  The integrated exploitation of data sources in the mobility domain is key to
providing added-value services to passengers, transport companies and
authorities. Indeed, multiple stakeholders operate and maintain different kinds
of data but several interoperability issues limit their effective usage. In
this paper, we present an architecture enabled by Semantic Web technologies to
overcome such issues and facilitate the development of an integrated solution
for mobility stakeholders. The proposed solution is composed of different
components that address challenges for enabling data interoperability, from the
findability of data sources to their integrated consumption adopting
standardised data formats. We report on the implementation and validation in
four European cities of the TANGENT solution enabling data-driven tools for the
dynamic management of multimodal traffic. Finally, we discuss the feedback
received by users testing the solution and the lessons learnt during its
development.


  This paper presents a Bayesian image segmentation model based on Potts prior
and loopy belief propagation. The proposed Bayesian model involves several
terms, including the pairwise interactions of Potts models, and the average
vectors and covariant matrices of Gauss distributions in color image modeling.
These terms are often referred to as hyperparameters in statistical machine
learning theory. In order to determine these hyperparameters, we propose a new
scheme for hyperparameter estimation based on conditional maximization of
entropy in the Potts prior. The algorithm is given based on loopy belief
propagation. In addition, we compare our conditional maximum entropy framework
with the conventional maximum likelihood framework, and also clarify how the
first order phase transitions in LBP's for Potts models influence our
hyperparameter estimation procedures.


  Employing numerical simulations, we provide an accurate insight into the of
heat transfer mechanisms in the Rayleigh-B\'enard convection of concentrated
emulsions with finite-size droplets. We focus on the unsteady dynamics
characterizing the thermal convection of these complex fluids close to the
transition from conductive to convective states, where the heat transfer
phenomenon, expressed in terms of the Nusselt number Nu, is characterized by
pronounced fluctuations triggered by collective droplets motion [Pelusi et al.,
Soft Matter 17(13), 3709 - 3721 (2021)]. By systematically increasing the
droplet concentration, we show how these fluctuations emerge along with the
segregation of "extreme events" in the boundary layers, causing intermittent
bursts in the heat flux fluctuations. Furthermore, we quantify the extension
$S$ and the duration $\mathcal{T}$ of the coherent droplet motion accompanying
these extreme events via a suitable statistical analysis involving the droplets
displacements. We show how the increase in droplet concentration results in a
power-law behaviour of the probability distribution function of $S$ and
$\mathcal{T}$ and how this outcome is robust at changing the analysis protocol.
Our work offers a comprehensive picture, linking macroscopic heat transfer
fluctuations with the statistics of droplets at the mesoscale.


  We show that the photon self-energy in quantum electrodynamics on
noncommutative $\mathbb{R}^4$ is renormalizable to all orders (both in $\theta$
and $\hbar$) when using the Seiberg-Witten map. This is due to the enormous
freedom in the Seiberg-Witten map which represents field redefinitions and
generates all those gauge invariant terms in the $\theta$-deformed classical
action which are necessary to compensate the divergences coming from loop
integrations.


  It has been recently shown that molecular clouds do not exhibit a unique
shape for the column density probability distribution function (Npdf). Instead,
clouds without star formation seem to possess a lognormal distribution, while
clouds with active star formation develope a power-law tail at high column
densities. The lognormal behavior of the Npdf has been interpreted in terms of
turbulent motions dominating the dynamics of the clouds, while the power-law
behavior occurs when the cloud is dominated by gravity. In the present
contribution we use thermally bi-stable numerical simulations of cloud
formation and evolution to show that, indeed, these two regimes can be
understood in terms of the formation and evolution of molecular clouds: a very
narrow lognormal regime appears when the cloud is being assembled. However, as
the global gravitational contraction occurs, the initial density fluctuations
are enhanced, resulting, first, in a wider lognormal Npdf, and later, in a
power-law Npdf. We thus suggest that the observed Npdf of molecular clouds are
a manifestation of their global gravitationally contracting state. We also show
that, contrary to recent suggestions, the exact value of the power-law slope is
not unique, as it depends on the projection in which the cloud is being
observed.


  In these notes, we introduce various approaches (GIT, Hodge theory, and KSBA)
to constructing and compactifying moduli spaces. We then discuss the pros and
cons for each approach, as well as some connections between them.


  This paper presents a robust, distributed algorithm to solve general linear
programs. The algorithm design builds on the characterization of the solutions
of the linear program as saddle points of a modified Lagrangian function. We
show that the resulting continuous-time saddle-point algorithm is provably
correct but, in general, not distributed because of a global parameter
associated with the nonsmooth exact penalty function employed to encode the
inequality constraints of the linear program. This motivates the design of a
discontinuous saddle-point dynamics that, while enjoying the same convergence
guarantees, is fully distributed and scalable with the dimension of the
solution vector. We also characterize the robustness against disturbances and
link failures of the proposed dynamics. Specifically, we show that it is
integral-input-to-state stable but not input-to-state stable. The latter fact
is a consequence of a more general result, that we also establish, which states
that no algorithmic solution for linear programming is input-to-state stable
when uncertainty in the problem data affects the dynamics as a disturbance. Our
results allow us to establish the resilience of the proposed distributed
dynamics to disturbances of finite variation and recurrently disconnected
communication among the agents. Simulations in an optimal control application
illustrate the results.


  Obtaining gold standard annotated data for object detection is often costly,
involving human-level effort. Semi-supervised object detection algorithms solve
the problem with a small amount of gold-standard labels and a large unlabelled
dataset used to generate silver-standard labels. But training on the silver
standard labels does not produce good results, because they are
machine-generated annotations. In this work, we design a modified loss function
to train on large silver standard annotated sets generated by a weak annotator.
We include a confidence metric associated with the annotation as an additional
term in the loss function, signifying the quality of the annotation. We test
the effectiveness of our approach on various test sets and use numerous
variations to compare the results with some of the current approaches to object
detection. In comparison with the baseline where no confidence metric is used,
we achieved a 4% gain in mAP with 25% labeled data and 10% gain in mAP with 50%
labeled data by using the proposed confidence metric.


  The current paradigm of star formation through accretion disks, and
magnetohydrodynamically driven gas ejections, predicts the development of
collimated outflows, rather than expansion without any preferential direction.
We present radio continuum observations of the massive protostar W75N(B)-VLA 2,
showing that it is a thermal, collimated ionized wind and that it has evolved
in 18 years from a compact source into an elongated one. This is consistent
with the evolution of the associated expanding water-vapor maser shell, which
changed from a nearly circular morphology, tracing an almost isotropic outflow,
to an elliptical one outlining collimated motions. We model this behavior in
terms of an episodic, short-lived, originally isotropic, ionized wind whose
morphology evolves as it moves within a toroidal density stratification.


  In this paper, we consider the Reed-Muller (RM) codes. For the first order RM
code, we prove that it is unique in the sense that any linear code with the
same length, dimension and minimum distance must be the first order RM code;
For the second order RM code, we give a constructive linear sub-code family for
the case when m is even. This is an extension of Corollary 17 of Ch. 15 in the
coding book by MacWilliams and Sloane. Furthermore, we show that the specified
sub-codes of length <= 256 have minimum distance equal to the upper bound or
the best known lower bound for all linear codes of the same length and
dimension. As another interesting result, we derive an additive commutative
group of the symplectic matrices with full rank.


  At an early age, human infants are able to learn and build a model of the
world very quickly by constantly observing and interacting with objects around
them. One of the most fundamental intuitions human infants acquire is intuitive
physics. Human infants learn and develop these models, which later serve as
prior knowledge for further learning. Inspired by such behaviors exhibited by
human infants, we introduce a graphical physics network integrated with deep
reinforcement learning. Specifically, we introduce an intrinsic reward
normalization method that allows our agent to efficiently choose actions that
can improve its intuitive physics model the most.
  Using a 3D physics engine, we show that our graphical physics network is able
to infer object's positions and velocities very effectively, and our deep
reinforcement learning network encourages an agent to improve its model by
making it continuously interact with objects only using intrinsic motivation.
We experiment our model in both stationary and non-stationary state problems
and show benefits of our approach in terms of the number of different actions
the agent performs and the accuracy of agent's intuition model.
  Videos are at https://www.youtube.com/watch?v=pDbByp91r3M&t=2s


  The emergence of ChatGPT has been rapid, and although it has demonstrated
positive impacts in certain domains, its influence is not universally
advantageous. Our analysis focuses on ChatGPT's capabilities in Mathematics
Education, particularly in teaching basic Linear Algebra. While there are
instances where ChatGPT delivers accurate and well-motivated answers, it is
crucial to recognize numerous cases where it makes significant mathematical
errors and fails in logical inference. These occurrences raise concerns
regarding the system's genuine understanding of mathematics, as it appears to
rely more on visual patterns rather than true comprehension. Additionally, the
suitability of ChatGPT as a teacher for students also warrants consideration.


  The aim of this paper is to study the continuity correction for barrier
options in jump-diusion models. For this purpose, we express the pay-off a
barrier option in terms of the maximum of the underlying process. We then
condition with respect to the jump times and to the values of the underlying at
the jump times and rely on the connection between the maximum of the Brownian
motion and Bessel processes.


  We consider the Euler equations on $\mathbb{T}^d$ with analytic data and
prove lower bounds for the radius of spatial analyticity $\epsilon(t)$ of the
solution using a new method based on inductive estimates in standard Sobolev
spaces. Our results are consistent with similar previous results proved by
Kukavica and Vicol, but give a more precise dependence of $\epsilon(t)$ on the
radius of analyticity of the initial datum.


