  In the first part of the paper the authors study the minimal and maximal
extension of a class of weighted pseudodifferential operators in the Fr\'echet
space $L^p_{\rm loc}(\Omega)$. In the second one non homogeneous microlocal
properties are introduced and propagation of Sobolev singularities for
solutions to (pseudo)differential equations is given. For both the arguments
actual examples are provided.


  We study CP-conserving non-minimal flavour violation in $A_4 \times SU(5)$
inspired Supersymmetric Grand Unified Theories (GUTs), focussing on the regions
of parameter space where dark matter is successfully accommodated due to a
light right-handed smuon a few GeV heavier than the lightest neutralino. In
this region of parameter space we find that some of the flavour-violating
parameters are constrained by the requirement of the dark matter relic density,
due to the delicate interplay between the smuon and neutralino masses. By
scanning over GUT scale flavour violating parameters, constrained by low-energy
quark and lepton flavour violating observables, we find a striking difference
in the results in which individual parameters are varied to those where
multiple parameters are varied simultaneously, where the latter relaxes the
constraints on flavour violating parameters due to cancellations and/or
correlations. Since charged lepton-flavour violation provides the strongest
constraints within a GUT framework, due to relations between quark and lepton
flavour violation, we examine in detail a prominent correlation between some of
the flavour violating parameters at the GUT scale consistent with the stringent
lepton flavour violating process $\mu \rightarrow e \gamma$. We also examine
the relation between GUT scale and low scale flavour violating parameters, for
both quarks and leptons, and show how the usual expectations may be violated
due to the correlations when multiple parameters are varied simultaneously.


  We investigate allowed regions in observable space of B --> pi K, B_d -->
pi^+pi^- and B_s --> K^+K^- decays, characterizing these modes in the Standard
Model. After a discussion of a new kind of contour plots for the $B\to\pi K$
system, we focus on the mixing- induced and direct CP asymmetries of the decays
B_d --> pi^+pi^- and B_s--> K^+K^-. Using experimental information on the
CP-averaged B_d --> pi^{+/-}K^{+/-} and B_d --> pi^+pi^- branching ratios, the
relevant hadronic penguin parameters can be constrained,implying certain
allowed regions in observable space. In the case of B_d --> pi^+pi^-, an
interesting situation arises now in view of the recent B-factory measurements
of CP violation in this channel, allowing us to obtain new constraints on the
CKM angle gamma as a function of the B^0_d--\bar{B^0_d} mixing phase
phi_d=2beta, which is fixed through A_{CP}^{mix}(B_d --> J/psi K_S) up to a
twofold ambiguity. If we assume that A_{CP}^{mix}(B_d --> pi^+pi^-) is
positive, as indicated by recent Belle data, and that phi_d is in agreement
with the ``indirect'' fits of the unitarity triangle, also the corresponding
values for gamma around 60 degrees can be accommodated. On the other hand, for
the second solution of phi_d, we obtain a gap around gamma ~ 60 degrees. The
allowed region in the space of A_{CP}^{mix}(B_s --> K^+K^-) and
A_{CP}^{dir}(B_s --> K^+K^-) is very constrained in the Standard Model, thereby
providing a narrow target range for run II of the Tevatron and the experiments
of the LHC era.


  Retrieving keywords (bidwords) with the same intent as query, referred to as
close variant keywords, is of prime importance for effective targeted search
advertising. For head and torso search queries, sponsored search engines use a
huge repository of same intent queries and keywords, mined ahead of time.
Online, this repository is used to rewrite the query and then lookup the
rewrite in a repository of bid keywords contributing to significant revenue.
Recently generative retrieval models have been shown to be effective at the
task of generating such query rewrites. We observe two main limitations of such
generative models. First, rewrites generated by these models exhibit low
lexical diversity, and hence the rewrites fail to retrieve relevant keywords
that have diverse linguistic variations. Second, there is a misalignment
between the training objective - the likelihood of training data, v/s what we
desire - improved quality and coverage of rewrites. In this work, we introduce
CLOVER, a framework to generate both high-quality and diverse rewrites by
optimizing for human assessment of rewrite quality using our diversity-driven
reinforcement learning algorithm. We use an evaluation model, trained to
predict human judgments, as the reward function to finetune the generation
policy. We empirically show the effectiveness of our proposed approach through
offline experiments on search queries across geographies spanning three major
languages. We also perform online A/B experiments on Bing, a large commercial
search engine, which shows (i) better user engagement with an average increase
in clicks by 12.83% accompanied with an average defect reduction by 13.97%, and
(ii) improved revenue by 21.29%.


  We describe a novel artificial dielectric material which has applications at
millimetre and submillimetre wavelengths. The material is manufactured from
layers of metal mesh patterned onto thin polypropylene sheets which are then
bonded together using a hot pressing process to provide planar rugged discs
which can be reliably cycled to cryogenic temperatures. The refractive index of
this material can be tuned by adjusting the geometry and spacing of the
metal-mesh layers. We demonstrate its usage by designing and characterising a
broadband anti-reflection coating for a Z-cut crystalline Quartz plate. The
coating was fabricated and applied to the quartz using the hot press technique
and characterized using a Fourier Transform Spectrometer. The performance is
shown to be in good agreement with HFSS and transmission line modelling
results.


  We present FiFTy, a modern file type identification tool for memory forensics
and data carving. In contrast to previous approaches based on hand-crafted
features, we design a compact neural network architecture, which uses a
trainable embedding space, akin to successful natural language processing
models. Our approach dispenses with explicit feature extraction which is a
bottleneck in legacy systems. We evaluate the proposed method on a novel
dataset with 75 file types - the most diverse and balanced dataset reported to
date. FiFTy consistently outperforms all baselines in terms of speed, accuracy
and individual misclassification rates. We achieved an average accuracy of
77.5% with processing speed of approx 38 sec/GB, which is better and more than
an order of magnitude faster than the previous state-of-the-art tool - Sceadan
(69% at 9 min/GB). Our tool and the corresponding dataset are available
publicly online.


  This paper develops a Decentralized Multi-Agent Reinforcement Learning
(Dec-MARL) method to solve the SoC balancing problem in the distributed energy
storage system (DESS). First, the SoC balancing problem is formulated into a
finite Markov decision process with action constraints derived from demand
balance, which can be solved by Dec-MARL. Specifically, the first-order average
consensus algorithm is utilized to expand the observations of the DESS state in
a fully-decentralized way, and the initial actions (i.e., output power) are
decided by the agents (i.e., energy storage units) according to these
observations. In order to get the final actions in the allowable range, a
counterfactual demand balance algorithm is proposed to balance the total demand
and the initial actions. Next, the agents execute the final actions and get
local rewards from the environment, and the DESS steps into the next state.
Finally, through the first-order average consensus algorithm, the agents get
the average reward and the expended observation of the next state for later
training. By the above procedure, Dec-MARL reveals outstanding performance in a
fully-decentralized system without any expert experience or constructing any
complicated model. Besides, it is flexible and can be extended to other
decentralized multi-agent systems straightforwardly. Extensive simulations have
validated the effectiveness and efficiency of Dec-MARL.


  We consider some crucial problems related to the secure and reliable
operation of power systems with high renewable penetrations: how much reserve
should we procure, how should reserve resources distribute among different
locations, and how should we price reserve and charge uncertainty sources.
These issues have so far been largely addressed empirically. In this paper, we
first develop a scenario-oriented energy-reserve co-optimization model, which
directly connects reserve procurement with possible outages and load/renewable
power fluctuations without the need for empirical reserve requirements.
Accordingly, reserve can be optimally procured system-wide to handle all
possible future uncertainties with the minimum expected system total cost.
Based on the proposed model, marginal pricing approaches are developed for
energy and reserve, respectively. Locational uniform pricing is established for
energy, and the similar property is also established for the combination of
reserve and re-dispatch. In addition, properties of cost recovery for
generators and revenue adequacy for the system operator are also proven.


  Two years on from the initial release of AlphaFold2 we have seen its
widespread adoption as a structure prediction tool. Here we discuss some of the
latest work based on AlphaFold2, with a particular focus on its use within the
structural biology community. This encompasses use cases like speeding up
structure determination itself, enabling new computational studies, and
building new tools and workflows. We also look at the ongoing validation of
AlphaFold2, as its predictions continue to be compared against large numbers of
experimental structures to further delineate the model's capabilities and
limitations.


  We present semi-analytic radiative-shock solutions in which grey Sn-transport
is used to model the radiation, and we include both constant cross sections and
cross sections that depend on temperature and density. These new solutions
solve for a variable Eddington factor (VEF) across the shock domain, which
allows for interesting physics not seen before in radiative-shock solutions.
Comparisons are made with the grey nonequilibrium-diffusion radiative-shock
solutions of Lowrie and Edwards [1], which assumed that the Eddington factor is
constant across the shock domain. It is our experience that the local Mach
number is monotonic when producing nonequilibrium-diffusion solutions, but that
this monotonicity may disappear while integrating the precursor region to
produce Sn-transport solutions. For temperature- and density-dependent cross
sections we show evidence of a spike in the VEF in the far upstream portion of
the radiative-shock precursor. We show evidence of an adaptation zone in the
precursor region, adjacent to the embedded hydrodynamic shock, as conjectured
by Drake [2, 3], and also confirm his expectation that the precursor
temperatures adjacent to the Zeldovich spike take values that are greater than
the downstream post-shock equilibrium temperature. We also show evidence that
the radiation energy density can be nonmonotonic under the Zeldovich spike,
which is indicative of anti-diffusive radiation flow as predicted by McClarren
and Drake [4]. We compare the angle dependence of the radiation flow for the
Sn-transport and nonequilibrium-diffusion radiation solutions, and show that
there are considerable differences in the radiation flow between these models
across the shock structure. Finally, we analyze the radiation flow to
understand the cause of the adaptation zone, as well as the structure of the
Sn-transport radiation-intensity solutions across the shock structure.


  We study one-dimensional general non-Hermitian models with asymmetric
long-range hopping and explore to analytically solve the systems under some
specific boundary conditions. Although the introduction of long-range hopping
terms prevents us from finding analytical solutions for arbitrary boundary
parameters, we identify the existence of exact solutions when the boundary
parameters fulfill some constraint relations, which give the specific boundary
conditions. Our analytical results show that the wave functions take simple
forms and are independent of hopping range, while the eigenvalue spectra
display rich model-dependent structures. Particularly, we find the existence of
a special point coined as pseudo-periodic boundary condition, for which the
eigenvalues are the same as the periodical system when the hopping parameters
fulfill certain conditions, whereas eigenstates display non-Hermitian skin
effect.


