  To understand the mass distribution and co-evolution of supermassive black
holes with their host galaxy, it is crucial to measure the black hole mass of
AGN. Reverberation mapping is a unique tool to estimate the black hole masses
in AGN. We performed spectroscopic reverberation study using long-term
monitoring data with more than 100 spectra of a radio-loud quasar PKS 0736+017
to estimate the size of the broad line region (BLR) and black hole mass. The
optical spectrum shows strong H$\mathrm{\beta}$ and H$\mathrm{\gamma}$ emission
lines. We generated the light curves of 5100{\AA} continuum flux ($f_{5100}$),
H$\beta$, and H$\gamma$. All the light curves are found to be strongly variable
with fractional variability of 69$\%$, 21$\%$, 30$\%$ for V-band, H$\beta$, and
H$\gamma$ light curves, respectively. Along with the thermal contribution,
non-thermal emission contributes to the estimated continuum luminosity at
5100\AA. Using different methods, e.g., CCF, {\small JAVELIN}, von-neumann, we
estimated the size of the BLR, which is found to be 66.4$^{+6.0}_{-4.2}$ light
days in the rest frame. The BLR size combined with the line width of H$\beta$
provides a black hole mass of 7.32$^{+0.89}_{-0.91} \times 10^{7}M_{\odot}$.
The source closely follows the BLR size-luminosity relation of AGN.


  We optimize the operation of single-electron charge pumps using full counting
statistics techniques. To this end, we evaluate the statistics of pumped charge
on a wide range of driving frequencies using Floquet theory, focusing here on
the current and the noise. For charge pumps controlled by one or two gate
voltages, we demonstrate that our theoretical framework may lead to enhanced
device performance. Specifically, by optimizing the driving parameters, we
predict a significant increase in the frequencies for which a quantized current
can be produced. For adiabatic two-parameter pumps, we exploit that the pumped
charge and the noise can be expressed as surface integrals over Berry
curvatures in parameter space. Our findings are important for the efforts to
realize high-frequency charge pumping, and our predictions may be verified
using current technology.


  Compact spin-polarized positron accelerators play a major role in promoting
significant positron application research, which typically require high
acceleration gradients and polarization degree, both of which, however, are
still great challenging. Here, we put forward a novel spin-polarized positron
acceleration method which employs an ultrarelativistic high-density electron
beam passing through any hole of multi-layer microhole array films to excite
strong electrostatic and transition radiation fields. Positrons in the
polarized electron-positron pair plasma, filled in the front of the multi-layer
films, can be captured, accelerated, and focused by the electrostatic and
transition radiation fields, while maintaining high polarization of above 90%
and high acceleration gradient of about TeV/m. Multi-layer design allows for
capturing more positrons and achieving cascade acceleration. Our method offers
a promising solution for accelerator miniaturization, positron injection, and
polarization maintaining, and also can be used to accelerate other charged
particles.


  The classical $L^2$ estimate for the $\overline{\partial}$ operators is a
basic tool in complex analysis of several variables. Naturally, it is expected
to extend this estimate to infinite dimensional complex analysis, but this is a
longstanding unsolved problem, due to the essential difficulty that there
exists no nontrivial translation invariance measure in the setting of infinite
dimensions. The main purpose in this series of work is to give an affirmative
solution to the above problem, and apply the estimates to the solvability of
the infinite dimensional $\overline{\partial}$ equations. In this first part,
we focus on the simplest case, i.e., $L^2$ estimates and existence theorems for
the $\overline{\partial}$ equations on the whole space of $\ell^p$ for $p\in
[1,\infty)$. The key of our approach is to introduce a suitable working space,
i.e., a Hilbert space for $(s,t)$-forms on $\ell^p$ (for each nonnegative
integers $s$ and $t$), and via which we define the $\overline{\partial}$
operator from $(s,t)$-forms to $(s,t+1)$-forms and establish the exactness of
these operators, and therefore in this case we solve a problem which has been
open for nearly forty years.


  With the development of mobile edge computing (MEC) and blockchain-based
federated learning (BCFL), a number of studies suggest deploying BCFL on edge
servers. In this case, resource-limited edge servers need to serve both mobile
devices for their offloading tasks and the BCFL system for model training and
blockchain consensus in a cost-efficient manner without sacrificing the service
quality to any side. To address this challenge, this paper proposes a resource
allocation scheme for edge servers, aiming to provide the optimal services with
the minimum cost. Specifically, we first analyze the energy consumed by the MEC
and BCFL tasks, and then use the completion time of each task as the service
quality constraint. Then, we model the resource allocation challenge into a
multivariate, multi-constraint, and convex optimization problem. To solve the
problem in a progressive manner, we design two algorithms based on the
alternating direction method of multipliers (ADMM) in both the homogeneous and
heterogeneous situations with equal and on-demand resource distribution
strategies, respectively. The validity of our proposed algorithms is proved via
rigorous theoretical analysis. Through extensive experiments, the convergence
and efficiency of our proposed resource allocation schemes are evaluated. To
the best of our knowledge, this is the first work to investigate the resource
allocation dilemma of edge servers for BCFL in MEC.


  The spatial development of hadronic showers in the CALICE scintillator-steel
analogue hadron calorimeter is studied using test beam data collected at CERN
and FNAL for single positive pions and protons with initial momenta in the
range from 10 to 80 GeV/c. Both longitudinal and radial development of hadron
showers are parametrised with two-component functions. The parametrisation is
fit to test beam data and simulations using the QGSP_BERT and FTFP_BERT physics
lists from Geant4 version 9.6. The parameters extracted from data and simulated
samples are compared for the two types of hadrons. The response to pions and
the ratio of the non-electromagnetic to the electromagnetic calorimeter
response, h/e, are estimated using the extrapolation and decomposition of the
longitudinal profiles.


  Most microscopic pedestrian navigation models use the concept of "forces"
applied to the pedestrian agents to replicate the navigation environment. While
the approach could provide believable results in regular situations, it does
not always resemble natural pedestrian navigation behaviour in many typical
settings. In our research, we proposed a novel approach using reinforcement
learning for simulation of pedestrian agent path planning and collision
avoidance problem. The primary focus of this approach is using human perception
of the environment and danger awareness of interferences. The implementation of
our model has shown that the path planned by the agent shares many similarities
with a human pedestrian in several aspects such as following common walking
conventions and human behaviours.


  We study soliton pulse compression in materials with cascaded quadratic
nonlinearities, and show that the group-velocity mismatch creates two different
temporally nonlocal regimes. They correspond to what is known as the stationary
and nonstationary regimes. The theory accurately predicts the transition to the
stationary regime, where highly efficient pulse compression is possible.


  We show that if FU Orionis objects harbour hot Jupiters embedded in their
discs, the resulting non-axisymmetric dissipation profile in the disc would be
manifest as time-dependent distortions in the absorption line profiles of these
objects. In order to affect the infrared line profiles, planets must lie within
approximately 0.5 au of the central star, whereas only planets within 0.1 au
would influence the optical line profiles. The timescale for modulation of the
line profiles is relatively short (months) in each case, so that the effect
could not have been discovered from published spectra (which combine data taken
in different observing seasons). The detection of hot Jupiters in FU Orionis
objects would be in line with the expectations of tidal migration theories
(which predict a high incidence of close planets around young stars) and would
also lend support to models which link the triggering of rapid rise FU Orionis
events to the existence of a close massive planet.


  The state-of-the-art deep learning methods have demonstrated impressive
performance in segmentation tasks. However, the success of these methods
depends on a large amount of manually labeled masks, which are expensive and
time-consuming to be collected. In this work, a novel Consistent
PerceptionGenerative Adversarial Network (CPGAN) is proposed for
semi-supervised stroke lesion segmentation. The proposed CPGAN can reduce the
reliance on fully labeled samples. Specifically, A similarity connection module
(SCM) is designed to capture the information of multi-scale features. The
proposed SCM can selectively aggregate the features at each position by a
weighted sum. Moreover, a consistent perception strategy is introduced into the
proposed model to enhance the effect of brain stroke lesion prediction for the
unlabeled data. Furthermore, an assistant network is constructed to encourage
the discriminator to learn meaningful feature representations which are often
forgotten during training stage. The assistant network and the discriminator
are employed to jointly decide whether the segmentation results are real or
fake. The CPGAN was evaluated on the Anatomical Tracings of Lesions After
Stroke (ATLAS). The experimental results demonstrate that the proposed network
achieves superior segmentation performance. In semi-supervised segmentation
task, the proposed CPGAN using only two-fifths of labeled samples outperforms
some approaches using full labeled samples.


  How does charge density constrain many-body wavefunctions in nature? The
Hohenberg-Kohn theorem for non-relativistic, interacting many-body
Schr\"odinger systems is well-known and was proved using
\emph{reductio-ad-absurdum}; however, the physical mechanism or principle which
enables this theorem in nature has not been understood. Here, we obtain
effective canonical operators in the interacting many-body problem -- (i) the
local electric field, which mediates interaction between particles, and
contributes to the potential energy; and (ii) the particle momenta, which
contribute to the kinetic energy. The commutation of these operators results in
the charge density distribution. Thus, quantum fluctuations of interacting
many-particle systems are constrained by charge density, providing a mechanism
by which an external potential, by coupling to the charge density, tunes the
quantum-mechanical many-body wavefunction. As an initial test, we obtain the
functional form for total energy of interacting many-particle systems, and in
the uniform density limit, find promising agreement with Quantum Monte Carlo
simulations.


  Historical fragmentation in spectrum access models accentuates the need for
novel concepts that allow for efficient sharing of already available but
underutilized spectrum. The emerging Licensed Shared Access (LSA) regulatory
framework is expected to enable more advanced spectrum sharing between a
limited number of users while guaranteeing their much needed interference
protection. However, the ultimate benefits of LSA may in practice be
constrained by space-time availability of the LSA bands. Hence, more dynamic
LSA spectrum management is required to leverage such real-time variability and
sustain reliability when e.g., the original spectrum user suddenly revokes the
previously granted frequency bands as they are required again. In this article,
we maintain the vision of highly dynamic LSA architecture and rigorously study
its future potential: from reviewing market opportunities and discussing
available technology implementations to conducting performance evaluation of
LSA dynamics and outlining the standardization landscape. Our investigations
are based on a comprehensive system-level evaluation framework, which has been
specifically designed to assess highly dynamic LSA deployments.