  Degradation of metal-insulator-semiconductor (MIS) capacitors of
gold/Parylene-C/Pentacene under constant voltage stress (CVS) was investigated
to explore the electrical stability and reliability of Parylene C as a gate
dielectric in flexible electronics. A stress voltage of fixed magnitude as high
as 20 V, both negative and positive in polarity, was applied to each MIS
capacitor at room temperature for a fixed duration as long as 10 s. The CVS
effects on the capacitance-voltage curve-shift, the time-dependent leakage
current, and the time-dependent dielectric breakdown were measured and
analyzed. CVS is observed to induce charge in Parylene-C and its interfaces
with gold and Pentacene. The net induced charge is positive and negative for,
respectively, negative and positive gate bias polarity during CVS. The
magnitude of the charge accumulated following positive gate CVS is
significantly higher than that following negative gate bias CVS in the range of
4 to 25 nC cm$^{-2}$. In contrast, the leakage current during the negative gate
stress is three orders of magnitude higher than that during the positive gate
stress for the same bias stress magnitude. The charge buildup and leakage
current are due to the trapping of electrons and holes near the
Parylene-C/Pentacene interface as well as in the Parylene-C layer. Before the
application of the CVS, a dielectric breakdown occurs at an electric field of
1.62 MV cm$^{-1}$. After the application of the CVS, the breakdown voltage
decreases and the density of the trapped charges increases as the stress
voltage increases in magnitude, with the polarity of the trapped charges
opposite to that of the stress voltage. The magnitude and direction of the
capacitance-voltage curve-shift depend on the trapping and recombination of
electrons and holes in the Parylene-C layer and in the proximity of the
Parylene-C/Pentacene interface during CVS.


  Many theoretical models of Active Galactic Nuclei (AGN) predict that the
X-ray corona, lying above the black hole, constitutes the base of the X-ray
jet. Thus, by studying the exact geometry of the close black hole environment,
we can pinpoint the launching site of the jet. Detection of negative X-ray
reverberation time delays (i.e. soft band X-ray variations lagging behind the
corresponding hard band X-ray variations) can yield significant information
about the geometrical properties of the AGN, such as the location of the X-ray
source, as well as the physical properties of the the black hole, such as its
mass and spin. In the frame-work of the lamp-post geometry, I present the first
systematic X-ray time-lag modelling results of an ensemble of 12 AGN, using a
fully general relativistic (GR) ray tracing approach for the estimation of the
systems' response functions. By combing these state-of-the art GR response
models with statistically innovative fitting routines, I derive the geometrical
layout of the close BH environment for each source, unveiling the position of
the AGN jet-base.


  We construct a space-time parallel method for solving parabolic partial
differential equations by coupling the Parareal algorithm in time with
overlapping domain decomposition in space. The goal is to obtain a
discretization consisting of "local" problems that can be solved on parallel
computers efficiently. However, this introduces significant sources of error
that must be evaluated. Reformulating the original Parareal algorithm as a
variational method and implementing a finite element discretization in space
enables an adjoint-based a posteriori error analysis to be performed. Through
an appropriate choice of adjoint problems and residuals the error analysis
distinguishes between errors arising due to the temporal and spatial
discretizations, as well as between the errors arising due to incomplete
Parareal iterations and incomplete iterations of the domain decomposition
solver. We first develop an error analysis for the Parareal method applied to
parabolic partial differential equations, and then refine this analysis to the
case where the associated spatial problems are solved using overlapping domain
decomposition. These constitute our Time Parallel Algorithm (TPA) and
Space-Time Parallel Algorithm (STPA) respectively. Numerical experiments
demonstrate the accuracy of the estimator for both algorithms and the
iterations between distinct components of the error.


  In this article, we have done a thorough investigation of the possible
effects of interaction between dark matter (DM) and neutrinos on reionization
history. We have constrained the interaction strength using 21 cm Cosmology and
found out possible deviations from standard, non-interacting $\Lambda$CDM
scenario. Comparing the results with the existing constraints from present
cosmological observations reveals that 21 cm observations are more competent to
constrain the interaction strength by a few orders of magnitude. We have also
searched for prospects of detecting any such interaction in the upcoming 21 cm
mission SKA1-Low by doing a forecast analysis and error estimation.


  In [J. Math. Phys. 51 (2010) 022104] a self-adjoint operator was introduced
that has the property that it indicates the direction of time within the
framework of standard quantum mechanics, in the sense that as a function of
time its expectation value decreases monotonically for any initial state. In
this paper we study some of this operator's properties. In particular, we
derive its spectrum and generalized eigenstates, and treat the example of the
free particle.


  We propose a simple description of the spectrum of edge states in the quantum
Hall regime, in terms of semiclassical quantization of skipping orbits along
hard wall boundaries, ${\cal A}=2 \pi (n+\gamma) \ell_B^2$, where ${\cal A}$ is
the area enclosed between a skipping orbit and the wall and $\ell_B$ is the
magnetic length. Remarkably, this description provides an excellent
quantitative agreement with the exact spectrum. We discuss the value of
$\gamma$ when the skipping orbits touch one or two edges, and its variation
when the orbits graze the edges and the semiclassical quantization has to be
corrected by diffraction effects. The value of $\gamma$ evolves continuously
from $1/2$ to $3/4$. We calculate the energy dependence of the drift velocity
along the different Landau levels. We compare the structure of the
semiclassical cyclotron orbits, their position with respect to the edge, to the
wave function of the corresponding eigenstates.


  The new measurement of $W$-boson mass by the CDF collaboration revealed a
remarkable $7\sigma$ disagreement with the Standard Model (SM) prediction. If
confirmed by other experiments, then the disagreement strongly indicates the
existence of new physics beyond the SM. In this work, seven vectorlike quark
(VLQ) extensions of the SM are investigated to interpret the anomaly, and it is
found that three can explain the anomaly in broad parameter space. The
explanations are consistent with the constraints from oblique parameters, the
LHC search for VLQs, the measurements of the properties for the top quark,
bottom quark, and Higgs boson, and the perturbativity criterion. The typical
size of the involved Yukawa coupling is around 1, which is comparable to the
top quark Yukawa coupling in the SM. The other extensions, however, either
predict a negative correction to the mass in reasonable parameter space or
explain the anomaly by unnatural theoretical input parameters.


  Let $K$ be a field of characteristic $p>0$. It is proved that each
automorphism $\s \in \Aut_K(\CDPn)$ of the ring $\CDPn$ of differential
operators on a polynomial algebra $P_n= K[x_1, ..., x_n]$ is {\em uniquely}
determined by the elements $\s (x_1), ... ,\s (x_n)$, and the set $\Frob
(\CDPn)$ of all the extensions of the Frobenius from certain maximal
commutative polynomial subalgebras of $\CDPn$, like $P_n$, is equal to
$\Aut_K(\CDPn) \cdot \CF$ where $\CF$ is the set of all the extensions of the
Frobenius from $P_n$ to $\CDPn$ that leave invariant the subalgebra of scalar
differential operators. The set
  $\CF$ is found explicitly, it is large (a typical extension depends on {\em
countably} many independent parameters).


  The application of the Reformulation Linearization Technique (RLT) to the
Quadratic Assignment Problem (QAP) leads to a tight linear relaxation with huge
dimensions that is hard to solve. Previous works found in the literature show
that these relaxations combined with branch-and-bound algorithms belong to the
state-of-the-art of exact methods for the QAP. For the level 3 RLT (RLT3),
using this relaxation is prohibitive in conventional machines for instances
with more than 22 locations due to memory limitations. This paper presents a
distributed version of a dual ascent algorithm for the RLT3 QAP relaxation that
approximately solves it for instances with up to 30 locations for the first
time. Although, basically, the distributed algorithm has been implemented on
top of its sequential conterpart, some changes, which improved not only the
parallel performance but also the quality of solutions, were proposed here.
When compared to other lower bounding methods found in the literature, our
algorithm generates the best known lower bounds for 26 out of the 28 tested
instances, reaching the optimal solution in 18 of them.


  Foundation Models (FMs) have demonstrated remarkable insights into the
relational dynamics of the world, leading to the crucial question: how do these
models acquire an understanding of world hybrid relations? Traditional
statistical learning, particularly for prediction problems, may overlook the
rich and inherently structured information from the data, especially regarding
the relationships between objects. We introduce a mathematical model that
formalizes relational learning as hypergraph recovery to study pre-training of
FMs. In our framework, the world is represented as a hypergraph, with data
abstracted as random samples from hyperedges. We theoretically examine the
feasibility of a Pre-Trained Model (PTM) to recover this hypergraph and analyze
the data efficiency in a minimax near-optimal style. By integrating rich graph
theories into the realm of PTMs, our mathematical framework offers powerful
tools for an in-depth understanding of pre-training from a unique perspective
and can be used under various scenarios. As an example, we extend the framework
to entity alignment in multimodal learning.


  This article begins with a study of convex effect-state spaces. We point out
that such spaces are equivalent to interval effect algebras that generate an
ordered linear space and possess an order-determining set of states. We then
discuss operations and instruments on interval effect algebras under the
assumption of an unrestrictive condition. Effects measured by operations and
sequential products of effects relative to operations are considered.
Observables are introduced and coexistence of effects are discussed. We also
present properties of sequential products of observables and conditioning of
observables related to instruments. The final section is devoted to Holevo
instruments. Pure and mixed Holevo operations are defined and extended to
instruments. The Holevo sequential product of two observables is defined and
the marginals of these products are computed. We define the commutant of two
effects and derive its properties. Examples are given that illustrate the
properties of previously presented concepts.


  We model the synthesis of molecules and dust in the inner wind of the
oxygen-rich Mira-type star IK Tau, by considering the effects of periodic
shocks induced by the stellar pulsation on the gas, and by following the
non-equilibrium chemistry in the shocked gas layers between 1 and 10 Rstar. We
consider a complete set of molecules and dust clusters, and combine the
nucleation phase of dust formation with the condensation of these clusters into
dust grains. Our derived molecular abundances and dust properties are compared
to the most recent observational data. The chemistry is described by using a
chemical kinetic network of reactions and the condensation mechanism is
described by a Brownian formalism. The shocks drive an active non-equilibrium
chemistry in the dust formation zone of IK Tau where the collision destruction
of CO in the post-shock gas triggers the formation of C-bearing species such as
HCN and CS. Most of the modelled molecular abundances agree well with the
latest values derived from Herschel data. Clusters of alumina are produced
within 2 Rstar and lead to a population of alumina grains close to the stellar
surface. Clusters of silicates form at larger radii (r > 3 Rstar), where their
nucleation is triggered by the formation of HSiO and H2SiO. They efficiently
condense and reach their final grain size distribution between ~ 6 and 8 Rstar,
with a major population of medium size grains peaking at~ 0.02 microns. This
two dust-shell configuration agrees with recent interferometric observations.
The derived dust-to-gas mass ratio for IK Tau is in the range 1-6x10^-3 and
agrees with values derived from observations of O-rich Mira-type stars. Our
results confirm the importance of periodic shocks in chemically shaping the
inner wind of AGB stars and providing gas conditions conducive to the efficient
synthesis of molecules and dust by non-equilibrium processes.