  We compute the two-loop contributions to the free energy in the null
compactification of perturbative string theory at finite temperature. The cases
of bosonic, Type II and heterotic strings are all treated. The calculation
exploits an explicit reductive parametrization of the moduli space of
infinite-momentum frame string worldsheets in terms of branched cover
instantons. Various arithmetic and physical properties of the instanton sums
are described. Applications to symmetric product orbifold conformal field
theories and to the matrix string theory conjecture are also briefly discussed.


  We have performed a complete study of BPS vortex solutions in the Abelian
sector of the standard model extension (SME). Specifically, we have coupled the
SME electromagnetism with a Higgs field which is supplemented with a
Lorentz-violating CPT-even term. We have verified that Lorentz violation (LV)
belonging to the Higgs sector allows to interpolate between some well known
models like, Maxwell-Higgs, Chern-Simons-Higgs and Maxwell-Chern-Simons-Higgs.
We can also observed that the electrical charged density distribution is
nonnull in both CPT-even and CPT-odd models; however, the total electric charge
in the CPT-even case is null, whereas in the CPT-odd one it is proportional to
the quantized magnetic flux. The following general results can be established
in relation to the LV introduced in the Higgs sector: it changes the vortex
ansatz and the gauge field boundary conditions. A direct consequence is that
the magnetic flux, besides being proportional to the winding number, also
depends explicitly on the Lorentz-violation belonging to the Higgs sector.


  The recent preprint by Mazin et al. [cond-mat/0212417] contains many
inappropriate evaluations and/or criticisms on our published work [Phys. Rev. B
66, 020513 (2002) and Nature 418, 758 (2002)]. The preprint
[cond-mat/0212417v1] was submitted to Physical Review B as a comment on one of
our papers [Phys. Rev. B 66, 020513 (2002)]. In the reviewing process, Mazin et
al. have withdrawn many of the statements contained in cond-mat/0212417v1,
however two claims remain in their revised manuscript [cond-mat/0212417v3]: (1)
the calculated variations of the superconducting energy gap within the sigma-
or the pi-bands are not observable in real samples due to scatterings, and (2)
the Coulomb repulsion mu(k,k') is negligibly small between sigma- and pi-states
and thus should be approximated by a diagonal 2 x 2 matrix in the sigma and pi
channels. Here, we point out that the former does not affect the validity of
our theoretical work which is for the clean limit, and that the latter is not
correct.


  We create a complete gravity torque map of the disk of the LINER/Seyfert 1.9
galaxy NGC4579. We quantify the efficiency of angular momentum transport and
search for signatures of secular evolution in the fueling process from r~15kpc
down to the inner r~50pc around the Active Galactic Nucleus (AGN). We use both
the 1-0 and 2-1 line maps of CO obtained with the Plateau de Bure
Interferometer (PdBI) as part of the NUclei of Galaxies-(NUGA)-project. We
derive the stellar potential from a NIR (K band) wide field image of the
galaxy. The K-band image, which reveals a stellar bar, together with a high
resolution HI map of NGC4579 obtained with the Very Large Array (VLA), allow us
to extend the gravity torque analysis to the outer disk. The bulk of the gas
response traced by the CO PdBI maps follows the expected gas flow pattern
induced by the bar potential in the presence of two Inner Lindblad Resonances
(ILR). We also detect an oval distortion in the inner r~200pc of the K-band
image. The oval is not aligned with the large-scale bar, a signature of
dynamical decoupling. The morphology of the outer disk suggests that the
neutral gas is currently piling up in a pseudo-ring formed by two winding
spiral arms that are morphologically decoupled from the bar structure. In the
outer disk, the decoupling of the spiral allows the gas to efficiently produce
net gas inflow on intermediate scales. The corotation barrier seems to be
overcome due to secular evolution processes. The gas in the inner disk is
efficiently funneled by gravity torques down to r~300pc. Closer to the AGN, the
two m=2 modes (bar and oval) act in concert to produce net gas inflow down to
r~50pc, providing a clear smoking gun evidence of fueling with associated short
dynamical time-scales.


  We compute low energy asymptotics for the resolvent of a planar obstacle, and
deduce asymptotics for the corresponding scattering matrix, scattering phase,
and exterior Dirichlet-to-Neumann operator. We use an identity of Vodev to
relate the obstacle resolvent to the free resolvent and an identity of Petkov
and Zworski to relate the scattering matrix to the resolvent. The leading
singularities are given in terms of the obstacle's logarithmic capacity or
Robin constant. We expect these results to hold for more general compactly
supported perturbations of the Laplacian on $\mathbb R^2$, with the definition
of the Robin constant suitably modified, under a generic assumption that the
spectrum is regular at zero.


  The pretrain-finetune paradigm has shown outstanding performance on many
applications of deep learning, where a model is pre-trained on a upstream large
dataset (e.g. ImageNet), and is then fine-tuned to different downstream tasks.
Though for most cases, the pre-training stage is conducted based on supervised
methods, recent works on self-supervised pre-training have shown powerful
transferability and even outperform supervised pre-training on multiple
downstream tasks. It thus remains an open question how to better generalize
supervised pre-training model to downstream tasks. In this paper, we argue that
the worse transferability of existing supervised pre-training methods arise
from the negligence of valuable intra-class semantic difference. This is
because these methods tend to push images from the same class close to each
other despite of the large diversity in their visual contents, a problem to
which referred as "overfit of upstream tasks". To alleviate this problem, we
propose a new supervised pre-training method based on Leave-One-Out
K-Nearest-Neighbor, or LOOK for short. It relieves the problem of overfitting
upstream tasks by only requiring each image to share its class label with most
of its k nearest neighbors, thus allowing each class to exhibit a multi-mode
distribution and consequentially preserving part of intra-class difference for
better transferring to downstream tasks. We developed efficient implementation
of the proposed method that scales well to large datasets. Experimental studies
on multiple downstream tasks show that LOOK outperforms other state-of-the-art
methods for supervised and self-supervised pre-training.


  We demonstrate narrowband orthogonally polarized optical RF single sideband
generation as well as dual-channel equalization based on an integrated
dual-polarization-mode high-Q microring resonator. The device operates in the
optical communications band and enables narrowband RF operation at either 16.6
GHz or 32.2 GHz, determined by the free spectral range and TE/TM mode interval
in the resonator. We achieve a very large dynamic tuning range of over 55 dB
for both the optical carrier-to-sideband ratio and the dual-channel RF
equalization.


  Following merger, a neutron star (NS) binary can produce roughly one of three
different outcomes: (1) a stable NS, (2) a black hole (BH), or (3) a
supra-massive, rotationally-supported NS, which then collapses to a BH
following angular momentum losses. Which of these fates occur and in what
proportion has important implications for the electromagnetic transient
associated with the mergers and the expected gravitational wave signatures,
which in turn depend on the high density equation of state (EOS). Here we
combine relativistic calculations of NS masses using realistic EOSs with Monte
Carlo population synthesis based on the mass distribution of NS binaries in our
Galaxy to predict the distribution of fates expected. For many EOSs, a
significant fraction of the remnants are NSs or supra-massive NSs. This lends
support to scenarios where a quickly spinning, highly magnetized NS may be
powering an electromagnetic transient. This also indicates that it will be
important for future gravitational wave (GW) observatories to focus on high
frequencies to study the post merger GW emission. Even in cases where
individual GW events are too low in signal to noise to study the post merger
signature in detail, the statistics of how many mergers produce NSs versus BHs
can be compared with our work to constrain the EOS. To match short gamma-ray
burst (SGRB) X-ray afterglow statistics, we find that the stiffest EOSs are
ruled out. Furthermore, many popular EOSs require ~60-70% of SGRBs to be from
NS-BH mergers rather than just binary NSs.


  We have designed and characterized a micro-SQUID with dispersive readout for
use in low temperature scanning probe microscopy systems. The design features a
capacitively shunted RF SQUID with a tunable resonance frequency from 5 to 12
GHz, micrometer spatial resolution and integrated superconducting coils for
local application of magnetic fields. The SQUID is operated as a nonlinear
oscillator with a flux- and power-dependent resonance frequency. Measurements
for device characterization and noise benchmarking were carried out at 4 K. The
measured flux noise above 10 kHz at 4 K is $80\;\mathrm{n}\Phi_0
\mathrm{Hz}^{-1/2}$ at a bandwidth of 200 MHz. Estimations suggest that one can
benefit from parametric gain based on inherent nonlinearity of the Josephson
junction and reduce the flux noise to $30\;\mathrm{n}\Phi_0\mathrm{Hz}^{-1/2}$
at 100 mK, which corresponds to $7.5\;\mathrm{\mu_B Hz^{-1/2}}$ for a magnetic
moment located at the center of the pickup loop.


  We address the question: Given a positive integer $N$, can any 2D convex
polygonal region be partitioned into $N$ convex pieces such that all pieces
have the same area and same perimeter? The answer to this question is easily
`yes' for $N$=2. We prove the answer to be `yes' for $N$=4 and also discuss
higher powers of 2.


  Understanding human actions in wild videos is an important task with a broad
range of applications. In this paper we propose a novel approach named
Hierarchical Attention Network (HAN), which enables to incorporate static
spatial information, short-term motion information and long-term video temporal
structures for complex human action understanding. Compared to recent
convolutional neural network based approaches, HAN has following advantages (1)
HAN can efficiently capture video temporal structures in a longer range; (2)
HAN is able to reveal temporal transitions between frame chunks with different
time steps, i.e. it explicitly models the temporal transitions between frames
as well as video segments and (3) with a multiple step spatial temporal
attention mechanism, HAN automatically learns important regions in video frames
and temporal segments in the video. The proposed model is trained and evaluated
on the standard video action benchmarks, i.e., UCF-101 and HMDB-51, and it
significantly outperforms the state-of-the arts


  Homomorphic encryption (HE) is a promising privacy-preserving technique for
cross-silo federated learning (FL), where organizations perform collaborative
model training on decentralized data. Despite the strong privacy guarantee,
general HE schemes result in significant computation and communication
overhead. Prior works employ batch encryption to address this problem, but it
is still suboptimal in mitigating communication overhead and is incompatible
with sparsification techniques.
  In this paper, we propose FLASHE, an HE scheme tailored for cross-silo FL. To
capture the minimum requirements of security and functionality, FLASHE drops
the asymmetric-key design and only involves modular addition operations with
random numbers. Depending on whether to accommodate sparsification techniques,
FLASHE is optimized in computation efficiency with different approaches. We
have implemented FLASHE as a pluggable module atop FATE, an industrial platform
for cross-silo FL. Compared to plaintext training, FLASHE slightly increases
the training time by $\leq6\%$, with no communication overhead.


