  Beams of light with helical wavefronts can be focused into ring-like optical
traps known as optical vortices. The orbital angular momentum carried by
photons in helical modes can be transferred to trapped mesoscopic objects and
thereby coupled to a surrounding fluid. We demonstrate that arrays of optical
vortices created with the holographic optical tweezer technique can assemble
colloidal spheres into dynamically reconfigurable microoptomechanical pumps
assembled by optical gradient forces and actuated by photon orbital angular
momentum.


  The community currently lacks a complete understanding of how resonant
inelastic x-ray scattering (RIXS) experiments probe the electron-phonon
($e$-ph) interaction in solids. For example, most theoretical models of this
process have focused on dispersionless Einstein phonons. Using a recently
developed momentum average (MA) variational approximation for computing RIXS
spectra of band insulators, we examine the influence of both electron and
phonon dispersion in the intermediate state of the scattering process. We find
that the inclusion of either, and their mutual interplay, introduces
significant momentum variations in the RIXS intensity, even for
momentum-independent electron-phonon coupling. The phonon dispersion also
induces nontrivial changes in the excitation line shapes, which can have a
quantitative impact on the data analysis. These results highlight the
considerable challenges of interpreting RIXS data in actual materials.


  We present the largest systematic, HST-based search to date for luminous
$z\gtrsim8$ galaxy candidates using $\sim$1267 arcmin$^{2}$ of (pure-)parallel
observations from a compilation of 288 random sightlines with ACS and WFC3
observations, derived from the SuperBoRG data set and together representing a
factor $\sim1.12\times$ larger than existing space-based data sets. Using NIR
color cuts and careful photo-$z$ analyses, we find 31 $z\gtrsim8$ galaxy
candidates over 29 unique sightlines, and derive global galaxy properties such
as UV magnitudes and continuum slopes, sizes, and rest-frame optical properties
(e.g., SFRs, stellar masses, $A_{\rm v}$). Taking advantage of the
(pure-)parallel nature of our data set - making it one of the most
representative thus far - and derived SFRs, we evaluate the cosmic star
formation rate density for the bright end of the UV luminosity function at
$z\sim8-10$ and test the validity of luminosity function-derived results using
a conversion factor. We find our method yields comparable results to those
derived with luminosity functions. Furthermore, we present follow up
observations of 5 (Super)BoRG targets with Keck/MOSFIRE, finding no evidence of
Ly$\alpha$ in $>3$ hrs of $Y-$band observations in either, consistent with a
largely neutral medium at $z\sim8$. Our results offer a definitive HST legacy
on the bright end of the luminosity function and provide a valuable benchmark
as well as targets for follow up with JWST.


  We have investigated the low-temperature local magnetic properties in the
bulk of molten salt-flux (MSF) grown single crystals of the candidate
odd-parity superconductor UTe2 by zero-field muon spin relaxation (muSR). In
contrast to previous muSR studies of UTe2 single crystals grown by a chemical
vapour transport (CVT) method, we find no evidence of magnetic clusters or
electronic moments fluctuating slow enough to cause a discernible relaxation of
the zero-field muSR asymmetry spectrum. Consequently, our measurements on
MSF-grown single crystals rule out the generation of spontaneous magnetic
fields in the bulk that would occur near impurities or lattice defects if the
superconducting state of UTe2 breaks time-reversal symmetry. This result
suggests UTe2 is characterized by a single-component superconducting order
parameter.


  Learning multiple gaits is non-trivial for legged robots, especially when
encountering different terrains and velocity commands. In this work, we present
an end-to-end training framework for learning multiple gaits for quadruped
robots, tailored to the needs of robust locomotion, agile locomotion, and
user's commands. A latent space is constructed concurrently by a gait encoder
and a gait generator, which helps the agent to reuse multiple gait skills to
achieve adaptive gait behaviors. To learn natural behaviors for multiple gaits,
we design gait-dependent rewards that are constructed explicitly from gait
parameters and implicitly from conditional adversarial motion priors (CAMP). We
demonstrate such multiple gaits control on a quadruped robot Go1 with only
proprioceptive sensors.


  The 2D space-fractional Schrodinger equation in the time-independent and
time-dependent cases for the scattering problem in the fractional quantum
mechanics is studied. We define and give the mathematical expression of the
Green's functions for the two cases. The asymptotic formulas of the Green's
functions are also given, and applied to get the approximate wave functions for
the fractional quantum scattering problems.


  In this paper, we consider the dynamical modeling of a class of quantum
network systems consisting of qubits. Qubit probes are employed to measure a
set of selected nodes of the quantum network systems. For a variety of
applications, a state space model is a useful way to model the system dynamics.
To construct a state space model for a quantum network system, the major task
is to find an accessible set containing all of the operators coupled to the
measurement operators. This paper focuses on the generation of a proper
accessible set for a given system and measurement scheme. We provide analytic
results on simplifying the process of generating accessible sets for systems
with a time-independent Hamiltonian. Since the order of elements in the
accessible set determines the form of state space matrices, guidance is
provided to effectively arrange the ordering of elements in the state vector.
Defining a system state according to the accessible set, one can develop a
state space model with a special pattern inherited from the system structure.
As a demonstration, we specifically consider a typical 1D-chain system with
several common measurements, and employ the proposed method to determine its
accessible set.


  With the widespread popularity of user-generated short videos, it becomes
increasingly challenging for content creators to promote their content to
potential viewers. Automatically generating appealing titles and covers for
short videos can help grab viewers' attention. Existing studies on video
captioning mostly focus on generating factual descriptions of actions, which do
not conform to video titles intended for catching viewer attention.
Furthermore, research for cover selection based on multimodal information is
sparse. These problems motivate the need for tailored methods to specifically
support the joint task of short video title generation and cover selection
(TG-CS) as well as the demand for creating corresponding datasets to support
the studies. In this paper, we first collect and present a real-world dataset
named Short Video Title Generation (SVTG) that contains videos with appealing
titles and covers. We then propose a Title generation and Cover selection with
attention Refinement (TCR) method for TG-CS. The refinement procedure
progressively selects high-quality samples and highly relevant frames and text
tokens within each sample to refine model training. Extensive experiments show
that our TCR method is superior to various existing video captioning methods in
generating titles and is able to select better covers for noisy real-world
short videos.


  The security of computer systems fundamentally relies on memory isolation,
e.g., kernel address ranges are marked as non-accessible and are protected from
user access. In this paper, we present Meltdown. Meltdown exploits side effects
of out-of-order execution on modern processors to read arbitrary kernel-memory
locations including personal data and passwords. Out-of-order execution is an
indispensable performance feature and present in a wide range of modern
processors. The attack works on different Intel microarchitectures since at
least 2010 and potentially other processors are affected. The root cause of
Meltdown is the hardware. The attack is independent of the operating system,
and it does not rely on any software vulnerabilities. Meltdown breaks all
security assumptions given by address space isolation as well as
paravirtualized environments and, thus, every security mechanism building upon
this foundation. On affected systems, Meltdown enables an adversary to read
memory of other processes or virtual machines in the cloud without any
permissions or privileges, affecting millions of customers and virtually every
user of a personal computer. We show that the KAISER defense mechanism for
KASLR has the important (but inadvertent) side effect of impeding Meltdown. We
stress that KAISER must be deployed immediately to prevent large-scale
exploitation of this severe information leakage.


  Defining and measuring internationality as a function of influence diffusion
of scientific journals is an open problem. There exists no metric to rank
journals based on the extent or scale of internationality. Measuring
internationality is qualitative, vague, open to interpretation and is limited
by vested interests. With the tremendous increase in the number of journals in
various fields and the unflinching desire of academics across the globe to
publish in "international" journals, it has become an absolute necessity to
evaluate, rank and categorize journals based on internationality. Authors, in
the current work have defined internationality as a measure of influence that
transcends across geographic boundaries. There are concerns raised by the
authors about unethical practices reflected in the process of journal
publication whereby scholarly influence of a select few are artificially
boosted, primarily by resorting to editorial maneuvres. To counter the impact
of such tactics, authors have come up with a new method that defines and
measures internationality by eliminating such local effects when computing the
influence of journals. A new metric, Non-Local Influence Quotient(NLIQ) is
proposed as one such parameter for internationality computation along with
another novel metric, Other-Citation Quotient as the complement of the ratio of
self-citation and total citation. In addition, SNIP and International
Collaboration Ratio are used as two other parameters.


  We show that there are no dynamic screening corrections to the Salpeter's
enhancement factor in the weak-screening limit.


  Context: Agile software development (ASD) sets social aspects like
communication and collaboration in focus. Thus, one may assume that the
specific work organization of companies impacts the work of ASD teams. A major
change in work organization is the switch to a 4-day work week, which some
companies investigated in experiments. Also, recent studies show that ASD teams
are affected by the switch to remote work since the Covid 19 pandemic outbreak
in 2020. Objective: Our study presents empirical findings on the effects on ASD
teams operating remote in a 4-day work week organization. Method: We performed
a qualitative single case study and conducted seven semi-structured interviews,
observed 14 agile practices and screened eight project documents and protocols
of agile practices. Results: We found, that the teams adapted the agile method
in use due to the change to a 4-day work week environment and the switch to
remote work. The productivity of the two ASD teams did not decrease. Although
the stress level of the ASD team member increased due to the 4-day work week,
we found that the job satisfaction of the individual ASD team members is
affected positively. Finally, we point to affects on social facets of the ASD
teams. Conclusions: The research community benefits from our results as the
current state of research dealing with the effects of a 4-day work week on ASD
teams is limited. Also, our findings provide several practical implications for
ASD teams working remote in a 4-day work week.


  We consider extensions of the Shannon relative entropy, referred to as
$f$-divergences.Three classical related computational problems are typically
associated with these divergences: (a) estimation from moments, (b) computing
normalizing integrals, and (c) variational inference in probabilistic models.
These problems are related to one another through convex duality, and for all
them, there are many applications throughout data science, and we aim for
computationally tractable approximation algorithms that preserve properties of
the original problem such as potential convexity or monotonicity. In order to
achieve this, we derive a sequence of convex relaxations for computing these
divergences from non-centered covariance matrices associated with a given
feature vector: starting from the typically non-tractable optimal lower-bound,
we consider an additional relaxation based on ``sums-of-squares'', which is is
now computable in polynomial time as a semidefinite program. We also provide
computationally more efficient relaxations based on spectral information
divergences from quantum information theory. For all of the tasks above, beyond
proposing new relaxations, we derive tractable convex optimization algorithms,
and we present illustrations on multivariate trigonometric polynomials and
functions on the Boolean hypercube.