  The Data Web refers to the vast and rapidly increasing quantity of
scientific, corporate, government and crowd-sourced data published in the form
of Linked Open Data, which encourages the uniform representation of
heterogeneous data items on the web and the creation of links between them. The
growing availability of open linked datasets has brought forth significant new
challenges regarding their proper preservation and the management of evolving
information within them. In this paper, we focus on the evolution and
preservation challenges related to publishing and preserving evolving linked
data across time. We discuss the main problems regarding their proper modelling
and querying and provide a conceptual model and a query language for modelling
and retrieving evolving data along with changes affecting them. We present in
details the syntax of the query language and demonstrate its functionality over
a real-world use case of evolving linked dataset from the biological domain.


  Blind face restoration usually relies on facial priors, such as facial
geometry prior or reference prior, to restore realistic and faithful details.
However, very low-quality inputs cannot offer accurate geometric prior while
high-quality references are inaccessible, limiting the applicability in
real-world scenarios. In this work, we propose GFP-GAN that leverages rich and
diverse priors encapsulated in a pretrained face GAN for blind face
restoration. This Generative Facial Prior (GFP) is incorporated into the face
restoration process via novel channel-split spatial feature transform layers,
which allow our method to achieve a good balance of realness and fidelity.
Thanks to the powerful generative facial prior and delicate designs, our
GFP-GAN could jointly restore facial details and enhance colors with just a
single forward pass, while GAN inversion methods require expensive
image-specific optimization at inference. Extensive experiments show that our
method achieves superior performance to prior art on both synthetic and
real-world datasets.


  We propose a multiple imputation method to deal with incomplete categorical
data. This method imputes the missing entries using the principal components
method dedicated to categorical data: multiple correspondence analysis (MCA).
The uncertainty concerning the parameters of the imputation model is reflected
using a non-parametric bootstrap. Multiple imputation using MCA (MIMCA)
requires estimating a small number of parameters due to the dimensionality
reduction property of MCA. It allows the user to impute a large range of data
sets. In particular, a high number of categories per variable, a high number of
variables or a small the number of individuals are not an issue for MIMCA.
Through a simulation study based on real data sets, the method is assessed and
compared to the reference methods (multiple imputation using the loglinear
model, multiple imputation by logistic regressions) as well to the latest works
on the topic (multiple imputation by random forests or by the Dirichlet process
mixture of products of multinomial distributions model). The proposed method
shows good performances in terms of bias and coverage for an analysis model
such as a main effects logistic regression model. In addition, MIMCA has the
great advantage that it is substantially less time consuming on data sets of
high dimensions than the other multiple imputation methods.


  We initiate the study of trade-offs between sparsity and the number of
measurements in sparse recovery schemes for generic norms. Specifically, for a
norm $\|\cdot\|$, sparsity parameter $k$, approximation factor $K>0$, and
probability of failure $P>0$, we ask: what is the minimal value of $m$ so that
there is a distribution over $m \times n$ matrices $A$ with the property that
for any $x$, given $Ax$, we can recover a $k$-sparse approximation to $x$ in
the given norm with probability at least $1-P$? We give a partial answer to
this problem, by showing that for norms that admit efficient linear sketches,
the optimal number of measurements $m$ is closely related to the doubling
dimension of the metric induced by the norm $\|\cdot\|$ on the set of all
$k$-sparse vectors. By applying our result to specific norms, we cast known
measurement bounds in our general framework (for the $\ell_p$ norms, $p \in
[1,2]$) as well as provide new, measurement-efficient schemes (for the
Earth-Mover Distance norm). The latter result directly implies more succinct
linear sketches for the well-studied planar $k$-median clustering problem.
Finally, our lower bound for the doubling dimension of the EMD norm enables us
to address the open question of [Frahling-Sohler, STOC'05] about the space
complexity of clustering problems in the dynamic streaming model.


  Condensation and sublimation of ices at the surface of the planet is a key
part of both the Martian H$_2$O and CO$_2$ cycles, either from a seasonal or
diurnal aspect. While most of the ice is located within the polar caps, surface
frost is known to be formed during nighttime down to equatorial latitudes.
Here, we use data from the Emirates Mars Infrared Spectrometer (EMIRS) onboard
the Emirates Mars Mission (EMM) to monitor the diurnal and seasonal evolution
of the ices at the surface of Mars over almost one Martian year. The unique
local time coverage provided by the instrument allows us to observe the
apparition of equatorial CO$_2$ frost in the second half of the Martian night
around the equinoxes, to its sublimation at sunrise.


  We analyze the stability of recurrent networks, specifically, reservoir
computing models during training by evaluating the eigenvalue spectra of the
reservoir dynamics. To circumvent the instability arising in examining a closed
loop reservoir system with feedback, we propose to break the closed loop
system. Essentially, we unroll the reservoir dynamics over time while
incorporating the feedback effects that preserve the overall temporal integrity
of the system. We evaluate our methodology for fixed point and time varying
targets with least squares regression and FORCE training, respectively. Our
analysis establishes eigenvalue spectra (which is, shrinking of spectral circle
as training progresses) as a valid and effective metric to gauge the
convergence of training as well as the convergence of the chaotic activity of
the reservoir toward stable states.


  We study planar random motions with finite velocities, of norm $c>0$, along
orthogonal directions and changing at the instants of occurrence of a
non-homogeneous Poisson process with rate function $\lambda(t),\ t\ge0$. We
focus on the distribution of the current position $\bigl(X(t), Y(t)\bigr),\
t\ge0$, in the case where the motion has orthogonal deviations and where also
reflection is admitted. In all the cases the process is located within the
closed square $S_{ct}=\{(x,y)\in \mathbb{R}^2\,:\,|x|+|y|\le ct\}$ and we
obtain the probability law inside $S_{ct}$, on the edge $\partial S_{ct}$ and
on the other possible singularities, by studying the partial differential
equations governing all the distributions examined. A fundamental result is
that the vector process $\bigl(X(t), Y(t)\bigr)$ is probabilistically
equivalent to a linear transformation of two (independent or dependent)
one-dimensional symmetric telegraph processes with rate function proportional
to $\lambda(t)$ and velocity $c/2$. Finally, we extend the results to a wider
class of orthogonal-type evolutions.


  Image processing is popular in our daily life because of the need to extract
essential information from our 3D world, including a variety of applications in
widely separated fields like bio-medicine, economics, entertainment, and
industry. The nature of visual information, algorithm complexity, and the
representation of 3D scenes in 2D spaces are all popular research topics. In
particular, the rapidly increasing volume of image data as well as increasingly
challenging computational tasks have become important driving forces for
further improving the efficiency of image processing and analysis. Since the
concept of quantum computing was proposed by Feynman in 1982, many achievements
have shown that quantum computing has dramatically improved computational
efficiency [1]. Quantum information processing exploit quantum mechanical
properties, such as quantum superposition, entanglement and parallelism, and
effectively accelerate many classical problems like factoring large numbers,
searching an unsorted database, Boson sampling, quantum simulation, solving
linear systems of equations, and machine learning. These unique quantum
properties may also be used to speed up signal and data processing. In quantum
image processing, quantum image representation plays a key role, which
substantively determines the kinds of processing tasks and how well they can be
performed.


  We propose a simple scheme for magnetic angular position sensor based on
current-induced spin-orbit torque effect. A full range detection of 360o is
realized with a pair of Hall crosses made of heavy metal/ferromagnet
heterostructures. The current axes of the two Hall crosses are aligned
orthogonal to each other such that when both devices are subject to a
rotational in-plane magnetic field, the differential Hall voltage due to
current pulses of opposite polarity exhibits a sine and cosine angular
dependence on the field direction, respectively. The field rotational angle is
then calculated from the sine and cosine output signals via the arctan2
function. A linear correspondence between the calculated and actual field angle
is obtained in the field range of 500-2000 Oe, with an average angle error of
0.38-0.65o.


  In the literature, two quite different phase-field formulations for the
problem of alloy solidification can be found. In the first, the material in the
diffuse interfaces is assumed to be in an intermediate state between solid and
liquid, with a unique local composition. In the second, the interface is seen
as a mixture of two phases that each retain their macroscopic properties, and a
separate concentration field for each phase is introduced. It is shown here
that both types of models can be obtained by the standard variational procedure
if a grand-potential functional is used as a starting point instead of a
free-energy functional. The dynamical variable is then the chemical potential
instead of the composition. In this framework, a complete analogy with
phase-field models for the solidification of a pure substance can be
established. This analogy is then exploited to formulate quantitative
phase-field models for alloys with arbitrary phase diagrams. The precision of
the method is illustrated by numerical simulations with varying interface
thickness.


  The Dodgson/Muir Identity is an identity on determinants of matrix minors
that generalizes the Dodgson Identity. Using the matrix tree theorem, we create
an equivalent forest identity on ordered sets of $k$ forests. We then prove the
generalized Forest Identity, and by extension the Dodgson/Muir Identity, using
an edge-swapping involution. This algorithm is a generalization of the Red Hot
Potato algorithm, developed by the author in 2021 to prove the Dodgson
Identity.


  Macroscopic models of crowd flow incorporating individual pedestrian choices
present many analytic and computational challenges. Anisotropic interactions
are particularly subtle, both in terms of describing the correct "optimal"
direction field for the pedestrians and ensuring that this field is uniquely
defined. We develop sufficient conditions, which establish a range of "safe"
densities and parameter values for each model. We illustrate our approach by
analyzing several established intra-crowd and inter-crowd models. For the
two-crowd case, we also develop sufficient conditions for the uniqueness of
Nash Equilibria in the resulting non-zero-sum game.