  We present a one-dimensional tight-binding chain of two-level systems coupled
only through common dissipative Markovian reservoirs. This quantum chain can
demonstrate anomalous thermodynamic behavior contradicting Fourier law.
Population dynamics of individual systems of the chain is polynomial with the
order determined by the initial state of the chain. The chain can simulate
classically hard problems, such as multi-dimensional random walks.


  In recent years, a market for mortality derivatives began developing as a way
to handle systematic mortality risk, which is inherent in life insurance and
annuity contracts. Systematic mortality risk is due to the uncertain
development of future mortality intensities, or {\it hazard rates}. In this
paper, we develop a theory for pricing pure endowments when hedging with a
mortality forward is allowed. The hazard rate associated with the pure
endowment and the reference hazard rate for the mortality forward are
correlated and are modeled by diffusion processes. We price the pure endowment
by assuming that the issuing company hedges its contract with the mortality
forward and requires compensation for the unhedgeable part of the mortality
risk in the form of a pre-specified instantaneous Sharpe ratio. The major
result of this paper is that the value per contract solves a linear partial
differential equation as the number of contracts approaches infinity. One can
represent the limiting price as an expectation under an equivalent martingale
measure. Another important result is that hedging with the mortality forward
may raise or lower the price of this pure endowment comparing to its price
without hedging, as determined in Bayraktar et al. [2009]. The market price of
the reference mortality risk and the correlation between the two portfolios
jointly determine the cost of hedging. We demonstrate our results using
numerical examples.


  Fractional difference operators possess nonlocal structure which largely
affects and complicates the qualitative analysis of fractional difference
equations. In this article, we discuss the effect of this memory property on
asymptotic behaviour of solutions of nabla fractional difference equations.


  We propose to use rich informations on the pp, pbar p total cross sections
sigma below N=10 GeV in order to predict the total cross section and rho ratio
at very high energies. Using the FESR as a constraint for high energy
parameters, we search for the simultaneous best fit to the data points of sigma
and rho ratio up to some energy (e.g., ISR, Tevatron) to determine the
high-energy parameters. We then predict sigma and rho in the LHC and
high-energy cosmic-ray regions. Using the data up to sqrt s =1.8 TeV(Tevatron),
we predict sigma(pp) and rho(pp) at the LHC energy(sqrt s = 14 TeV) as 106.3 +-
5.1(syst) +- 2.4(stat) mb and 0.126 +- 0.007(syst) +- 0.004(stat),
respectively. The predicted values of sigma in terms of the same parameters are
in good agreement with the cosmic-ray experimental data sample up to Plab =
10^(8--9) GeV by Block, Halzen, and Stanov.


  A repeatedly discussed gedanken experiment, proposed by Fermi to check
Einstein causality, is reconsidered. It is shown that, contrary to a recent
statement made by Hegerfeldt, there appears no causality paradoxon in a proper
theoretical description of the experiment.


  WebView is an essential component in Android and iOS. It enables applications
to display content from on-line resources. It simplifies task of performing a
network request, parsing the data and rendering it. WebView uses a number of
APIs which can interact with the web contents inside WebView. In the current
paper, Cross-site scripting attacks or XSS attacks specific to Android WebView
are discussed. Cross site scripting (XSS) is a type of vulnerability commonly
found in web applications. This vulnerability makes it possible for attackers
to run malicious code into victim's WebView,through HttpClient APIs. Using this
malicious code, the attackers can steal the victim's credentials, such as
cookies. The access control policies (that is,the same origin policy) employed
by the browser to protect those credentials can be bypassed by exploiting the
XSS vulnerability.


  Entity set expansion and synonym discovery are two critical NLP tasks.
Previous studies accomplish them separately, without exploring their
interdependencies. In this work, we hypothesize that these two tasks are
tightly coupled because two synonymous entities tend to have similar
likelihoods of belonging to various semantic classes. This motivates us to
design SynSetExpan, a novel framework that enables two tasks to mutually
enhance each other. SynSetExpan uses a synonym discovery model to include
popular entities' infrequent synonyms into the set, which boosts the set
expansion recall. Meanwhile, the set expansion model, being able to determine
whether an entity belongs to a semantic class, can generate pseudo training
data to fine-tune the synonym discovery model towards better accuracy. To
facilitate the research on studying the interplays of these two tasks, we
create the first large-scale Synonym-Enhanced Set Expansion (SE2) dataset via
crowdsourcing. Extensive experiments on the SE2 dataset and previous benchmarks
demonstrate the effectiveness of SynSetExpan for both entity set expansion and
synonym discovery tasks.


  Using a data sample of 17.7 $\rm pb^{-1}$ collected at 3.773 GeV with the
BES-II detector at the BEPC, the cross sections for $D^0 \bar D^{0}$ and
$D^+D^-$ productions at 3.773 GeV have been measured. From the data sample
about 33 $\rm pb^{-1}$ taken around 3.773 GeV, 3 purely leptonic decay events
of $D^+ \to \mu^+\nu$ are observed. The branching fraction and the decay
constant are measured to be $BF(D^+ \to
\mu^+\nu)=(0.120^{+0.092+0.010}_{-0.063-0.009}) %$ and
$f_D=(365^{+121+32}_{-113-28})$ MeV. The semileptonic decay branching fractions
for $D^0 \to K^-e^+\nu$, $D^0 \to \pi^-e^+\nu$ and $D^+ \to \bar K^0 e^+\nu$
are measured to be $BF(D^0 \to K^-e^+\nu_e)=(3.52 \pm 0.36\pm 0.25)%$, $BF(D^0
\to \pi^-e^+\nu_e)=(0.36 \pm 0.14\pm 0.03)%$ and $BF(D^+ \to \bar K^0
e^+\nu_e)=(8.64 \pm 1.51\pm 0.72)%$. The vector form factors are determined to
be $|f^K_+(0)| = 0.75 \pm 0.04 \pm 0.03$ and $|f^{\pi}_+(0)| = 0.76 \pm 0.15
\pm 0.06$. The ratio of the two form factors is extracted to be
$|f^{\pi}_+(0)/f^K_+(0)|= 1.01 \pm 0.20 \pm 0.08$. The ratio of the decay
widths is measured to be $\Gamma(D^0 \to K^-e^+\nu)/\Gamma(D^+ \to \bar K^0
e^+\nu) =1.04\pm 0.21 \pm 0.08$. From the data sample of about 27 $\rm
pb^{-1}$, the evidence of $\psi(3770) \to J/\psi \pi^+\pi^-$ non-${D \bar D}$
decay is observed. The branching fraction is determined to be $BF(\psi(3770)
\to J/\psi \pi^+\pi^-)=(0.34\pm 0.14 \pm 0.08)%$, corresponding to the partial
width of $\Gamma(\psi(3770) \to J/\psi \pi^+\pi^-) = (80 \pm 32 \pm 21)$ keV.


  Link prediction is an important and frequently studied task that contributes
to an understanding of the structure of knowledge graphs (KGs) in statistical
relational learning. Inspired by the success of graph convolutional networks
(GCN) in modeling graph data, we propose a unified GCN framework, named
TransGCN, to address this task, in which relation and entity embeddings are
learned simultaneously. To handle heterogeneous relations in KGs, we introduce
a novel way of representing heterogeneous neighborhood by introducing
transformation assumptions on the relationship between the subject, the
relation, and the object of a triple. Specifically, a relation is treated as a
transformation operator transforming a head entity to a tail entity. Both
translation assumption in TransE and rotation assumption in RotatE are explored
in our framework. Additionally, instead of only learning entity embeddings in
the convolution-based encoder while learning relation embeddings in the decoder
as done by the state-of-art models, e.g., R-GCN, the TransGCN framework trains
relation embeddings and entity embeddings simultaneously during the graph
convolution operation, thus having fewer parameters compared with R-GCN.
Experiments show that our models outperform the-state-of-arts methods on both
FB15K-237 and WN18RR.


  Inertia-gravity mode and Rossby mode dispersion properties are examined for
discretisations of the linearized rotating shallow-water equations using the
$P1_{DG}$-$P2$ finite element pair on arbitrary triangulations in planar
geometry. A discrete Helmholtz decomposition of the functions in the velocity
space based on potentials taken from the pressure space is used to provide a
complete description of the numerical wave propagation for the discretised
equations. In the $f$-plane case, this decomposition is used to obtain
decoupled equations for the geostrophic modes, the inertia-gravity modes, and
the inertial oscillations. As has been noticed previously, the geostrophic
modes are steady. The Helmholtz decomposition is used to show that the
resulting inertia-gravity wave equation is third-order accurate in space. In
general the \pdgp finite element pair is second-order accurate, so this leads
to very accurate wave propagation. It is further shown that the only spurious
modes supported by this discretisation are spurious inertial oscillations which
have frequency $f$, and which do not propagate. The Helmholtz decomposition
also allows a simple derivation of the quasi-geostrophic limit of the
discretised $P1_{DG}$-$P2$ equations in the $\beta$-plane case, resulting in a
Rossby wave equation which is also third-order accurate.


  In recent years, deep learning-based networks have achieved state-of-the-art
performance in medical image segmentation. Among the existing networks, U-Net
has been successfully applied on medical image segmentation. In this paper, we
propose an extension of U-Net, Bi-directional ConvLSTM U-Net with Densely
connected convolutions (BCDU-Net), for medical image segmentation, in which we
take full advantages of U-Net, bi-directional ConvLSTM (BConvLSTM) and the
mechanism of dense convolutions. Instead of a simple concatenation in the skip
connection of U-Net, we employ BConvLSTM to combine the feature maps extracted
from the corresponding encoding path and the previous decoding up-convolutional
layer in a non-linear way. To strengthen feature propagation and encourage
feature reuse, we use densely connected convolutions in the last convolutional
layer of the encoding path. Finally, we can accelerate the convergence speed of
the proposed network by employing batch normalization (BN). The proposed model
is evaluated on three datasets of: retinal blood vessel segmentation, skin
lesion segmentation, and lung nodule segmentation, achieving state-of-the-art
performance.


  We present a new method for the decomposition of multi-loop Euclidean Feynman
integrals into quasi-finite Feynman integrals. These are defined in shifted
dimensions with higher powers of the propagators, make explicit both infrared
and ultraviolet divergences, and allow for an immediate and trivial expansion
in the parameter of dimensional regularization. Our approach avoids the
introduction of spurious structures and thereby leaves integrals particularly
accessible to direct analytical integration techniques. Alternatively, the
resulting convergent Feynman parameter integrals may be evaluated numerically.
Our approach is guided by previous work by the second author but overcomes
practical limitations of the original procedure by employing integration by
parts reduction.