  A picture is worth a thousand words. Albeit a clich\'e, for the fashion
industry, an image of a clothing piece allows one to perceive its category
(e.g., dress), sub-category (e.g., day dress) and properties (e.g., white
colour with floral patterns). The seasonal nature of the fashion industry
creates a highly dynamic and creative domain with evermore data, making it
unpractical to manually describe a large set of images (of products). In this
paper, we explore the concept of visual recognition for fashion images through
an end-to-end architecture embedding the hierarchical nature of the annotations
directly into the model. Towards that goal, and inspired by the work of [7], we
have modified and adapted the original architecture proposal. Namely, we have
removed the message passing layer symmetry to cope with Farfetch category tree,
added extra layers for hierarchy level specificity, and moved the message
passing layer into an enriched latent space. We compare the proposed unified
architecture against state-of-the-art models and demonstrate the performance
advantage of our model for structured multi-level categorization on a dataset
of about 350k fashion product images.


  There are two major alternatives for violating the (usual) Lorentz invariance
at large (Planckian) energies or momenta - either not all inertial frames (in
the Planck regime) are equivalent (e.g., there is an effectively preferred
frame) or the transformations from one frame to another are (non-linearly)
deformed (``doubly special relativity''). We demonstrate that the natural (and
reasonable) assumption of an energy-dependent speed of light in the latter
method goes along with violations of locality/separability (and even
translational invariance) on macroscopic scales.
  PACS: 03.30.+p, 11.30.Cp, 04.60.-m, 04.50.+h.


  Let $k$ be a noetherian commutative ring and let $G$ be a finite flat group
scheme over $k$. Let $G$ act rationally on a finitely generated commutative
$k$-algebra $A$. We show that the cohomology algebra $H^*(G,A)$ is a finitely
generated $k$-algebra. This unifies some earlier results.


  In the last two decades, the continuous increase of computational power has
produced an overwhelming flow of data which has called for a paradigm shift in
the computing architecture and large scale data processing mechanisms.
MapReduce is a simple and powerful programming model that enables easy
development of scalable parallel applications to process vast amounts of data
on large clusters of commodity machines. It isolates the application from the
details of running a distributed program such as issues on data distribution,
scheduling and fault tolerance. However, the original implementation of the
MapReduce framework had some limitations that have been tackled by many
research efforts in several followup works after its introduction. This article
provides a comprehensive survey for a family of approaches and mechanisms of
large scale data processing mechanisms that have been implemented based on the
original idea of the MapReduce framework and are currently gaining a lot of
momentum in both research and industrial communities. We also cover a set of
introduced systems that have been implemented to provide declarative
programming interfaces on top of the MapReduce framework. In addition, we
review several large scale data processing systems that resemble some of the
ideas of the MapReduce framework for different purposes and application
scenarios. Finally, we discuss some of the future research directions for
implementing the next generation of MapReduce-like solutions.


  Vectorial partners of the Standard Model quarks and leptons are predicted in
many dynamical models of electroweak symmetry breaking. The most easily
accessible of these new particles, either due to mass or couplings, are
typically expected to be the partners of the third-generation fermions. It is
therefore essential to explore the signatures of these particles at future
high-energy colliders. We study the potential of a high-energy muon collider to
singly produce a vector-like top-quark partner via an electroweak dipole moment
operator, such an operator being typical of composite constructions beyond the
Standard Model. We use a phenomenological model for third-generation quarks and
their partners that satisfies an extended custodial symmetry. This
automatically protects the $W$-boson and $Z$-boson masses from receiving large
electroweak corrections, and it allows the model to be viable given current
electroweak data. We demonstrate that cross sections associated with
dipole-induced vector-like quark production can easily exceed those inherent to
more conventional single-production modes via ordinary electroweak couplings.
We then explore the associated phenomenology, and we show that at least one
(and often more than one) of the extra vector-like states can be studied at
high-energy muon colliders. Typical accessible masses are found to range up to
close to the kinematic production threshold, when the vector-like partners are
produced in combination with an ordinary top quark.


  Electrides, with their excess electrons distributed in crystal cavities
playing the role of anions, exhibit a variety of unique properties which make
these materials desirable for many applications in catalysis, nonlinear optics
and electron emission. While the first electride was discovered almost four
decades ago, only few electride materials are known today, which limits our
fundamental understanding as well as the practical use of these exotic
materials. In this work, we propose an automated computational screening scheme
to search for interstitial electrons and quantify their distributions inside
the crystal cavities and energy space. Applying this scheme to all candidate
materials in the Inorganic Crystal Structure Database (ICSD), we report the
identification of 167 potential electride materials. This work significantly
increases the current library of electride materials, which enables an in-depth
investigation of their chemistry-structure-property relations and opens new
avenues for future electride design.


  We investigate the Robust Multiperiod Network Design Problem, a
generalization of the Capacitated Network Design Problem (CNDP) that, besides
establishing flow routing and network capacity installation as in a canonical
CNDP, also considers a planning horizon made up of multiple time periods and
protection against fluctuations in traffic volumes. As a remedy against traffic
volume uncertainty, we propose a Robust Optimization model based on Multiband
Robustness (B\"using and D'Andreagiovanni, 2012), a refinement of classical
Gamma-Robustness by Bertsimas and Sim that uses a system of multiple deviation
bands. Since the resulting optimization problem may prove very challenging even
for instances of moderate size solved by a state-of-the-art optimization
solver, we propose a hybrid primal heuristic that combines a randomized fixing
strategy inspired by ant colony optimization, which exploits information coming
from linear relaxations of the problem, and an exact large neighbourhood
search. Computational experiments on a set of realistic instances from the
SNDlib show that our original heuristic can run fast and produce solutions of
extremely high quality associated with low optimality gaps.


  It is possible to generate an accelerated period of expansion from reasonable
potentials acting between the universe particle constituents. The pressure of
primordial nucleons interacting via a simple nuclear potential is obtained via
Mayer's cluster expansion technique. The attractive part of the potential
engenders a negative pressure and may therefore be responsible for the cosmic
acceleration.


  The core is a traditional and useful solution concept in economic theory. But
in discrete exchange economies without transfers, when endowments are complex,
the core may be empty. This motivates Balbuzanov and Kotowski (2019) to
interpret endowments as exclusion rights and propose a new concept called
exclusion core. Our contribution is twofold. First, we propose a rectification
of the core to solve its problem under complex endowments. Second, we propose a
refinement of Balbuzanov and Kotowski's exclusion core to improve its
performance. Our two core concepts share a common idea of correcting the
misused altruism of unaffected agents in blocking coalitions. We propose a
mechanism to find allocations in the two cores.


  Many have speculated about the presence of a stiff fluid in very early stage
of the universe. Such a stiff fluid was first introduced by Zel'dovich.
Recently the late acceleration of the universe was studied by taking bulk
viscous stiff fluid as the dominant cosmic component, but the age predicted by
such a model is less than the observed value. We consider a flat universe with
viscous stiff fluid and decaying vacuum energy as the cosmic components and
found that the model predicts a reasonable background evolution of the universe
with de Sitter epoch as end phase of expansion. More over the model also
predicts a reasonable value for the age of the present universe. We also
perform a dynamical system analysis of the model and found that the end de
Sitter phase predicted by the model is stable.


  Artificial intelligence, and specifically deep neural networks (DNNs), has
rapidly emerged in the past decade as the standard for several tasks from
specific advertising to object detection. The performance offered has led DNN
algorithms to become a part of critical embedded systems, requiring both
efficiency and reliability. In particular, DNNs are subject to malicious
examples designed in a way to fool the network while being undetectable to the
human observer: the adversarial examples. While previous studies propose
frameworks to implement such attacks in black box settings, those often rely on
the hypothesis that the attacker has access to the logits of the neural
network, breaking the assumption of the traditional black box. In this paper,
we investigate a real black box scenario where the attacker has no access to
the logits. In particular, we propose an architecture-agnostic attack which
solve this constraint by extracting the logits. Our method combines hardware
and software attacks, by performing a side-channel attack that exploits
electromagnetic leakages to extract the logits for a given input, allowing an
attacker to estimate the gradients and produce state-of-the-art adversarial
examples to fool the targeted neural network. Through this example of
adversarial attack, we demonstrate the effectiveness of logits extraction using
side-channel as a first step for more general attack frameworks requiring
either the logits or the confidence scores.


  Marketing optimization plays an important role to enhance user engagement in
online Internet platforms. Existing studies usually formulate this problem as a
budget allocation problem and solve it by utilizing two fully decoupled stages,
i.e., machine learning (ML) and operation research (OR). However, the learning
objective in ML does not take account of the downstream optimization task in
OR, which causes that the prediction accuracy in ML may be not positively
related to the decision quality.
  Decision Focused Learning (DFL) integrates ML and OR into an end-to-end
framework, which takes the objective of the downstream task as the decision
loss function and guarantees the consistency of the optimization direction
between ML and OR. However, deploying DFL in marketing is non-trivial due to
multiple technological challenges. Firstly, the budget allocation problem in
marketing is a 0-1 integer stochastic programming problem and the budget is
uncertain and fluctuates a lot in real-world settings, which is beyond the
general problem background in DFL. Secondly, the counterfactual in marketing
causes that the decision loss cannot be directly computed and the optimal
solution can never be obtained, both of which disable the common
gradient-estimation approaches in DFL. Thirdly, the OR solver is called
frequently to compute the decision loss during model training in DFL, which
produces huge computational cost and cannot support large-scale training data.
In this paper, we propose a decision focused causal learning framework (DFCL)
for direct counterfactual marketing optimization, which overcomes the above
technological challenges. Both offline experiments and online A/B testing
demonstrate the effectiveness of DFCL over the state-of-the-art methods.
Currently, DFCL has been deployed in several marketing scenarios in Meituan,
one of the largest online food delivery platform in the world.