  A phase transition of gas-liquid type with an upper critical point is
examined which arises in a model of charges of one sign on compensating
background (OCP). The phase transition parameters are dependent on the detailed
assumptions about the compressibility of the background, but the occurrence of
this transition is independent on the background equation of state. In the
electron-gas model ('jellium'), this transition appears to rule out Wigner
crystallization. A variational principle in statistical mechanics is used to
derive so-called Double-OCP model for a superposition of two one-component
plasma models for charges of opposite sign. The free energy of this model sets
an upper bound to that of a real plasma. Situations are discussed where this
transition should manifest itself in anomalies in the approximate description
of a non-ideal plasma.


  Time series classification (TSC) aims to predict the class label of a given
time series, which is critical to a rich set of application areas such as
economics and medicine. State-of-the-art TSC methods have mostly focused on
classification accuracy and efficiency, without considering the
interpretability of their classifications, which is an important property
required by modern applications such as appliance modeling and legislation such
as the European General Data Protection Regulation. To address this gap, we
propose a novel TSC method - the Randomized-Supervised Time Series Forest
(r-STSF). r-STSF is highly efficient, achieves state-of-the-art classification
accuracy and enables interpretability. r-STSF takes an efficient interval-based
approach to classify time series according to aggregate values of
discriminatory sub-series (intervals). To achieve state-of-the-art accuracy,
r-STSF builds an ensemble of randomized trees using the discriminatory
sub-series. It uses four time series representations, nine aggregation
functions and a supervised binary-inspired search combined with a feature
ranking metric to identify highly discriminatory sub-series. The discriminatory
sub-series enable interpretable classifications. Experiments on extensive
datasets show that r-STSF achieves state-of-the-art accuracy while being orders
of magnitude faster than most existing TSC methods. It is the only classifier
from the state-of-the-art group that enables interpretability. Our findings
also highlight that r-STSF is the best TSC method when classifying complex time
series datasets.


  The total and angular differential cross sections of the coherent process
$\bar p + {}^AZ \to {}^A_\Lambda(Z-1) + \bar{\Lambda}$ are evaluated at the
beam momenta $1.5\div20$ GeV/c within the meson exchange model with bound
proton and $\Lambda$-hyperon wave functions. It is shown that the shape of the
beam momentum dependence of the hypernucleus production cross sections with
various discrete $\Lambda$ states is strongly sensitive to the presence of the
scalar $\kappa$-meson exchange in the $\bar p p \to \bar\Lambda \Lambda$
amplitude. This can be used as a clean test of the exchange by scalar $\pi K$
correlation in coherent $\bar p A$ reactions.


  Landauer's principle makes a strong connection between information theory and
thermodynamics by stating that erasing a one-bit memory at temperature $T_0$
requires an average energy larger than $W_{LB}=k_BT_0 \ln2$, with $k_B$
Boltzmann's constant. This tiny limit has been saturated in model experiments
using quasi-static processes. For faster operations, an overhead proportional
to the processing speed and to the memory damping appears. In this article, we
show that underdamped systems are a winning strategy to reduce this extra
energetic cost. We prove both experimentally and theoretically that, in the
limit of vanishing dissipation mechanisms in the memory, the physical system is
thermally insulated from its environment during fast erasures, i.e. fast
protocols are adiabatic as no heat is exchanged with the bath. Using a fast
optimal erasure protocol we also show that these adiabatic processes produce a
maximum adiabatic temperature $T_a=2T_0$, and that Landauer's bound for fast
erasures in underdamped systems becomes the adiabatic bound: $W_a = k_B T_0$.


  Using multi-epoch Very Long Baseline Array observations, we have measured the
trigonometric parallax of the weak-line T Tauri star HP Tau/G2 in Taurus. The
best fit yields a distance of 161.2 $\pm$ 0.9 pc, suggesting that the eastern
portion of Taurus (where HP Tau/G2 is located) corresponds to the far side of
the complex. Previous VLBA observations have shown that T Tau, to the South of
the complex, is at an intermediate distance of about 147 pc, whereas the region
around L1495 corresponds to the near side at roughly 130 pc. Our observations
of only four sources are still too coarse to enable a reliable determination of
the three-dimensional structure of the entire Taurus star-forming complex. They
do demonstrate, however, that VLBA observations of multiple sources in a given
star-forming region have the potential not only to provide a very accurate
estimate of its mean distance, but also to reveal its internal structure. The
proper motion measurements obtained simultaneously with the parallax allowed us
to study the kinematics of the young stars in Taurus. Combining the four
observations available so far, we estimate the peculiar velocity of Taurus to
be about 10.6 km s-1 almost completely in a direction parallel to the Galactic
plane. Using our improved distance measurement, we have refined the
determination of the position on the HR diagram of HP Tau/G2, and of two other
members of the HP Tau group (HP Tau itself and HP Tau/G3). Most pre-main
sequence evolutionary models predict significantly discrepant ages (by 5 Myr)
for those three stars -expected to be coeval. Only in the models of Palla &
Stahler (1999) do they fall on a single isochrone (at 3 Myr).


  The rapid growth of the automotive industry has exacerbated the conflict
between the complex traffic environment, increasing communication demands, and
limited resources. Given the imperative to mitigate traffic and network
congestion, analyzing the performance of Internet of Vehicles (IoV) mesh
networks is of great practical significance. Most studies focus solely on
individual performance metrics and influencing factors, and the adopted
simulation tools, such as OPNET, cannot achieve the dynamic link generation of
IoV mesh networks. To address these problems, a network performance analysis
model based on actual switches is proposed. First, a typical IoV mesh network
architecture is constructed and abstracted into a mathematical model that
describes how the link and topology changes over time. Then, the task
generation model and the task forwarding model based on actual switches are
proposed to obtain the real traffic distribution of the network. Finally, a
scientific network performance indicator system is constructed. Simulation
results demonstrate that, with rising task traffic and decreasing node caching
capacity, the packet loss rate increases, and the task arrival rate decreases
in the network. The proposed model can effectively evaluate the network
performance across various traffic states and provide valuable insights for
network construction and enhancement.


  Active particles which are self-propelled by converting energy into
mechanical motion represent an expanding research realm in physics and
chemistry. For micron-sized particles moving in a liquid ("microswimmers"),
most of the basic features have been described by using the model of overdamped
active Brownian motion. However, for macroscopic particles or microparticles
moving in a gas, inertial effects become relevant such that the dynamics is
underdamped. Therefore, recently, active particles with inertia have been
described by extending the active Brownian motion model to active Langevin
dynamics which include inertia. In this perspective article recent developments
of active particles with inertia ("microflyers") are summarized both for single
particle properties and for collective effects of many particles. There
include: inertial delay effects between particle velocity and self-propulsion
direction, tuning of the long-time self-diffusion by the moment of inertia,
effects of fictitious forces in non-inertial frames, and the influence of
inertia on motility-induced phase separation. Possible future developments and
perspectives are also proposed and discussed.


  This paper analyses the problem of a semi-infinite fluid-driven fracture
propagating through multiple stress layers in a permeable elastic medium. Such
a problem represents the tip region of a planar hydraulic fracture. When the
hydraulic fracture crosses a stress layer, the use of a standard tip asymptotic
solution may lead to a considerable reduction of accuracy, even for the
simplest case of a height-contained fracture. In this study, we propose three
approaches to incorporate the effect of stress layers into the tip asymptote:
non-singular integral formulation, toughness-corrected asymptote, and an
ordinary differential equation approximation of the non-singular integral
formulation mentioned above. As illustrated in the paper, these approaches for
stress-corrected asymptotes differ in computational complexity, the complexity
of implementation, and the accuracy of the approximation. In addition, the size
of the validity region of the stress-corrected asymptote is evaluated, and it
is shown to be greatly reduced relative to the case without layers. In order to
address the issue, the stress relaxation factor is introduced. This, in turn,
allows for enhancing the accuracy of the layer-crossing computation on a
relatively coarse mesh to utilize the stress-corrected asymptote in hydraulic
fracturing simulators for the purpose of front tracking.


  For the purpose of deriving the helium abundances in chemically peculiar
stars, the importance of assuming a correct helium abundance has been
investigated for determining the effective temperature and gravity of main
sequence B-type stars, making full use of the present capability of reproducing
their helium lines.
  Even if the flux distribution of main sequence B-type stars appears to depend
only on the effective temperature for any helium abundance, the effective
temperature, gravity and helium abundance have to be determined simultaneously
by matching the Balmer line profiles. New MULTI NLTE calculations, performed
adopting ATLAS9 model atmospheres and updated helium atomic parameters,
reproduce most of the observed equivalent widths of neutral helium lines for
main sequence B-type stars and they make us confident of the possibility to
correctly derive the helium abundance in chemically peculiar stars.
  An application of previous methods to the helium rich star HD 37017 shows
that helium could be stratified in the magnetic pole regions, as expected in
the framework of the diffusion theory in the presence of mass loss.


  Because the Impact Factor (IF) is an average quantity and most journals are
small, IFs are volatile. We study how a single paper affects the IF using data
from 11639 journals in the 2017 Journal Citation Reports. We define as
volatility the IF gain (or loss) caused by a single paper, and this is
inversely proportional to journal size. We find high volatilities for hundreds
of journals annually due to their top-cited paper: whether it is a highly-cited
paper in a small journal, or a moderately (or even low) cited paper in a small
and low-cited journal. For example, 1218 journals had their most cited paper
boost their IF by more than 20%, while for 231 journals the boost exceeded 50%.
We find that small journals are rewarded much more than large journals for
publishing a highly-cited paper, and are also penalized more for publishing a
low-cited paper, especially if they have a high IF. This produces a strong
incentive for prestigious, high-IF journals to stay small, to remain
competitive in IF rankings. We discuss the implications for breakthrough papers
to appear in prestigious journals. We also question the practice of ranking
journals by IF given this uneven reward mechanism.