  We present a catalog of compact sources derived from the QUaD Galactic Plane
Survey. The survey covers ~800 square degrees of the inner galaxy (|b|<4
degrees) in Stokes I, Q and U parameters at 100 and 150 GHz, with angular
resolution 5 and 3.5 arcminutes. 505 unique sources are identified in I, of
which 239 are spatially matched between frequency bands, with 50 (216) detected
at 100 (150) GHz alone; 182 sources are identified as ultracompact HII (UCHII)
regions. Approximating the distribution of total intensity source fluxes as a
power-law, we find a slope of $\gamma_{S,100}=-1.8\pm0.4$ at 100 GHz, and
$\gamma_{S,150}=-2.2\pm0.4$ at 150 GHz. Similarly, the power-law index of the
source two-point angular correlation function is
$\gamma_{\theta,100}=-1.21\pm0.04$ and $\gamma_{\theta,150}=-1.25\pm0.04$. The
total intensity spectral index distribution peaks at $\alpha_{I}\sim0.25$,
indicating that dust emission is not the only source of radiation produced by
these objects between 100 and 150 GHz; free-free radiation is likely
significant in the 100 GHz band. Four sources are detected in polarized
intensity P, of which three have matching counterparts in I. Three of the
polarized sources lie close to the galactic center, Sagittarius A*, Sagittarius
B2 and the Galactic Radio Arc, while the fourth is RCW 49, a bright HII region.
An extended polarized source, undetected by the source extraction algorithm on
account of its $\sim0.5^{\circ}$ size, is identified visually, and is an
isolated example of large-scale polarized emission oriented distinctly from the
bulk galactic dust polarization.


  We present an optimized version of a cluster labeling algorithm previously
introduced by the authors. This algorithm is well suited for large-scale Monte
Carlo simulations of spin models using cluster dynamics on parallel computers
with large numbers of processors. The algorithm divides physical space into
rectangular cells which are assigned to processors and combines a serial local
labeling procedure with a relaxation process across nearest-neighbor
processors. By controlling overhead and reducing inter-processor communication
this method attains good computational speed-up and efficiency. Large systems
of up to 65536 X 65536 spins have been simulated at updating speeds of 11
nanosecs/site (90.7 million spin updates/sec) using state-of-the-art
supercomputers. In the second part of the article we use the cluster algorithm
to study the relaxation of magnetization and energy on large Ising models using
Swendsen-Wang dynamics. We found evidence that exponential and power law
factors are present in the relaxation process as has been proposed by Hackl et
al.


  Extensions of standard one-dimensional supersymmetric quantum mechanics are
discussed. Supercharges involving higher order derivatives are introduced
leading to an algebra which incorporates a higher order polynomial in the
Hamiltonian. We study scattering amplitudes for that problem. We also study the
role of a dilatation of the spatial coordinate leading to a q-deformed
supersymmetric algebra. An explicit model for the scattering amplitude is
constructed in terms of a hypergeometric function which corresponds to a
reflectionless potential with infinitely many bound states.


  We report a kind of quantum phase transition which takes place in isolated
quantum systems with non-thermal equilibrium states and an extra symmetry that
commutes with the Hamiltonian for any values of the system parameters. A
critical energy separates two different phases, one in which the symmetry is
broken. This critical behavior is ruled out as soon as the system is put in
contact with a thermal bath. The critical point is crossed when a sufficent
amount of work is performed on the system, keeping it isolated from the
environment. Different phases are identified by means of an order parameter,
which is only different from zero in the symmetry-breaking phase. The behavior
of the system near the critical point is determined by a set of critical
exponents. We illustrate this phenomenon by means of numerical calculations in
three different two-level systems.


  We consider families of strongly consistent multivariate conditional risk
measures. We show that under strong consistency these families admit a
decomposition into a conditional aggregation function and a univariate
conditional risk measure as introduced Hoffmann et al. (2016). Further, in
analogy to the univariate case in F\"ollmer (2014), we prove that under
law-invariance strong consistency implies that multivariate conditional risk
measures are necessarily multivariate conditional certainty equivalents.


  We extend previous studies of mixed-composition extragalactic cosmic-ray
source models, by investigating the influence of a non-negligible extragalactic
magnetic field on the propagated cosmic-ray spectrum and composition. We study
the transport of charged particles in turbulent fields and the transition from
a ballistic to a diffusive propagation regime. We introduce a method allowing a
fast integration of the particle trajectories, which allows us to calculate
extragalactic cosmic-ray spectra in the general case, without using either the
diffusive or the rectilinear approximation. We find that the main features of
the mixed-composition models -- regarding the interpretation of the ankle and
the non-monotonous evolution of the average cosmic-ray mass -- remain
essentially unchanged as long as the magnetic field intensity does not exceed a
few nG.


  Instruction combiner (IC) is a critical compiler optimization pass, which
replaces a sequence of instructions with an equivalent and optimized
instruction sequence at basic block level. There can be thousands of
instruction-combining patterns which need to be frequently updated as new
coding idioms/applications and novel hardware evolve over time. This results in
frequent updates to the IC optimization pass thereby incurring considerable
human effort and high software maintenance costs. To mitigate these challenges
associated with the traditional IC, we design and implement a Neural
Instruction Combiner (NIC) and demonstrate its feasibility by integrating it
into the standard LLVM compiler optimization pipeline. NIC leverages neural
sequence-to-sequence (Seq2Seq) models for generating optimized encoded IR
sequence from the unoptimized encoded IR sequence. To the best of our
knowledge, ours is the first work demonstrating the feasibility of a neural
instruction combiner built into a full-fledged compiler pipeline. Given the
novelty of this task, we built a new dataset for training our NIC neural model.
We show that NIC achieves exact match results percentage of 72% for optimized
sequences as compared to traditional IC and neural machine translation metric
Bleu precision score of 0.94, demonstrating its feasibility in a production
compiler pipeline.


  Heralded single photon source (HSPS) is an important way in generating
genuine single photon, having advantages of experimental simplicity and
versatility. However, HSPS intrinsically suffers from the trade-off between the
heralded single photon rate and the single photon purity. To overcome this, one
can apply multiplexing technology in different degrees of freedom to enhance
the performance of HSPS. Here, by employing spectral multiplexing and active
feed-forward spectral manipulating, we demonstrate a HSPS at 1.5 {\mu}m
telecom-band. Our experimental results show that the spectral multiplexing
effectively erases the frequency correlation of pair source and significantly
improves the heralded single photon rate while keeping the g{^(^2^)}(0) as low
as 0.0006{\pm}0.0001. The Hong-Ou-Mandel interference between the heralded
single photons and photons from an independent weak coherent source indicates a
high indistinguishability. Our results pave a way for scalable HSPS by spectral
multiplexing towards deterministic single photon emission.


  Room temperature ferromagnetism is observed in undoped TiO2 films deposited
on Si substrates using pulsed laser deposition (PLD). The ferromagnetic
properties of the samples depend on the oxygen partial pressure during the PLD
synthesis. The appearance of higher binding energy component (HBEC) in the
oxygen 1s core peak from x-ray photoelectron spectroscopy (XPS) suggests the
presence of oxygen vacancies in these samples. The amount of oxygen during the
synthesis determines the vacancy concentration in the samples which is directly
related to the magnetic behavior of the samples. The magnetic moment decreases
with oxygen vacancy concentration in the samples. Valence band measurements
were performed to study the electronic structure of both stoichometric and
reduced TiO2. The analyses show the presence of Ti 3d band near the Fermi level
in reduced TiO2 samples. These bands are otherwise empty in stoichiometric TiO2
and reside in the conduction band which makes them unobservable by XPS. The
existence of this Ti 3d band near the Fermi level can possibly lead to Stoner
splitting of the band.


  Character-level models of tokens have been shown to be effective at dealing
with within-token noise and out-of-vocabulary words. But these models still
rely on correct token boundaries. In this paper, we propose a novel end-to-end
character-level model and demonstrate its effectiveness in multilingual
settings and when token boundaries are noisy. Our model is a semi-Markov
conditional random field with neural networks for character and segment
representation. It requires no tokenizer. The model matches state-of-the-art
baselines for various languages and significantly outperforms them on a noisy
English version of a part-of-speech tagging benchmark dataset. Our code and the
noisy dataset are publicly available at http://cistern.cis.lmu.de/semiCRF.


  In this paper we study the properties of Drinfeld's twisting for
finite-dimensional Hopf algebras. We determine how the integral of the dual to
a unimodular Hopf algebra $H$ changes under twisting of $H$. We show that the
classes of cosemisimple unimodular, cosemisimple involutive, cosemisimple
quasitriangular finite-dimensional Hopf algebras are stable under twisting. We
also prove the cosemisimplicity of a coalgebra obtained by twisting of a
cosemisimple unimodular Hopf algebra by two different twists on two sides (such
twists are closely related to biGalois extensions), and describe the
representation theory of its dual. Next, we define the notion of a
non-degenerate twist for a Hopf algebra $H$, and set up a bijection between
such twists for $H$ and $H^*$. This bijection is based on Miyashita-Ulbrich
actions of Hopf algebras on simple algebras. It generalizes to the
non-commutative case the procedure of inverting a non-degenerate skew-symmetric
bilinear form on a vector space. Finally, we apply these results to
classification of twists in group algebras and of cosemisimple triangular
finite-dimensional Hopf algebras in positive characteristic, generalizing the
previously known classification in characteristic zero.


  In this paper, we study the dividend strategies for a shareholder with
non-constant discount rate in a diffusion risk model. We assume that the
dividends can only be paid at a bounded rate and restrict ourselves to the
Markov strategies. This is a time inconsistent control problem. The extended
HJB equation is given and the verification theorem is proved for a general
discount function. Considering the pseudo-exponential discount functions (Type
I and Type II), we get the equilibrium dividend strategies and the equilibrium
value functions by solving the extended HJB equations.


  The ability of fast similarity search at large scale is of great importance
to many Information Retrieval (IR) applications. A promising way to accelerate
similarity search is semantic hashing which designs compact binary codes for a
large number of documents so that semantically similar documents are mapped to
similar codes (within a short Hamming distance). Although some recently
proposed techniques are able to generate high-quality codes for documents known
in advance, obtaining the codes for previously unseen documents remains to be a
very challenging problem. In this paper, we emphasise this issue and propose a
novel Self-Taught Hashing (STH) approach to semantic hashing: we first find the
optimal $l$-bit binary codes for all documents in the given corpus via
unsupervised learning, and then train $l$ classifiers via supervised learning
to predict the $l$-bit code for any query document unseen before. Our
experiments on three real-world text datasets show that the proposed approach
using binarised Laplacian Eigenmap (LapEig) and linear Support Vector Machine
(SVM) outperforms state-of-the-art techniques significantly.