  We are witnessing increasing interests in the effective use of road networks.
For example, to enable effective vehicle routing, weighted-graph models of
transportation networks are used, where the weight of an edge captures some
cost associated with traversing the edge, e.g., greenhouse gas (GHG) emissions
or travel time. It is a precondition to using a graph model for routing that
all edges have weights. Weights that capture travel times and GHG emissions can
be extracted from GPS trajectory data collected from the network. However, GPS
trajectory data typically lack the coverage needed to assign weights to all
edges. This paper formulates and addresses the problem of annotating all edges
in a road network with travel cost based weights from a set of trips in the
network that cover only a small fraction of the edges, each with an associated
ground-truth travel cost. A general framework is proposed to solve the problem.
Specifically, the problem is modeled as a regression problem and solved by
minimizing a judiciously designed objective function that takes into account
the topology of the road network. In particular, the use of weighted PageRank
values of edges is explored for assigning appropriate weights to all edges, and
the property of directional adjacency of edges is also taken into account to
assign weights. Empirical studies with weights capturing travel time and GHG
emissions on two road networks (Skagen, Denmark, and North Jutland, Denmark)
offer insight into the design properties of the proposed techniques and offer
evidence that the techniques are effective.


  The finite temperature phase diagram is obtained for an infinite honeycomb
lattice with spin-$1/2$ Ising interaction $J$ by using thermal-state fidelity
and von Neumann entropy based on the infinite projected entangled pair state
algorithm with ancillas. % The tensor network representation of the fidelity,
which is defined as an overlap measurement between two thermal states, is
presented for thermal states on the honeycomb lattice. % We show that the
fidelity per lattice site and the von Neumann entropy can capture the phase
transition temperatures for applied magnetic field, consistent with the
transition temperatures obtained via the transverse magnetizations, which
indicates that a continuous phase transition occurs in the system. In the
temperature-magnetic field plane, the phase boundary is found to have the
functional form $(k_BT_c)^2 + h_c^2/2 = a J^2$ with a single numerical fitting
coefficient $a = 2.298$, where $T_c$ and $h_c$ are the critical temperature and
field with the Boltzmann constant $k_B$. For the quantum state at zero
temperature, this phase boundary function gives the critical field estimate
$h_c = \sqrt{2a} J \simeq 2.1438 J$, consistent with the known value $h_c =
2.13250(4)\, J$ calculated from a Cluster Monte Carlo approach. The critical
temperature in the absence of magnetic field is estimated as $k_BT_c =
\sqrt{a}J \simeq 1.5159\, J$, consistent with the exact result $k_BT_c =
1.51865...\, J$.


  Candidate galaxies at redshifts of $z \sim 10$ are now being found in
extremely deep surveys, probing very small areas. As a consequence, candidates
are very faint, making spectroscopic confirmation practically impossible. In
order to overcome such limitations, we have undertaken the CF-HiZELS survey,
which is a large area, medium depth near infrared narrow-band survey targeted
at $z=8.8$ Lyman-$\alpha$ (Ly$\alpha$) emitters (LAEs) and covering 10 deg$^2$
in part of the SSA22 field with the Canada-France-Hawaii Telescope. We surveyed
a comoving volume of $4.7\times 10^6$ Mpc$^3$ to a Ly$\alpha$ luminosity limit
of $6.3\times10^{43}$ erg s$^{-1}$. We look for Ly$\alpha$ candidates by
applying the following criteria: i) clear emission line source, ii) no optical
detections ($ugriz$ from CFHTLS), iii) no visible detection in the optical
stack ($ugriz > 27$), iv) visually checked reliable NB$_J$ and $J$ detections
and v) $J-K \leq 0$. We compute photometric redshifts and remove a significant
amount of dusty lower redshift line-emitters at $z \sim 1.4 $ or $2.2$. A total
of 13 Ly$\alpha$ candidates were found, of which two are marked as strong
candidates, but the majority have very weak constraints on their SEDs. Using
follow-up observations with SINFONI/VLT we are able to exclude the most robust
candidates as Ly$\alpha$ emitters. We put a strong constraint on the Ly$\alpha$
luminosity function at $z \sim 9$ and make realistic predictions for ongoing
and future surveys. Our results show that surveys for the highest redshift LAEs
are susceptible of multiple contaminations and that spectroscopic follow-up is
absolutely necessary.


  We report the discovery of a 7.3 Mjup exoplanet WASP-14b, one of the most
massive transiting exoplanets observed to date. The planet orbits the
tenth-magnitude F5V star USNO-B1 11118-0262485 with a period of 2.243752 days
and orbital eccentricity e = 0.09. A simultaneous fit of the transit light
curve and radial velocity measurements yields a planetary mass of 7.3+/-0.5
Mjup and a radius of 1.28+/-0.08 Rjup. This leads to a mean density of about
4.6 g/cm^3 making it densest transiting exoplanets yet found at an orbital
period less than 3 days. We estimate this system to be at a distance of
160+/-20 pc. Spectral analysis of the host star reveals a temperature of
6475+/-100 K, log g = 4.07 cm/s^2 and vsin i = 4.9+/-1.0 km/s, and also a high
lithium abundance, log N(Li} = 2.84+/-0.05. The stellar density, effective
temperature and rotation rate suggest an age for the system of about 0.5-1.0
Gyr.


  A remarkable connection between the order of a maximum clique and the
Lagrangian of a graph was established by Motzkin and Straus in 1965. This
connection and its extensions were applied in Tur\'{a}n problems of graphs and
uniform hypergraphs. Very recently, the study of Tur\'{a}n densities of
non-uniform hypergraphs has been motivated by extremal poset problems. In this
paper, we give some Motzkin-Straus type results for non-uniform hypergraphs.


  In this paper, we are interested in the following one dimensional forward
stochastic differential equation (SDE) \[ d X_{t}=b(t,X_{t},\omega)d t +\sigma
d B_{t},\quad 0\leq t\leq T,\quad X_{0}=\,x\in \mathbb{R}, \] where the driving
noise $B_{t}$ is a $d$-dimensional Brownian motion. The drift coefficient
$b:[0,T] \times\Omega\times \mathbb{R}\longrightarrow \mathbb{R}$ is Borel
measurable and can be decomposed into a deterministic and a random part, i.e.,
$b(t,x,\omega) = b_1(t,x) + b_2(t,x,\omega)$. Assuming that $b_1$ is of spacial
linear growth and $b_2$ satisfies some integrability conditions, we obtain the
existence and uniqueness of a strong solution. The method we use is purely
probabilitic and relies on Malliavin calculus. As byproducts, we obtain
Malliavin differentiability of the solutions, provide an explicit
representation for the Malliavin derivative and prove existence of weighted
Sobolev differentiable flows.


  Tabled evaluation is an implementation technique that solves some problems of
traditional Prolog systems in dealing with recursion and redundant
computations. Most tabling engines determine if a tabled subgoal will produce
or consume answers by using variant checks. A more refined method, named call
subsumption, considers that a subgoal A will consume from a subgoal B if A is
subsumed by (an instance of) B, thus allowing greater answer reuse. We recently
developed an extension, called Retroactive Call Subsumption, that improves upon
call subsumption by supporting bidirectional sharing of answers between
subsumed/subsuming subgoals. In this paper, we present both an algorithm and an
extension to the table space data structures to efficiently implement instance
retrieval of subgoals for subsumptive tabled evaluation of logic programs.
Experiments results using the YapTab tabling system show that our
implementation performs quite well on some complex benchmarks and is robust
enough to handle a large number of subgoals without performance degradation.


  The dissipation generated during a quasistatic thermodynamic process can be
characterised by introducing a metric on the space of Gibbs states, in such a
way that minimally-dissipating protocols correspond to geodesic trajectories.
Here, we show how to generalize this approach to open quantum systems by
finding the thermodynamic metric associated to a given Lindblad master
equation. The obtained metric can be understood as a perturbation over the
background geometry of equilibrium Gibbs states, which is induced by the
Kubo-Mori-Bogoliubov (KMB) inner product. We illustrate this construction on
two paradigmatic examples: an Ising chain and a two-level system interacting
with a bosonic bath with different spectral densities.


  The role of social media in information dissemination and agenda-setting has
significantly expanded in recent years. By offering real-time interactions,
online platforms have become invaluable tools for studying societal responses
to significant events as they unfold. However, online reactions to external
developments are influenced by various factors, including the nature of the
event and the online environment. This study examines the dynamics of public
discourse on digital platforms to shed light on this issue. We analyzed over 12
million posts and news articles related to two significant events: the release
of ChatGPT in 2022 and the global discussions about COVID-19 vaccines in 2021.
Data was collected from multiple platforms, including Twitter, Facebook,
Instagram, Reddit, YouTube, and GDELT. We employed topic modeling techniques to
uncover the distinct thematic emphases on each platform, which reflect their
specific features and target audiences. Additionally, sentiment analysis
revealed various public perceptions regarding the topics studied. Lastly, we
compared the evolution of engagement across platforms, unveiling unique
patterns for the same topic. Notably, discussions about COVID-19 vaccines
spread more rapidly due to the immediacy of the subject, while discussions
about ChatGPT, despite its technological importance, propagated more gradually.


  Two important tasks at the intersection of knowledge graphs and natural
language processing are graph-to-text (G2T) and text-to-graph (T2G) conversion.
Due to the difficulty and high cost of data collection, the supervised data
available in the two fields are usually on the magnitude of tens of thousands,
for example, 18K in the WebNLG~2017 dataset after preprocessing, which is far
fewer than the millions of data for other tasks such as machine translation.
Consequently, deep learning models for G2T and T2G suffer largely from scarce
training data. We present CycleGT, an unsupervised training method that can
bootstrap from fully non-parallel graph and text data, and iteratively back
translate between the two forms. Experiments on WebNLG datasets show that our
unsupervised model trained on the same number of data achieves performance on
par with several fully supervised models. Further experiments on the
non-parallel GenWiki dataset verify that our method performs the best among
unsupervised baselines. This validates our framework as an effective approach
to overcome the data scarcity problem in the fields of G2T and T2G. Our code is
available at https://github.com/QipengGuo/CycleGT.