  The rise in popularity of text-to-image generative artificial intelligence
(AI) has attracted widespread public interest. We demonstrate that this
technology can be attacked to generate content that subtly manipulates its
users. We propose a Backdoor Attack on text-to-image Generative Models (BAGM),
which upon triggering, infuses the generated images with manipulative details
that are naturally blended in the content. Our attack is the first to target
three popular text-to-image generative models across three stages of the
generative process by modifying the behaviour of the embedded tokenizer, the
language model or the image generative model. Based on the penetration level,
BAGM takes the form of a suite of attacks that are referred to as surface,
shallow and deep attacks in this article. Given the existing gap within this
domain, we also contribute a comprehensive set of quantitative metrics designed
specifically for assessing the effectiveness of backdoor attacks on
text-to-image models. The efficacy of BAGM is established by attacking
state-of-the-art generative models, using a marketing scenario as the target
domain. To that end, we contribute a dataset of branded product images. Our
embedded backdoors increase the bias towards the target outputs by more than
five times the usual, without compromising the model robustness or the
generated content utility. By exposing generative AI's vulnerabilities, we
encourage researchers to tackle these challenges and practitioners to exercise
caution when using pre-trained models. Relevant code, input prompts and
supplementary material can be found at https://github.com/JJ-Vice/BAGM, and the
dataset is available at:
https://ieee-dataport.org/documents/marketable-foods-mf-dataset.
  Keywords: Generative Artificial Intelligence, Generative Models,
Text-to-Image generation, Backdoor Attacks, Trojan, Stable Diffusion.


  We present a review on the study of metastable silicon, primarily focusing
mainly on the aspects of liquid-liquid transition, critical point and phase
behaviour, structural and dynamic properties of liquid phase as well as crystal
nucleation. We begin with an extensive survey of the investigations of liquid
silicon pursued over three decades, with salient experimental, theoretical and
simulation results. Following which we present various scenarios put forward to
rationalize the density and related anomalies often observed in water and other
network forming liquids. After which we present the more recent investigations
(both simulation and experimental works) of the phase behavior of Silicon.
Since a significant part of metastable silicon work is on a classical empirical
potential an important question to address is the reliability of this potential
in describing the behavior of silicon. To provide a critical assessment of the
applicability of classical simulation results to real silicon we present a
comparison of the structural, dynamical, and thermodynamic quantities obtained
from the SW potential with those from ab initio simulations and with available
experimental data. We also discuss the sensitivity of the thermodynamic
properties to model parameters.


  Let ${\mathbb M}_{g, 1}$, $g \geq 1$, be the moduli space of triples $(C,
P_0, v)$ of genus $g$, where $C$ is a compact Riemann surface of genus $g$,
$P_0 \in C$, and $v \in T_{P_0}C\setminus\{0\}$. Using Chen's iterated
integrals we introduce a higher analogue of the period matrix for a triple $(C,
P_0, v)$, {\it the harmonic Magnus expansion}. It induces a flat connection on
a vector bundle over the space ${\mathbb M}_{g, 1}$, whose holonomy gives all
the higher Johnson homomorphisms of the mapping class group. The connection
form, which is computed as an explicit quadratic differential, induces
"canonical" differential forms representing (twisted) Morita-Mumford classes
and their higher relators on ${\mathbb M}_{g, 1}$. In particular, we construct
a family of twisted differential forms on ${\mathbb M}_{g, 1}$ representing the
$(0, p+2)$-twisted Morita-Mumford class $m_{0, p+2}$ combinatorially
parametrized by the Stasheff associahedron $K_{p+1}$.


  We establish a characterization of adequate knots in terms of the degree of
their colored Jones polynomial. We show that, assuming the Strong Slope
conjecture, our characterization can be reformulated in terms of "Jones slopes"
of knots and the essential surfaces that realize the slopes .For alternating
knots the reformulated characterization follows by recent work of J. Greene and
J. Howie.


  The peculiar velocity reconstruction methods allow one to have a deeper
insight into the distribution of dark matter: both to measure mean matter
density and to obtain the primordial density fluctuations. We present here the
Monge-Ampere-Kantorovitch method applied to mock catalogues mimicking in both
redshift and distance catalogues. After having discussed the results obtained
for a class of biases that may be corrected for, we focus on the systematics
coming from the unknown distribution of unobserved mass and from the
statistical relationship between mass and luminosity. We then show how to use
these systematics to put constraints on the dark matter distribution. Finally a
preliminary application to an extended version (c z < 3000 km/s) of the
Neighbour Galaxy Catalogue is presented. We recover the peculiar velocities in
our neighbourhood and present a preliminary measurement of the local Omega_M.


  We consider the problem of learning optimal binary classification trees.
Literature on the topic has burgeoned in recent years, motivated both by the
empirical suboptimality of heuristic approaches and the tremendous improvements
in mixed-integer programming (MIP) technology. Yet, existing approaches from
the literature do not leverage the power of MIP to its full extent. Indeed,
they rely on weak formulations, resulting in slow convergence and large
optimality gaps. To fill this gap in the literature, we propose a flow-based
MIP formulation for optimal binary classification trees that has a stronger
linear programming relaxation. Our formulation presents an attractive
decomposable structure. We exploit this structure and max-flow/min-cut duality
to derive a Benders' decomposition method, which scales to larger instances. We
conduct extensive computational experiments on standard benchmark datasets on
which we show that our proposed approaches are 50 times faster than
state-of-the art MIP-based techniques and improve out of sample performance up
to 13.8%.


  The stochastic model that describes radiative heat transfer in dielectric
medium is built. The model is based on the representation that heat transfer is
realized both by heat conductivity mechanism in it and due to the
electromagnetic radiation that is generated by thermal fluctuations of atoms in
the medium. Using the fluctuation-dissipative theorem, on the basis of such
physical suppositions, the stochastic model is formulated in the form of the
infinite dimensional Ornstein-Uhlenbeck process that describes medium
fluctuations. In the model frameworks, the energy flux density of fluctuating
electromagnetic field is calculated in the form of the functional of
temperature distribution in three-dimensional medium sample.


  A very explicit analytic formula of the separability criterion of two-party
Gaussian systems is given. This formula is compared to the past formulation of
the separability criterion of continuous variables two-party Gaussian systems.


  The thermal entanglement is investigated in a two-qubit Heisenberg XXZ system
with Dzyaloshinskii-Moriya (DM) interaction. It is shown that the entanglement
can be efficiently controlled by the DM interaction parameter and coupling
coefficient $J_{z}$. $D_{x}$(the x-component parameter of the DM interaction)
has a more remarkable influence on the entanglement and the critical
temperature than $D_{z}$(the z-component parameter of the DM interaction).
Thus, by the change of DM interaction direction, we can get a more efficient
control parameter to increase the entanglement and the critical temperature.


  Using reinforcement learning to learn control policies is a challenge when
the task is complex with potentially long horizons. Ensuring adequate but safe
exploration is also crucial for controlling physical systems. In this paper, we
use temporal logic to facilitate specification and learning of complex tasks.
We combine temporal logic with control Lyapunov functions to improve
exploration. We incorporate control barrier functions to safeguard the
exploration and deployment process. We develop a flexible and learnable system
that allows users to specify task objectives and constraints in different forms
and at various levels. The framework is also able to take advantage of known
system dynamics and handle unknown environmental dynamics by integrating
model-free learning with model-based planning.


  The goal of the LHCb experiment is the indirect search for New Physics
through precision measurements of B-decays. A short description of the detector
and its performance after the first data taking in 2009 and 2010 will be
presented. In addition first preliminary results of a $\rm K_{s}$ differential
cross section measurement at a center of mass energy of $\sqrt{s} = 900\; \rm
GeV$ and a measurement of the $\frac{\bar{\lambda}}{\lambda}$ production ratio
at $\sqrt{s} = 900\; \rm GeV$ and $\sqrt{s} = 7\; \rm TeV$ will be discussed.


  By an explicit construction, it is shown that the geometry of the SU(3) pion
multiplet with respect to the group manifold SU_L(3) x SU_R(3) maybe deformed
to admit a second pseudoscalar multiplet that is analogous to the Z_0 in
unified theories of the electroweak interactions. This observation is found to
play a key role in the construction of the N = 1 supersymmetric models with
pions and Dirac-like spin-1/2 superpartners ("pionini").


  We present a study on the spatio-temporal pattern underlying the climate
dynamics in various locations spread over India, including the Himalayan
region, coastal region, central and northeastern parts of India. We try to
capture the variations in the complexity of their dynamics derived from
temperature and relative humidity data from 1948-2022. By estimating the
recurrence-based measures from the reconstructed phase space dynamics using a
sliding window analysis on the data sets, we study the climate variability in
different spatial locations. The study brings out the variations in the
complexity of the underlying dynamics as well as their heterogeneity across the
locations in India. We find almost all locations indicate shifts to more
irregular and stochastic dynamics for temperature data around 1972-79 and
shifts back to more regular dynamics beyond 2000. These patterns correlate with
reported shifts in the climate and Indian Summer Monsoon related to strong and
moderate ENSO events and confirm their associated regional variability.


  We show that the query containment problem for monadic datalog on finite
unranked labeled trees can be solved in 2-fold exponential time when (a)
considering unordered trees using the axes child and descendant, and when (b)
considering ordered trees using the axes firstchild, nextsibling, child, and
descendant. When omitting the descendant-axis, we obtain that in both cases the
problem is EXPTIME-complete.


  The transverse radiation pressure force and acceleration is compared for two
parametrically optimized designs: prismatic and two-pillar metasurface
gratings. The numerical results were cross-verified with both Maxwell stress
tensor and modal analysis. Solar blackbody irradiance was assumed for
wavelengths ranging from 0.33 [um] to the grating cutoff at 1.5 [um],
encompassing 83% of the solar constant. This multi-objective optimizer study
found that neither design comprised Si3N4 performed as well as those
corresponding to a low refractive index, low mass density material. The
predicted transverse acceleration of the optimized low-index metasurface
grating is compared to that of a state-of-the-art reflective solar sail.


  Selected topics on halo and molecular states in light, neutron-rich nuclei
are discussed. In particular, work on $x\alpha$:X$n$ structures is briefly
reviewed. The use of proton radiative capture as a probe of clustering is also
presented through the example provided by the $^6$He(p,$\gamma$) reaction.