  We present a data-efficient framework for solving sequential decision-making
problems which exploits the combination of reinforcement learning (RL) and
latent variable generative models. The framework, called GenRL, trains deep
policies by introducing an action latent variable such that the feed-forward
policy search can be divided into two parts: (i) training a sub-policy that
outputs a distribution over the action latent variable given a state of the
system, and (ii) unsupervised training of a generative model that outputs a
sequence of motor actions conditioned on the latent action variable. GenRL
enables safe exploration and alleviates the data-inefficiency problem as it
exploits prior knowledge about valid sequences of motor actions. Moreover, we
provide a set of measures for evaluation of generative models such that we are
able to predict the performance of the RL policy training prior to the actual
training on a physical robot. We experimentally determine the characteristics
of generative models that have most influence on the performance of the final
policy training on two robotics tasks: shooting a hockey puck and throwing a
basketball. Furthermore, we empirically demonstrate that GenRL is the only
method which can safely and efficiently solve the robotics tasks compared to
two state-of-the-art RL methods.


  The formation of the radial electric field, $E_{\rm r}$ in the SOL has been
experimentally studied for attached divertor conditions in stellarator W7-X.
The main objective of this study is to test the validity in a complex 3D island
divertor of simple models, typically developed in tokamaks, relating $E_{\rm
r}$ to the sheath potential drop gradient at the target. Additionally, we
investigate the effect of the edge $E_{\rm r}$ shear on the reduction of
density fluctuation amplitude, a well-established phenomenon according to the
existing bibliography. The main diagnostic for measurements in the SOL is a
V-band Doppler reflectometer that can provide the measurement of the $E_{\rm
r}$ and density fluctuations with good spatial resolution. Three-dimensional
measurements of divertor parameters has been carried out using infrared
cameras, with $\lambda_{\rm q}$ resulting a suitable proxy for the
model-relevant $\lambda_{\rm T}$. In the investigated attached regimes, it is
shown for the first time that the formation of the $E_{\rm r}$ in the SOL
depends on parameters at the divertor, following a $E_{\rm r} \propto T_{\rm e}
/\lambda_q$ qualitatively similar to that found in a tokamak. Then, from the
analyzed plasmas, the observed $E_{\rm r}$ shear at the edge is linked to a
moderate local reduction of the amplitude of density fluctuations.


  We introduce the problem of regret minimization in adversarial multi-dueling
bandits. While adversarial preferences have been studied in dueling bandits,
they have not been explored in multi-dueling bandits. In this setting, the
learner is required to select $m \geq 2$ arms at each round and observes as
feedback the identity of the most preferred arm which is based on an arbitrary
preference matrix chosen obliviously. We introduce a novel algorithm, MiDEX
(Multi Dueling EXP3), to learn from such preference feedback that is assumed to
be generated from a pairwise-subset choice model. We prove that the expected
cumulative $T$-round regret of MiDEX compared to a Borda-winner from a set of
$K$ arms is upper bounded by $O((K \log K)^{1/3} T^{2/3})$. Moreover, we prove
a lower bound of $\Omega(K^{1/3} T^{2/3})$ for the expected regret in this
setting which demonstrates that our proposed algorithm is near-optimal.


  Test beam and irradiation facilities are the key enabling infrastructures for
research in high energy physics (HEP) and astro-particles. In the last 11 years
the Beam-Test Facility (BTF) of the DA{\Phi}NE accelerator complex in the
Frascati laboratory has gained an important role in the European
infrastructures devoted to the development and testing of particle detectors.
At the same time the BTF operation has been largely shadowed, in terms of
resources, by the running of the DA{\Phi}NE electron-positron collider. The
present proposal is aimed at improving the present performance of the facility
from two different points of view: extending the range of application for the
LINAC beam extracted to the BTF lines, in particular in the (in some sense
opposite) directions of hosting fundamental physics and providing electron
irradiation also for industrial users; extending the life of the LINAC beyond
or independently from its use as injector of the DA{\Phi}NE collider, as it is
also a key element of the electron/positron beam facility. The main lines of
these two developments can be identified as: consolidation of the LINAC
infrastructure, in order to guarantee a stable operation in the longer term;
upgrade of the LINAC energy, in order to increase the facility capability
(especially for the almost unique extracted positron beam); doubling of the BTF
beam-lines, in order to cope with the signicant increase of users due to the
much wider range of applications.


  Large Language Models (LLMs) provide a possibility to make a great
breakthrough in medicine. The establishment of a standardized medical benchmark
becomes a fundamental cornerstone to measure progression. However, medical
environments in different regions have their local characteristics, e.g., the
ubiquity and significance of traditional Chinese medicine within China.
Therefore, merely translating English-based medical evaluation may result in
\textit{contextual incongruities} to a local region. To solve the issue, we
propose a localized medical benchmark called CMB, a Comprehensive Medical
Benchmark in Chinese, designed and rooted entirely within the native Chinese
linguistic and cultural framework. While traditional Chinese medicine is
integral to this evaluation, it does not constitute its entirety. Using this
benchmark, we have evaluated several prominent large-scale LLMs, including
ChatGPT, GPT-4, dedicated Chinese LLMs, and LLMs specialized in the medical
domain. We hope this benchmark provide first-hand experience in existing LLMs
for medicine and also facilitate the widespread adoption and enhancement of
medical LLMs within China. Our data and code are publicly available at
https://github.com/FreedomIntelligence/CMB.


  Contour integration techniques have become a popular choice for solving the
linear and non-linear eigenvalue problems. They principally include the
Sakurai-Sugiura methods, the Beyn's algorithm, the FEAST/NLFEAST algorithms and
other rational filtering techniques. While these methods can result in
effective 'black-box' approach for solving linear eigenvalue problems, they
still present several shortcomings for addressing nonlinear eigenvalue problems
which are both mathematically and practically far more challenging. In this
paper, we introduce a new hybrid algorithm that advantageously combines the
iterative nature of NLFEAST with the effectiveness of Beyn's approach to deal
with general non-linearity. In doing so, this NLFEAST-Beyn hybrid algorithm can
overcome current limitations of both algorithms taken separately. After
presenting its derivation from both a Beyn's and NLFEAST's perspective, several
numerical examples are discussed to demonstrate the efficiency of the new
technique.


  For certain families of finite quantum graphs, we study the question of how
eigenfunctions are distributed over the graph. To characterize properties of
the distribution, generalized entropies of the R\'{e}nyi and Tsallis types are
considered. The presented approach is similar to entropic uncertainty relations
of the Maassen-Uffink type. Using the Riesz theorem, we derive lower bounds on
symmetrized generalized entropies of eigenfunctions. A quality of such
estimates will depend on boundary conditions used at vertices of the given
graph. R\'{e}nyi and Tsallis entropies of eigenfunctions of star graphs are
separately examined. Relations between generalized entropies and variances of
eigenfunctions are considered as well. When such relations remain valid on
average, they may be used in studies of quantum ergodicity.


  We consider Chebyshev polynomials, $T_n(z)$, for infinite, compact sets
$\frak{e} \subset \mathbb{R}$ (that is, the monic polynomials minimizing the
sup-norm, $\Vert T_n \Vert_{\frak{e}}$, on $\frak{e}$). We resolve a $45+$ year
old conjecture of Widom that for finite gap subsets of $\mathbb{R}$, his
conjectured asymptotics (which we call Szeg\H{o}-Widom asymptotics) holds. We
also prove the first upper bounds of the form $\Vert T_n \Vert_{\frak{e}} \leq
Q C({\frak{e}})^n$ (where $C(\frak{e})$ is the logarithmic capacity of
$\frak{e}$) for a class of $\frak{e}$'s with an infinite number of components,
explicitly for those $\frak{e} \subset \mathbb{R}$ that obey a Parreau-Widom
condition.


  The study of alternative models for elliptic curves has found recent interest
from cryptographic applications, once it was recognized that such models
provide more efficiently computable algorithms for the group law than the
standard Weierstrass model. Examples of such models arise via symmetries
induced by a rational torsion structure. We analyze the module structure of the
space of sections of the addition morphisms, determine explicit dimension
formulas for the spaces of sections and their eigenspaces under the action of
torsion groups, and apply this to specific models of elliptic curves with
parametrized torsion subgroups.


  Structural colors generated due to light scattering from static
all-dielectric metasurfaces have successfully enabled high-resolution,
high-saturation, and wide-gamut color printing applications. Despite recent
advances, most demonstrations of these structure-dependent colors lack
post-fabrication tunability. This hinders their applicability for front-end
dynamic display technologies. Phase-change materials (PCMs), with significant
contrast of their optical properties between their amorphous and crystalline
states, have demonstrated promising potentials in reconfigurable nanophotonics.
Herein, we leverage tunable all-dielectric reflective metasurfaces made of
newly emerged classes of low-loss optical PCMs, i.e., antimony trisulphide
(Sb$_2$S$_3$) and antimony triselenide (Sb$_2$Se$_3$), with superb
characteristics to realize switchable, high-saturation, high-efficiency and
high-resolution dynamic meta-pixels. Exploiting polarization-sensitive building
blocks, the presented meta-pixel can generate two different colors when
illuminated by either one of two orthogonally polarized incident beams. Such
degrees of freedom (i.e., material phase and polarization state) enable a
single reconfigurable metasurface with fixed geometrical parameters to generate
four distinct wide-gamut colors. We experimentally demonstrate, for the first
time, an electrically-driven micro-scale display through the integration of
phase-change metasurfaces with an on-chip heater formed by transparent
conductive oxide. Our experimental findings enable a versatile platform
suitable for a wide range of applications, including tunable full-color
printing, enhanced dynamic displays, information encryption, and
anti-counterfeiting.


  In this paper we shed light on the impact of fine-tuning over social media
data in the internal representations of neural language models. We focus on bot
detection in Twitter, a key task to mitigate and counteract the automatic
spreading of disinformation and bias in social media. We investigate the use of
pre-trained language models to tackle the detection of tweets generated by a
bot or a human account based exclusively on its content. Unlike the general
trend in benchmarks like GLUE, where BERT generally outperforms generative
transformers like GPT and GPT-2 for most classification tasks on regular text,
we observe that fine-tuning generative transformers on a bot detection task
produces higher accuracies. We analyze the architectural components of each
transformer and study the effect of fine-tuning on their hidden states and
output representations. Among our findings, we show that part of the
syntactical information and distributional properties captured by BERT during
pre-training is lost upon fine-tuning while the generative pre-training
approach manage to preserve these properties.