  Large Language Models (LLMs) still struggle with natural language reasoning
tasks. Motivated by the society of minds (Minsky, 1988), we propose ReConcile,
a multi-model multi-agent framework designed as a round table conference among
diverse LLM agents. ReConcile enhances collaborative reasoning between LLM
agents via multiple rounds of discussion, learning to convince other agents to
improve their answers, and employing a confidence-weighted voting mechanism
that leads to a better consensus. In each round, ReConcile initiates discussion
between agents via a 'discussion prompt' that consists of (a) grouped answers
and explanations generated by each agent in the previous round, (b) their
confidence scores, and (c) demonstrations of answer-rectifying human
explanations, used for convincing other agents. Experiments on seven benchmarks
demonstrate that ReConcile significantly improves LLMs' reasoning -- both
individually and as a team -- surpassing prior single-agent and multi-agent
baselines by up to 11.4% and even outperforming GPT-4 on three datasets.
ReConcile also flexibly incorporates different combinations of agents,
including API-based, open-source, and domain-specific models, leading to an 8%
improvement on MATH. Finally, we analyze the individual components of
ReConcile, demonstrating that the diversity originating from different models
is critical to its superior performance. Code:
https://github.com/dinobby/ReConcile


  Joint inversion of geophysical datasets is instrumental in subsurface
characterization and has garnered significant popularity, leveraging
information from multiple geophysical methods. In this study, we implemented
the joint inversion of DC resistivity with MT data using the Multi-Objective
Grey Wolf Optimization (MOGWO) algorithm. As an extension of the widely-used
Grey Wolf Optimization algorithm, MOGWO offers a suite of pareto optimal
non-dominated solutions, eliminating the need for weighting parameters in the
objective functions. This set of non-dominated predictions also facilitates the
understanding of uncertainty in the predicted model parameters. Through a field
case study in the region around Broken Hill in South Central Australia, the
paper showcases MOGWO's capabilities in joint inversion, providing confident
estimates of the model parameters (resistivity profiles), as indicated by a
narrow spread in the suite of solutions. The obtained results are comparable to
well established methodologies and highlight the efficacy of MOGWO as a
reliable tool in geophysical exploration.


  We study the problem of interference management in large-scale small cell
networks, where each user equipment (UE) needs to determine in a distributed
manner when and at what power level it should transmit to its serving small
cell base station (SBS) such that a given network performance criterion is
maximized subject to minimum quality of service (QoS) requirements by the UEs.
We first propose a distributed algorithm for the UE-SBS pairs to find a subset
of weakly interfering UE-SBS pairs, namely the maximal independent sets (MISs)
of the interference graph in logarithmic time (with respect to the number of
UEs). Then we propose a novel problem formulation which enables UE-SBS pairs to
determine the optimal fractions of time occupied by each MIS in a distributed
manner. We analytically bound the performance of our distributed policy in
terms of the competitive ratio with respect to the optimal network performance,
which is obtained in a centralized manner with NP (non-deterministic polynomial
time) complexity. Remarkably, the competitive ratio is independent of the
network size, which guarantees scalability in terms of performance for
arbitrarily large networks. Through simulations, we show that our proposed
policies achieve significant performance improvements (from 150% to 700%) over
the existing policies.


  We study the complexity of equilibrium computation in discrete preference
games. These games were introduced by Chierichetti, Kleinberg, and Oren (EC
'13, JCSS '18) to model decision-making by agents in a social network that
choose a strategy from a finite, discrete set, balancing between their
intrinsic preferences for the strategies and their desire to choose a strategy
that is `similar' to their neighbours. There are thus two components: a social
network with the agents as vertices, and a metric space of strategies. These
games are potential games, and hence pure Nash equilibria exist. Since their
introduction, a number of papers have studied various aspects of this model,
including the social cost at equilibria, and arrival at a consensus.
  We show that in general, equilibrium computation in discrete preference games
is PLS-complete, even in the simple case where each agent has a constant number
of neighbours. If the edges in the social network are weighted, then the
problem is PLS-complete even if each agent has a constant number of neighbours,
the metric space has constant size, and every pair of strategies is at distance
1 or 2. Further, if the social network is directed, modelling asymmetric
influence, an equilibrium may not even exist. On the positive side, we show
that if the metric space is a tree metric, or is the product of path metrics,
then the equilibrium can be computed in polynomial time.


  Long-duration GRB~200829A was detected by Fermi-GBM and Swift-BAT/XRT, and
then rapidly observed by other ground-based telescopes. It has a weak
$\gamma$-ray emission in the very early phase and followed by a bright spiky
$\gamma$-ray emission pulse. The radiation spectrum of the very early emission
is best fitted by a power-law function with index $\sim -1.7$. However, the
bright spiky $\gamma$-ray pulse, especially the time around the peak, exhibits
a distinct two-component radiation spectra, i.e., Band function combined with a
blackbody radiation spectrum. We infer the photospheric properties and reveal a
medium magnetization at photospheric position by adopting the initial size of
the outflow as $r_0=10^9$~cm. It implies that Band component in this pulse may
be formed during the dissipation of magnetic field. The power-law radiation
spectra found in the very early prompt emission may imply the external-shock
origination of this phase. Then, we perform Markov Chain Monte Carlo method
fitting on the light-curves of this burst, where the jet corresponding to the
$\gamma$-ray pulses at around $20$~s is used to refresh the external-shock. It
is shown that the light-curves of very early phase and X-ray afterglow after
$40$~s, involving the X-ray bump at around $100$~s, can be well modelled in the
external-shock scenario. For the obtained initial outflow, we estimate the
minimum magnetization factor of the jet based on the fact that the photospheric
emission of this jet is missed in the very early phase.


  We study the automatic generation of navigation instructions from 360-degree
images captured on indoor routes. Existing generators suffer from poor visual
grounding, causing them to rely on language priors and hallucinate objects. Our
MARKY-MT5 system addresses this by focusing on visual landmarks; it comprises a
first stage landmark detector and a second stage generator -- a multimodal,
multilingual, multitask encoder-decoder. To train it, we bootstrap grounded
landmark annotations on top of the Room-across-Room (RxR) dataset. Using text
parsers, weak supervision from RxR's pose traces, and a multilingual image-text
encoder trained on 1.8b images, we identify 971k English, Hindi and Telugu
landmark descriptions and ground them to specific regions in panoramas. On
Room-to-Room, human wayfinders obtain success rates (SR) of 71% following
MARKY-MT5's instructions, just shy of their 75% SR following human instructions
-- and well above SRs with other generators. Evaluations on RxR's longer,
diverse paths obtain 61-64% SRs on three languages. Generating such
high-quality navigation instructions in novel environments is a step towards
conversational navigation tools and could facilitate larger-scale training of
instruction-following agents.


  DG Tau B is a Class I young stellar source that drives the asymmetric HH 159
bipolar jet. At optical wavelengths it is obscured by circumstellar
optically-thick material. Using VLA and JVLA observations, we determine for the
first time the proper motions of this source and find them to be consistent,
within error, with those of the nearby young star DG Tau. We also discuss an
ejection event that is evident in the 1994 VLA data. As the optical and
molecular outflows, this ejection traced in the radio continuum is markedly
asymmetric and was detected only to the NW of the star. We propose that this
knot, no longer detectable in the radio, could be observed in future optical
images of DG Tau B. The positions of the VLA source and of a nearby infrared
object are not coincident and we suggest that the VLA source traces the
exciting object, while the infrared source could be a reflection lobe.


  We study the complexity of the computational task ``Given a colouring $c :
\mathbb{Q} \to \mathbf{k}$, find a monochromatic $S \subseteq \mathbb{Q}$ such
that $(S,<) \cong (\mathbb{Q},<)$''. The framework is Weihrauch reducibility.
Our results answer some open questions recently raised by Gill, and by
Dzhafarov, Solomon and Valenti.


  We study laterally trapped dipolar exciton ensembles in coupled GaAs quantum
wells at high magnetic fields in the Faraday configuration. In
photoluminescence experiments, we identify three magnetic field regimes. At low
fields, the exciton density is increased by a reduced charge carrier escape
from the trap, and additionally, the excitons' emission energy is corrected by
a positive diamagnetic shift. At intermediate fields, magnetic field dependent
correction terms apply which follow the characteristics of a neutral
magnetoexciton. Due to a combined effect of an increasing binding energy and
lifetime, the exciton density is roughly doubled from zero to about seven
Tesla. At the latter high field value, the charge carriers occupy only the
lowest Landau level. In this situation, the exciton trap can overflow
independently from the electrostatic depth of the trapping potential, and the
energy shift of the excitons caused by the so-called quantum confined Stark
effect is effectively compensated. Instead, the exciton energetics seem to be
driven by the magnetic field dependent renormalization of the many-body
interaction terms. In this regime, the impact of parasitic in-plane fields at
the edge of trapping potential is eliminated.


  The $2$-layer drawing model is a well-established paradigm to visualize
bipartite graphs. Several beyond-planar graph classes have been studied under
this model. Surprisingly, however, the fundamental class of $k$-planar graphs
has been considered only for $k=1$ in this context. We provide several
contributions that address this gap in the literature. First, we show tight
density bounds for the classes of $2$-layer $k$-planar graphs with
$k\in\{2,3,4,5\}$. Based on these results, we provide a Crossing Lemma for
$2$-layer $k$-planar graphs, which then implies a general density bound for
$2$-layer $k$-planar graphs. We prove this bound to be almost optimal with a
corresponding lower bound construction. Finally, we study relationships between
$k$-planarity and $h$-quasiplanarity in the $2$-layer model and show that
$2$-layer $k$-planar graphs have pathwidth at most $k+1$.


  We define a class of representations of the fundamental group of a closed
surface of genus $2$ to $\mathrm{PSL}_2 (\mathbb C)$: the pentagon
representations. We show that they are exactly the non-elementary
$\mathrm{PSL}_2 (\mathbb C)$-representations of surface groups that do not
admit a Schottky decomposition, i.e. a pants decomposition such that the
restriction of the representation to each pair of pants is an isomorphism onto
a Schottky group. In doing so, we exhibit a gap in the proof of Gallo, Kapovich
and Marden that every non-elementary representation of a surface group to
$\mathrm{PSL}_2 (\mathbb C)$ is the holonomy of a projective structure,
possibly with one branched point of order $2$. We show that pentagon
representations arise as such holonomies and repair their proof.


