 and
21 microns from the MSX survey, we calibrate the distance scale with a
statistical method by Stanghellini et al. 2008 (SSV). The database used in the
calibration consisted of 67 Galactic PNe with MSX counterparts and distances
determined by SSV. We apply the method to a sample of PNe detected at 8 microns
in the GLIMPSE infrared survey, and determine the distance of a sample of PNe
located along the Galactic plane and bulge.


  This work presents the first projection-free algorithm to solve stochastic
bi-level optimization problems, where the objective function depends on the
solution of another stochastic optimization problem. The proposed
$\textbf{S}$tochastic $\textbf{Bi}$-level $\textbf{F}$rank-$\textbf{W}$olfe
($\textbf{SBFW}$) algorithm can be applied to streaming settings and does not
make use of large batches or checkpoints. The sample complexity of SBFW is
shown to be $\mathcal{O}(\epsilon^{-3})$ for convex objectives and
$\mathcal{O}(\epsilon^{-4})$ for non-convex objectives. Improved rates are
derived for the stochastic compositional problem, which is a special case of
the bi-level problem, and entails minimizing the composition of two
expected-value functions. The proposed $\textbf{S}$tochastic
$\textbf{C}$ompositional $\textbf{F}$rank-$\textbf{W}$olfe ($\textbf{SCFW}$) is
shown to achieve a sample complexity of $\mathcal{O}(\epsilon^{-2})$ for convex
objectives and $\mathcal{O}(\epsilon^{-3})$ for non-convex objectives, at par
with the state-of-the-art sample complexities for projection-free algorithms
solving single-level problems. We demonstrate the advantage of the proposed
methods by solving the problem of matrix completion with denoising and the
problem of policy value evaluation in reinforcement learning.


  We present results related to the search of SU(2) instantons on a geometry
$[0,L]^3\times [0,T]$ obtained using over-improved cooling with fixed boundary
conditions. We also introduce a criterion for finding a sphaleron at the top of
the energy barrier of the instanton path.


  Proton decay from the 3$\hbar\omega$ isoscalar giant dipole resonance (ISGDR)
in $^{58}$Ni has been measured using the ($\alpha,\alpha'p$) reaction at a
bombarding energy of 386 MeV to investigate its decay properties. We have
extracted the ISGDR strength under the coincidence condition between
inelastically scattered $\alpha$ particles at forward angles and decay protons
emitted at backward angles. Branching ratios for proton decay to low-lying
states of $^{57}$Co have been determined, and the results compared to
predictions of recent continuum-RPA calculations. The final-state spectra of
protons decaying to the low-lying states in $^{57}$Co were analyzed for a more
detailed understanding of the structure of the ISGDR. It is found that there
are differences in the structure of the ISGDR as a function of excitation
energy.


  Implicit Neural representations (INRs) are widely used for scientific data
reduction and visualization by modeling the function that maps a spatial
location to a data value. Without any prior knowledge about the spatial
distribution of values, we are forced to sample densely from INRs to perform
visualization tasks like iso-surface extraction which can be very
computationally expensive. Recently, range analysis has shown promising results
in improving the efficiency of geometric queries, such as ray casting and
hierarchical mesh extraction, on INRs for 3D geometries by using arithmetic
rules to bound the output range of the network within a spatial region.
However, the analysis bounds are often too conservative for complex scientific
data. In this paper, we present an improved technique for range analysis by
revisiting the arithmetic rules and analyzing the probability distribution of
the network output within a spatial region. We model this distribution
efficiently as a Gaussian distribution by applying the central limit theorem.
Excluding low probability values, we are able to tighten the output bounds,
resulting in a more accurate estimation of the value range, and hence more
accurate identification of iso-surface cells and more efficient iso-surface
extraction on INRs. Our approach demonstrates superior performance in terms of
the iso-surface extraction time on four datasets compared to the original range
analysis method and can also be generalized to other geometric query tasks.


  Lossless variable-length source coding with unequal cost function is
considered for general sources. In this problem, the codeword cost instead of
codeword length is important. The infimum of average codeword cost has already
been determined for general sources. We consider the overflow probability of
codeword cost and determine the infimum of achievable overflow threshold. Our
analysis is on the basis of information-spectrum methods and hence valid
through the general source.