  Background 15 The success of cementless hip arthroplasty depends on the
primary stability of the femoral stem. It remains difficult to assess the
optimal number of impacts to guarantee the femoral stem stability while
avoiding bone fracture. The aim of this study is to validate a method using a
hammer instrumented with a force sensor to monitor the insertion of femoral
stem in bovine femoral samples. Methods 20 Different cementless femoral stem
were impacted into five bovine femur samples, leading to 99 configurations.
Three methods were used to quantify the insertion endpoint: the impact hammer,
video motion tracking and the surgeon proprioception. For each configuration,
the number of impacts performed by the surgeon until he felt a correct
insertion was noted Nsurg. The insertion depth E was measured through video
motion tracking, and the impact number Nvid corresponding to the end of the
insertion was estimated. Two indicators, noted I and D, 25 were determined from
the analysis of the time variation of the force, and the impact number Nd
corresponding to a threshold reached in D variation was estimated. Findings The
pullout force of the femoral stem was significantly correlated with I
(R${}^2$=0.81). The values of Nsurg, Nvid and Nd were similar for all
configurations. 30 Interpretation The results validate the use of the impact
hammer to assess the primary stability of the femoral stem and the moment when
the surgeon should stop the impaction procedure for an optimal insertion, which
could lead to the development of a decision support system. Abstract: 248
words. Main text: 4658 words


  Emission line Doppler tomography is a powerful tool that resolves the
accretion flow in binaries on micro-arcsecond scales using time-resolved
spectroscopy. I present an extension to Doppler tomography that relaxes one of
its fundamental axioms and permits the mapping of time-dependent emission
sources. Significant variability on the orbital period is a common
characteristic of the emission sources that are observed in the accretion flows
of cataclysmic variables and X-ray binaries. Modulation Doppler tomography maps
sources varying harmonically as a function of the orbital period through the
simultaneous reconstruction of three Doppler tomograms. One image describes the
average flux distribution like in standard tomography, while the two additional
images describe the variable component in terms of its sine and cosine
amplitudes. I describe the implementation of such an extension in the form of
the maximum entropy based fitting code MODMAP. Test reconstructions of
synthetic data illustrate that the technique is robust and well constrained.
Artifact free reconstructions of complex emission distributions can be achieved
under a wide range of signal to noise levels. An application of the technique
is illustrated by mapping the orbital modulations of the asymmetric accretion
disc emission in the dwarf nova IP Pegasi.


  In this paper, we analyze the clustering of galaxies using a modified theory
of gravity, in which the field content of general relativity has been be
increased. This increasing in the field content of general relativity changes
the large distance behavior of the theory, and in weak field approximation, it
will also modify the large distance behavior of Newtonian potential. So, we
will analyzing the clustering of multi-component system of galaxies interacting
through this modified Newtonian potential. We will obtain the partition
function for this multi-component system, and study the thermodynamics of this
system. So, we will analyze the effects of the large distance modification to
the Newtonian potential on Helmholtz free energy, internal energy, entropy,
pressure and chemical potential of this system. We obtain also the modified
distribution function and the modified clustering parameter for this system,
and hence observe the effect of large distance modification of Newtonian
potential on clustering of galaxies.


  Two-dimensional (2D) semiconductors have demonstrated great potential for
next-generation electronics and optoelectronics. An important property for
these applications is the phonon-limited charge carrier mobility. The common
approach to calculate the mobility from first principles relies on the
interpolation of the electron-phonon coupling (EPC) matrix. However, it
neglects the scattering by the dynamical quadrupoles generated by phonons,
limiting its accuracy. Here we present a first-principles method to incorporate
the quadrupole scattering, which results in a much better interpolation quality
and thus a more accurate mobility as exemplified by monolayer MoS2 and InSe.
This method also allows for a natural incorporation of the effects of the free
carriers, enabling us to efficiently compute the screened EPC and thus the
mobility for doped semiconductors. Particularly, we find that the electron
mobility of InSe is more sensitive to the carrier concentration than that of
MoS2 due to the stronger long-range scattering in intrinsic InSe. With
increasing electron concentration, the InSe mobility can reach ~4 times of the
intrinsic value, then decrease owing to the involvement of heavier electronic
states. Our work provides accurate and efficient methods to calculate the
phonon-limited mobility in the intrinsic and doped 2D materials, and improves
the fundamental understanding of their transport mechanism.


  Derived decompositions of abelian categories are introduced in internal terms
of abelian subcategories to construct semi-orthogonal decompositions (or
Bousfield localizations, or hereditary torsion pairs) in various derived
categories of abelian categories. We give a sufficient condition for arbitrary
abelian categories to have such derived decompositions and show that it is also
necessary for abelian categories with enough projectives and injectives. For
bounded derived categories, we describe which semi-orthogonal decompositions
are determined by derived decompositions. The necessary and sufficient
condition is then applied to the module categories of rings: localizing
subcategories, homological ring epimorphisms, commutative noetherian rings and
nonsingular rings. Moreover, for a commutative noetherian ring of Krull
dimension at most $1$, a derived stratification of its module category is
established.


  We study the problem of optimal control of dissipative quantum dynamics.
Although under most circumstances dissipation leads to an increase in entropy
(or a decrease in purity) of the system, there is an important class of
problems for which dissipation with external control can decrease the entropy
(or increase the purity) of the system. An important example is laser cooling.
In such systems, there is an interplay of the Hamiltonian part of the dynamics,
which is controllable and the dissipative part of the dynamics, which is
uncontrollable. The strategy is to control the Hamiltonian portion of the
evolution in such a way that the dissipation causes the purity of the system to
increase rather than decrease. The goal of this paper is to find the strategy
that leads to maximal purity at the final time. Under the assumption that
Hamiltonian control is complete and arbitrarily fast, we provide a general
framework by which to calculate optimal cooling strategies. These assumptions
lead to a great simplification, in which the control problem can be
reformulated in terms of the spectrum of eigenvalues of $\rho$, rather than
$\rho$ itself. By combining this formulation with the Hamilton-Jacobi-Bellman
theorem we are able to obtain an equation for the globaly optimal cooling
strategy in terms of the spectrum of the density matrix. For the three-level
$\Lambda$ system, we provide a complete analytic solution for the optimal
cooling strategy. For this system it is found that the optimal strategy does
not exploit system coherences and is a 'greedy' strategy, in which the purity
is increased maximally at each instant.


  In an earlier paper, a new class of thin-shell cavities were proposed to
evade the steep frequency scaling of conventional axion haloscopes. In this
follow-up work, we see that a generalized conic geometry enables robust
frequency-tuning for these large-volume cm-wave cavities. The
frequency-defining dimension of a conic shell-cavity changes symmetrically and
uniformly during tuning, maintaining a high axion coupling efficiency (the form
factor) to an external solenoid field. It is further shown that such tunable
geometry is not restricted to circular cones. A general prescription for
arbitrary volume-filling conic shell-cavities is developed and direct solutions
are obtained for the created numerical models. The largest of the realized
designs is a meandering "brain" cavity that is tunable over a frequency range
of 20%. The scan rate of this cavity is three orders of magnitude larger than
that of a scaled cylindrical cavity used in the current generation experiments.
The prospects for such a large improvement in the scan rate should motivate R &
D efforts in fabrication and other implementation techniques. If these
engineering challenges can be met, cavity-based axion haloscopes can stay
competitive at frequencies higher than a few GHz. We propose an experimental
configuration at 20 GHz (~ 80 $\mu$eV) using an array of brain cavities and
compare it with other proposals for similar frequencies.


  The response of advection-dominated accretion disks to local disturbances is
examined by one-dimensional numerical simulations. It is generally believed
that advection-dominated disks are thermally stable. We, however, find that any
disurbance added onto accretion flow at large radii does not decay so rapidly
that it can move inward with roughly the free-fall velocity. Although
disturbances continue to be present, the global disk structure will not be
modified largely. This can account for persistent hard X-ray emission with
substantial variations observed in active galactic nuclei and stellar black
hole candidates during the hard state. Moreover, when the disturbance reaches
the innermost parts, an acoustic wave emerges, propagating outward as a shock
wave. The resultant light variation is roughly (time) symmetric and is quite
reminiscent of the observed X-ray shots of Cygnus X-1.


  A detailed analysis of the bremsstrahlung spectrum at nonrelativistic
electron scattering on argon and xenon is carried out. It is shown that the
approximate formulas widely used for the description of bremsstrahlung spectra
lead to predictions that significantly differ from the exact results. In the
limit when the photon frequency tends to zero, a rigorous proof of the
relationship between the spectrum of the bremsstrahlung with a transport cross
section of electron scattering on an atom is given. This proof does not require
any assumptions about the dependence of the scattering phases on energy. For
electron energies lower than the luminescence threshold, it is shown that the
predictions for a number of radiated photons obtained by the exact formula are
in good agreement with the available experimental data.


  We discuss how the method of maximum entropy, MaxEnt, can be extended beyond
its original scope, as a rule to assign a probability distribution, to a
full-fledged method for inductive inference. The main concept is the (relative)
entropy S[p|q] which is designed as a tool to update from a prior probability
distribution q to a posterior probability distribution p when new information
in the form of a constraint becomes available. The extended method goes beyond
the mere selection of a single posterior p, but also addresses the question of
how much less probable other distributions might be. Our approach clarifies how
the entropy S[p|q] is used while avoiding the question of its meaning.
Ultimately, entropy is a tool for induction which needs no interpretation.
Finally, being a tool for generalization from special examples, we ask whether
the functional form of the entropy depends on the choice of the examples and we
find that it does. The conclusion is that there is no single general theory of
inductive inference and that alternative expressions for the entropy are
possible.


