  Recent scanning tunnelling microscopy (STM) experiments on underdoped
cuprates have displayed modulations in the local electronic density of states
which are centered on a Cu-O-Cu bond (Kohsaka et. al., cond-mat/0703309). As a
paradigm of the pinning of such bond-centered ordering in strongly correlated
systems, we present the theory of valence bond solid (VBS) correlations near a
single impurity in a square lattice antiferromagnet. The antiferromagnet is
assumed to be in the vicinity of a quantum transition from a magnetically
ordered Neel state to a spin-gap state with long-range VBS order. We identify
two distinct classes of impurities: i) local modulation in the exchange
constants, and ii) a missing or additional spin, for which the impurity
perturbation is represented by an uncompensated Berry phase. The `boundary'
critical theory for these classes is developed: in the second class we find a
`VBS pinwheel' around the impurity, accompanied by a suppression in the VBS
susceptibility. Implications for numerical studies of quantum antiferromagnets
and for STM experiments on the cuprates are noted.


  Conditions in the protosolar nebula have left their mark in the composition
of cometary volatiles, thought to be some of the most pristine material in the
solar system. Cometary compositions represent the end point of processing that
began in the parent molecular cloud core and continued through the collapse of
that core to form the protosun and the solar nebula, and finally during the
evolution of the solar nebula itself as the cometary bodies were accreting.
Disentangling the effects of the various epochs on the final composition of a
comet is complicated. But comets are not the only source of information about
the solar nebula. Protostellar disks around young stars similar to the protosun
provide a way of investigating the evolution of disks similar to the solar
nebula while they are in the process of evolving to form their own solar
systems. In this way we can learn about the physical and chemical conditions
under which comets formed, and about the types of dynamical processing that
shaped the solar system we see today.
  This paper summarizes some recent contributions to our understanding of both
cometary volatiles and the composition, structure and evolution of protostellar
disks.


  Ni-based superalloy Inconel-718 is ubiquitous in metal 3D printing where high
cooling rate and thermal gradient are present. These manufacturing conditions
are conducive to high initial dislocation density and porosity or void in the
material. This work proposes a molecular dynamics (MD) analysis method that can
examine the role of dislocations, cooling rates, void, and their interactions
governing the material properties and failure mechanism in Inconel-718 using
Embedded Atom Method (EAM) potential. Three different structures: nanowire
(NW), nanopillar, and nanoplate are used throughout this work. Initially,
strain rates are varied from 10^8s^-1 to 10^10s^-1 keeping the NW diameter and
temperature constant at 3.17 nm and 300K respectively. Compressive loading is
applied to a 7.04 nm nanopillar by applying a constant strain rate of 109 s^-1
while temperature is varied from 100K to 700K. Different cooling rates ranging
from 0.5x10^10 K/s to 1 x 10^14 K/s are applied to nanoplates (with and without
a central void). The size of the central void is kept fixed at 2.12 nm.
Increasing strain rates in tension not only results in strain hardening but
also increase in dislocation density. Our computational method is successful to
capture extensive sliding on {111} shear plane, which leads to significant
necking of the alloy before fracture due to dislocation. The high cooling rates
creating non-equilibrium structure leads to high strength and ductile behavior.
On the other hand, the low cooling rate forming well defined crystalline
structure causes low strength and brittle behavior. This brittle to ductile
transition is observed solely due to cooling rate. Cooling rate may diminish
the void by healing the structure during solidifications process. Subsequent
mechanical properties by varying temperature and size are also presented in
detail.


  Spontaneous nuclear ortho-para transitions are shown to be possible in
hydrogen molecule and molecular ion as due to hyperfine interaction odd-odd
relative to the space or spin nuclear coordinate permutations. A part of this
interaction inversely proportional to the first power of nuclear mass is found
for hydrogen molecular ion.


  Applied magnetic field induces metal - insulator and re-entrant
insulator-metal transitions in both graphite and rhombohedral bismuth. The
corresponding transition boundaries plotted on the magnetic field - temperature
(B - T) plane nearly coincide for these semimetals and can be best described by
power laws T ~ (B - B_c)^k, where B_c is a critical field at T = 0 and k = 0.45
+/- 0.05. We show that insulator-metal-insulator (I-M-I) transformations take
place in the Landau level quantization regime and illustrate how the IMT in
quasi-3D graphite transforms into a cascade of I-M-I transitions, related to
the quantum Hall effect in quasi-2D graphite samples. We discuss the possible
coupling of superconducting and excitonic correlations with the observed
phenomena, as well as the signatures of quantum phase transitions associated
with the M-I and I-M transformations.