  We introduce a quantum measurement process that is capable of characterizing
an unknown state of a system almost without disturbing or collapsing it. The
underlying idea is to extract information of a system from the thermodynamic
quantities like work(s) and heat in a process, thereby uncovering a fundamental
correspondence between information and thermodynamics. We establish an improved
notion of information isolation and show that a process is isolated if it
respects the first law of quantum thermodynamics for a given set of conserved
quantities or charges. The measurement process involves a global unitary
evolution of the system, an apparatus, and a battery which supplies work(s).
The global unitary respects the first law. The full information about the
system is accessed by counting the charge-wise work costs to implement the
reduced evolution on the system and the apparatus. After the work costs are
determined, the process is undone where a state of the system is retrieved
arbitrarily close to the original initial state. The measurement process is
also capable of characterizing an unknown quantum operation. Fundamentally, our
findings make an important step towards resolving the paradoxes arising from
the quantum measurement problem, such as the Wigner's friend paradox, and the
issue related to the objective reality of quantum states. We discuss the
technological implications of the almost collapse-free measurement process.


  We analyse a model of binary opinion dynamics in which iterative discussions
take place in local groups of individuals and study the effects of random
deviations from the group majority. The probability of a deviation or flip
depends on the magnitude of the majority. Depending on the values of the flip
parameters which give the probability of a deviation, the model shows a wide
variety of behaviour. We are interested in the characteristics of the model
when the flip parameters are themselves randomly selected, following some
probability distribution. Examples of these characteristics are whether large
majorities and ties are attractors or repulsors, or the number of fixed points
in the dynamics of the model. Which of the features of the model are likely to
appear? Which ones are unlikely because they only present as events of low
probability with respect to the distribution of the flip parameters? Answers to
such questions allow us to distinguish mathematical properties which are stable
under a variety of assumptions on the distribution of the flip parameters from
features which are very rare and thus more of theoretical than practical
interest. In this article, we present both exact numerical results for specific
distributions of the flip parameters and small discussion groups and rigorous
results in the form of limit theorems for large discussion groups. Small
discussion groups model friend or work groups - people that personally know
each other and frequently spend time together. Large groups represent scenarios
such as social media or political entities such as cities, states, or
countries.


  This paper summarizes some of the recent results on magnetism in high dense
mediums, where the phenomenon of color superconductivity can be present, and
its possible implications for the astrophysics of compact objects. The
presentation will be organized through the answers to three fundamental
questions.


  We analyse the planetary nebulae (PNe) population of the Small Magellanic
Cloud (SMC), based on evolutionary models of stars with metallicities in the
range $10^{-3} \leq Z \leq 4\times 10^{-3}$ and mass $0.9 M\odot < M <
8M\odot$, evolved through the asymptotic giant branch (AGB) phase. The models
used account for dust formation in the circumstellar envelope. To characterise
the PNe sample of the SMC, we compare the observed abundances of the various
species with the final chemical composition of the AGB models: this study
allows us to identify the progenitors of the PNe observed, in terms of mass and
chemical composition. According to our interpretation, most of the PNe descend
from low-mass ($M < 2 M\odot$) stars, which become carbon rich, after
experiencing repeated third dredge-up episodes, during the AGB phase. A
fraction of the PNe showing the signature of advanced CNO processing are
interpreted as the progeny of massive AGB stars, with mass above $\sim 6
M\odot$, undergoing strong hot bottom burning. The differences with the
chemical composition of the PNe population of the Large Magellanic Cloud (LMC)
is explained on the basis of the diverse star formation history and
age-metallicity relation of the two galaxies. The implications of the present
study for some still highly debated points regarding the AGB evolution are also
commented.


  We explore properties of stellar kinematics and ionized gas in a sample of
1106 local (U)LIRGs from the AKARI telescope. We combine data from $Wide-field\
Infrared\ Survey\ Explorer$ (WISE) and Sloan Digital Sky Survey (SDSS) Data
Release 13 (DR13) to fit the spectral energy distribution (SED) of each source
to constrain the contribution of active galactic nuclei (AGNs) to the total IR
luminosity and estimate physical parameters such as stellar mass and
star-formation rate (SFR). We split our sample into AGNs and weak/non-AGNs. We
find that our sample is considerably above the main sequence. The highest SFRs
and stellar masses are associated with ULIRGs. We also fit the H$\beta$ and
H$\alpha$ regions to characterize the outflows. We find that the incidence of
ionized gas outflows in AGN (U)LIRGs ($\sim$ 72\%) is much higher than that in
weak/non-AGN ones ($\sim$ 39\%). The AGN ULIRGs have extreme outflow velocities
(up to $\sim$ 2300 km s$^{-1}$) and high mass-outflow rates (up to $\sim$ 60
\solarm~yr$^{-1}$). Our results suggest that starbursts are insufficient to
produce such powerful outflows. We explore the correlations of SFR and specific
SFR (sSFR) with ionized gas outflows. We find that AGN hosts with the highest
SFRs exhibit a negative correlation between outflow velocity and sSFR.
Therefore, in AGNs containing large amounts of gas, the negative feedback
scenario might be suggested.


  Motivated by the possibility of inflation in the cosmic landscape, which may
be approximated by a complicated potential, we study the density perturbations
in multi-field inflation with a random potential. The random potential causes
the inflaton to undergo a Brownian motion with a drift in the D-dimensional
field space. To quantify such an effect, we employ a stochastic approach to
evaluate the two-point and three-point functions of primordial perturbations.
We find that in the weakly random scenario the resulting power spectrum
resembles that of the single field slow-roll case, with up to 2% more red tilt.
The strongly random scenario, leads to rich phenomenologies, such as primordial
fluctuations in the power spectrum on all angular scales. Such features may
already be hiding in the error bars of observed CMB TT (as well as TE and EE)
power spectrum and can be detected or falsified with more data coming in the
future. The tensor power spectrum itself is free of fluctuations and the tensor
to scalar ratio is enhanced. In addition a large negative running of the power
spectral index is possible. Non-Gaussianity is generically suppressed by the
growth of adiabatic perturbations on super-horizon scales, but can possibly be
enhanced by resonant effects or arise from the entropic perturbations during
the onset of (p)reheating. The formalism developed in this paper can be applied
to a wide class of multi-field inflation models including, e.g. the N-flation
scenario.


  We demonstrate theoretically that electromagnetically induced transparency
can be achieved in metamaterials, in which electromagnetic radiation is
interacting resonantly with mesoscopic oscillators rather than with atoms. We
describe novel metamaterial designs that can support full dark resonant state
upon interaction with an electromagnetic beam and we present results of its
frequency-dependent effective permeability and permittivity. These results,
showing a transparency window with extremely low absorption and strong
dispersion, are confirmed by accurate simulations of the electromagnetic field
propagation in the metamaterial.


  In this paper we survey our recent work on C*-correspondences and their
associated operator algebras; in particular, on adding tails, the Shift
Equivalence Problem and Hilbert bimodules.


  We present a dynamic van der Waals theory. It is useful to study phase
separation when the temperature varies in space. We show that if heat flow is
applied to liquid suspending a gas droplet at zero gravity, a convective flow
occurs such that the temperature gradient within the droplet nearly vanishes.
As the heat flux is increased, the droplet becomes attached to the heated wall
that is wetted by liquid in equilibrium. In one case corresponding to partial
wetting by gas, an apparent contact angle can be defined. In the ther case with
larger heat flux, the droplet completely wets the heated wall expelling liquid.


  A critical component in the implementation of a concurrent tabling system is
the design of the table space. One of the most successful proposals for
representing tables is based on a two-level trie data structure, where one trie
level stores the tabled subgoal calls and the other stores the computed
answers. In this work, we present a simple and efficient lock-free design where
both levels of the tries can be shared among threads in a concurrent
environment. To implement lock-freedom we took advantage of the CAS atomic
instruction that nowadays can be widely found on many common architectures. CAS
reduces the granularity of the synchronization when threads access concurrent
areas, but still suffers from low-level problems such as false sharing or cache
memory side-effects. In order to be as effective as possible in the concurrent
search and insert operations over the table space data structures, we based our
design on a hash trie data structure in such a way that it minimizes potential
low-level synchronization problems by dispersing as much as possible the
concurrent areas. Experimental results in the Yap Prolog system show that our
new lock-free hash trie design can effectively reduce the execution time and
scale better than previous designs.


  We quantify the efficiency of temporal difference (TD) learning over the
direct, or Monte Carlo (MC), estimator for policy evaluation in reinforcement
learning, with an emphasis on estimation of quantities related to rare events.
Policy evaluation is complicated in the rare event setting by the long
timescale of the event and by the need for \emph{relative accuracy} in
estimates of very small values. Specifically, we focus on least-squares TD
(LSTD) prediction for finite state Markov chains, and show that LSTD can
achieve relative accuracy far more efficiently than MC. We prove a central
limit theorem for the LSTD estimator and upper bound the \emph{relative
asymptotic variance} by simple quantities characterizing the connectivity of
states relative to the transition probabilities between them. Using this bound,
we show that, even when both the timescale of the rare event and the relative
accuracy of the MC estimator are exponentially large in the number of states,
LSTD maintains a fixed level of relative accuracy with a total number of
observed transitions of the Markov chain that is only \emph{polynomially} large
in the number of states.


  Developing efficient electrocatalysts for CO$_2$ reduction into value-added
products is crucial for the green economy. Inspired by the recent synthesis of
Biphenylene (BPH), we have systematically investigated pristine, defective, and
Cu-decorated BPH as an electrocatalyst for the CO$_2$ reduction reactions
(CRR). Our first-principles calculations show the CO$_2$ molecules weakly
interact with the pristine BPH surface while defective BPH facilitates the
CO$_2$ adsorption with a binding energy ($E_b$) of -3.22 eV, indicating the
detrimental process for the CRR on the surface of both systems. Furthermore, we
have investigated the binding energy and kinetic stability of Cu-decorated BPH
as a single-atom-catalyst (SAC). The molecular dynamics simulations confirm the
kinetic stability, revealing that the Cu-atom avoids agglomeration under low
metal dispersal conditions. The CO$_2$ molecule gets adsorbed horizontally on
the Cu-BPH surface with $E_b$ of -0.52 eV. The CRR mechanism is investigated
using two pathways beginning with two different initial intermediate states,
formate ($\mathrm{^*OCOH}$) and the carboxylic ($\mathrm{^*COOH}$) pathways.
The formate pathway confirms the conversion of $\mathrm{^*OCOH}$ to
$\mathrm{^*HCOOH}$ with the rate-limiting potential ($U_L$) of 0.57 eV for the
production of HCOOH, while for the carboxylic pathway, the conversion of
$\mathrm{^*COH}$ to $\mathrm{^*CHOH}$ has $U_L$ of 0.49 eV for the production
of CH$_3$OH. We have also investigated the effect of protons using charged
hydrogen pseudopotential, which hints towards the possible formation of
CH$_3$OH as fuel. Our findings propose Cu-BPH as an efficient single-atom
catalyst for CO$_2$ conversion compared to the well-known Cu metal.