  Using quantum devices supported by classical computational resources is a
promising approach to quantum-enabled computation. One example of such a hybrid
quantum-classical approach is the variational quantum eigensolver (VQE) built
to utilize quantum resources for the solution of eigenvalue problems and
optimizations with minimal coherence time requirements by leveraging classical
computational resources. These algorithms have been placed among the candidates
for first to achieve supremacy over classical computation. Here, we provide
evidence for the conjecture that variational approaches can automatically
suppress even non-systematic decoherence errors by introducing an exactly
solvable channel model of variational state preparation. Moreover, we show how
variational quantum-classical approaches fit in a more general hierarchy of
measurement and classical computation that allows one to obtain increasingly
accurate solutions with additional classical resources. We demonstrate
numerically on a sample electronic system that this method both allows for the
accurate determination of excited electronic states as well as reduces the
impact of decoherence, without using any additional quantum coherence time or
formal error correction codes.


  Stellar flares with ${10^2-10^7}$ times more energy than the largest solar
flare have been detected from 9 normal F and G main sequence stars (Schaefer,
King & Deliyannis 1999). These superflares have durations of hours to days and
are visible from at least x-ray to optical frequencies. The absence of
world-spanning aurorae in historical records and of anomalous extinctions in
the geological record indicate that our Sun likely does not suffer superflares.
In seeking to explain this new phenomenon, we are struck by its similarity to
large stellar flares on RS Canum Venaticorum binary systems, which are caused
by magnetic reconnection events associated with the tangling of magnetic fields
between the two stars. The superflare stars are certainly not of this class,
although we propose a similar flare mechanism. That is, superflares are caused
by magnetic reconnection between fields of the primary star and a close-in
Jovian planet. Thus, by only invoking known planetary properties and
reconnection scenarios, we can explain the energies, durations, and spectra of
superflares, as well as explain why our Sun does not have such events.


  The environmental impact of pollutants and effluents discharged into the
atmosphere or the oceans has led researchers to conduct studies related to this
issue. Several works have been carried out in this context in order to reduce
the effect on the local environment. These types of ejections in nature are
modeled as jets in the presence of a density gradient. In this study we treated
the problem of inclined round turbulent buoyant jets and plumes ejected in a
homogeneous or stratified fluid, at rest or in motion. The prediction of the
flow behavior, i.e. the evolution of its variables, is first treated
theoretically from a model whose formalism is valid in both the Boussinesq case
as well as in the non-Boussinesq general case. Solving the equations governing
the plumes is performed numerically using a Runge-Kutta 4th order. To validate
the model, laboratory experiments are performed with round jets of air and
helium for a wide range of densities. The confrontation theory-experience aims
here to fix the limits of validity of the theoretical model.
  Keywords: Buoyant jet, plume, non-Boussinesq, laser tomography, image
processing, perturbation method.


  Strain engineering is a powerful tool for tuning physical properties of 2D
materials, including monolayer transition metal dichalcogenides (TMD) -- direct
bandgap semiconductors with strong excitonic response. Here, we demonstrate an
approach for local characterization of strain-induced modification of excitonic
photoluminescence in TMD-based materials. We reversibly stress a monolayer of
MoSe$_2$ with an AFM tip and perform spatio-spectral mapping of the excitonic
photoluminescence in the vicinity of the indentation point. To fully reproduce
the experimental data, we introduce the linear dependence of the exciton energy
and corresponding photoluminescence intensity on the induced strain. Careful
account for the optical resolution allows extracting these quantities with good
agreement with the previous measurements, which involved macroscopic sample
deformation. Our approach is a powerful tool for the study of local
optomechanical properties of 2D direct bandgap semiconductors with strong
excitonic response.


  The cross section of $e^+e^- \rightarrow \eta J/\psi$ has been measured by
BESIII and Belle experiments. Fit to the $e^+e^- \rightarrow \eta J/\psi$ line
shape, three resonant structures are evident. The parameters for the three
resonant structures are $M_{1}=(3980\pm17\pm7)$ MeV/$c^{2}$,
$\Gamma_{1}=(104\pm32\pm13)$ MeV; $M_{2}=(4219\pm5\pm4)$ MeV/$c^{2}$,
$\Gamma_{2}=(63\pm9\pm3)$ MeV; $M_{3}=(4401\pm12\pm4)$ MeV/$c^{2}$,
$\Gamma_{3}=(49\pm19\pm4)$ MeV, where the first uncertainties are statistical
and the second systematic. We attribute the three structures to $\psi(4040)$,
$Y(4220)$ and $\psi(4415)$ states. The branching fractions
$\mathcal{B}(\psi(4040) \rightarrow \eta J/\psi)$ and $\mathcal{B}(\psi(4415)
\rightarrow \eta J/\psi)$ are given. If $Y(4220)$ is taken as $\psi(4S)$ state,
the branching fraction $\mathcal{B}(\psi(4S) \rightarrow \eta J/\psi)$ is also
given. Combining all $Y(4220)$ parameters obtained from different decays, we
give average parameters for $Y(4220)$, which are $M_{Y(4220)}=(4220.8\pm2.4)$
MeV/$c^{2}$, $\Gamma_{Y(4220)}=(54.8\pm3.3)$ MeV.


  We construct a cosmological model based on a free particle model which is
constrained on an embedded toroidal brane, with a general rotation around a
specific axis in the bulk space. Some related issues such as the rotation axis
of the brane, the presence of gravitomagnetic background and its relation to
the general angular velocity of the brane, and its quantum mechanics and
related issues such as minimal length and minimal momentum of the quantum model
in the $\mathbb{T}^3$ brane are studied. Also, some cosmological features such
as the constraint which is imposed upon the toroidal universe by the isotropy
and homogeneity conditions, the corresponding Hubble law, and accelerating
expansion for the spinning toroidal model without considering a cosmological
constant are also studied.


  We present 1D numerical simulations, which consider the effects of radiative
cooling and gravity on the hydrodynamics of the matter reinserted by stellar
winds and supernovae within young nuclear starbursts with a central
supermassive black hole (SMBH). The simulations confirm our previous
semi-analytic results for low energetic starbursts, evolving in a
quasi-adiabatic regime, and extend them to more powerful starbursts evolving in
the catastrophic cooling regime. The simulations show a bimodal hydrodynamic
solution in all cases. They present a quasi-stationary accretion flow onto the
black hole, defined by the matter reinserted by massive stars within the
stagnation volume and a stationary starburst wind, driven by the high thermal
pressure acquired in the region between the stagnation and the starburst radii.
In the catastrophic cooling regime, the stagnation radius rapidly approaches
the surface of the starburst region, as one considers more massive starbursts.
This leads to larger accretion rates onto the SMBH and concurrently to powerful
winds able to inhibit interstellar matter from approaching the nuclear
starburst.
  Our self-consistent model thus establishes a direct physical link between the
SMBH accretion rate and the nuclear star formation activity of the host galaxy
and provides a good upper limit to the accretion rate onto the central black
hole.


  The quark <\bar\psi \psi> and gluon <F_{\mu\nu}F^{\mu\nu}> vacuum expectation
values are non-vanishing at low orders in \alpha_s when the perturbative ground
state includes quark and gluon pairs. This offers possibilities of studying the
effects of a non-trivial vacuum using formally exact perturbative methods. The
QCD Feynman rules are modified only for the free, on-shell quark and gluon
propagators at zero four-momentum. Gauge and lorentz invariance is maintained,
while chiral symmetry is spontaneously broken by the ground state.


  We have shown experimentally that an electric field decreases the energy
separation between the two components of a dense spin-polarized exciton gas in
a coupled double quantum well, from a maximum splitting of $\sim 4$ meV to
zero, at a field of $\sim $35 kV/cm. This decrease, due to the field-induced
deformation of the exciton wavefunction, is explained by an existing
calculation of the change in the spin-dependent exciton-exciton interaction
with the electron-hole separation. However, a new theory that considers the
modification of screening with that separation is needed to account for the
observed dependence on excitation power of the individual energies of the two
exciton components.


  UVES spectra of the very young (~10^7 years) peculiar B-type star HR 6000
were analyzed in the near-UV and visual spectral regions (3050-9460 A) with the
aim to extend to other spectral ranges the study made previously in the UV
using IUE spectra. Stellar parameters Teff=12850K, logg=4.10, and xi=0km/s, as
determined from H_beta, H_gamma, H_delta Balmer profiles and from the Fe I, Fe
II ionization equilibrium, were used to compute an individual abundances
ATLAS12 model. We identified spectral peculiarities and obtained final stellar
abundances by comparing observed and computed equivalent widths and line
profiles. The adopted model fails to reproduce the (b-y) and c color indices.
The spectral analysis has revealed: the presence of emission lines for Mn II,
Cr II, and Fe II; isotopic anomalies for Hg, Ca; the presence of interstellar
lines of Na I at lambda lambda 3302.3, 3302.9, 5890, 5896 A, and of K I at
7665, 7699 A; the presence of a huge quantity of unidentified lines, which we
presume to be mostly due to Fe II transitions owing to the large Fe
overabundance amounting to [+0.7]. The main chemical peculiarities are an
extreme overabundance of Xe, followed by those of Hg, P, Y, Mn, Fe, Be, and Ti.
The most underabundant element is Si, followed by C, N, Al, S, Mg, V, Sr, Co,
Cl, Sc, and Ni. The silicon underabundance [-2.9] is the lowest value for Si
ever observed in any HgMn star. The observed lines of He I can not be
reproduced by a single value of the He abundance, but they require values
ranging from [-0.8] to [-1.6]. Furthermore, when the observed and computed
wings of He I lines are fitted, the observed line cores are much weaker than
the computed ones. From the present analysis we infer the presence of vertical
abundance stratification for He, Mn, and possibly also P.


  As a transformative general-purpose technology, AI has empowered various
industries and will continue to shape our lives through ubiquitous
applications. Despite the enormous benefits from wide-spread AI deployment, it
is crucial to address associated downside risks and therefore ensure AI
advances are safe, fair, responsible, and aligned with human values. To do so,
we need to establish effective AI governance. In this work, we show that the
strategic interaction between the regulatory agencies and AI firms has an
intrinsic structure reminiscent of a Stackelberg game, which motivates us to
propose a game-theoretic modeling framework for AI governance. In particular,
we formulate such interaction as a Stackelberg game composed of a leader and a
follower, which captures the underlying game structure compared to its
simultaneous play counterparts. Furthermore, the choice of the leader naturally
gives rise to two settings. And we demonstrate that our proposed model can
serves as a unified AI governance framework from two aspects: firstly we can
map one setting to the AI governance of civil domains and the other to the
safety-critical and military domains, secondly, the two settings of governance
could be chosen contingent on the capability of the intelligent systems. To the
best of our knowledge, this work is the first to use game theory for analyzing
and structuring AI governance. We also discuss promising directions and hope
this can help stimulate research interest in this interdisciplinary area. On a
high, we hope this work would contribute to develop a new paradigm for
technology policy: the quantitative and AI-driven methods for the technology
policy field, which holds significant promise for overcoming many shortcomings
of existing qualitative approaches.