  There is a long-standing experimental observation that the melting of
topologically constrained DNA, such as circular-closed plasmids, is less abrupt
than that of linear molecules. This finding points to an intriguing role of
topology in the physics of DNA denaturation, which is however poorly
understood. Here, we shed light on this issue by combining large-scale Brownian
Dynamics simulations with an analytically solvable phenomenological Landau mean
field theory. We find that the competition between melting and supercoiling
leads to phase coexistence of denatured and intact phases at the single
molecule level. This coexistence occurs in a wide temperature range, thereby
accounting for the broadening of the transition. Finally, our simulations show
an intriguing topology-dependent scaling law governing the growth of
denaturation bubbles in supercoiled plasmids, which can be understood within
the proposed mean field theory.


  The purpose of this paper consists in proposing a generalized solution for a
porous media type equation on a half-line with Neumann boundary condition and
prove a probabilistic representation of this solution in terms of an associated
microscopic diffusion. The main idea is to construct a stochastic differential
equation with reflection which has a solution in law and whose marginal law
densities provide the unique solution of the porous media type equation.


  We introduce the task of action-driven stochastic human motion prediction,
which aims to predict multiple plausible future motions given a sequence of
action labels and a short motion history. This differs from existing works,
which predict motions that either do not respect any specific action category,
or follow a single action label. In particular, addressing this task requires
tackling two challenges: The transitions between the different actions must be
smooth; the length of the predicted motion depends on the action sequence and
varies significantly across samples. As we cannot realistically expect training
data to cover sufficiently diverse action transitions and motion lengths, we
propose an effective training strategy consisting of combining multiple motions
from different actions and introducing a weak form of supervision to encourage
smooth transitions. We then design a VAE-based model conditioned on both the
observed motion and the action label sequence, allowing us to generate multiple
plausible future motions of varying length. We illustrate the generality of our
approach by exploring its use with two different temporal encoding models,
namely RNNs and Transformers. Our approach outperforms baseline models
constructed by adapting state-of-the-art single action-conditioned motion
generation methods and stochastic human motion prediction approaches to our new
task of action-driven stochastic motion prediction. Our code is available at
https://github.com/wei-mao-2019/WAT.


  The rapid advancement of artificial intelligence (AI) has brought significant
challenges to the education and workforce skills required to take advantage of
AI for human-AI collaboration in the workplace. As AI continues to reshape
industries and job markets, the need to define how AI literacy can be
considered in lifelong learning has become increasingly critical (Cetindamar et
al., 2022; Laupichler et al., 2022; Romero et al., 2023). Like any new
technology, AI is the subject of both hopes and fears, and what it entails
today presents major challenges (Cugurullo \& Acheampong, 2023; Villani et al.,
2018). It also raises profound questions about our own humanity. Will the
machine surpass the intelligence of the humans who designed it? What will be
the relationship between so-called AI and our human intelligences? How could
human-AI collaboration be regulated in a way that serves the Sustainable
Development Goals (SDGs)? This paper provides a review of the challenges of
lifelong learning in the era of AI from a computational thinking, critical
thinking, and creative competencies perspective, highlighting the implications
for management and leadership in organizations.


  We describe an experiment dedicated to the study of the trajectories of a
ball bouncing randomly on a vibrating plate. The system was originally used,
considering a sinusoidal vibration, to illustrate period doubling and the route
to chaos. Our experimental device makes it possible to impose, to the plate,
arbitrary trajectories and not only sinusoidal or random, as is generally the
case. We show that the entire trajectory of the ball can still be reconstructed
from the measurement of the collisions times. First, we make use of the
experimental system to introduce the notion of dissipative collisions and to
propose three different ways to measure the associated restitution coefficient.
Then, we report on correlations in the chaotic regime and discuss theoretically
the complex pattern which they exhibit in the case of a sinusoidal vibration.
At last, we show that the use of an aperiodic motion makes it possible to get
rid of part of the correlations and to discuss theoretically the average energy
of the ball in the chaotic regime.


  We study a family of quadratic stochastic differential equations in the
plane, motivated by applications to turbulent transport of heavy particles.
Using Lyapunov functions, we find a critical parameter value
$\alpha_{1}=\alpha_{2}$ such that when $\alpha_{2}>\alpha_{1}$ the system is
ergodic and when $\alpha_{2}<\alpha_{1}$ solutions are not defined for all
times. H\"{o}rmander's hypoellipticity theorem and geometric control theory are
also utilized.