  The IEEE 802.11ad standard extends WiFi operation to the millimeter wave
frequencies, and introduces novel features concerning both the physical (PHY)
and Medium Access Control (MAC) layers. However, while there are extensive
research efforts to develop mechanisms for establishing and maintaining
directional links for mmWave communications, fewer works deal with transmission
scheduling and the hybrid MAC introduced by the standard. The hybrid MAC layer
provides for two different kinds of resource allocations: Contention Based
Access Periods (CBAPs) and contention free Service Periods (SPs). In this
paper, we propose a Markov Chain model to represent CBAPs, which takes into
account operation interruptions due to scheduled SPs and the deafness and
hidden node problems that directional communication exacerbates. We also
propose a mathematical analysis to assess interference among stations. We
derive analytical expressions to assess the impact of various transmission
parameters and of the Data Transmission Interval configuration on some key
performance metrics such as throughput, delay and packet dropping rate. This
information may be used to efficiently design a transmission scheduler that
allocates contention-based and contention-free periods based on the application
requirements.


  I consider a family of games with corresponding payoff matrices, parametrized
by the parameter The informal question of interest is: what game is the best?
Instead of attempting to suggest a more or less arbitrary definition of the
best game, I allow natural selection to find it through honest competition
between games. Specifically, I consider a model of a community composed of
populations with different payoff matrices and study the natural selection
between the populations. The outcome of the community evolution determines the
best game. I develop here a mathematical toolbox, that allows the study of
evolution of parametrized games. The developed approach is applied to three
examples of parametrized games from the literature: local replicator dynamics,
pairwise competition and the game of alleles in diploid genomes.


  Multi-agent consensus problems can often be seen as a sequence of autonomous
and independent local choices between a finite set of decision options, with
each local choice undertaken simultaneously, and with a shared goal of
achieving a global consensus state. Being able to estimate probabilities for
the different outcomes and to predict how long it takes for a consensus to be
formed, if ever, are core issues for such protocols.
  Little attention has been given to protocols in which agents can remember
past or outdated states. In this paper, we propose a framework to study what we
call \emph{memory consensus protocol}. We show that the employment of memory
allows such processes to always converge, as well as, in some scenarios, such
as cycles, converge faster. We provide a theoretical analysis of the
probability of each option eventually winning such processes based on the
initial opinions expressed by agents. Further, we perform experiments to
investigate network topologies in which agents benefit from memory on the
expected time needed for consensus.


  The analysis of the resonant spin-flavour (RSF) solutions to the solar
neutrino problem in the framework of simplest analytic solutions to the solar
magneto-hydrodynamics (MHD) equations is presented. We performed the global fit
of the recent solar neutrino data, including event rates as well as day and
night recoil electron spectra induced by solar neutrino interactions in
SuperKamiokande. We compare quantitatively our simplest MHD-RSF fit with vacuum
oscillation (VAC) and MSW--type (SMA, LMA and LOW) solutions to the solar
neutrino problem using a common well-calibrated theoretical calculation and fit
procedure and find MHD-RSF fit to be somewhat better than those obtained for
the favored neutrino oscillation solutions. We made the predictions for future
experiments to disentangle the MHD-RSF scenario from other scenarios.


  Nitrogen is the most common element in Earth's atmosphere and also appears to
be present in significant amounts in the mantle. However, its long-term cycling
between these two reservoirs remains poorly understood. Here a range of biotic
and abiotic mechanisms are evaluated that could have caused nitrogen exchange
between Earth's surface and interior over time. In the Archean, biological
nitrogen fixation was likely strongly limited by nutrient and/or electron
acceptor constraints. Abiotic fixation of dinitrogen becomes efficient in
strongly reducing atmospheres, but only once temperatures exceed around 1000 K.
Hence if atmospheric N2 levels really were as low as they are today 3.0 - 3.5
Ga, the bulk of Earth's mantle nitrogen must have been emplaced in the Hadean,
most likely at a time when the surface was molten. The elevated atmospheric N
content on Venus compared to Earth can be explained abiotically by a water loss
redox pump mechanism, where oxygen liberated from H2O photolysis and subsequent
H loss to space oxidises the mantle, causing enhanced outgassing of nitrogen.
This mechanism has implications for understanding the partitioning of other
Venusian volatiles and atmospheric evolution on exoplanets.