  In this work, we investigate the effects of the ghost sector on the dynamical
mass generation for the gauge boson of a pure Yang-Mills theory. The generation
of a dynamical mass for the gluon is realized by the Schwinger mechanism, which
is triggered by the existence of longitudinally coupled massless poles in the
fundamental vertices of the theory. The appearance of such poles occurs by
purely dynamical reasons and is governed by a set of Bethe-Salpeter equations.
In previous studies, only the presence of massless poles in the
background-gauge three-gluon vertex was considered. Here, we include the
possibility for such poles to appear also in the corresponding ghost-gluon
vertex. Then, we solve the resulting Bethe-Salpeter system, which reveals that
the contribution associated with the poles of the ghost-gluon vertex is
suppressed with respect to those originating from the three-gluon vertex.


  An effective spin-orbit Hamiltonian is derived for a spin-1/2 trimerized
kagome antiferromagnet in the second-order of perturbation theory in the ratio
of two coupling constants. Low-energy singlet states of the obtained model are
mapped to a quantum dimer model on a triangular lattice. The quantum dimer
model is dominated by dimer resonances on a few shortest loops of the
triangular lattice. Characteristic energy scale for the dimer model constitutes
only a small fraction of the weaker exchange coupling constant.


  The exciton dissociation and charge separation occurring on subpicosecond
time scales following the photoexcitation are studied in a model donor/acceptor
heterojunction using a fully quantum approach. Higher-than-LUMO acceptor
orbitals which are energetically aligned with the donor LUMO orbital
participate in the ultrafast interfacial dynamics by creating photon-absorbing
charge-bridging states in which charges are spatially separated and which can
be directly photoexcited. Along with the states brought about by
single-particle resonances, the two-particle (exciton) mixing gives rise to
bridge states in which charges are delocalized. Bridge states open up a number
of photophysical pathways that indirectly connect the initial donor states with
states of spatially separated charges and compete with the efficient
progressive deexcitation within the manifold of donor states. The diversity and
efficiency of these photophysical pathways depend on a number of factors, such
as the precise energy alignment of exciton states, the central frequency of the
excitation, and the strength of carrier-phonon interaction.


  The notions of left-right noncommutative Poisson algebra ($\NP^{lr}$-algebra)
and left-right algebra with bracket $\AWB^{lr}$ are introduced. These algebras
are special cases of $\NLP$-algebras and algebras with bracket $\AWB$,
respectively, studied earlier. An $\NP^{lr}$-algebra is a noncommutative
analogue of the classical Poisson algebra. Properties of the new algebras are
studied. The constructions of free objects in the corresponding categories are
given. The relations between the properties of $\NP^{lr}$-algebras, the
underlying $\AWB^{lr}$, associative and Leibniz algebras are investigated. In
the categories $\AWB^{lr}$ and $\NP^{lr}$-algebras the notions of actions,
representations, centers, actors and crossed modules are described as special
cases of the corresponding well-known notions in categories of groups with
operations. The cohomologies of $\NP^{lr}$-algebras and $\AWB^{lr}$ (resp. of
$\NP^r$-algebras and $\AWB^r$) are defined and the relations between them and
the Hochschild, Quillen and Leibniz cohomologies are detected. The cases $P$ is
a free $\NP^{r}$ or $\NP^{l}$-algebra, the Hochschild or/and Leibniz
cohomological dimension of $P$ is $\leq n$ are considered separately,
exhibiting interesting possibilities of representations of the new cohomologies
by the well-known ones and relations between the corresponding cohomological
dimensions.


  Mixed-Criticality (MC) systems have recently been devised to address the
requirements of real-time systems in industrial applications, where the system
runs tasks with different criticality levels on a single platform. In some
workloads, a high-critically task might overrun and overload the system, or a
fault can occur during the execution. However, these systems must be
fault-tolerant and guarantee the correct execution of all high-criticality
tasks by their deadlines to avoid catastrophic consequences, in any situation.
Furthermore, in these MC systems, the peak power consumption of the system may
increase, especially in an overload situation and exceed the processor Thermal
Design Power (TDP) constraint. This may cause generating heat beyond the
cooling capacity, resulting the system stop to avoid excessive heat and halting
the processor. In this paper, we propose a technique for dependent
dual-criticality tasks in fault-tolerant multi-core MC systems to manage peak
power consumption and temperature. The technique develops a tree of possible
task mapping and scheduling at design-time to cover all possible scenarios and
reduce the low-criticality task drop rate in the high-criticality mode. At
run-time, the system exploits the tree to select a proper schedule according to
fault occurrences and criticality mode changes. Experimental results show that
the average task schedulability is 74.14% on average for the proposed method,
while the peak power consumption and maximum temperature are improved by 16.65%
and 14.9 C on average, respectively, compared to a recent work. In addition,
for a real-life application, our method reduces the peak power and maximum
temperature by up to 20.06% and 5 C, respectively, compared to a
state-of-the-art approach.


  In this paper we present the techniques for computing cosmological bounces in
polynomial $f(R)$ theories, whose order is more than two, for spatially flat
FLRW spacetime. In these cases the conformally connected Einstein frame shows
up multiple scalar potentials predicting various possibilities of cosmological
evolution in the Jordan frame where the $f(R)$ theory lives. We present a
reasonable way in which one can associate the various possible potentials in
the Einstein frame, for cubic $f(R)$ gravity, to the cosmological development
in the Jordan frame. The issue concerning the energy conditions in $f(R)$
theories is presented. We also point out the very important relationships
between the conformal transformations connecting the Jordan frame and the
Einstein frame and the various instabilities of $f(R)$ theory. All the
calculations are done for cubic $f(R)$ gravity but we hope the results are
sufficiently general for higher order polynomial gravity.


  We propose a set of benchmarks that specifically targets a major cause of
performance degradation in high performance computing platforms: irregular
access patterns. These benchmarks are meant to be used to asses the performance
of optimizing compilers on codes with a varying degree of irregular access. The
irregularity caused by the use of pointers and indirection arrays are a major
challenge for optimizing compilers. Codes containing such patterns are
notoriously hard to optimize but they have a huge impact on the performance of
modern architectures, which are under-utilized when encountering irregular
memory accesses. In this paper, a set of benchmarks is described that
explicitly measures the performance of kernels containing a variety of
different access patterns found in real world applications. By offering a
varying degree of complexity, we provide a platform for measuring the
effectiveness of transformations. The difference in complexity stems from a
difference in traversal patterns, the use of multiple indirections and control
flow statements. The kernels used cover a variety of different access patterns,
namely pointer traversals, indirection arrays, dynamic loop bounds and run-time
dependent if-conditions. The kernels are small enough to be fully understood
which makes this benchmark set very suitable for the evaluation of
restructuring transformations.


  Drug membrane interaction is a very significant bioprocess to consider in
drug discovery. Here, we propose a novel deep learning framework coined DMInet
to study drug-membrane interactions that leverages large-scale Martini
coarse-grained molecular simulations of permeation of drug-like molecules
across six different lipid membranes. The network of DMInet receives three
inputs, viz, the drug-like molecule, membrane type, and spatial distance across
membrane thickness, and predicts the potential of mean force with structural
resolution across the lipid membrane and membrane selectivity. Inheriting from
coarse-grained Martini representation of organic molecules and combined with
deep learning, DMInet has the potential for more accelerated high throughput
screening in drug discovery across a much larger chemical space than that can
be explored by physics-based simulations alone. Moreover, DMInet is highly
flexible in its nature and holds the possibilities for other properties
prediction without significant changes in the architecture. Last but not least,
the architecture of DMInet is general and can be applied to other membrane
problems involving permeation and selection.


  Continuous-time quantum walks and adiabatic quantum evolution are two general
techniques for quantum computing, both of which are described by Hamiltonians
that govern their evolutions by Schr\"odinger's equation. In the former, the
Hamiltonian is fixed, while in the latter, the Hamiltonian varies with time. As
a result, their formulations of Grover's algorithm evolve differently through
Hilbert space. We show that this difference is fundamental; they cannot be made
to evolve along each other's path without introducing structure more powerful
than the standard oracle for unstructured search. For an adiabatic quantum
evolution to evolve like the quantum walk search algorithm, it must interpolate
between three fixed Hamiltonians, one of which is complex and introduces
structure that is stronger than the oracle for unstructured search. Conversely,
for a quantum walk to evolve along the path of the adiabatic search algorithm,
it must be a chiral quantum walk on a weighted, directed star graph with
structure that is also stronger than the oracle for unstructured search. Thus
the two techniques, although similar in being described by Hamiltonians that
govern their evolution, compute by fundamentally irreconcilable means.


  We analyze the emission spectrum of a (fundamentally quantum) black hole in
the Kerr-Newman family by assuming a discretization of black hole geometry and
the holographic entropy-area relation. We demonstrate that, given the above
structure of black hole entropy, a macroscopic black hole always has
non-continuously separated mass states and therefore they descend down in
discrete manner. We evaluate the step size of the discrete spectrum, which
vanishes in the extremal limit, leading to a continuum spectrum as expected
from thermal nature of black holes. This further reveals an interesting
relation, in each class, between the dynamic and kinematic length scales for
all black holes belonging to the Kerr-Newman family, pointing towards a
possible universal character across the class, dependent only on black hole
mass. Further, we have presented the computation of maximum number of emitted
quanta from the black hole as well as an estimation of its lifetime. We also
argue the independence of these features from the presence of additional
spacetime dimensions.


  The reliability of information in participatory sensing (PS) systems largely
depends on the accuracy of the location of the participating users. However,
existing PS applications are not able to efficiently validate the position of
users in large-scale outdoor environments. In this paper, we present an
efficient and scalable Location Validation System (LVS) to secure PS systems
from location-spoofing attacks. In particular, the user location is verified
with the help of mobile WiFi hot spots (MHSs), which are users activating the
WiFi hotspot capability of their smartphones and accepting connections from
nearby users, thereby validating their position inside the sensing area. The
system also comprises a novel verification technique called Chains of Sight,
which tackles collusion-based attacks effectively. LVS also includes a
reputation-based algorithm that rules out sensing reports of location-spoofing
users. The feasibility and efficiency of the WiFi-based approach of LVS is
demonstrated by a set of indoor and outdoor experiments conducted using
off-the-shelf smartphones, while the energy-efficiency of LVS is demonstrated
by experiments using the Power Monitor energy tool. Finally, the security
properties of LVS are analyzed by simulation experiments. Results indicate that
the proposed LVS system is energy-efficient, applicable to most of the
practical PS scenarios, and efficiently secures existing PS systems from
location-spoofing attacks.