  It is well known that superconductivity in thin films is generally suppressed
with decreasing thickness. This suppression is normally governed by either
disorder-induced localization of Cooper pairs, weakening of Coulomb screening,
or generation and unbinding of vortex-antivortex pairs as described by the
Berezinskii-Kosterlitz-Thouless (BKT) theory. Defying general expectations,
few-layer NbSe2 - an archetypal example of ultrathin superconductors - has been
found to remain superconducting down to monolayer thickness. Here we report
measurements of both the superconducting energy gap and critical temperature in
high-quality monocrystals of few-layer NbSe2, using planar-junction tunneling
spectroscopy and lateral transport. We observe a fully developed gap that
rapidly reduces for devices with the number of layers N < 5, as does their
ctitical temperature. We show that the observed reduction cannot be explained
by disorder, and the BKT mechanism is also excluded by measuring its transition
temperature that for all N remains very close to Tc. We attribute the observed
behavior to changes in the electronic band structure predicted for mono- and
bi- layer NbSe2 combined with inevitable suppression of the Cooper pair density
at the superconductor-vacuum interface. Our experimental results for N > 2 are
in good agreement with the dependences of the gap and Tc expected in the latter
case while the effect of band-structure reconstruction is evidenced by a
stronger suppression of the gap and the disappearance of its anisotropy for N =
2. The spatial scale involved in the surface suppression of the density of
states is only a few angstroms but cannot be ignored for atomically thin
superconductors.


  In this paper, we revisit Johanna Drucker's question, "Is there a digital art
history?" -- posed exactly a decade ago -- in the light of the emergence of
large-scale, transformer-based vision models. While more traditional types of
neural networks have long been part of digital art history, and digital
humanities projects have recently begun to use transformer models, their
epistemic implications and methodological affordances have not yet been
systematically analyzed. We focus our analysis on two main aspects that,
together, seem to suggest a coming paradigm shift towards a "digital" art
history in Drucker's sense. On the one hand, the visual-cultural repertoire
newly encoded in large-scale vision models has an outsized effect on digital
art history. The inclusion of significant numbers of non-photographic images
allows for the extraction and automation of different forms of visual logics.
Large-scale vision models have "seen" large parts of the Western visual canon
mediated by Net visual culture, and they continuously solidify and concretize
this canon through their already widespread application in all aspects of
digital life. On the other hand, based on two technical case studies of
utilizing a contemporary large-scale visual model to investigate basic
questions from the fields of art history and urbanism, we suggest that such
systems require a new critical methodology that takes into account the
epistemic entanglement of a model and its applications. This new methodology
reads its corpora through a neural model's training data, and vice versa: the
visual ideologies of research datasets and training datasets become entangled.


  In the first part, this paper studies the characteristic rank of the
canonical oriented $k$-plane bundle over the Grassmann manifold $SO(n)/(SO(k)
\times SO(n-k))$ of oriented $k$-planes in Euclidean $n$-space. It presents
infinitely many new exact values if $k = 3$ or $k = 4$, as well as new lower
bounds for the number in question if $k > 4$. In the second part, these results
enable us to improve on the general upper bounds for the $Z/2Z$-cup-length of
$SO(n)/(SO(k) \times SO(n-k))$. In particular, for $SO(2^t)/(SO(3) \times
SO(2^t-3))$ (with $t > 2$) we prove that the cup-length is equal to $2^t-3$,
which verifies the corresponding claim of Tomohiro Fukaya's conjecture from
2008.


  From the luminosity, effective temperature, and age of the Hyades brown dwarf
2MASSJ04183483+2131275 (2M0418), sub-stellar evolutionary models predict a mass
in the range 39-55 Jupiter masses (M_Jup) which is insufficient to produce any
substantial lithium burning except for the very upper range >53 M_Jup. Our goal
is to measure the abundance of lithium in this object, test the consistency
between models and observations and refine constraints on the mass and age of
the object.
  We used the 10.4-m Gran Telescopio Canarias (GTC) with its low-dispersion
optical spectrograph to obtain ten spectra of 2277s each covering the range
6300-10300 Angstroms with a resolving power of R~500.
  In the individual spectra, which span several months, we detect persistent
unresolved H_alpha in emission with pseudo equivalent widths (pEW) in the range
45-150 Angstroms and absorption lines of various alkalis with the typical
strengths found in objects of L5 spectral type. The lithium resonance line at
6707.8 Angstroms is detected with pEW of 18+/-4 Angstroms in 2M0418 (L5).
  We determine a lithium abundance of log N(Li) = 3.0+/-0.4 dex consistent with
a minimum preservation of 90% of this element which confirms 2M0418 as a brown
dwarf with a maximum mass of 52 M_Jup. We infer a maximum age for the Hyades of
775 Myr from a comparison with the BHAC15 models. Combining recent results from
the literature with our study, we constrain the mass of 2M0418 to 45-52 M_Jup
and the age of the cluster to 580-775 Myr (1 sigma) based on the lithium
depletion boundary method.


  We apply stochastic average gradient (SAG) algorithms for training
conditional random fields (CRFs). We describe a practical implementation that
uses structure in the CRF gradient to reduce the memory requirement of this
linearly-convergent stochastic gradient method, propose a non-uniform sampling
scheme that substantially improves practical performance, and analyze the rate
of convergence of the SAGA variant under non-uniform sampling. Our experimental
results reveal that our method often significantly outperforms existing methods
in terms of the training objective, and performs as well or better than
optimally-tuned stochastic gradient methods in terms of test error.


  We present a combined resummation for the transverse momentum distribution of
a colorless final state in perturbative QCD, expressed as a function of
transverse momentum pt and the scaling variable x. Its expression satisfies
three requirements: it reduces to standard transverse momentum resummation to
any desired logarithmic order in the limit pt-> 0 for fixed x, up to power
suppressed corrections in pt; it reduces to threshold resummation to any
desired logarithmic order in the limit x-> 1 for fixed pt, up to power
suppressed correction in 1-x; upon integration over transverse momentum it
reproduces the resummation of the total cross cross at any given logarithmic
order in the threshold x->1 limit. Its main ingredient, and our main new
result, is a modified form of transverse momentum resummation, which leads to
threshold resummation upon integration over pt, and for which we provide a
simple closed-form analytic expression in Fourier-Mellin (b,N) space. We give
explicit coefficients up to NNLL order for the specific case of Higgs
production in gluon fusion in the effective field theory limit. Our result
allows for a systematic improvement of the transverse momentum distribution
through threshold resummation which holds for all pt, and elucidates the
relation between transverse momentum resummation and threshold resummation at
the inclusive level, specifically by providing within perturbative QCD a simple
derivation of the main consequence of the so-called collinear anomaly of SCET.


  The most common way to sample from a probability distribution is to use
Monte-Carlo methods. For distributions on a continuous state space, one can
find diffusions with the target distribution as equilibrium measure, so that
the state of the diffusion after a long time provides a good sample from the
desired distribution. There exist many diffusions with a common equilibrium,
and one would naturally like to choose those that make the convergence to
equilibrium faster. One way to do this is to consider a reversible diffusion,
and add to it an antisymmetric drift which preserves the invariant measure. It
has been proven that, in general, the irreversible algorithm performs better
than the reversible one, in that the spectral gap is larger. In the present
work, asymptotic variance is used as the criterion to compare these algorithms.
We first provide a general comparison result, and then apply it to the specific
cases of a diffusion on $\mathbb{R}^d$, or on a compact Riemannian manifold. We
prove that, in general, adding an antisymmetric drift to a reversible diffusion
reduces the asymptotic variance. We also provide some extensions of this result
concerning strict inequality, the worst-case analysis, and the behavior of the
asymptotic variance when the drift goes to infinity.


  By a canonical (resp. terminal) weak $\mathbb{Q}$-Fano $3$-fold we mean a
normal projective one with at worst canonical (resp. terminal) singularities on
which the anti-canonical divisor is $\mathbb{Q}$-Cartier, nef and big. For a
canonical weak $\mathbb{Q}$-Fano $3$-fold $V$, we show that there exists a
terminal weak $\mathbb{Q}$-Fano $3$-fold $X$, being birational to $V$, such
that the $m$-th anti-canonical map defined by $|-mK_{X}|$ is birational for all
$m\geq 52$. As an intermediate result, we show that for any $K$-Mori fiber
space $Y$ of a canonical weak $\mathbb{Q}$-Fano $3$-fold, the $m$-th
anti-canonical map defined by $|-mK_{Y}|$ is birational for all $m\geq 52$.


  In this paper, we propose a method to study the nature of resonant relaxation
in near-Keplerian systems. Our technique is based on measuring the fractal
dimension of the angular momentum trails and we use it to analyze the outcome
of N-body simulations. With our method, we can reliably determine the timescale
for resonant relaxation, as well as the rate of change of angular momentum in
this regime. We find that growth of angular momentum is more rapid than random
walk, but slower than linear growth. We also determine the presence of long
term correlations, arising from the bounds on angular momentum growth. We
develop a toy model that reproduces all essential properties of angular
momentum evolution.


  We propose two detection techniques that take advantage of a small sky area
approximation and are based on modifications of the "internal linear
combination" (ILC) method, an approach widely used in Cosmology for the
separation of the various components that contribute to the microwave
background. The main advantage of the proposed approach, especially in handling
multi-frequency maps of the same region, is that it does not require the "a
priori" knowledge of the spatial power-spectrum of either the CMB and/or the
Galactic foreground. Hence, it is more robust, easier and more intuitive to
use. The performance of the proposed algorithms is tested with numerical
experiments that mimic the physical scenario expected for high Galactic
latitude observations with the Atacama Large Millimeter/submillimeter Array
(ALMA).