  An optimal randomized strategy for design of balanced, normalized mass
transport plans is developed. It replaces -- but specializes to -- the
deterministic, regularized optimal transport (OT) strategy, which yields only a
certainty-equivalent plan. The incompletely specified -- and therefore
uncertain -- transport plan is acknowledged to be a random process. Therefore,
hierarchical fully probabilistic design (HFPD) is adopted, yielding an optimal
hyperprior supported on the set of possible transport plans, and consistent
with prior mean constraints on the marginals of the uncertain plan. This
Bayesian resetting of the design problem for transport plans -- which we call
HFPD-OT -- confers new opportunities. These include (i) a strategy for the
generation of a random sample of joint transport plans; (ii) randomized
marginal contracts for individual source-target pairs; and (iii) consistent
measures of uncertainty in the plan and its contracts. An application in
algorithmic fairness is outlined, where HFPD-OT enables the recruitment of a
more diverse subset of contracts -- than is possible in classical OT -- into
the delivery of an expected plan. Also, it permits fairness proxies to be
endowed with uncertainty quantifiers.


  Kapitza-Dirac-Talbot-Lau interferometry (KDTLI) has recently been established
for demonstrating the quantum wave nature of large molecules. A phase space
treatment permits us to derive closed equations for the near-field interference
pattern, as well as for the Moire-type pattern that would arise if the
molecules were to be treated as classical particles. The model provides a
simple and elegant way to account for the molecular phase shifts related to the
optical dipole potential as well as for the incoherent effect of photon
absorption at the second grating. We present experimental results for different
molecular masses, polarizabilities and absorption cross sections using
fullerenes and fluorofullerenes and discuss the alignment requirements. Our
results with C60 and C70, C60F36 and C60F48 verify the theoretical description
to a high degree of precision.


  Density of vortices and monopoles after a rapid pressure quench is predicted.
Critical exponents are worked out in overdamped and underdamped limits.


  We study the fluctuations of smooth linear statistics of Laplace eigenvalues
of compact hyperbolic surfaces lying in short energy windows, when averaged
over the moduli space of surfaces of a given genus. The average is taken with
respect to the Weil-Petersson measure. We show that first taking the large
genus limit, then a short window limit, the distribution tends to a Gaussian.
The variance was recently shown to be given by the corresponding quantity for
the Gaussian Orthogonal Ensemble (GOE), and the Gaussian fluctuations are also
consistent with those in Random Matrix Theory, as conjectured in the physics
literature for a fixed surface.


  Dietary studies showed that dietary-related problem such as obesity is
associated with other chronic diseases like hypertension, irregular blood sugar
levels, and increased risk of heart attacks. The primary cause of these
problems is poor lifestyle choices and unhealthy dietary habits, which are
manageable using interactive mHealth apps. However, traditional dietary
monitoring systems using manual food logging suffer from imprecision,
underreporting, time consumption, and low adherence. Recent dietary monitoring
systems tackle these challenges by automatic assessment of dietary intake
through machine learning methods. This survey discusses the most performing
methodologies that have been developed so far for automatic food recognition
and volume estimation. First, we will present the rationale of visual-based
methods for food recognition. The core of the paper is the presentation,
discussion and evaluation of these methods on popular food image databases.
Following that, we discussed the mobile applications that are implementing
these methods. The survey ends with a discussion of research gaps and open
issues in this area.


  In the hyperspace of subcontinua of a compact surface we consider a second
order Hausdorff distance. This metric space is compactified in such a way that
the stable foliation of a pseudo-Anosov map is naturally identified with a
hypercontinuum. We show that negative iterates of a stable arc converges to
this hypercontinuum in the considered metric. Some dynamical properties of
pseudo-Anosov maps, as topological mixing and the density of stable leaves, are
generalized for cw-expansive homeomorphisms of pseudo-Anosov type on compact
metric spaces.


  Line intensity mapping is a promising probe of the universe's large-scale
structure. We explore the sensitivity of the DSA-2000, a forthcoming array
consisting of over 2000 dishes, to the statistical power spectrum of neutral
hydrogen's 21 cm emission line. These measurements would reveal the
distribution of neutral hydrogen throughout the near-redshift universe without
necessitating resolving individual sources. The success of these measurements
relies on the instrument's sensitivity and resilience to systematics. We show
that the DSA-2000 will have the sensitivity needed to detect the 21 cm power
spectrum at z=0.5 and across power spectrum modes of 0.03-35.12 h/Mpc with 0.1
h/Mpc resolution. We find that supplementing the nominal array design with a
dense core of 200 antennas will expand its sensitivity at low power spectrum
modes and enable measurement of Baryon Acoustic Oscillations (BAOs). Finally,
we present a qualitative discussion of the DSA-2000's unique resilience to
sources of systematic error that can preclude 21 cm intensity mapping.


  Many mathematical models involve input parameters, which are not precisely
known. Global sensitivity analysis aims to identify the parameters whose
uncertainty has the largest impact on the variability of a quantity of interest
(output of the model). One of the statistical tools used to quantify the
influence of each input variable on the output is the Sobol sensitivity index,
which can be estimated using a large sample of evaluations of the output. We
propose a variance reduction technique, based on the availability of a fast
approximation of the output, which can enable significant computational savings
when the output is costly to evaluate.


  It is shown that the length of the algorithmic minimal sufficient statistic
of a binary string x, either in a representation of a finite set, computable
semimeasure, or a computable function, has a length larger than the
computational depth of x, and can solve the Halting problem for all programs
with length shorter than the m-depth of x. It is also shown that there are
strings for which the algorithmic minimal sufficient statistics can contain a
substantial amount of information that is not Halting information. The weak
sufficient statistic is introduced, and it is shown that a minimal weak
sufficient statistic for x is equivalent to a minimal typical model of x, and
to the Halting problem for all strings shorter than the BB-depth of x.


  The ordered alloys of alkali metals (Rb and Cs) and gold (Au) have the B2
(CsCl-type) structure and show a semiconducting property, irrespective to the
metallic constituents. Francium (Fr) is classed as an alkali metal and is
expected to form the B2 structure with Au. However, it is difficult to
synthesize such a compound experimentally due to a half-life of a few ten
minutes in the Fr atom. In this paper, by using the first-principles method, we
study the structural and electronic properties of FrAu in the B2 structure. The
FrAu has a relatively large lattice constant and a relatively small bulk
modulus among 310 B2 compounds. The profiles of the electron and phonon band
structures of the FrAu are quite similar to those of the CsAu. We predict that
the FrAu is included to one of the ionic compounds as well as the RbAu and
CsAu.


  We propose an analysis method for the leading-twist operator product
expansion based lattice QCD determinations of the valence parton distribution
function (PDF). In the first step, we determine the confidence-intervals of the
leading-twist $\overline{\mathrm{MS}}$ Wilson coefficients, $C_n(\mu^2 z^2)$,
of the equal-time bilocal quark bilinear, given the lattice QCD matrix element
of Ioffe-time distribution for a particular hadron $H$ as well as the prior
knowledge of the valence PDF, $f(x,\mu)$ of the hadron $H$ determined via
global fit from the experimental data. In the next step, we apply the
numerically estimated $C_n$ in the lattice QCD determinations of the valence
PDFs of other hadrons, and for the zero-skewness generalized parton
distribution (GPD) of the same hadron $H$ at non-zero momentum transfers. Our
proposal still assumes the dominance of leading-twist terms, but it offers a
pragmatic alternative to the usage of perturbative Wilson coefficients and
their associated higher-loop uncertainties such as the effect of all-order
logarithms at larger sub-Fermi quark-antiquark separations $z$.


  An important task of community discovery in networks is assessing
significance of the results and robust ranking of the generated candidate
groups. Often in practice, numerous candidate communities are discovered, and
focusing the analyst's time on the most salient and promising findings is
crucial. We develop simple efficient group scoring functions derived from tail
probabilities using binomial models. Experiments on synthetic and numerous
real-world data provides evidence that binomial scoring leads to a more robust
ranking than other inexpensive scoring functions, such as conductance.
Furthermore, we obtain confidence values ($p$-values) that can be used for
filtering and labeling the discovered groups. Our analyses shed light on
various properties of the approach. The binomial tail is simple and versatile,
and we describe two other applications for community analysis: degree of
community membership (which in turn yields group-scoring functions), and the
discovery of significant edges in the community-induced graph.


  A well-known question in classical differential geometry and geometric
analysis asks for a description of possible boundaries of $K$-surfaces, which
are smooth, compact hypersurfaces in $\mathbb{R}^d$ having constant Gauss
curvature equal to $K \geq 0$. This question generated a considerable amount of
remarkable results in the last few decades. Motivated by these developments
here we study the question of determining a $K$-surface when only part of its
boundary is fixed, and in addition the surface hits a given manifold at some
fixed angle. While this general setting is out of reach for us at the present,
we settle a model case of the problem, which in its analytic formulation
reduces to a Bernoulli type free boundary problem for the Monge-Amp\`ere
equation. We study both the cases of 0-curvature and of positive curvature. The
formulation of the free boundary condition and its regularity are the most
delicate and challenging questions addressed in this work. In this regard we
introduce a notion of a Blaschke extension of a solution which might be of
independent interest.
  The problem we study can also be interpreted as the Alt-Caffarelli problem
for the Monge-Amp\`ere equation. Moreover, it also relates to the problem of
isometric embedding of a positive metric on the annulus with partially
prescribed boundary and optimal transport with free mass.