  Our recent study using historic data of paddy yield and associated conditions
include humidity, luminescence, and temperature. By incorporating regression
models and neural networks (NN), one can produce highly satisfactory
forecasting of paddy yield. Simulations indicate that our model can predict
paddy yield with high accuracy while concurrently detecting diseases that may
exist and are oblivious to the human eye. Crop Yield Prediction Using
Regression and Neural Networks (CYPUR-NN) is developed here as a system that
will facilitate agriculturists and farmers to predict yield from a picture or
by entering values via a web interface. CYPUR-NN has been tested on stock
images and the experimental results are promising.


  We present Risk Integrated's Enterprise Spreadsheet Platform (ESP), a
technical approach to the near-elimination of spreadsheet risk in the
enterprise computing environment, whilst maintaining the full flexibility of
spreadsheets for modelling complex financial structures and processes. In its
Basic Mode of use, the system comprises a secure and robust centralised
spreadsheet management framework. In Advanced Mode, the system can be viewed as
a robust computational framework whereby users can "submit jobs" to the
spreadsheet, and retrieve the results from the computations, but with no direct
access to the underlying spreadsheet. An example application, Monte Carlo
simulation, is presented to highlight the benefits of this approach with regard
to mitigating spreadsheet risk in complex, mission-critical, financial
calculations.


  Classical gravitational bremsstrahlung in particle collisions at
transplanckian energies is studied in ${\mathcal M}_4\times {\mathcal T}^d$.
The radiation efficiency $\epsilon\equiv E_{\rm rad}/E_{\rm initial}$ is
computed in terms of the Schwarzschild radius $r_S(\sqrt{s})$, the impact
parameter $b$ and the Lorentz factor $\gamma_{\rm cm}$ and found to be
$\epsilon=C_d (r_S/b)^{3d+3} \gamma_{\rm cm}^{2d+1}$, larger than previous
estimates by many powers of $\gamma_{\rm cm}\gg 1$. The result is reliable for
impact parameters in the overlap of $r_S<b<b_c {\rm and} b>\lambda_C$, with
$b_c$ marking (for $d\neq 0$) the loss of the notion of classical trajectories
and $\lambda_C\equiv \hbar/mc$ the Compton length of the scattered particles.
The condition on $s$ and $m$ for extreme radiation damping and (presumably) no
black hole production is also derived.


  We present near-infrared spectroscopy and Hubble Space Telescope (HST)
imaging of EROJ003707+0909.5, the brightest of three gravitationally-lensed
images of an Extremely Red Object (ERO) at z=1.6, in the field of the massive
cluster A68 (z=0.255). We exploit the superlative resolution of our HST data
and the enhanced spatial resolution and sensitivity afforded by the lens
amplification to reconstruct the source-plane properties of this ERO. Our
morphological and photometric analysis reveals that EROJ003707 is an L*
early-type disk-galaxy and we estimate that ~10 per cent of EROs with
(R-K)>=5.3 and K<=21 may have similar properties. The unique association of
passive EROs with elliptical galaxies therefore appears to be too simplistic.
We speculate on the evolution of EROJ003707: if gas continues to cool onto this
galaxy in the manner predicted by hierarchical galaxy formation models, then by
the present day, EROJ003707 could evolve into a very luminous spiral galaxy.


  A uniform matrix product state defined on a tripartite system of spins,
denoted by $ABC,$ is shown to be an approximate quantum Markov chain when the
size of subsystem $B,$ denoted $|B|,$ is large enough. The quantum conditional
mutual information (QCMI) is investigated and proved to be bounded by a
function proportional to $\exp(-q(|B|-K)+2K\ln|B|)$, with $q$ and $K$
computable constants. The properties of the bounding function are derived by a
new approach, with a corresponding improved value given for its asymptotic
decay rate $q$. We show the improved value of $q$ to be optimal. Numerical
investigations of the decay of QCMI are reported for a collection of matrix
product states generated by selecting the defining isometry with respect to
Haar measure.