  Learned wavelet image and video coding approaches provide an explainable
framework with a latent space corresponding to a wavelet decomposition. The
wavelet image coder iWave++ achieves state-of-the-art performance and has been
employed for various compression tasks, including lossy as well as lossless
image, video, and medical data compression. However, the approaches suffer from
slow decoding speed due to the autoregressive context model used in iWave++. In
this paper, we show how a parallelized context model can be integrated into the
iWave++ framework. Our experimental results demonstrate a speedup factor of
over 350 and 240 for image and video compression, respectively. At the same
time, the rate-distortion performance in terms of Bj{\o}ntegaard delta bitrate
is slightly worse by 1.5\% for image coding and 1\% for video coding. In
addition, we analyze the learned wavelet decomposition by visualizing its
subband impulse responses.


  The observed astrophysical phenomenon of dark matter has generated new
interest in the problem of whether the principles underlying QFT are consistent
with invisibility/inertness of energy-momentum carrying "stuff" as e.g.
"unparticles". We show that the 2-dim. model which has been used to illustrate
the meaning of unparticles belongs to the class of former infraparticles models
and the latter are known to describe electrically charged particles in d=1+3
which despite their nonlocality are our best particle physics "candles". The
"invisibility" in this case refers to the infinite infrared photon cloud with
energies below the resolution and can be made arbitrarily small by increasing
the photon registering sensitivity. This is not quite the kind of invisibility
which the unparticle community attributes to their invisible "stuff" and which
would probably contradict the asymptotic completeness property. The main aim of
the present work is to show that knowledge about this part of QFT is still in
its infancy and express the hope that the work on unparticles may rekindle a
new interest in conceptually subtle old unsolved important problems.


  We present the first spatially resolved analysis of rest-frame optical and UV
imaging and spectroscopy for a lensed galaxy at z = 2.39 hosting a Seyfert
active galactic nucleus (AGN). Proximity to a natural guide star has enabled
high signal-to-noise VLT SINFONI + adaptive optics observations of rest-frame
optical diagnostic emission lines, which exhibit an underlying broad component
with FWHM ~ 700 km/s in both the Balmer and forbidden lines. Measured line
ratios place the outflow robustly in the region of the ionization diagnostic
diagrams associated with AGN. This unique opportunity - combining gravitational
lensing, AO guiding, redshift, and AGN activity - allows for a magnified view
of two main tracers of the physical conditions and structure of the
interstellar medium in a star-forming galaxy hosting a weak AGN at cosmic noon.
By analyzing the spatial extent and morphology of the Ly-alpha and
dust-corrected H-alpha emission, disentangling the effects of star formation
and AGN ionization on each tracer, and comparing the AGN induced mass outflow
rate to the host star formation rate, we find that the AGN does not
significantly impact the star formation within its host galaxy.


  We present an efficient and parsimonious algorithm to solve mixed
initial/final-value problems. The algorithm optimally limits the memory storage
and the computational time requirements: with respect to a simple forward
integration, the cost factor is only logarithmic in the number of time-steps.
As an example, we discuss the solution of the final-value problem for a
Fokker-Planck equation whose drift velocity solves a different initial-value
problem -- a relevant issue in the context of turbulent scalar transport.


  We investigate the role of undetermined finite contributions generated by
radiative corrections in a $SU(2)\times SU(2)$ linear sigma model with quarks.
Although some of such terms can be absorbed in the renormalization procedure,
one such contribution is left in the expression for the pion decay constant.
This arbitrariness is eliminated by chiral symmetry.


  We study Bianchi type-I space time with cosmological constant lambda using
some conditions.


  We have studied intersubband decay of E22 excitons in semiconducting carbon
nanotubes experimentally and theoretically. Photoluminescence excitation line
widths of semiconducting nanotubes with chiral indicess (n, m) can be mapped
onto a connectivity grid with curves of constant (n-m) and (2n+m). Moreover,
the global behavior of E22 linewidths is best characterized by a strong
increase with energy irrespective of their (n-m) mod(3)= \pm 1 family
affiliation. Solution of the Bethe-Salpeter equations shows that the E22
linewidths are dominated by phonon assisted coupling to higher momentum states
of the E11 and E12 exciton bands. The calculations also suggest that the
branching ratio for decay into exciton bands vs free carrier bands,
respectively is about 10:1.


  It has been shown that the Cauchy problem for geodesics in the space of
K\"ahler metrics with a fixed cohomology class on a compact complex manifold
$M$ can be effectively reduced to the problem of finding the flow of a related
hamiltonian vector field $X_H$, followed by analytic continuation of the time
to complex time.
  This opens the possibility of expressing the geodesic $\omega_t$ in terms of
Gr\"obner Lie series of the form $\exp(\sqrt{-1} \, tX_H)(f)$, for local
holomorphic functions $f$. The main goal of this paper is to use truncated Lie
series as a new way of constructing approximate solutions to the geodesic
equation. For the case of an elliptic curve and $H$ a certain Morse function
squared, we approximate the relevant Lie series by their first twelve terms,
calculated with the help of Mathematica. This leads to approximate geodesics
which hit the boundary of the space of K\"ahler metrics in finite geodesic
time. For quantum mechanical applications, one is interested also on the
non-K\"ahler polarizations that one obtains by crossing the boundary of the
space of K\"ahler structures. Properties of the approximate geodesics and its
extensions are also studied using Mathematica.


  In this work we exploit the integrability of the two-lead Anderson model to
compute transport properties of a quantum dot, in and out of equilibrium. Our
method combines the properties of integrable scattering together with a
Landauer-Buttiker formalism. Although we use integrability, the nature of the
problem is such that our results are not generically exact, but must only be
considered as excellent approximations which nonetheless are valid all the way
through crossover regimes.
  The key to our approach is to identify the excitations that correspond to
scattering states and then to compute their associated scattering amplitudes.
We are able to do so both in and out of equilibrium. In equilibrium and at zero
temperature, we reproduce the Friedel sum rule for an arbitrary magnetic field.
At finite temperature, we study the linear response conductance at the
symmetric point of the Anderson model, and reproduce Costi et al.'s numerical
renormalization group computation of this quantity. We then explore the
out-of-equilibrium conductance for a near-symmetric Anderson model, and arrive
at quantitative expressions for the differential conductance, both in and out
of a magnetic field. We find the expected splitting of the differential
conductance peak into two in a finite magnetic field, $H$. We determine the
width, height, and position of these peaks. In particular we find for H >> T_k,
the Kondo temperature, the differential conductance has maxima of e^2/h
occuring for a bias V close to but smaller than H. The nature of our
construction of scattering states suggests that our results for the
differential magneto-conductance are not merely approximate but become exact in
the large field limit.


  A spin filtering device using quantum spin interference is theoretically
proposed in a GaAs/AlGaAs electron gas that has both Rashba and Dresselhaus
spin-orbit couplings. The device achieves polarized electron currents by
separating spin up and spin down components without a magnetic field gradient.
We find two broad spin filtering regimes, one where the interferometer has
symmetrical arms, where a small magnetic flux is needed to achieve spin
separation, and the other with asymmetric arms where the change in path length
renders an extra phase emulating the effects of a magnetic field. We identify
operating points for the device where optimal electron polarization is achieved
within value ranges found in a 2D electron gas. Both device setups apply for
arbitrary incoming electron polarization and operate at broad energy ranges
within the incoming electron band.


  To study the characteristics of synchrotron radiation in magnetic fields of
accelerators first the author was necessary to obtain a continuous solutions of
Hill's equation. For this purpose the gradient or the components of magnetic
field were developed in a series. The same procedure is followed now in the
case of storage rings. This approach proved to be interesting not only from the
point of view of describing the motion of partiles in ordinary
three-dimensional space but also in the fact that we get new differential
equations. This brief review can be regarded as an introduction to the proposed
method. The next step may be to add nonlinearities. This would be the best
approximation to the determination of betatron oscillations in the existing
accelerators.


  A genus one curve of degree 5 is defined by the 4 x 4 Pfaffians of a 5 x 5
alternating matrix of linear forms on P^4. We describe a general method for
investigating the invariant theory of such models. We use it to explain how we
found our algorithm for computing the invariants [12] and to extend our method
in [14] for computing equations for visible elements of order 5 in the
Tate-Shafarevich group of an elliptic curve. As a special case of the latter we
find a formula for the family of elliptic curves 5-congruent to a given
elliptic curve in the case the 5-congruence does not respect the Weil pairing.
We also give an algorithm for doubling elements in the 5-Selmer group of an
elliptic curve, and make a conjecture about the matrices representing the
invariant differential on a genus one normal curve of arbitrary degree.


  A forbidden transition graph is a graph defined together with a set of
permitted transitions i.e. unordered pair of adjacent edges that one may use
consecutively in a walk in the graph. In this paper, we look for the smallest
set of transitions needed to be able to go from any vertex of the given graph
to any other. We prove that this problem is NP-hard and study approximation
algorithms. We develop theoretical tools that help to study this problem.


  The recent innovations and breakthroughs in diffusion models have
significantly expanded the possibilities of generating high-quality videos for
the given prompts. Most existing works tackle the single-scene scenario with
only one video event occurring in a single background. Extending to generate
multi-scene videos nevertheless is not trivial and necessitates to nicely
manage the logic in between while preserving the consistent visual appearance
of key content across video scenes. In this paper, we propose a novel
framework, namely VideoDrafter, for content-consistent multi-scene video
generation. Technically, VideoDrafter leverages Large Language Models (LLM) to
convert the input prompt into comprehensive multi-scene script that benefits
from the logical knowledge learnt by LLM. The script for each scene includes a
prompt describing the event, the foreground/background entities, as well as
camera movement. VideoDrafter identifies the common entities throughout the
script and asks LLM to detail each entity. The resultant entity description is
then fed into a text-to-image model to generate a reference image for each
entity. Finally, VideoDrafter outputs a multi-scene video by generating each
scene video via a diffusion process that takes the reference images, the
descriptive prompt of the event and camera movement into account. The diffusion
model incorporates the reference images as the condition and alignment to
strengthen the content consistency of multi-scene videos. Extensive experiments
demonstrate that VideoDrafter outperforms the SOTA video generation models in
terms of visual quality, content consistency, and user preference.