  Many current neural networks for medical imaging generalise poorly to data
unseen during training. Such behaviour can be caused by networks overfitting
easy-to-learn, or statistically dominant, features while disregarding other
potentially informative features. For example, indistinguishable differences in
the sharpness of the images from two different scanners can degrade the
performance of the network significantly. All neural networks intended for
clinical practice need to be robust to variation in data caused by differences
in imaging equipment, sample preparation and patient populations.
  To address these challenges, we evaluate the utility of spectral decoupling
as an implicit bias mitigation method. Spectral decoupling encourages the
neural network to learn more features by simply regularising the networks'
unnormalised prediction scores with an L2 penalty, thus having no added
computational costs.
  We show that spectral decoupling allows training neural networks on datasets
with strong spurious correlations and increases networks' robustness for data
distribution shifts. To validate our findings, we train networks with and
without spectral decoupling to detect prostate cancer tissue slides and
COVID-19 in chest radiographs. Networks trained with spectral decoupling
achieve up to 9.5 percent point higher performance on external datasets.
  Our results show that spectral decoupling helps with generalisation issues
associated with neural networks, and can be used to complement or replace
computationally expensive explicit bias mitigation methods, such as stain
normalization in histological images. We recommend using spectral decoupling as
an implicit bias mitigation method in any neural network intended for clinical
use.


  In this paper we give a description of the first order deformation space of a
regular embedding of reduced algebraic schemes. We compare our result with
results of Ran (in particular [Ran, Prop. 1.3]).


  In this paper, we propose two novel parallel hybrid methods for finding a
common element of the set of solutions of a finite family of generalized
equilibrium problems for monotone bifunctions $\left\{f_i\right\}_{i=1}^N$ and
$\alpha$ - inverse strongly monotone operators $\left\{A_i\right\}_{i=1}^N$ and
the set of common fixed points of a finite family of (asymptotically) $\kappa$-
strictly pseudocontractive mappings $\left\{S_j\right\}_{j=1}^M$ in Hilbert
spaces. The strong convergence theorems are established under the standard
assumptions imposed on equilibrium bifunctions and operators. A numerical
example is presented to illustrate the efficiency of the proposed parallel
methods.


  We carry out a numerical study on the dynamics of a single non-Brownian
flexible fiber in two-dimensional Couette flows at finite Reynolds numbers. We
employ the bead-spring model of flexible fibers to extend the fluid particle
dynamics (FPD) method that is originally developed for rigid particles in
viscous liquids. We implement the extended FPD method using a
multiple-relaxation-time (MRT) scheme of the lattice Boltzmann method (LBM).
The numerical scheme is validated firstly by a series of benchmark simulations
that involve liquid-solid coupling. The method is then used to study the
dynamics of flexible fibers in Couette flows. We only consider the highly
symmetric case where the fibers are placed on the symmetry center of Couette
flows and we focus on the effects of the fiber stiffness, the confinement
strength, and the finite Reynolds number (from 1 to 10). A diagram of the fiber
shape is obtained. For fibers under weak confinement and a small Reynolds
number, three distinct tumbling orbits have been identified. (1) Jeffery orbits
of rigid fibers. The fibers behave like rigid rods and tumble periodically
without any visible deformation. (2) S-turn orbits of slightly flexible fibers.
The fiber is bent to an S-shape and is straightened again when it orients to an
angle of around 45 degrees relative to the positive x direction. (3) S-coiled
orbits of fairly flexible fibers. The fiber is folded to an S-shape and tumbles
periodically and steadily without being straightened anymore during its
rotation. Moreover, the fiber tumbling is found to be hindered by increasing
either the Reynolds number or the confinement strength, or both.


  We present a declarative language, PP, for the high-level specification of
preferences between possible solutions (or trajectories) of a planning problem.
This novel language allows users to elegantly express non-trivial,
multi-dimensional preferences and priorities over such preferences. The
semantics of PP allows the identification of most preferred trajectories for a
given goal. We also provide an answer set programming implementation of
planning problems with PP preferences.


  Doubly charged Higgs bosons are predicted in many new physics models with an
extended Higgs sector that contains a Higgs triplet field. Current experimental
searches have been focusing mainly on the scenario in which the same-sign
dilepton decay modes are the dominant ones. We study the scenario where the
vacuum expectation value of the triplet field is sufficiently large so that the
associated charged Higgs bosons decay dominantly to a pair of weak gauge bosons
instead. A detailed simulation of the signal and the backgrounds is performed
for the CERN Large Hadron Collider at the collision energy of 8 TeV and 14 TeV.
We find that different cuts should be imposed for the events, depending on
whether the doubly charged Higgs boson mass is greater than about 200 GeV. In
the higher mass region, the forward jet tagging proves to be useful in
enhancing the signal significance. We show the discovery reach of the LHC
running at 8 and 14 TeV, with two benchmark triplet vacuum expectation values.
With an integrated luminosity of 10 fb${}^{-1}$ at 8 TeV, the doubly charged
Higgs boson with a mass of $\sim 180$ GeV can be tested at $5\sigma$ level in
such a scenario.


  Walrasian equilibrium is a prominent market equilibrium notion, but rarely
exists in markets with indivisible items. We introduce a new market equilibrium
notion, called two-price equilibrium (2PE). A 2PE is a relaxation of Walrasian
equilibrium, where instead of a single price per item, every item has two
prices: one for the item's owner and a (possibly) higher one for all other
buyers. Thus, a 2PE is given by a tuple
$(\textbf{S},\mathbf{\hat{p}},\mathbf{\check{p}})$ of an allocation
$\textbf{S}$ and two price vectors $\mathbf{\hat{p}},\mathbf{\check{p}}$, where
every buyer $i$ is maximally happy with her bundle $S_i$, given prices
$\mathbf{\check{p}}$ for items in $S_i$ and prices $\mathbf{\hat{p}}$ for all
other items. 2PE generalizes previous market equilibrium notions, such as
conditional equilibrium, and is related to relaxed equilibrium notions like
endowment equilibrium. We define the {\em discrepancy} of a 2PE -- a measure of
distance from Walrasian equilibrium -- as the sum of differences
$\hat{p}_j-\check{p}_j$ over all items (normalized by social welfare). We show
that the social welfare degrades gracefully with the discrepancy; namely, the
social welfare of a 2PE with discrepancy $d$ is at least a fraction
$\frac{1}{d+1}$ of the optimal welfare. We use this to establish welfare
guarantees for markets with subadditive valuations over identical items. In
particular, we show that every such market admits a 2PE with at least $1/7$ of
the optimal welfare. This is in contrast to Walrasian equilibrium or
conditional equilibrium which may not even exist. Our techniques provide new
insights regarding valuation functions over identical items, which we also use
to characterize instances that admit a WE.


  We propose a new reinforcement learning algorithm derived from a regularized
linear-programming formulation of optimal control in MDPs. The method is
closely related to the classic Relative Entropy Policy Search (REPS) algorithm
of Peters et al. (2010), with the key difference that our method introduces a
Q-function that enables efficient exact model-free implementation. The main
feature of our algorithm (called QREPS) is a convex loss function for policy
evaluation that serves as a theoretically sound alternative to the widely used
squared Bellman error. We provide a practical saddle-point optimization method
for minimizing this loss function and provide an error-propagation analysis
that relates the quality of the individual updates to the performance of the
output policy. Finally, we demonstrate the effectiveness of our method on a
range of benchmark problems.


  The HI Parkes All Sky Survey (HIPASS) galaxy catalogue is cross-correlated
with known low redshift, low column density (N_HI <10^15 cm^-2) Lyman-alpha
absorbers from the literature. The redshift-space correlation is found to be
similar in strength to HIPASS galaxy self-clustering (correlation length
s_0,ag=6+/-4 and s_0,gg=3.1+/-0.5 h^-1 Mpc respectively). In real-space the
cross-correlation is stronger than the galaxy auto-correlation (correlation
length r_0,ag=7.2+/-1.4 and r_0,gg=3.5+/-0.7 h^-1 Mpc respectively) on scales
from 1-10 h^-1 Mpc, ruling out the mini-halo model for the confinement
Lyman-alpha absorbers at the 99 percent confidence level. Provided that the
cause of the strong cross-correlation is purely gravitational, the ratio of
correlation lengths suggest that absorbers are embedded in dark matter haloes
with masses log(M/Msun)=14.2 h^-1, similar to those of galaxy groups. The
flattening of the cross-correlation at separations less than ~600 h^-1 kpc
could correspond to the thickness of filaments in which absorbers are embedded.
This work provides indirect statistical evidence for the notion that galaxy
groups and large-scale filaments, particularly those that comprise gas-rich
galaxies, are the dominant environments of low column density Lyman-alpha
absorbers at z=0.


  For a graph $G$ and a positive integer $k$, a vertex labelling
$f:V(G)\to\{1,2\ldots,k\}$ is said to be $k$-distinguishing if no non-trivial
automorphism of $G$ preserves the sets $f^{-1}(i)$ for each
$i\in\{1,\ldots,k\}$. The distinguishing chromatic number of a graph $G$,
denoted $\chi_D(G)$, is defined as the minimum $k$ such that there is a
$k$-distinguishing labelling of $V(G)$ which is also a proper coloring of the
vertices of $G$. In this paper, we prove the following theorem: Given
$k\in\mathbb{N}$, there exists an infinite sequence of vertex-transitive graphs
$G_{i}=(V_i,E_i)$ such that $\chi_D(G_i)>\chi(G_i)>k$ and
$|\mathrm{Aut}(G_i)|=O_k(|V_i|)$, where $\mathrm{Aut}(G_i)$ denotes the full
automorphism group of $G_i$. In particular, this answers a problem raised in
the paper $\chi_D(G)$, $|\mathrm{Aut}(G)|$ and a variant of the Motion lemma.


  ${\rm B - L}$ cosmic strings form in a wide class of theories beyond the
Standard Model which contain a ${\rm U}(1)_{{\rm B - L}}$ gauge symmetry. They
can form at the end of hybrid inflation and explain, together with inflation,
the Cosmic Microwave Background anisotropies and the formation of large scale
structure. They can produce Cold Dark Matter in the form of the Lightest
SuperParticle and they can be at the origin of the baryon asymmetry of our
universe. One major advantage of these mechanisms is that they are non-thermal.


  The paper is a survey of notions and results related to classical and new
generalizations of the notion of a periodic sequence. The topics related to
almost periodicity in combinatorics on words, symbolic dynamics, expressibility
in logical theories, algorithmic computability, Kolmogorov complexity, number
theory, are discussed.