  A matching on a set $X$ is a collection of pairwise disjoint subsets of $X$
of size two. Using computers, we analyze the integral homology of the matching
complex $M_n$, which is the simplicial complex of matchings on the set $\{1,
>..., n\}$. The main result is the detection of elements of order $p$ in the
homology for $p \in \{5,7,11,13\}$. Specifically, we show that there are
elements of order 5 in the homology of $M_n$ for $n \ge 18$ and for $n \in
{14,16}$. The only previously known value was $n = 14$, and in this particular
case we have a new computer-free proof. Moreover, we show that there are
elements of order 7 in the homology of $M_n$ for all odd $n$ between 23 and 41
and for $n=30$. In addition, there are elements of order 11 in the homology of
$M_{47}$ and elements of order 13 in the homology of $M_{62}$. Finally, we
compute the ranks of the Sylow 3- and 5-subgroups of the torsion part of
$H_d(M_n;Z)$ for $13 \le n \le 16$; a complete description of the homology
already exists for $n \le 12$. To prove the results, we use a
representation-theoretic approach, examining subcomplexes of the chain complex
of $M_n$ obtained by letting certain groups act on the chain complex.


  We present a general formulation to analyze the structure of slowly rotating
relativistic stars in a broad class of scalar-tensor theories with disformal
coupling to matter. Our approach includes theories with generalized kinetic
terms, generic scalar field potentials and contains theories with conformal
coupling as particular limits. In order to investigate how the disformal
coupling affects the structure of relativistic stars, we propose a minimal
model of a massless scalar-tensor theory and investigate in detail how the
disformal coupling affects the spontaneous scalarization of slowly rotating
neutron stars. We show that for negative values of the disformal coupling
parameter between the scalar field and matter, scalarization can be suppressed,
while for large positive values of the disformal coupling parameter stellar
models cannot be obtained. This allows us to put a mild upper bound on this
parameter. We also show that these properties can be qualitatively understood
by linearizing the scalar field equation of motion in the background of a
general-relativistic incompressible star. To address the intrinsic degeneracy
between uncertainties in the equation-of-state of neutron stars and
gravitational theory, we also show the existence of universal
equation-of-state-independent relations between the moment of inertia and
compactness of neutron stars in this theory. We show that in a certain range of
the theory's parameter space the universal relation largely deviates from that
of general relativity, allowing, in principle, to probe the existence of
spontaneous scalarization with future observations.


  Water is ubiquitously important but least known. This perspective features
the latest finding of two exotic forms of water called quasisolid and
supersolid phases due to the cooperativity and disparity of the O:H-O bond in
its segmental length, energy, and specific heat when subjected to thermal,
electric, and undercoordination perturbation. The quasisolid (QS) phase only
appears at temperatures between melting and ice nucleation, regardless of
sample size, and this phase has a negative thermal expansivity (NTE). However,
polarization or molecular undercoordination creates the supersolid phase in
skins of water and ice, droplets, ionic hydration cells, and volumetric water
with a current flow or under a 106 eV/cm electric bias. This phase is
characterized by ~10% H-O bond contraction and vibrating at ~3450 cm-1. The
supersolid has unique properties such as high elasticity, mechanical strength,
optical reflectivity, structure order, thermal stability, diffusivity,
catalytic activity, and chemical reactivity. Liquid-QS-Ice transition with QS
phase energy absorption occurs for water due to H-O bond contraction during
thermal decay but not for the supersolid phase of saturated NaCl solution. The
NTE of the QS fosters ice buoyancy and the supersolidity endows ice
slipperiness, supercooling, superheating, premelting, low-temperature fiber
elasticity, water bridge, and warm water fast cooling, as well as on water
chemistry.


  In this article, stabilization result for the viscoelastic fluid flow problem
governed by Kelvin-Voigt model, that is, convergence of the unsteady solution
to a steady state solution is proved under the assumption that linearized
self-adjoint steady state eigenvalue problem has a minimal positive eigenvalue.
Both power and exponential convergence results are derived under various
conditions on the forcing function. It is shown that results are valid
uniformly in the time relaxation or some times called regularization parameter
$\kappa$ as $\kappa\to 0$, which in turn, establishes results for the
Navier-Stokes system.


  We prove that a finitely generated group contains a sequence of non-trivial
elements which converge to the identity in every compact homomorphic image if
and only if the group is not virtually abelian.