  During binary black hole (BBH) mergers, energy and momenta are carried away
from the binary system as gravitational radiation. Access to the radiated
energy and momenta allows us to predict the properties of the remnant black
hole. We develop a Python package gw_remnant to compute the remnant mass,
remnant spin, peak luminosity, and the final kick imparted on the remnant black
hole from the gravitational radiation. Using this package, we compute the
remnant properties of the final black hole in case of non-spinning BBH mergers
with mass ratios ranging from q=2.5 to q=1000 using waveform modes generated
from BHPTNRSur1dq1e4, a recently developed numerical-relativity-informed
surrogate model based on black-hole perturbation theory framework. We validate
our results against the remnant properties estimated from numerical relativity
(NR) surrogate models in the comparable mass ratio regime and against recently
available high-mass-ratio NR simulations at q=[15,32,64]. We find that our
remnant property estimates computed from fluxes at future null infinity closely
match the estimates obtained from the NR surrogate model of apparent horizon
data. Using Gaussian process regression fitting methods, we train a surrogate
model, {BHPTNR_Remnant, for the properties of the remnant black hole arising
from BBH mergers with mass ratios from q=2.5 to q=1000. Finally, we discuss
potential improvements in the BHPTNRSur1dq1e4 waveform model when including
remnant information. We make both the gw_remnant and BHPTNR_Remnant packages
publicly available.


  Mechanisms involved in the star formation process and in particular the
duration of the different phases of the cloud contraction are not yet fully
understood. Photometric data alone suggest that objects coexist in the young
cluster NGC6530 with ages from ~1 Myr up to 10 Myrs. We want to derive accurate
stellar parameters and, in particular, stellar ages to be able to constrain a
possible age spread in the star-forming region NGC6530. We used low-resolution
spectra taken with VIMOS@VLT and literature spectra of standard stars to derive
spectral types of a subsample of 94 candidate members of this cluster. We
assign spectral types to 86 of the 88 confirmed cluster members and derive
individual reddenings. Our data are better fitted by the anomalous reddening
law with R$_{\rm V}$=5. We confirm the presence of strong differential
reddening in this region. We derive fundamental stellar parameters, such as
effective temperatures, photospheric colors, luminosities, masses, and ages for
78 members, while for the remaining 8 YSOs we cannot determine the interstellar
absorption, since they are likely accretors, and their V-I colors are bluer
than their intrinsic colors. The cluster members studied in this work have
masses between 0.4 and 4 M$_\odot$ and ages between 1-2 Myrs and 6-7 Myrs. We
find that the SE region is the most recent site of star formation, while the
older YSOs are loosely clustered in the N and W regions. The presence of two
distint generations of YSOs with different spatial distribution allows us to
conclude that in this region there is an age spread of ~6-7 Myrs. This is
consistent with the scenario of sequential star formation suggested in
literature.


  Some years ago Szab\'o and Fine proposed a {\it local} hidden variable theory
for the GHZ experiment based on the assumption that "the detection efficiency
is not (only) the effect of random errors in the detector equipment, but it is
a more fundamental phenomenon, the manifestation of a predetermined hidden
property of the particles". Szab\'o and Fine, however, did not provide a
general approach to quantum phenomena which avoids nonlocality. Such an
approach, based on the same assumption, was instead recently supplied by some
of us and called {\it extended semantic realism} ({\it ESR}) model. We show
here that one can extract from the ESR model several local finite models
referring to the specific physical situation considered in the GHZ experiment,
and that these models can be converted into the toy models for the GHZ
experiment worked out by Szab\'o and Fine.


  In this paper, we present a framework for automatic generation of CHR solvers
given the logical specification of the constraints. This approach takes
advantage of the power of tabled resolution for constraint logic programming,
in order to check the validity of the rules. Compared to previous works where
different methods for automatic generation of constraint solvers have been
proposed, our approach enables the generation of more expressive rules (even
recursive and splitting rules) that can be used directly as CHR solvers.


  We examine various ways in which disk accretion can heat an accreting star.
These include 1) radiation emitted from the disk surface which is intercepted
by the stellar surface, 2) radiative flux directly across the disk-star
interface, and 3) advection of thermal energy from the disk into the star. For
each of these, the physics of the boundary layer between the disk and the star
is crucial to determining the amount of stellar heating that occurs.
  We assess the importance of the methods listed above for heating the star in
accreting pre-main-sequence stars and cataclysmic variables, using recent
models of boundary layers in these systems. We find that intercepted radiation
tends to be the most important source of stellar heating in thin disk systems
such as T Tauri stars and high-$\dot M$ cataclysmic variables. We argue that
direct radiation across the disk-star interface will be unimportant in
steady-state systems. However, it may be important in outbursting systems,
where the disk temperature rises and falls rapidly. Advection of thermal energy
into the star becomes the dominant source of stellar heating in thick disk
systems such as FU Orionis objects.


  This exploratory study examines the strategies of social bots on Twitter that
were retweeted following a mass shooting event. Using a case study method to
frame our work, we collected over seven million tweets during a one-month
period following a mass shooting in Parkland, Florida. From this dataset, we
selected retweets of content generated by over 400 social bot accounts to
determine what strategies these bots were using and the effectiveness of these
strategies as indicated by the number of retweets. We employed qualitative and
quantitative methods to capture both macro- and micro-level perspectives. Our
findings suggest that bots engage in more diverse strategies than solely waging
disinformation campaigns, including baiting and sharing information. Further,
we found that while bots amplify conversation about mass shootings, humans were
primarily responsible for disseminating bot-generated content. These findings
add depth to the current understanding of bot strategies and their
effectiveness. Understanding these strategies can inform efforts to combat
dubious information as well as more insidious disinformation campaigns.


  Based on the conventional sequential-accretion paradigm, we have proposed
that, during the migration of first-born gas giants outside the orbits of
planetary embryos, super Earth planets will form inside the 2:1 resonance
location by sweeping of mean motion resonances (Zhou et al. 2005). In this
paper, we study the subsequent evolution of a super Earth (m_1) under the
effects of tidal dissipation and perturbation from a first-born gas giant (m_2)
in an outside orbit. Secular perturbation and mean motion resonances
(especially 2:1 and 5:2 resonances) between m_1 and m_2 excite the eccentricity
of m_1, which causes the migration of m_1 and results in a hot super Earth. The
calculated final location of the hot super Earth is independent of the tidal
energy dissipation factor Q'. The study of migration history of a Hot Super
Earth is useful to reveal its Q' value and to predict its final location in the
presence of one or more hot gas giants. When this investigation is applied to
the GJ876 system, it correctly reproduces the observed location of GJ876d
around 0.02AU.


  We consider here chiral symmetry breaking through nontrivial vacuum structure
with quark antiquark condensates. We then relate the condensate function to the
wave function of pion as a Goldstone mode. This simultaneously yields the pion
also as a quark antiquark bound state as a localised zero mode in vacuum. We
illustrate the above with Nambu Jona-Lasinio model to calculate different
pionic properties in terms of the vacuum structure for breaking of exact or
approximate chiral symmetry, as well as the condensate fluctuations giving rise
to $\sigma$ mesons.


  We propose a method to construct on-shell component actions for theories with
1/2 partial breaking of global supersymmetry within the nonlinear realization
(coset) approach. In contrast with the standard superfield approach in which
unbroken supersymmetry plays the leading role, we have shifted the attention to
the spontaneously broken supersymmetry. It turns out that in theories in which
half of supersymmetries is spontaneously broken, all physical fermions are just
the fermions of the nonlinear realization. Moreover, transformation properties
of these fermions with respect to broken supersymmetry are the same as in the
Volkov-Akulov model. Just this completely fixed all possible appearances of
fermions in the component action: they can enter the action through the
determinant of the vielbein and covariant derivatives, only. In our
parametrization of the coset the rest of physical components, i.e. all bosonic
components, transform as "matter fields" with respect to broken supersymmetry.
Clearly, the component action acquires the form of the Volkov-Akulov action for
these "matter fields". The complete form of the action can be further fixed by
two additional requirements: a) to reproduce the bosonic limit, which is
explicitly known in many interesting cases, and b) to have a proper linearized
form, which has to be invariant with respect to linearized unbroken
supersymmetry. In some cases additional Wess-Zumino terms (which disappear in
the bosonic limit) have to be added to the action. We supply the general
consideration by detailed examples of actions for the superparticle in D=3,5,
the on-shell component action for N=1, D=5 supermembrane and its dual cousins
and the component action of N=1 supermembrane in D=4, providing the exact proof
of the invariance of the constructed component actions with respect to both
broken and unbroken supersymmetries.


  Absorption, excitation and emission spectra of cadmium fluoride crystals
doped with rare-earth ions were investigated. In contrast to alkaline-earth
fluorides the absorption spectra due to 4f - 5d transitions of Ce$^{3+}$,
Pr$^{3+}$ and Tb$^{3+}$ ions are broadened. No 5d-4f emissions were observed.
These prove that 5d(e$_g$) levels of rare earth ions lie in conduction band of
CdF$_2$ crystal. Emission spectra of Tb$^{3+}$ show the group of 4f-4f
$^5$D$_4$-$^7$F$_j$ lines in contrast to other alkaline-earth fluorides where
emission due to $^5$D$_3$-$^7$F$_j$ transitions is also observed. The absence
of the emission is due to position of $^5$D$_3$ level within condution band.
  Among the all measured crystals doped with impurity ions (Pr, Nd, Eu, Ho, Tb,
Tm, Yb, Ga, In or Mn), the CdF$_2$ doped with Pr$^{3+}$, Tb$^{3+}$, or
Mn$^{2+}$ ions have the highest light outputs under x-ray excitation.


  Supply Shortage Outages are a major concern during peak demand for developing
countries. In the Philippines, commercial loads have unused backup generation
of up to 3000 MW, at the same time there are shortages of as much as 700 MW
during peak demand. This gives utilities the incentive to implement Demand
Response programs to minimize this shortage. But when considering Demand
Response from a modeling perspective, social welfare through profit is always
the major objective for program implementation. That isn't always the case
during an emergency situation as there can be a trade-off between grid
resilience and cost of electricity.
  The question is how the Distribution Utility (DU) shall optimally allocate
the unused generation to meet the shortage when this trade-off exists. We
formulate a combined multi-objective optimal dispatch model where we can make a
direct comparison between the least-cost and resilience objectives.
  We find that this trade-off is due to the monotonically increasing nature of
energy cost functions. If the supply is larger than the demand, the DU can
perform a least-cost approach in the optimal dispatch since maximizing the
energy generated in this case can lead to multiple solutions. We also find in
our simulation that in cases where the supply of energy from the customers is
less than shortage quantity, the DU must prioritize maximizing the generated
energy rather than minimizing cost.