  In 1665, Huygens observed that two pendulum clocks hanging from the same
board became synchronized in antiphase after hundreds of swings. On the other
hand, modern experiments with metronomes placed on a movable platform show that
they often tend to synchronize in phase, not antiphase. Here we study both
in-phase and antiphase synchronization in a model of pendulum clocks and
metronomes and analyze their long-term dynamics with the tools of perturbation
theory. Specifically, we exploit the separation of timescales between the fast
oscillations of the individual pendulums and the much slower adjustments of
their amplitudes and phases. By scaling the equations appropriately and
applying the method of multiple timescales, we derive explicit formulas for the
regimes in parameter space where either antiphase or in-phase synchronization
are stable, or where both are stable. Although this sort of perturbative
analysis is standard in other parts of nonlinear science, it has been applied
surprisingly rarely in the context of Huygens's clocks. Unusual features of our
approach include its treatment of the escapement mechanism, a small-angle
approximation up to cubic order, and both a two- and three-timescale asymptotic
analysis.


  We present a detailed description of our calculation of next-to-leading order
QCD corrections to heavy quark production in e^+ e^- collisions including mass
effects. In particular, we study the observables $R_3^{b\ql}$ and $D_2^{b\ql}$
in the E, EM, JADE and DURHAM jet-clustering algorithms and show how one can
use these observables to obtain $m_b(m_Z)$ from data at the $Z$ peak.


  In this paper, the convergence time of federated learning (FL), when deployed
over a realistic wireless network, is studied. In particular, a wireless
network is considered in which wireless users transmit their local FL models
(trained using their locally collected data) to a base station (BS). The BS,
acting as a central controller, generates a global FL model using the received
local FL models and broadcasts it back to all users. Due to the limited number
of resource blocks (RBs) in a wireless network, only a subset of users can be
selected to transmit their local FL model parameters to the BS at each learning
step. Moreover, since each user has unique training data samples, the BS
prefers to include all local user FL models to generate a converged global FL
model. Hence, the FL performance and convergence time will be significantly
affected by the user selection scheme. Therefore, it is necessary to design an
appropriate user selection scheme that enables users of higher importance to be
selected more frequently. This joint learning, wireless resource allocation,
and user selection problem is formulated as an optimization problem whose goal
is to minimize the FL convergence time while optimizing the FL performance. To
solve this problem, a probabilistic user selection scheme is proposed such that
the BS is connected to the users whose local FL models have significant effects
on its global FL model with high probabilities. Given the user selection
policy, the uplink RB allocation can be determined. To further reduce the FL
convergence time, artificial neural networks (ANNs) are used to estimate the
local FL models of the users that are not allocated any RBs for local FL model
transmission at each given learning step, which enables the BS to enhance its
global FL model and improve the FL convergence speed and performance.


  Since the invention of dynamic diode, its physical properties and potential
applications have attracted wide attentions. A lot of attempts have been made
to harvest the rebounding current and voltage of dynamic diode. However, the
underlying physical mechanism of its carrier transport characteristic was
rarely explored carefully. Here, the electrical transport properties of the
dynamic diode are systematically investigated with a mechanical motion tuned
method, where the dynamic current-voltage curve shows a gentler growth trend
compared to the static curve. The rebounding current increases with motion
velocity and contact force, resulting in a reduced current with the same bias
voltage and an oscillation current with a changing velocity and force. Besides,
we propose a circuit model with an accurate mathematical formula expression to
describe the oscillation current, where an imaginary parameter n0 is creatively
added to the exponential growth term. This work shows a physical picture of
adjust microscopic carrier motion with macroscopic mechanical motion, which
provides strong theoretical support for designing dynamic diode devices with
better performance in the future.


  We investigate the exclusive two-pion production at the $Z$-pole through the
process $e^+e^-\to Z \to \pi\pi \gamma$. In the kinematical region where the
invariant mass of the two pions is much smaller than the mass of the $Z$ boson,
the process can be factorized into the convolution of a hard coefficient and a
soft matrix element, the generalized distribution amplitude of two pions. We
calculate the differential cross-section of charged pion pair production and
neutral pion pair production and find the former to be much larger than the
later. We show that combining the measurements of charged pion pair production
and neutral pion pair production at the $Z$-pole provides a convenient approach
to access the $C$-odd part of the $2\pi$ distribution amplitudes.


  I investigate a discrete model of quantum gravity on a causal null-lattice
with \SLC structure group. The description is geometric and foliates in a
causal and physically transparent manner. The general observables of this model
are constructed from local Lorentz symmetry considerations only. For smooth
configurations, the local lattice actions reduce to the Hilbert-Palatini
action, a cosmological term and the three topological terms of dimension four
of Pontyagin, Euler and Nieh-Yan. Consistency conditions for a topologically
hypercubic complex with null 4-simplexes are derived and a topological lattice
theory that enforces these non-local constraints is constructed. The lattice
integration measure is derived from an \SLC-invariant integration measure by
localization of the non-local structure group. This measure is unique up to a
density that depends on the local 4-volume. It can be expressed in terms of
manifestly coordinate invariant geometrical quantities. The density provides an
invariant regularization of the lattice integration measure that suppresses
configurations with small local 4-volumes. Amplitudes conditioned on geodesic
distances between local observables have a physical interpretation and may have
a smooth ultraviolet limit. Numerical studies on small lattices in the
unphysical strong coupling regime of large imaginary cosmological constant
suggest that this model of triangulated causal manifolds is finite. Two
topologically different triangulations of space-time are discussed: a single,
causally connected universe and a duoverse with two causally disjoint connected
components. In the duoverse, two hypercubic sublattices are causally disjoint
but the local curvature depends on fields of both sublattices. This may
simulate effects of dark matter in the continuum limit.


  The secondary spectra of the gravitons induced by a waterfall-like field are
computed and the general bounds on the spectral energy density of the tensor
modes of the geometry are translated into explicit constraints on the amplitude
and slope of the waterfall spectrum. The obtained results are compared with the
primary gravitational wave spectra of the concordance model and of its
neighboring extensions as well as with the direct Ligo/Virgo bounds on
stochastic backgrounds of relic gravitons. Space-borne interferometers (such as
Lisa, Bbo, Decigo) seem to be less relevant but their potential implications
are briefly outlined.


  The role of axonal synaptic delays in the efficacy and performance of
artificial neural networks has been largely unexplored. In step-based
analog-valued neural network models (ANNs), the concept is almost absent. In
their spiking neuroscience-inspired counterparts, there is hardly a systematic
account of their effects on model performance in terms of accuracy and number
of synaptic operations.This paper proposes a methodology for accounting for
axonal delays in the training loop of deep Spiking Neural Networks (SNNs),
intending to efficiently solve machine learning tasks on data with rich
temporal dependencies. We then conduct an empirical study of the effects of
axonal delays on model performance during inference for the Adding task, a
benchmark for sequential regression, and for the Spiking Heidelberg Digits
dataset (SHD), commonly used for evaluating event-driven models. Quantitative
results on the SHD show that SNNs incorporating axonal delays instead of
explicit recurrent synapses achieve state-of-the-art, over 90% test accuracy
while needing less than half trainable synapses. Additionally, we estimate the
required memory in terms of total parameters and energy consumption of
accomodating such delay-trained models on a modern neuromorphic accelerator.
These estimations are based on the number of synaptic operations and the
reference GF-22nm FDX CMOS technology. As a result, we demonstrate that a
reduced parameterization, which incorporates axonal delays, leads to
approximately 90% energy and memory reduction in digital hardware
implementations for a similar performance in the aforementioned task.


  We report on a study that compares energetic particle fluxes in corotating
interaction regions (CIRs) associated with type III radio storm with those in
nonstorm CIRs. In a case study, we compare the CIR particle events on
2010October 21 and 2005 November 2. The two events have similar solar and solar
wind circumstances, except that the former is associated with a type III radio
storm and has a higher CIR particle flux and fluence. We also perform a
statistical study, which shows that the proton and electron fluences are higher
in the storm associated CIRs by factor of about 6 and 8, respectively than
those in the storm-free CIRs.


  A spoken language understanding (SLU) system includes two main tasks, slot
filling (SF) and intent detection (ID). The joint model for the two tasks is
becoming a tendency in SLU. But the bi-directional interrelated connections
between the intent and slots are not established in the existing joint models.
In this paper, we propose a novel bi-directional interrelated model for joint
intent detection and slot filling. We introduce an SF-ID network to establish
direct connections for the two tasks to help them promote each other mutually.
Besides, we design an entirely new iteration mechanism inside the SF-ID network
to enhance the bi-directional interrelated connections. The experimental
results show that the relative improvement in the sentence-level semantic frame
accuracy of our model is 3.79% and 5.42% on ATIS and Snips datasets,
respectively, compared to the state-of-the-art model.


  Composed ensembles of random unitary matrices are defined via products of
matrices, each pertaining to a given canonical circular ensemble of Dyson. We
investigate statistical properties of spectra of some composed ensembles and
demonstrate their physical relevance. We discuss also the methods of generating
random matrices distributed according to invariant Haar measure on the
orthogonal and unitary group.


  Aims: We investigate the effect of ram pressure stripping (RPS) on
simulations of merging pairs of gas-rich spiral galaxies. Our goal is to
provide an estimate of the combined effect of merging and RPS on stripping
efficiency and star formation rate.
  Methods: We make use of the combined N-body/hydrodynamic code GADGET-2. In
our simulations, we vary mass ratios between 1:4 and 1:8 in a binary merger. We
sample different geometric configurations of the merging systems (edge-on and
face-on mergers, different impact parameters). Furthermore, we vary the
properties of the intracluster medium (ICM) in rough steps: The speed of the
merging system relative to the ICM between 500 and 1000 km/s, the ICM density
between $10^{-29}$ and $10^{-27}$ g/cm$^3$, and the ICM direction relative to
the mergers' orbital plane. Ram pressure is kept constant within a simulation
time period, as is the ICM temperature of $10^7$ K. Each simulation in the ICM
is compared to simulations of the merger in vacuum and the non-merging galaxies
with acting ram pressure.
  Results: Averaged over the simulation time (1 Gyr) the merging pairs show a
negligible 5% enhancement in SFR, when compared to single galaxies under the
same environmental conditions. The SFRs peak at the time of the galaxies first
fly-through. There, our simulations show SFRs of up to 20 M$_{\odot}$/yr
(compared to 3 M$_{\odot}$/yr of the non-merging galaxies in vacuum). In the
most extreme case, this constitutes a short-term ($<50$ Myr) SFR increase of
50% over the non-merging galaxies experiencing ram pressure. The wake of
merging galaxies in the ICM typically has a third to half the star mass seen in
the non-merging galaxies and 5% to 10 % less gas mass. The joint effect of RPS
and merging, according to our simulations, is not significantly different from
pure ram pressure effects.