  We construct a fully quantum zero-temperature electron star in a soft-wall
regulated anti-de-Sitter Einstein-Maxwell-Dirac theory that is
thermodynamically stable compared to the Reissner-Nordstr\"{o}m black hole. The
soft wall only acts on the effective mass of the fermionic degrees of freedom,
and allows for a controlled fully backreacted solution. The star is
holographically dual to an RG flow where a gapped Fermi liquid starts to emerge
from a UV CFT, but decouples again once the effective energy scale becomes
lower than the the gap of the fermionic degrees of freedom. The RG flow then
returns to a non-trivial strongly coupled relativistic fixed point with a
holographic dual. Our regulated quantum electron star is thus the fermionic
analogue of the Horowitz-Roberts-Gubser-Rocha AdS-to-AdS domain wall solution
for the holographic superconductor.


  Maintaining optical alignment between stations of a free-space optical link
requires a persistent beam tracking operation. This is achieved using a
position-sensitive photodetector at each station which measures the azimuth and
elevation of tracking error. A pointing assembly adjusts the heading of
transceivers according to measurement of the tracking error. The measurement at
each receiver also depends on the pointing error of the opposite transmitter,
therefore a cooperative beam tracking system can be regarded as two dynamically
coupled subsystems. We developed a stochastic model for a cooperative beam
tracking system to get insight into solution of an associated optimal control
problem with goal of maximizing the flow of optical power between the stations.


  We explore simple models aimed at the study of social contagion, in which
contagion proceeds through two stages. When coupled with demographic turnover,
we show that two-stage contagion leads to nonlinear phenomena which are not
present in the basic `classical' models of mathematical epidemiology. These
include: bistability, critical transitions, endogenous oscillations, and
excitability, suggesting that contagion models with stages could account for
some aspects of the complex dynamics encountered in social life. These
phenomena, and the bifurcations involved, are studied by a combination of
analytical and numerical means.


  This paper proposes a theoretical analysis of recommendation systems in an
online setting, where items are sequentially recommended to users over time. In
each round, a user, randomly picked from a population of $m$ users, requests a
recommendation. The decision-maker observes the user and selects an item from a
catalogue of $n$ items. Importantly, an item cannot be recommended twice to the
same user. The probabilities that a user likes each item are unknown. The
performance of the recommendation algorithm is captured through its regret,
considering as a reference an Oracle algorithm aware of these probabilities. We
investigate various structural assumptions on these probabilities: we derive
for each structure regret lower bounds, and devise algorithms achieving these
limits. Interestingly, our analysis reveals the relative weights of the
different components of regret: the component due to the constraint of not
presenting the same item twice to the same user, that due to learning the
chances users like items, and finally that arising when learning the underlying
structure.


  We have studied self-conjugate second-order equations with spinor
wavefunctions for fermions moving in an external Coulomb field. For stationary
states, the equations are characterized by separated states with positive and
negative energies, which render probabilistic interpretation possible. For the
Coulomb field of attraction, the energy spectrum of the second-order equation
coincides with the spectrum of the Dirac equation, while the probability
densities of states are slightly different. For a Coulomb field of repulsion,
there exists an impermeable potential barrier with radius depending on the
classical electron radius and on the electron energy. The existence of the
impermeable barrier does not contradict the results of experiment for
determining the inner electron structure and does not affect (in the lowest
order of perturbation theory) the Coulomb electron scattering cross section.
The existence of the impermeable barrier can lead to positron confinement in
supercritical nuclei with $Z \geq 170$ in case of realization of spontaneous
emission of vacuum electron-positron pairs.


  We determine the critical exponent and the recurrence function of
complementary symmetric Rote sequences. The formulae are expressed in terms of
the continued fraction expansions associated with the S-adic representations of
the corresponding standard Sturmian sequences. The results are based on a
thorough study of return words to bispecial factors of Sturmian sequences.
Using the formula for the critical exponent, we describe all complementary
symmetric Rote sequences with the critical exponent less than or equal to 3,
and we show that there are uncountably many complementary symmetric Rote
sequences with the critical exponent less than the critical exponent of the
Fibonacci sequence. Our study is motivated by a~conjecture on sequences rich in
palindromes formulated by Baranwal and Shallit. Its recent solution by Curie,
Mol, and Rampersad uses two particular complementary symmetric Rote sequences.


  Sharp tip nanoindentation of glassy polymers is a constrained, localized
viscoelastoplastic deformation. We interpret this complexity, in terms of the
well-understood uniaxial deformation. From the uniaxial compression data in the
literature, for PMMA, PC and crosslinked SU-8, we obtain their universal,
yield-normalized recovery curves, with eps*=eps/eps_y, being one measure of the
corresponding strain states (CSS). Nanoindentation recovery is determined from
the 2sec constant rate unloading h-P data, modeled by a generalized power-law
(variable power exponent). Comparing these data-sets, yields the correlation
coefficient between the notional nanoindentation strain rate epsdot_N and
strain and true strain rate and strain, c=epsdot_N/epsdot_t=eps_N/eps_t. The
equivalent strain, eps, and the c value for any polymer, are within a narrow
range, from the onset of indentation. Combining residual profiles via scanning
probe microscopy with mathematical modeling of the indenter tip, provides the
strain distribution beneath the tip. CSS measures examined here, indicate
polymer-specific regions to regions common to glassy polymers, which are
reached very early in the nanoindentation.


  We study the antiferromagnetic spin-1/2 Heisenberg model on a two-dimensional
bipartite quasiperiodic structure, the octagonal tiling -- the aperiodic
equivalent of the square lattice for periodic systems.
  An approximate block spin renormalization scheme is described for this
problem. The ground state energy and local staggered magnetizations for this
system are calculated, and compared with the results of a recent Quantum Monte
Carlo calculation for the tiling. It is conjectured that the ground state
energy is exactly equal to that of the quantum antiferromagnet on the square
lattice.


  Responding to a lack in the literature, mechanical properties of polygonal
wood particles are determined for use in a discrete element model (DEM) for
flow analysis in silos, and some methods are proposed for determining such
parameters. The parameters arrived at here have also formed part of the input
to the SPOLY software, developed in-house to compute the DEM model with
spheropolyhedron elements. The model is validated using a 2D physical model,
where prismatic particles with polygonal cross sections are placed inside a
silo with variable aperture and hopper angle. Validation includes comparison of
flow-rates computed by SPOLY, displacement profiles, and clogging thresholds
with experimental results. The good agreement that emerges will encourage
future use of miniature triaxial tests, grain-surface profilometry, inclined
slope tests, and numerical analysis of the intragranular stresses - toward a
direct construction of the contact-deformation relations required in realistic
DEM modelling of particle flow with angular-shaped particles.


  We analyze the perturbative quantization of the spectral action in
noncommutative geometry and establish its one-loop renormalizability in a
generalized sense, while staying within the spectral framework of
noncommutative geometry. Our result is based on the perturbative expansion of
the spectral action in terms of higher Yang-Mills and Chern-Simons forms. In
the spirit of random noncommutative geometries, we consider the path integral
over matrix fluctuations around a fixed noncommutative gauge background and
show that the corresponding one-loop counterterms are of the same form so that
they can be safely subtracted from the spectral action. A crucial role will be
played by the appropriate Ward identities, allowing for a fully spectral
formulation of the quantum theory at one loop.


  This paper is an extended version of our previous short letter \cite{ZG2} and
is attempted to give a detailed account for the results presented in that
paper. Let $U_q({\cal G}^{(1)})$ be the quantized nontwisted affine Lie algebra
and $U_q({\cal G})$ be the corresponding quantum simple Lie algebra. Using the
previous obtained universal $R$-matrix for $U_q(A_1^{(1)})$ and
$U_q(A_2^{(1)})$, we determine the explicitly spectral-dependent universal
$R$-matrix for $U_q(A_1)$ and $U_q(A_2)$. We apply these spectral-dependent
universal $R$-matrix to some concrete representations. We then reproduce the
well-known results for the fundamental representations and we are also able to
derive for the first time the extreamly explicit and compact formula of the
spectral-dependent $R$-matrix for the adjoint representation of $U_q(A_2)$, the
simplest nontrival case when the tensor product of the representations is {\em
not} multiplicity-free.


  Synthesis of protein molecules in a cell are carried out by ribosomes. A
ribosome can be regarded as a molecular motor which utilizes the input chemical
energy to move on a messenger RNA (mRNA) track that also serves as a template
for the polymerization of the corresponding protein. The forward movement,
however, is characterized by an alternating sequence of translocation and
pause. Using a quantitative model, which captures the mechanochemical cycle of
an individual ribosome, we derive an {\it exact} analytical expression for the
distribution of its dwell times at the successive positions on the mRNA track.
Inverse of the average dwell time satisfies a ``Michaelis-Menten-like''
equation and is consistent with the general formula for the average velocity of
a molecular motor with an unbranched mechano-chemical cycle. Extending this
formula appropriately, we also derive the exact force-velocity relation for a
ribosome. Often many ribosomes simultaneously move on the same mRNA track,
while each synthesizes a copy of the same protein. We extend the model of a
single ribosome by incorporating steric exclusion of different individuals on
the same track. We draw the phase diagram of this model of ribosome traffic in
3-dimensional spaces spanned by experimentally controllable parameters. We
suggest new experimental tests of our theoretical predictions.


  Spectrophotometry in the 3400-7400 range is presented for 13 areas of the
brightest H II region in the SMC: NGC 346. The observations were obtained at
CTIO with the 4-m telescope. Based on these observations its chemical
composition is derived. The helium and oxygen abundances by mass are given by:
Y(SMC)=0.2405+-0.0018 and O(SMC)=0.00171+-0.00025. From models and observations
of irregular and blue compact galaxies it is found that dY/dO=3.5+-0.9 and
consequently that the primordial helium abundance by mass is given by:
Yp=0.2345+-0.0026 (1-sigma). This result is compared with values derived from
Big Bang nucleosynthesis, and with other determinations of Yp.


  When $\mathbb{K}$ is a field, and $\mathcal{A}$ and $\mathcal{B}$ denote
commuting subspaces of $\text{M}_n(\K)$ each of which contains a non-scalar
matrix, we prove that $\dim \mathcal{A} +\dim \mathcal{B} \leq (n-1)^2+3$. We
also give a complete description of the cases when equality holds.