  We show the convergence of the solutions to the massive nonlinear
Klein-Gordon equation toward solutions to a relativistic Euler with potential
type system in the semi-classical limit. In particular, the momentum and the
density of Klein-Gordon converge to the the momentum and the density of the
relativistic Euler system in Lebesgue norms. The relativistic Euler with
potential is equivalent to the usual relativistic Euler with pressure up to a
rescaling. The proof relies on the modulated energy method adapted to the wave
equation and the relativistic setting.


  Some micro-algae are sensitive to light intensity gradients. This property is
known as phototaxis: the algae swim toward a light source (positive
phototaxis). We use this property to control the motion of micro-algae within a
Poiseuille flow using light. The combination of flow vorticity and phototaxis
results in a concentration of algae around the center of the flow. Intermittent
light exposure allows analysis of the dynamics of this phenomenon and its
reversibility. With this phenomenon, we hope to pave the way toward new algae
concentration techniques (a bottleneck challenge in hydrogen algal production)
and toward the improvement of pollutant bio-detector technology.


  We investigate the problem of finding the local analogue of the ergotropy,
that is the maximum work that can be extracted from a system if we can only
apply local unitary transformation acting on a given subsystem.
  In particular, we provide a closed formula for the local ergotropy in the
special case in which the local system has only two levels, and give analytic
lower bounds and semidefinite programming upper bounds for the general case. As
non-trivial examples of application, we compute the local ergotropy for a atom
in an electromagnetic cavity with Jaynes-Cummings coupling, and the local
ergotropy for a spin site in an XXZ Heisenberg chain, showing that the amount
of work that can be extracted with an unitary operation on the coupled system
can be greater than the work obtainable by quenching off the coupling with the
environment before the unitary transformation.


  Angular resolved digital holography is presented as a technique for real-time
characterization of the full optical field (amplitude and phase) of
space-division multiplexing components and fibers, here a 6-mode
photonic-lantern is characterized.


  We prove that the sequence of averaged quantities
$\int_{\R^m}u_n(\mx,\msnop)$ $\rho(\msnop)d\msnop$, is strongly precompact in
$\Ldl\Rd$, where $\rho\in \Ldc{\R^m}$, and $u_n\in
  \Ld{\R^m; \pL s\Rd}$, $s\geq 2$, are weak solutions to differential operator
equations with variable coefficients. In particular, this includes differential
operators of hyperbolic, parabolic or ultraparabolic type, but also fractional
differential operators. If $s>2$ then the coefficients can be discontinuous
with respect to the space variable $\mx\in \R^d$, otherwise, the coefficients
are continuous functions. In order to obtain the result we prove a
representation theorem for an extension of the $H$-measures.


  In this paper we prove a sharp version of the Moser-Trudinger inequality for
the Euler-Lagrange functional of a singular Toda system, motivated by the study
of models in Chern-Simons theory. Our result extends those for the scalar case,
as well as for the regular Toda system. We expect this inequality to be a basic
tool to attack variationally the existence problem under general assumptions.


  We obtain the following characterization of Hilbert spaces. Let $E$ be a
Banach space whose unit sphere $S$ has a hyperplane of symmetry. Then $E$ is a
Hilbert space iff any of the following two conditions is fulfilled: a) the
isometry group ${\rm Iso}\, E$ of $E$ has a dense orbit in S; b) the identity
component $G_0$ of the group ${\rm Iso}\, E$ endowed with the strong operator
topology acts topologically irreducible on $E$. Some related results on
infinite dimentional Coxeter groups generated by isometric reflexions are given
which allow to analyse the structure of isometry groups containing sufficiently
many reflexions.


  The recent observation of superconductivity in infinite-layer nickelate
Nd$_{0.8}$Sr$_{0.2}$NiO$_{2}$ has received considerable attention. Despite the
many efforts to understand the superconductivity in infinite-layer nickelates,
a consensus on the underlying mechanism for the superconductivity has yet to be
reached, partly owing to the challenges with the material synthesis. Here, we
report the successful growth of superconducting infinite-layer
Nd$_{0.8}$Sr$_{0.2}$NiO$_{2}$ films by pulsed-laser deposition and soft
chemical reduction. The details on growth process will be discussed.


  We consider finding a zero point of the maximally monotone operator $T$.
First, instead of using the proximal point algorithm (PPA) for this purpose, we
employ PPA to solve its Yosida regularization $T_{\lambda}$. Then, based on an
$O(a_{k+1})$ ($a_{k+1}\geq \varepsilon>0$) resolvent index of $T$, it turns out
that we can establish a convergence rate of $O
(1/{\sqrt{\sum_{i=0}^{k}a_{i+1}^2}})$ for both the $\|T_{\lambda}(\cdot)\|$ and
the gap function $\mathtt{Gap}(\cdot)$ in the non-ergodic sense, and
$O(1/\sum_{i=0}^{k}a_{i+1})$ for $\mathtt{Gap}(\cdot)$ in the ergodic sense.
Second, to enhance the convergence rate of the newly-proposed PPA, we introduce
an accelerated variant called the Contracting PPA. By utilizing a resolvent
index of $T$ bounded by $O(a_{k+1})$ ($a_{k+1}\geq \varepsilon>0$), we
establish a convergence rate of $O(1/\sum_{i=0}^{k}a_{i+1})$ for both
$\|T_{\lambda}(\cdot)\|$ and $\mathtt {Gap}(\cdot)$, considering the
non-ergodic sense. Third, to mitigate the limitation that the Contracting PPA
lacks a convergence guarantee, we propose two additional versions of the
algorithm. These novel approaches not only ensure guaranteed convergence but
also provide sublinear and linear convergence rates for both
$\|T_{\lambda}(\cdot)\|$ and $\mathtt {Gap}(\cdot)$, respectively, in the
non-ergodic sense.


  By engineering an anti-parity-time (anti-PT) symmetric cavity magnonics
system with precise eigenspace controllability, we observe two different
singularities in the same system. One type of singularity, the exceptional
point (EP), is produced by tuning the magnon damping. Between two EPs, the
maximal coherent superposition of photon and magnon states is robustly
sustained by the preserved anti-PT symmetry. The other type of singularity,
arising from the dissipative coupling of two anti-resonances, is an
unconventional bound state in the continuum (BIC). At the settings of BICs, the
coupled system exhibits infinite discontinuities in the group delay. We find
that both singularities co-exist at the equator of the Bloch sphere, which
reveals a unique hybrid state that simultaneously exhibits the maximal coherent
superposition and slow light capability.


  Quantum decoherence, the evolution of pure states into mixed states, may be a
feature of quantum gravity. In this paper, we show how these effects can be
modelled for atmospheric neutrinos and illustrate how the standard oscillation
picture is modified. We examine how neutrino telescopes, such as ANTARES, are
able to place upper bounds on these quantum decoherence effects.


  Nowadays, Computer Science tightly entered all spheres of human activity. To
improve quality and speed of development process, it is important to help
programmers improve their working conditions. This paper proposes a vision on
exploring this issue and presents in conjunction a factor that has been claimed
multiple time to affect the effectiveness of software production, concentration
and attention of software developers. We choose to focus on developers brain
activity and features that can be extracted from it.


  Due to neutron irradiation, solid breeder blankets are subjected to complex
thermo-mechanical conditions. Within one breeder unit, the ceramic breeder bed
is composed of spherical-shaped lithium orthosilicate pebbles, and as a type of
granular material, it exhibits strong coupling between temperature and stress
fields. In this paper, we study these thermo-mechanical problems by developing
a thermal discrete element method (Thermal-DEM). This proposed simulation tool
models each individual ceramic pebble as one element and considers grain-scale
thermo-mechanical interactions between elements. A small section of solid
breeder pebble bed in HCPB is modelled using thousands of individual pebbles
and subjected to volumetric heating profiles calculated from neutronics under
ITER-relevant conditions. We consider heat transfer at the grain-scale between
pebbles through both solid-to-solid contacts and the interstitial gas phase,
and we calculate stresses arising from thermal expansion of pebbles. The
overall effective conductivity of the bed depends on the resulting compressive
stress state during the neutronic heating. The thermal-DEM method proposed in
this study provides the access to the grain-scale information, which is
beneficial for HCPB design and breeder material optimization, and a better
understanding of overall thermo-mechanical responses of the breeder units under
fusion-relevant conditions.


  We report a first-principles study on electronic structures of the deformed
armchair graphene nanoribbons (AGNRs). The variation of the energy gap of AGNRs
as a function of uniaxial strain displays a zigzag pattern, which indicates
that the energy gaps of AGNRs can be effectively tuned. The spatial
distributions of two occupied and two empty subbands close to the Fermi level
are swapped under different strains. The tunable width of energy gaps becomes
narrower as increasing the width of AGNRs. Our simulations with tight binding
approximation, including the nearest neighbor hopping integrals between $\pi$-
orbitals of carbon atoms, reproduce these results by first-principles
calculations. One simple empirical formula is obtained to describe the scaling
behavior of the maximal value of energy gap as a function of the width of
AGNRs.


  GraphiQ is a versatile open-source framework for designing photonic graph
state generation schemes, with a particular emphasis on photon-emitter hybrid
circuits. Built in Python, GraphiQ consists of a suite of design tools,
including multiple simulation backends and optimization methods. The library
supports scheme optimization in the presence of circuit imperfections, as well
as user-defined optimization goals. Our framework thus represents a valuable
tool for the development of practical schemes adhering to
experimentally-relevant constraints. As graph states are a key resource for
measurement-based quantum computing, all-photonic quantum repeaters, and robust
quantum metrology, among others, we envision GraphiQ's broad impact for
advancing quantum technologies.


  We investigate the reactions D(e,e'p)n and D(\vec e,e'p)n at GeV energies and
discuss the opportunities to distinguish between different models for the
nuclear ground state by measuring the response functions. In calculating the
final-state interaction (FSI) we employ Glauber theory, and we also include
relativistic effects in the electromagnetic current. We include not only the
central FSI, but also the spin-orbit FSI which is usually neglected in (e,e'p)
calculations within the Glauber framework and we show that this contribution
plays a crucial role for the fifth response function. All of the methods
developed here can be applied to any target nucleus.


  Visual question answering (VQA) is a critical multimodal task in which an
agent must answer questions according to the visual cue. Unfortunately,
language bias is a common problem in VQA, which refers to the model generating
answers only by associating with the questions while ignoring the visual
content, resulting in biased results. We tackle the language bias problem by
proposing a self-supervised counterfactual metric learning (SC-ML) method to
focus the image features better. SC-ML can adaptively select the
question-relevant visual features to answer the question, reducing the negative
influence of question-irrelevant visual features on inferring answers. In
addition, question-irrelevant visual features can be seamlessly incorporated
into counterfactual training schemes to further boost robustness. Extensive
experiments have proved the effectiveness of our method with improved results
on the VQA-CP dataset. Our code will be made publicly available.