  We consider Berry's random planar wave model (1977) for a positive Laplace
eigenvalue $E>0$, both in the real and complex case, and prove limit theorems
for the nodal statistics associated with a smooth compact domain, in the
high-energy limit ($E\to \infty$). Our main result is that both the nodal
length (real case) and the number of nodal intersections (complex case) verify
a Central Limit Theorem, which is in sharp contrast with the non-Gaussian
behaviour observed for real and complex arithmetic random waves on the flat
$2$-torus, see Marinucci et al. (2016) and Dalmao et al. (2016). Our findings
can be naturally reformulated in terms of the nodal statistics of a single
random wave restricted to a compact domain diverging to the whole plane. As
such, they can be fruitfully combined with the recent results by Canzani and
Hanin (2016), in order to show that, at any point of isotropic scaling and for
energy levels diverging sufficently fast, the nodal length of any Gaussian
pullback monochromatic wave verifies a central limit theorem with the same
scaling as Berry's model. As a remarkable byproduct of our analysis, we
rigorously confirm the asymptotic behaviour for the variances of the nodal
length and of the number of nodal intersections of isotropic random waves, as
derived in Berry (2002).


  The earlier article tried to construct an algorithm to compute the Heegaard
Floer homology \hat{HF}(Y) for a 3-manifold Y. However there is an error in a
proof which the author, as of now, is unable to fix.


  The acoustic neutrino detection technique is a promising approach for future
large-scale detectors with the aim of measuring the small expected flux of
neutrinos at energies in the EeV-range and above. The technique is based on the
thermo-acoustic model, which implies that the energy deposition by a particle
cascade - resulting from a neutrino interaction in a medium with suitable
thermal and acoustic properties - leads to a local heating and a subsequent
characteristic pressure pulse that propagates in the surrounding medium.
Current or recent test setups for acoustic neutrino detection have either been
add-ons to optical neutrino telescopes or have been using acoustic arrays built
for other purposes, typically for military use. While these arrays have been
too small to derive competitive limits on neutrino fluxes, they allowed for
detailed studies of the experimental technique. With the advent of the research
infrastructure KM3NeT in the Mediterranean Sea, new possibilities will arise
for acoustic neutrino detection. In this article, results from the "first
generation" of acoustic arrays will be summarized and implications for the
future of acoustic neutrino detection will be discussed.


  The Higgs mechanism, i.e., spontaneous symmetry breaking of the quantum
vacuum, is a cross-disciplinary principle, universal for understanding dark
energy, antimatter and quantum materials, from superconductivity to magnetism.
Yet, Higgs modes in one-band superconductors (SCs) are currently under debate
due to their competition with charge-density fluctuations. A distinct Higgs
mode, controllable by terahertz (THz) laser pulses, can arise in multi-band,
unconventional SCs via strong {\em interband} Coulomb interaction, but is yet
to be accessed. Here we both discover and demonstrate quantum control of such
collective mode in iron-based high-temperature superconductors. Using
two-pulse, phase coherent THz spectroscopy, we observe a tunable and coherent
2$\Delta_{\mathrm{SC}}$ amplitude oscillation of the complex order parameter in
such SC with coupled lower and upper bands. The nonlinear dependence of the
amplitude mode oscillations on the THz driving fields is distinct from any
one-band and conventional SC results: we observe a large nonlinear change of
resonance strength, yet with a persisting mode frequency. We argue that this
result provides compelling evidence for a transient coupling between the
electron and hole amplitude modes via strong interband coherent interaction. To
support this scenario, we perform quantum kinetic modeling of a hybrid Higgs
mechanism without invoking extra disorder or phonons. In addition to
distinguishing between collective modes and charge fluctuations, the light
quantum control of multiband SCs can be extended to probe and manipulate
many-body entanglement and hidden symmetries in different quantum materials.


  We analytically determine the correlation functions of the stochastic
response of a generic mapping system driven by colored noise. We also address
the issue of noise cascading in coupled-element systems, particularly in a
uni-directionally coupled system with dc-filtered coupling. A noise-feedback
method and an opposite-pairing method are introduced to control the stochastic
response. Excellent agreements are obtained between analytical results and
numerical simulations.


  This note reviews the progress on the low energy dynamics of N=2
supersymmetric Yang-Mills theories after the works of Seiberg and Witten.
Specifically, the theory of prepotential for non-specialists is reviewed.


  Ultrathin, solution-processed emerging solar cells with high power-per-weight
(PPW) outputs demonstrate unique potential for applications where low weight,
high power output, and flexibility are indispensable. The following perspective
explores the literature of emerging PVs and highlights the maximum reported PPW
values of Perovskite Solar Cells (PSCs) 29.4 W/g, Organic Solar Cells (OSCs)
32.07 W/g and Quantum Dot Solar Cells (QDSC) 15.02 W/g, respectively. The
record PPW values of OSCs and PSCs are approximately one order of magnitude
higher compared to their inorganic ultrathin solar cells counterparts (approx.
3.2 W/g for CIGS and a-Si). This consists emerging PVs, very attractive for a
variety of applications where the PPW is the key parameter. In particular, both
OSCs and PSCs can be implemented in different scenarios of applications (indoor
and biocompatible applications for OSCs and outdoor and high-energy radiation
conversion conditions for the PSCs) due to their unique optoelectronic and
physiochemical properties. Finally, our theoretical optical and electrical
simulation and optimization study for the most promising and well-suited PV
technologies, showed an impressive maximum realistic theoretical PPW limit of
74.3 and 93.7 W/g for PSCs and OSCs, respectively. Our finding shows that the
literature PSCs and OSCs towards high PPW outputs, is not quite close to the
theoretical maximum and thus more work needs to be done to further increase the
PPW output of these promising PV technologies.


  We investigate the boundedness and large time behavior of solutions of the
Cauchy-Dirichlet problem for the one-dimensional degenerate parabolic equation
with gradient nonlinearity: $$ u_t = (|u-x|^{p-2} u-x)_x+|u_x|^q \qquad
\text{in}\quad (0, +\infty)\tiles(0, 1),\qquad q > p > 2.$$
  We prove that: either $u_x$ blows up in finite time, or $u$ is global and
converges in $W^{1, \infty}$norm to the unique steady state. This in particular
eliminates the possibility of global solutions with unbounded gradient. For
that purpose a Lyapunov functional is constructed by the approach of Zelenyak.


  Locomotion in Virtual Reality (VR) is an important part of VR applications.
Many scientists are enriching the community with different variations that
enable locomotion in VR. Some of the most promising methods are gesture-based
and do not require additional handheld hardware. Recent work focused mostly on
user preference and performance of the different locomotion techniques. This
ignores the learning effect that users go through while new methods are being
explored. In this work, it is investigated whether and how quickly users can
adapt to a hand gesture-based locomotion system in VR. Four different
locomotion techniques are implemented and tested by participants. The goal of
this paper is twofold: First, it aims to encourage researchers to consider the
learning effect in their studies. Second, this study aims to provide insight
into the learning effect of users in gesture-based systems.


  In this paper we show the existence of approximate completely positive
semidefinite (cpsd) factorizations with a cpsd-rank bounded above (almost)
independently from the cpsd-rank of the initial matrix. This is particularly
relevant since the cpsd-rank of a matrix cannot, in general, be upper bounded
by a function only depending on its size. For this purpose, we make use of the
Approximate Caratheodory Theorem in order to construct an approximate matrix
with a low-rank Gram representation. We then employ the Johnson-Lindenstrauss
Lemma to improve to a logarithmic dependence of the cpsd-rank on the size.


  This paper addresses the optimal scheduling of the liquidation of a portfolio
using a new angle. Instead of focusing only on the scheduling aspect like
Almgren and Chriss, or only on the liquidity-consuming orders like Obizhaeva
and Wang, we link the optimal trade-schedule to the price of the limit orders
that have to be sent to the limit order book to optimally liquidate a
portfolio. Most practitioners address these two issues separately: they compute
an optimal trading curve and they then send orders to the markets to try to
follow it. The results obtained here solve simultaneously the two problems. As
in a previous paper that solved the "intra-day market making problem", the
interactions of limit orders with the market are modeled via a Poisson process
pegged to a diffusive "fair price" and a Hamilton-Jacobi-Bellman equation is
used to solve the problem involving both non-execution risk and price risk.
Backtests are carried out to exemplify the use of our results, both on long
periods of time (for the entire liquidation process) and on slices of 5 minutes
(to follow a given trading curve).


  We use the recently proposed directed-path algorithm to study the chiral
limit of strongly coupled lattice QCD with staggered quarks at finite
temperatures. The new algorithm allows us to compute the chiral susceptibility
and the pion decay constant accurately on large lattices for massless quarks.
In the low temperature phase we find clear evidence for the singularities
predicted by chiral perturbation theory. We also show convincingly that the
chiral phase transition is of second order and belongs to the O(2) universality
class.