  Many scientific software platforms provide plugin mechanisms that simplify
the integration, deployment, and execution of externally developed
functionality. One of the most widely used platforms in the imaging space is
Fiji, a popular open-source application for scientific image analysis. Fiji
incorporates and builds on the ImageJ and ImageJ2 platforms, which provide a
powerful plugin architecture used by thousands of plugins to solve a wide
variety of problems. This capability is a major part of Fiji's success, and it
has become a widely used biological image analysis tool and a target for new
functionality. However, a plugin-based software architecture cannot unify
disparate platforms operating on incompatible data structures; interoperability
necessitates the creation of adaptation or "bridge" layers to translate data
and invoke functionality. As a result, while platforms like Fiji enable a high
degree of interconnectivity and extensibility, they were not fundamentally
designed to integrate across the many data types, programming languages, and
architectural differences of various software platforms.To help address this
challenge, we present SciJava Ops, a foundational software library for
expressing algorithms as plugins in a unified and extensible way. Continuing
the evolution of Fiji's SciJava plugin mechanism, SciJava Ops enables users to
harness algorithms from various software platforms within a central execution
environment. In addition, SciJava Ops automatically adapts data into the most
appropriate structure for each algorithm, allowing users to freely and
transparently combine algorithms from otherwise incompatible tools. While
SciJava Ops is initially distributed as a Fiji update site, the framework does
not require Fiji, ImageJ, or ImageJ2, and would be suitable for integration
with additional image analysis platforms.


  Neutrinos can gain mass from coupling to an ultralight field in slow roll.
When such a field is displaced from its minimum, its vev acts just like the
Higgs vev in spontaneous symmetry breaking. Although these masses may
eventually vanish, they do it over a very long time. The theory is technically
natural, with the ultralight field-dependent part being the right-handed
Majorana mass. The mass variation induced by the field correlates with the
cosmological evolution. The change of the mass term changes the mixing matrix,
and therefore suppresses the fraction of sterile neutrinos at earlier times and
increases it at later times. Since the issue of quantum gravity corrections to
field theories with large field variations remains open, this framework may
give an observational handle on the Weak Gravity Conjecture.


  The theory of statistical mechanics is studied in the presence of
Lorentz-violating background fields. The analysis is performed using the
Standard-Model Extension (SME) together with a Jaynesian formulation of
statistical inference. Conventional laws of thermodynamics are obtained in the
presence of a perturbed hamiltonian that contains the Lorentz violating terms.
As an example, properties of the nonrelativistic ideal gas are calculated in
detail. To lowest order in Lorentz violation, the scalar thermodynamic
variables are only corrected by a rotationally invariant combination of
parameters that mimics a (frame dependent) effective mass. Spin couplings can
induce a temperature independent polarization in the classical gas that is not
present in the conventional case. Precision measurements in the residual
expectation values of the magnetic moment of Fermi gases in the limit of high
temperature may provide interesting limits on these parameters.


  The coupled Burgers equation is solved by way of the trigonometric B-spline
collocation method. The unknown of the coupled Burgers equation is integrated
in time by aid of the Crank-Nicolson method. Resulting time-integrated coupled
Burgers equation is discretized using the trigonometric cubic B-spline
collocation method. Fully-integrated couupled Burgers equation which is a
system of nonlinear algebraic equation is solved with a variant of Thomas
algorithm. The three model test problems are studied to illustrate the accuracy
of the suggested method.


  We use the entropy function formalism introduced by A. Sen to obtain the
entropy of $AdS_{2}\times S^{d-2}$ extremal and static black holes in four and
five dimensions, with higher derivative terms of a general type. Starting from
a generalized Einstein--Maxwell action with nonzero cosmological constant, we
examine all possible scalar invariants that can be formed from the complete set
of Riemann invariants (up to order 10 in derivatives). The resulting entropies
show the deviation from the well known Bekenstein--Hawking area law $S=A/4G$
for Einstein's gravity up to second order derivatives.


  There is an overlooked iceberg of problems in end user computing.
Spreadsheets are developed by people who are very skilled in their main job
function, be it finance, procurement, or production planning, but often have
had no formal training in spreadsheet use. IT auditors focus on mainstream
information systems but regard spreadsheets as user problems, outside their
concerns. Internal auditors review processes, but not the tools that support
decision making in these processes.
  This paper highlights the gaps between risk management and end user awareness
in spreadsheet research. In addition the potential benefits of software agent
technologies to the management of risk in spreadsheets are explored. This paper
discusses the current research into end user computing and spreadsheet use
awareness.


  Crisis responders are increasingly using social media, data and other digital
sources of information to build a situational understanding of a crisis
situation in order to design an effective response. However with the increased
availability of such data, the challenge of identifying relevant information
from it also increases. This paper presents a successful automatic approach to
handling this problem. Messages are filtered for informativeness based on a
definition of the concept drawn from prior research and crisis response
experts. Informative messages are tagged for actionable data -- for example,
people in need, threats to rescue efforts, changes in environment, and so on.
In all, eight categories of actionability are identified. The two components --
informativeness and actionability classification -- are packaged together as an
openly-available tool called Emina (Emergent Informativeness and
Actionability).


  We perform an analysis of jet quenching in heavy and light ion collisions for
scenarios without and with quark-gluon plasma formation in $pp$ collisions. We
find that the results for these scenarios are very similar, and both of them
are in reasonable agreement with data for heavy ion collisions. However, their
results become differ significantly for light nuclei. Using the parameters
fitted to heavy ion data on the nuclear modification factor $R_{AA}$, we make
predictions for 0.2 and 7 TeV O+O collisions that can be verified by future
experiments at RHIC and the LHC.


  We investigate the cocompact action of Higman's group on a CAT(0) square
complex associated to its standard presentation. We show that this action is in
a sense intrinsic, which allows for the use of geometric techniques to study
the endomorphisms of the group, and show striking similarities with mapping
class groups of hyperbolic surfaces, outer automorphism groups of free groups
and linear groups over the integers. We compute explicitly the automorphism
group and outer automorphism group of Higman's group, and show that the group
is both hopfian and co-hopfian. We actually prove a stronger rigidity result
about the endomorphisms of Higman's group: Every non-trivial morphism from the
group to itself is an automorphism. We also study the geometry of the action
and prove a surprising result: Although the CAT(0) square complex acted upon
contains uncountably many flats, the Higman group does not contain subgroups
isomorphic to Z^2. Finally, we show that this action possesses features
reminiscent of negative curvature, which we use to prove a refined version of
the Tits alternative for Higman's group.


  Multi-agent reinforcement learning (MARL) algorithms have accomplished
remarkable breakthroughs in solving large-scale decision-making tasks.
Nonetheless, most existing MARL algorithms are model-free, limiting sample
efficiency and hindering their applicability in more challenging scenarios. In
contrast, model-based reinforcement learning (MBRL), particularly algorithms
integrating planning, such as MuZero, has demonstrated superhuman performance
with limited data in many tasks. Hence, we aim to boost the sample efficiency
of MARL by adopting model-based approaches. However, incorporating planning and
search methods into multi-agent systems poses significant challenges. The
expansive action space of multi-agent systems often necessitates leveraging the
nearly-independent property of agents to accelerate learning. To tackle this
issue, we propose the MAZero algorithm, which combines a centralized model with
Monte Carlo Tree Search (MCTS) for policy search. We design a novel network
structure to facilitate distributed execution and parameter sharing. To enhance
search efficiency in deterministic environments with sizable action spaces, we
introduce two novel techniques: Optimistic Search Lambda (OS($\lambda$)) and
Advantage-Weighted Policy Optimization (AWPO). Extensive experiments on the
SMAC benchmark demonstrate that MAZero outperforms model-free approaches in
terms of sample efficiency and provides comparable or better performance than
existing model-based methods in terms of both sample and computational
efficiency. Our code is available at https://github.com/liuqh16/MAZero.


  This article aims to: i) review the current membrane-based methods in REEs
separation focusing on non-liquid membranes (imprinted, polymer inclusion,
nanocomposite, metal-/covalent organic framework membranes), ii) present the
considerations of the essential scientific and technical issues, e.g.
extraction performances, separation efficiency, REEs transport features, and
iii) discuss their transport models and mechanisms as well as membrane
stability.


  The main result of this paper is an almost approximation-preserving
polynomial-time reduction from the most general multi-parameter Bayesian
contract design (BCD) to single-parameter BCD. That is, for any multi-parameter
BCD instance $I^M$, we construct a single-parameter instance $I^S$ such that
any $\beta$-approximate contract (resp. menu of contracts) of $I^S$ can in turn
be converted to a $(\beta -\epsilon)$-approximate contract (resp. menu of
contracts) of $I^M$. The reduction is in time polynomial in the input size and
$\log(\frac{1}{\epsilon})$; moreover, when $\beta = 1$ (i.e., the given
single-parameter solution is exactly optimal), the dependence on
$\frac{1}{\epsilon}$ can be removed, leading to a polynomial-time exact
reduction. This efficient reduction is somewhat surprising because in the
closely related problem of Bayesian mechanism design, a polynomial-time
reduction from multi-parameter to single-parameter setting is believed to not
exist. Our result demonstrates the intrinsic difficulty of addressing moral
hazard in Bayesian contract design, regardless of being single-parameter or
multi-parameter.
  As byproducts, our reduction answers two open questions in recent literature
of algorithmic contract design: (a) it implies that optimal contract design in
single-parameter BCD is not in APX unless P=NP even when the agent's type
distribution is regular, answering the open question of [Alon et al. 2021] in
the negative; (b) it implies that the principal's (order-wise) tight utility
gap between using a menu of contracts and a single contract is $\Theta(n)$
where $n$ is the number of actions, answering the major open question of
[Guruganesh et al. 2021] for the single-parameter case.