  A systematic, rigorous, and complete investigation of the Bloch equations in
time-harmonic driving classical field is performed. Our treatment is unique in
that it takes full advantage of the partial fraction decomposition over real
number field, which makes it possible to find and classify all analytic
solutions. Torrey's analytic solution in the form of exponentially damped
harmonic oscillations [Phys. Rev. {\bf 76}, 1059 (1949)] is found to dominate
the parameter space, which justifies its use at numerous occasions in magnetic
resonance and in quantum optics of atoms, molecules, and quantum dots. The
unorthodox solutions of the Bloch equations, which do not have the form of
exponentially damped harmonic oscillations, are confined to rather small
detunings $\delta^2\lesssim (\gamma-\gamma_t)^2/27$ and small field strengths
$\Omega^2\lesssim 8 (\gamma-\gamma_t)^2/27$, where $\gamma$ and $\gamma_t$
describe decay rates of the excited state (the total population relaxation
rate) and of the coherence, respectively. The unorthodox solutions being
readily accessible experimentally are characterized by rather featureless time
dependence.


  We study the cumulants and their generating functions of the probability
distributions of the conductance, shot noise and Wigner delay time in ballistic
quantum dots. Our approach is based on the integrable theory of certain matrix
integrals and applies to all the symmetry classes beta=1,2,4 of Random Matrix
Theory. We compute the weak localization corrections to the mixed cumulants of
the conductance and shot noise for beta=1,4, thus proving a number of
conjectures of Khoruzhenko et al. (Phys. Rev. B, Vol. 80 (2009), 125301). We
derive differential equations that characterize the cumulant generating
functions for all beta=1,2,4. Furthermore, we show that the cumulant generating
function of the Wigner delay time can be expressed in terms of the Painleve'
III' transcendant. This allows us to study properties of the cumulants of the
Wigner delay time in the asymptotic limit n -> infinity. Finally, for all the
symmetry classes and for any number of open channels, we derive a set of
recurrence relations that are very efficient for computing cumulants at all
orders.


  The spontaneously broken of translational symmetry is usually due to the
competition between local interactions and long-range interactions. However, in
this paper, we show how a crystalline order can be generated by the competition
between local interaction and long-range correlation by frustration. Here we
propose a positive hopping Bose Hubbard model on triangle lattices with a pair
creation term which comes from frustrated linked cavity arrays with degenerate
quantum gases in them. We find by increasing the strength of pair creation term
against local interaction strength, two kinds of density wave ordered
superradiant photonic fluid phase can be realized and a first order transition
between two different density wave ordered states is found. This proposal shows
us a new way to produce coherent "solid" phase without the help of long range
interactions.


  The Internet of Things (IoT) is gaining ground as a pervasive presence around
us by enabling miniaturized things with computation and communication
capabilities to collect, process, analyze, and interpret information.
Consequently, trustworthy data act as fuel for applications that rely on the
data generated by these things, for critical decision-making processes, data
debugging, risk assessment, forensic analysis, and performance tuning.
Currently, secure and reliable data communication in IoT is based on public-key
cryptosystems such as Elliptic Curve Cryptosystem (ECC). Nevertheless, reliance
on the security of de-facto cryptographic primitives is at risk of being broken
by the impending quantum computers. Therefore, the transition from classical
primitives to quantum-safe primitives is indispensable to ensure the overall
security of data en route. In this paper, we investigate applications of one of
the post-quantum signatures called Hash-Based Signature (HBS) schemes for the
security of IoT devices in the quantum era. We give a succinct overview of the
evolution of HBS schemes with emphasis on their construction parameters and
associated strengths and weaknesses. Then, we outline the striking features of
HBS schemes and their significance for the IoT security in the quantum era. We
investigate the optimal selection of HBS in the IoT networks with respect to
their performance-constrained requirements, resource-constrained nature, and
design optimization objectives. In addition to ongoing standardization efforts,
we also highlight current and future research and deployment challenges along
with possible solutions. Finally, we outline the essential measures and
recommendations that must be adopted by the IoT ecosystem while preparing for
the quantum world.


  The null energy condition has sweeping consequences in general relativity. I
argue here that it has been misunderstood as a property exclusively of matter,
when in fact it arises only in a theory of both matter and gravity. I then
derive an equivalent geometric formulation of the null energy condition from
worldsheet string theory, where it arises beautifully as simply Einstein's
equations in two dimensions. But further, I show that this condition also has a
thermodynamic origin, following from a local version of the second law of
thermodynamics, applied to gravitational entropy. Thus, far from being an
incidental property of matter, the validity of the null energy condition hints
at the deep dual origins of gravity.


  Zero-Shot Object Navigation (ZSON) requires agents to autonomously locate and
approach unseen objects in unfamiliar environments and has emerged as a
particularly challenging task within the domain of Embodied AI. Existing
datasets for developing ZSON algorithms lack consideration of dynamic
obstacles, object attribute diversity, and scene texts, thus exhibiting
noticeable discrepancies from real-world situations. To address these issues,
we propose a Dataset for Open-Vocabulary Zero-Shot Object Navigation in Dynamic
Environments (DOZE) that comprises ten high-fidelity 3D scenes with over 18k
tasks, aiming to mimic complex, dynamic real-world scenarios. Specifically,
DOZE scenes feature multiple moving humanoid obstacles, a wide array of
open-vocabulary objects, diverse distinct-attribute objects, and valuable
textual hints. Besides, different from existing datasets that only provide
collision checking between the agent and static obstacles, we enhance DOZE by
integrating capabilities for detecting collisions between the agent and moving
obstacles. This novel functionality enables the evaluation of the agents'
collision avoidance abilities in dynamic environments. We test four
representative ZSON methods on DOZE, revealing substantial room for improvement
in existing approaches concerning navigation efficiency, safety, and object
recognition accuracy. Our dataset can be found at
https://DOZE-Dataset.github.io/.


  We have carried out a detailed study to investigate the existence of an
insulating parent phase for FeSe superconductor. The insulating Fe4Se5 with
specific Fe-vacancy order shows a 3D-Mott variable range hopping behavior with
a Verwey-like electronic correlation at around 45 K. The application of the RTA
process at 450 celcius degree results in the destruction of Fe-vacancy order
and induces more electron carriers by increasing the Fe3+ valence state.
Superconductivity emerges with Tc ~ 8K without changing the chemical
stoichiometry of the sample after the RTA process by resulting in the addition
of extra carriers in favor of superconductivity.


  In the following we show the strong comparison principle for the fractional
$p$-Laplacian, i.e. we analyze functions $v,w$ which satisfy $v\geq w$ in
$\mathbb{R}^N$ and
  \[
  (-\Delta)^s_pv+q(x)|v|^{p-2}v\geq (-\Delta)^s_pw+q(x)|w|^{p-2}w \quad
\text{in $D$,}
  \] where $s\in(0,1)$, $p>1$, $D\subset \mathbb{R}^N$ is an open set, and
$q\in L^{\infty}(\mathbb{R}^N)$ is a nonnegative function. Under suitable
conditions on $s,p$ and some regularity assumptions on $v,w$ we show that
either $v\equiv w$ in $\mathbb{R}^N$ or $v>w$ in $D$. Moreover, we apply this
result to analyze the geometry of nonnegative solutions in starshaped rings and
in the half space.


  We give a short account of the quantisation of the Szekeres spacetime by
considering the symmetries of a reduced action principle. This is an
alternative approach than the one followed in the literature for the study of
inhomogeneities, which is usually based on perturbations of an inhomogeneous
field on the spacetime background. Here, we examine the emergence of
classicality with an exact inhomogeneous solution. We check whether the two
criteria for classicality are satisfied, that is the correlations on the phase
space and decoherence. We verify that these two properties indeed hold, thus
the classical behaviour emerges from our considerations. We comment on the
connection between the emergence of an inhomogeneous spacetime and the current
cosmological observations of a highly homogeneous universe at large scales.


  We present a method for total energy minimizations and molecular dynamics
simulations based either on tight-binding or on Kohn-Sham hamiltonians. The
method leads to an algorithm whose computational cost scales linearly with the
system size. The key features of our approach are
  (i) an orbital formulation with single particle wavefunctions constrained to
be localized in given regions of space, and (ii) an energy functional which
does not require either explicit orthogonalization of the electronic orbitals,
or inversion of an overlap matrix.
  The foundations and accuracy of the approach and the performances of the
algorithm are discussed, and illustrated with several numerical examples
including Kohn-Sham hamiltonians. In particular we present calculations with
tight-binding hamiltonians for diamond, graphite, a carbon linear chain and
liquid carbon at low pressure. Even for a complex case such as liquid carbon --
a disordered metallic system with differently coordinated atoms -- the
agreement between standard diagonalization schemes and our approach is very
good. Our results establish the accuracy and reliability of the method for a
wide class of systems and show that tight binding molecular dynamics
simulations with a few thousand atoms are feasible on small workstations.


  We study spontaneous-symmetry-broken phase-separated vortex lattice in a
weakly interacting uniform rapidly rotating binary Bose superfluid contained in
a quasi-two-dimensional circular or square bucket. For the inter-species
repulsion above a critical value, the two superfluid components separate and
form a demixed phase with practically no overlap in the vortex lattices of the
two components, which will permit an efficient experimental observation of such
vortices and study their properties. In case of a circular bucket with equal
intra-species energies of the two components, the two components separate into
two non-overlapping semicircular domains for all frequencies of rotation
$\Omega$ generating distinct demixed vortex lattices. In case of a binary Bose
superfluid in both circular and square buckets, (a) the number of vortices
increases linearly with $\Omega$ in agreement with a suggestion by Feynman, and
(b) the rotational energy in the rotating frame decreases quadratically with
$\Omega$ in agreement with a suggestion by Fetter.


  The algebra generated by the down and up operators on a differential
partially ordered set (poset) encodes essential enumerative and structural
properties of the poset. Motivated by the algebras generated by the down and up
operators on posets, we introduce here a family of infinite-dimensional
associative algebras called down-up algebras. We show that down-up algebras
exhibit many of the important features of the universal enveloping algebra
$U(\fsl)$ of the Lie algebra $\fsl$ including a Poincar\'e-Birkhoff-Witt type
basis and a well-behaved representation theory. We investigate the structure
and representations of down-up algebras and focus especially on Verma modules,
highest weight representations, and category $\mathcal O$ modules for them. We
calculate the exact expressions for all the weights, since that information has
proven to be particularly useful in determining structural results about
posets.