  We constrain the space density and properties of massive galaxy candidates at
redshifts of z>=3.5 in the GOODS-N field. By selecting sources in the
Spitzer+IRAC bands, a highly stellar mass-complete sample is
assembled,including massive galaxies which are very faint in the
optical/near-IR bands that would be missed by samples selected at shorter
wavelengths. The z>=3.5 sample was selected down to 23 mag at 4.5 micron using
photometric redshifts that have been obtained by fitting the galaxies SEDs at
optical, near-IR and IRAC bands. We also require that the brightest band in
which candidates are detected is the IRAC 8 micron band in order to ensure that
the near-IR 1.6 micron (rest-frame) peak is falling in or beyond this band. We
found 53 z>=3.5 candidates, with masses in the range of M~10^10-10^11M_sun. At
least ~81% of these galaxies are missed by traditional Lyman Break selection
methods based on UV light. Spitzer+MIPS emission is detected for 60% of the
sample of z>=3.5 galaxy candidates. Although in some cases this might suggest a
residual contamination from lower redshift star-forming galaxies or AGN, 37% of
these objects are also detected in the sub-mm/mm bands in recent SCUBA,AzTEC
and MAMBO surveys, and have properties fully consistent with vigorous starburst
galaxies at z>=3.5. The comoving number density of galaxies with stellar masses
>= 5x10^10M_sun(a reasonable stellar mass completeness limit for our sample) is
2.6x10^-5Mpc^-3 (using the volume within 3.5<z<5), and the corresponding
stellar mass density is ~2.9x10^6M_sunMpc^-3, or~3% of the local density above
the same stellar mass limit.For the sub-sample of MIPS-undetected galaxies,we
find a number density of ~0.97x10^-5Mpc^-3 and a stellar mass density of
~1.15x10^6M_sun Mpc^-3.[abridged]


  For many physical systems the transition from a stationary solution to
sustained small amplitude oscillations corresponds to a Hopf bifurcation. For
systems involving impacts, thresholds, switches, or other abrupt events,
however, this transition can be achieved in fundamentally different ways. This
paper reviews 20 such `Hopf-like' bifurcations for two-dimensional ODE systems
with state-dependent switching rules. The bifurcations include boundary
equilibrium bifurcations, the collision or change of stability of equilibria or
folds on switching manifolds, and limit cycle creation via hysteresis or time
delay. In each case a stationary solution changes stability and possibly form,
and emits one limit cycle. Each bifurcation is analysed quantitatively in a
general setting: we identify quantities that govern the onset, criticality, and
genericity of the bifurcation, and determine scaling laws for the period and
amplitude of the resulting limit cycle. Complete derivations based on
asymptotic expansions of Poincare maps are provided. Many of these are new,
done previously only for piecewise-linear systems. The bifurcations are
collated and compared so that dynamical observations can be matched to
geometric mechanisms responsible for the creation of a limit cycle. The results
are illustrated with impact oscillators, relay control, automated balancing
control, predator-prey systems, ocean circulation, and the McKean and
Wilson-Cowan neuron models.


  We develop a theoretical proposal for the charge Kondo effect in mesoscopic
normal-superconductor-normal heterostructures, where the superconducting gap
exceeds the electrostatic charging energy. Charge-Kondo correlations in these
devices alter the conventional temperature-dependence of Andreev reflection and
electron cotunneling. We predict typical Kondo temperatures of $\gtrsim 10 {\rm
mK}$, and suggest experimental architectures that combine superconducting
charge-qubits with semiconducting nanowires at cryogenic temperatures.


  A Butson-Hadamard matrix H is a square matrix of dimension n whose entries
are complex roots of unity such that HH*= nI. In the first part of this work,
some new results on generalized Gray map are studied. In the second part, codes
obtained from Butson-Hadamard matrices and some bounds on the minimum distance
of these codes are proved. In particular, we show that the code obtained from a
Butson-Hadamard matrix meets the Plotkin bound under a non-homogeneous weight.
We also give the parameters of some code families which are obtained from
modified Butson-Hadamard matrices under a (non)homogeneous Gray map.


  The purpose of this study has extremely dedicated to exposing the correlation
between coronavirus pandemic and space observation on unhealthy air quality in
India. The world has undergone lockdown to break the chain of coronavirus
infection. The Air Quality Index (AQI) has started to improve after the
commencement of lockdown due to industrial and transportation sectors
temporally closed. This study compiled the data recently released by NASA
(National Aeronautics and Space Administration), ESA (European Space Agency),
and ISRO (Indian Space and Research Organization). In this paper, we have
discussed the space observation on Nitrogen Dioxide (NO2), Aerosol Optical
Depth (AOD), PM2.5, and PM10 influenced the air quality across the various
region of India. We analyzed the detoxing of air quality before and during the
lockdown period over the same time the frame of current and the previous year.
The result has shown a positive impact on the detoxing of unhealthy air quality
during lockdown stated as the emission of NO2 has reduced to 40% - 50% and
optical level of aerosol indexed at low compared to the last 20 years in
northern India.


  A two-field model of potential vorticity (PV) staircase structure and
dynamics relevant to both beta-plane and drift-wave plasma turbulence is
studied numerically and analytically. The model evolves averaged PV whose flux
is both driven by and regulates, a potential enstrophy field, $\varepsilon$.
The model employs a closure using a mixing length model. Its link to
bistability, vital to staircase generation, is analyzed and verified by
integrating the equations numerically. Long-time staircase evolution
consistently manifests a pattern of meta-stable quasi-periodic configurations,
lasting for hundreds of time units, yet interspersed with abrupt ($\Delta
t\ll1$) mergers of adjacent steps in the staircase. The mergers occur at the
staircase lattice defects where the pattern has not completely relaxed to a
strictly periodic solution that can be obtained analytically. Other types of
stationary solutions are solitons and kinks in the PV gradient and
$\varepsilon$ - profiles. The waiting time between mergers increases strongly
as the number of steps in the staircase decreases. This is because of an
exponential decrease in inter-step coupling strength with growing spacing. The
long-time staircase dynamics is shown numerically be determined by local
interaction with adjacent steps. Mergers reveal themselves through the
explosive growth of the turbulent PV-flux which, however, abruptly drops to its
global constant value once the merger is completed.


  We have designed and tested a parallel 8-bit ERSFQ arithmetic logic unit
(ALU). The ALU design employs wave-pipelined instruction execution and features
modular bit-slice architecture that is easily extendable to any number of bits
and adaptable to current recycling. A carry signal synchronized with an
asynchronous instruction propagation provides the wave-pipeline operation of
the ALU. The ALU instruction set consists of 14 arithmetical and logical
instructions. It has been designed and simulated for operation up to a 10 GHz
clock rate at the 10-kA/cm2 fabrication process. The ALU is embedded into a
shift-register-based high-frequency testbed with on-chip clock generator to
allow for comprehensive high frequency testing for all possible operands. The
8-bit ERSFQ ALU, comprising 6840 Josephson junctions, has been fabricated with
MIT Lincoln Lab 10-kA/cm2 SFQ5ee fabrication process featuring eight Nb wiring
layers and a high-kinetic inductance layer needed for ERSFQ technology. We
evaluated the bias margins for all instructions and various operands at both
low and high frequency clock. At low frequency, clock and all instruction
propagation through ALU were observed with bias margins of +/-11% and +/-9%,
respectively. Also at low speed, the ALU exhibited correct functionality for
all arithmetical and logical instructions with +/-6% bias margins. We tested
the 8-bit ALU for all instructions up to 2.8 GHz clock frequency.


  We give explicit bounds for Jordan constants of groups of birational
automorphisms of rationally connected threefolds over fields of zero
characteristic, in particular, for Cremona groups of ranks 2 and 3.


  As a newly discovered class of radio-loud active galactic nuclei (AGNs), the
\gamma-ray detected narrow-line Seyfert 1 galaxies (NLS1s) launch powerful jets
which are generally found only in blazars and radio galaxies. However, their
black hole (BH) masses as estimated from the broad emission lines are one order
of magnitude or more lower than those in blazars. This brings new challenges
for explaining the radio loudness triggering in AGNs. It is still under debate
whether their BH masses from the commonly used virial method are
underestimated. Here we present an estimate of the BH mass for the \gamma-ray
detected NLS1 1H 0323+342, an archetype of this class, from the X-ray
variability which is inclination independent. Our results independently confirm
that this \gamma-ray detected NLS1 harbors a $(2.8-7.9)\times10^6\,M_{\odot}$
BH similar to those in normal NLS1s rather than those in blazars.


  Natal supernova kicks, the linear momentum compact remnants receive during
their formation, are an essential part of binary population synthesis (BPS)
models. Although these kicks are well-supported by evidence, their underlying
distributions and incorporation into BPS models is uncertain. In this work, we
investigate the nature of natal kicks using a previously proposed analytical
prescription where the strength of the kick is given by
$v_\text{k}=\alpha\frac{m_\text{ejecta}}{m_\text{remnant}}+\beta~\text{km
s}^{-1}$, for free parameters $\alpha$ and $\beta$. We vary the free parameters
over large ranges of possible values, comparing these synthetic populations
simultaneously against four constraints: the merger rate of compact binary
neutron star (BNS) systems, the period-eccentricity distribution of galactic
BNSs, the velocity distribution of single-star pulsars, and the likelihood for
low-ejecta mass supernovae to produce low-velocity kicks. We find that
different samples of the parameter space satisfy each tests, and only 1 per
cent of the models satisfy all four constraints simultaneously. Although we
cannot identify a single best kick model, we report
$\alpha=115^{+40}_{-55}~\text{km s}^{-1}, \beta=15^{+10}_{-15}~\text{km
s}^{-1}$ as the center of the region of the parameter space that fulfils all of
our constraints, and expect $\beta\geq0~\text{km s}^{-1}$ as a further
constraint. We also suggest further observations that will enable future
refinement of the kick model. A sensitive test for the kick model will be the
redshift evolution of the BNS merger rate since this is effectively a direct
measure of the delay-time distribution for mergers. For our best fitting
values, we find that the peak of the BNS merger rate is the present-day.


  In this paper, we establish some Hadamard-type inequalities based on
coordinated quasi-convexity. Also we define a new mapping associated to
coordinated convexity and we prove some properties of this mapping.


  The main purpose of this macro-study is to shed light on the broad impact of
books. For this purpose, the impact of a very large collection of books has
been analyzed by using PlumX, an analytical tool providing a great number of
different metrics provided by various tools.


  Style is an important concept in today's challenges in natural language
generating. After the success in the field of image style transfer, the task of
text style transfer became actual and attractive. Researchers are also
interested in the tasks of style reproducing in generation of the poetic text.
Evaluation of style reproducing in natural poetry generation remains a problem.
I used 3 character-based LSTM-models to work with style reproducing assessment.
All three models were trained on the corpus of texts by famous Russian-speaking
poets. Samples were shown to the assessors and 4 answer options were offered,
the style of which poet this sample reproduces. In addition, the assessors were
asked how well they were familiar with the work of the poet they had named.
Students studying history of literature were the assessors, 94 answers were
received. It has appeared that accuracy of definition of style increases if the
assessor can quote the poet by heart. Each model showed at least 0.7
macro-average accuracy. The experiment showed that it is better to involve a
professional rather than a naive reader in the evaluation of style in the tasks
of poetry generation, while lstm models are good at reproducing the style of
Russian poets even on a limited training corpus.


  Spatially varying exposure (SVE) is a promising choice for high-dynamic-range
(HDR) imaging (HDRI). The SVE-based HDRI, which is called single-shot HDRI, is
an efficient solution to avoid ghosting artifacts. However, it is very
challenging to restore a full-resolution HDR image from a real-world image with
SVE because: a) only one-third of pixels with varying exposures are captured by
camera in a Bayer pattern, b) some of the captured pixels are over- and
under-exposed. For the former challenge, a spatially varying convolution (SVC)
is designed to process the Bayer images carried with varying exposures. For the
latter one, an exposure-guidance method is proposed against the interference
from over- and under-exposed pixels. Finally, a joint demosaicing and HDRI deep
learning framework is formalized to include the two novel components and to
realize an end-to-end single-shot HDRI. Experiments indicate that the proposed
end-to-end framework avoids the problem of cumulative errors and surpasses the
related state-of-the-art methods.


  We construct an algebra of generalized functions endowed with a canonical
embedding of the space of Schwartz distributions. We offer a solution to the
problem of multiplication of Schwartz distributions similar to but different
from Colombeau's solution. We show that the set of scalars of our algebra is an
algebraically closed field unlike its counterpart in Colombeau theory, which is
a ring with zero divisors. We prove a Hahn-Banach extension principle which
does not hold in Colombeau theory. We establish a connection between our theory
with non-standard analysis and thus answer, although indirectly, a question
raised by J.F. Colombeau. This article provides a bridge between Colombeau
theory of generalized functions and non-standard analysis.


  The fraction of heavy vector mesons produced in a heavy ion collision, as
compared to a proton proton collision, serves as an important indication of the
formation of a thermal medium, the quark gluon plasma. This sort of analysis
strongly depends on understanding the thermal effects of a medium like the
plasma on the states of heavy mesons. In particular, it is crucial to know the
temperature ranges where they undergo a thermal dissociation, or melting.
AdS/QCD models are know to provide an important tool for the calculation of
hadronic masses, but in general are not consistent with the observation that
decay constants of heavy vector mesons decrease with excitation level. It has
recently been shown that this problem can be overcome using a soft wall
background and introducing an extra energy parameter, through the calculation
of correlation functions at a finite position of anti-de Sitter space. This
approach leads to the evaluation of masses and decay constants of S wave
quarkonium states with just one flavor dependent and one flavor independent
parameters. Here we extend this more realistic model to finite temperatures and
analyse the thermal behavior of the states $1S, 2S$ and $ 3S$ of bottomonium
and charmonium. The corresponding spectral function exhibits a consistent
picture for the melting of the states where, for each flavor, the higher
excitations melt at lower temperatures. We estimate for these six states, the
energy ranges in which the heavy vector mesons undergo a transition from a well
defined peak in the spectral function to complete melting in the thermal
medium. A very clear distinction between the heavy flavors emerges, with
bottomonium state $\Upsilon (1S)$ surviving deconfinemet transition at
temperatures much larger than the critical deconfinement temperature of the
medium.


  The coherence properties of a gas of bosonic atoms above the BEC transition
temperature were studied. Bragg diffraction was used to create two spatially
separated wave packets, which interfere during expansion. Given sufficient
expansion time, high fringe contrast could be observed in a cloud of arbitrary
temperature. Fringe visibility greater than 90% was observed, which decreased
with increasing temperature, in agreement with a simple model. When the sample
was "filtered" in momentum space using long, velocity-selective Bragg pulses,
the contrast was significantly enhanced in contrast to predictions.


  The processes of radiation defects formation and evolution have been
simulated in cubic dielectric crystals by the computational method of cellular
automata. If suppose that the defects concentration as a parameter, which
characterizes a system state, reaches some critical value at the irradiation
process, in this case there would be collective effects in the system that lead
to self-organization phenomena and demonstrate a formation of one-type defect
clusters. The fractal theory is used to detect synergistic effects and
described the spatial and temporal transformation of defect structure in a
crystal.


  We consider an alternative to the usual spin glass paradigm for disordered
magnetism, consisting of the previously unstudied combination of frustrated
magnetic interactions and pseudo-dipolar disorder in spin positions. We argue
that this model represents a general limiting case for real systems as well as
a realistic model for certain binary fluorides and oxides. Furthermore, it is
of great relevance to the highly topical subjects of the Coulomb phase and
`charge ice'. We derive an analytical solution for the ground state phase
diagram of a model system constructed in this paradigm and identify magnetic
phases that remain either disordered or partially ordered even at zero
temperature. These phases are of a hitherto unobserved type, but may be broadly
classified as either `spin liquids' or `semi-spin liquids' in contrast to the
usual spin glass or semi-spin glass. Numerical simulations are used to show
that the spin liquid phase exhibits no spin glass transition at finite
temperature, despite the combination of frustration and disorder. By mapping
onto a model of uncoupled loops of Ising spins, we show that the magnetic
structure factor of this phase acts, in the limit $T\rightarrow0$, as a
sensitive probe of the positional disorder correlations. We suggest that this
result can be generalized to more complex systems, including experimental
realizations of canonical spin glass models.


  The $k$-means method is an iterative clustering algorithm which associates
each observation with one of $k$ clusters. It traditionally employs cluster
centers in the same space as the observed data. By relaxing this requirement,
it is possible to apply the $k$-means method to infinite dimensional problems,
for example multiple target tracking and smoothing problems in the presence of
unknown data association. Via a $\Gamma$-convergence argument, the associated
optimization problem is shown to converge in the sense that both the $k$-means
minimum and minimizers converge in the large data limit to quantities which
depend upon the observed data only through its distribution. The theory is
supplemented with two examples to demonstrate the range of problems now
accessible by the $k$-means method. The first example combines a non-parametric
smoothing problem with unknown data association. The second addresses tracking
using sparse data from a network of passive sensors.


  Linear stability analysis has proven to be a useful tool in the analysis of
dominant coherent structures, such as the von K\'{a}rm\'{a}n vortex street and
the global spiral mode associated with the vortex breakdown of swirling jets.
In recent years, linear stability analysis has been applied successfully to
turbulent time-mean flows, instead of laminar base-flows,
\textcolor{black}{which requires turbulent models that account for the
interaction of the turbulent field with the coherent structures. To retain the
stability equations of laminar flows, the Boussinesq approximation with a
spatially nonuniform but isotropic eddy viscosity is typically employed. In
this work we assess the applicability of this concept to turbulent strongly
swirling jets, a class of flows that is particularly unsuited for isotropic
eddy viscosity models. Indeed we find that unsteady RANS simulations only match
with experiments with a Reynolds stress model that accounts for an anisotropic
eddy viscosity. However, linear stability analysis of the mean flow is shown to
accurately predict the global mode growth rate and frequency if the employed
isotropic eddy viscosity represents a least-squares approximation of the
anisotropic eddy viscosity. Viscosities derived from the $k-\epsilon$ model did
not achieve a good prediction of the mean flow nor did they allow for accurate
stability calculations. We conclude from this study that linear stability
analysis can be accurate for flows with strongly anisotropic turbulent
viscosity and the capability of the Boussinesq approximation in terms of
URANS-based mean flow prediction is not a prerequisite.


  This is the sequel of the recent work (Du, Huang, Pu, Commun. Math. Phys,
2023, doi: 10.1007/s00220-023-04651-7) on axially symmetric gravity water waves
with general vorticities, which has investigated the singular wave profile of
the free boundary near the degenerate points. In this companion paper, we are
interested in the regularity of the free surface of the water wave near the
non-degenerate point. Precisely, we showed that the free boundary is
$C^{1,\gamma}$ smooth for some $\gamma\in(0,1)$ near all non-degenerate points.
The problem is intrinsically intertwined with the regularity theory of the
semilinear Bernoulli-type free boundary problem. Our approach is closely
related to the monotonicity formula developed by Weiss in his celebrated work
(Weiss, J. Geom. Anal. 9: 317-326, 1999), and to a partial boundary Harnack
inequality for the one-phase free boundary problem, which is dedicated to De
Silva (De Silva, Interfaces Free Bound. 13, 223-238, 2011). Mathematically, we
associate the existence of viscosity solutions with the Weiss boundary-adjusted
energy. Compared to the classical approach of Caffarelli (Caffarelli, Ann.
Scuola Norm. Sup. Pisa, 15, 583-602, 1988), we provide an alternative proof of
the existence of viscosity solutions for a large class of semilinear free
boundary problems.


  The double pulsar system PSR J0737-3039A/B is a highly relativistic double
neutron star (DNS) binary, with a 2.4-hour orbital period. The low mass of the
second-formed NS, as well the low system eccentricity and proper motion, point
to a different evolutionary scenario compared to other known DNS systems. We
describe analysis of the pulse profile shape over 6 years of observations, and
present the resulting constraints on the system geometry. We find the recycled
pulsar in this system, PSR J0737-3039A, to have a low misalignment between its
spin and orbital angular momentum axes, with a 68.3% upper limit of 6.1
degrees, assuming emission from both magnetic poles. This tight constraint
lends credence to the idea that the supernova that formed the second pulsar was
relatively symmetric, possibly involving electron-capture onto an O-Ne-Mg core.


  Even though Pulsar Timing Arrays already have the potential to detect the
gravitational wave background by finding a quadrupole correlation in the timing
residuals, this goal has not yet been achieved. Motivated by some theoretical
arguments, we analyzed some advantages of including the millisecond pulsars
within globular clusters, especially those in their cores, in current and
future Pulsar Timing Array projects for detecting the gravitational waves
emitted by an ensemble of supermassive black holes.


  Topological swirling spin textures, such as skyrmions and merons, have
recently attracted much attention as a unique building block for high-density
magnetic information devices. The controlled transformation among different
types of such quasi-particles is an important challenge, while it was
previously achieved only in a few non-centrosymmetric systems characterized by
Dzyaloshinskii-Moriya interaction. Here, we report an experimental discovery of
multi-step topological transitions among a variety of meron and skyrmion
crystal states in a centrosymmetric magnet GdRu$_2$Ge$_2$. By performing the
detailed magnetic structure analysis based on resonant X-ray and neutron
scattering experiments as well as electron transport measurements, we have
found that this compound hosts periodic lattice of elliptic skyrmions,
meron/anti-meron pairs, and circular skyrmions as a function of external
magnetic field. The diameter of these objects is as small as 2.7 nm, which is
almost two orders of magnitude smaller than typical non-centrosymmetric
magnets. Such an intricate manner of topological magnetic transitions are well
reproduced by a theoretical model considering the competition between RKKY
interactions at inequivalent wave vectors. The present findings demonstrate
that even a simple centrosymmetric magnet with competing interactions can be a
promising material platform to realize a richer variety of nanometric magnetic
quasi-particles with distinctive symmetry and topology, whose stability may be
tunable by various external stimuli.