  We present Sounding Board, a social chatbot that won the 2017 Amazon Alexa
Prize. The system architecture consists of several components including spoken
language processing, dialogue management, language generation, and content
management, with emphasis on user-centric and content-driven design. We also
share insights gained from large-scale online logs based on 160,000
conversations with real-world users.


  Glitches in the rotational frequency of a spinning neutron star could be
promising sources of gravitational wave signals lasting between a few
microseconds to a few weeks. The emitted signals and their properties depend
upon the internal properties of the neutron star. In neutron stars, the most
important physical properties of the fluid core are the viscosity of the fluid,
the stratification of flow in the equilibrium state and the adiabatic sound
speed. Such models were previously studied by van Eysden and Melatos [73] and
Bennett et al. [26] following simple assumptions on all contributing factors,
in which the post-glitch relaxation phase could be driven by the well-known
process of Ekman pumping [76, 17]. We explore the hydrodynamic properties of
the flow of fluid during this phase following more relaxed assumptions on the
stratification of flow and the pressure-density gradients within the neutron
star than previously studied. We calculate the time-scales of duration as well
as the amplitudes of the resulting gravitational wave signals, and we detail
their dependence on the physical properties of the fluid core. We find that it
is possible for the neutron star to emit gravitational wave signals in a wide
range of decay time-scales and within the detection sensitivity of aLIGO for
selected domains of physical parameters.


  I review the early development of Aperture Arrays and their role in radio
astronomy. The demise of this technology at the end of the 1960's, and the
reasons for the rise of parabolic dishes is also considered. The parallels with
the Antikythera mechanism (see these proceedings) as a lost technology are
briefly presented. Aperture Arrays re-entered the world of radio astronomy as
the idea to build a huge radio telescope with a collecting area of one square
kilometre (the Square Kilometre Array, SKA) arose. Huge ICT technology advances
had transformed Aperture Arrays in terms of their capability, flexibility and
reliability. In the mid-1990s, ASTRON started to develop and experiment with
the first high frequency aperture array tiles for radio astronomy - AAD, OSMA,
THEA & EMBRACE. In the slipstream of these efforts, Phased Array Feeds (PAFs)
for radio astronomy were invented and LOFAR itself emerged as a next generation
telescope and a major pathfinder for the SKA. Meanwhile, the same advantages
that aperture arrays offered to radio astronomy had already made dishes
obsolete in many different civilian and military applications. The first
commissioning results from LOFAR and other Aperture Arrays (MWA, LWA and PAPER)
currently demonstrate that this kind of technology can transform radio
astronomy over 2 decades of the radio spectrum, and at frequencies up to at
least 1.5 GHz. This "reinvention of radio astronomy" has important implications
for the design and form of the full SKA. Building a SKA that is simply the "VLA
on steroids" is simply not good enough. Like the Antikythera mechanism itself,
we must amaze future generations of astronomers - they and the current
generation deserve nothing less.


  In this article we take a probabilistic look at H\"older's inequality,
considering the ratio of terms in the classical H\"older inequality for random
vectors in $\mathbb{R}^n$. We prove a central limit theorem for this ratio,
which then allows us to reverse the inequality up to a multiplicative constant
with high probability. The models of randomness include the uniform
distribution on $\ell_p^n$ balls and spheres. We also provide a Berry-Esseen
type result and prove a large and a moderate deviation principle for the
suitably normalized H\"older ratio.


  We introduce Cayley posets as posets arising naturally from pairs $S<T$ of
semigroups, much in the same way that Cayley graph arises from a (semi)group
and a subset. We show that Cayley posets are a common generalization of several
known classes of posets, e.g. posets of numerical semigroups (with torsion) and
more generally affine semigroups. Furthermore, we give Sabidussi-type
characterizations for Cayley posets and for several subclasses in terms of
their endomorphism monoid. We show that large classes of posets are Cayley
posets, e.g., series-parallel posets and (generalizations of)
join-semilattices, but also provide examples of posets which cannot be
represented this way. Finally, we characterize (locally finite, with a finite
number of atoms) auto-equivalent posets - a class that generalizes a recently
introduced notion for numerical semigroups - as those posets coming from a
finitely generated submonoid of an abelian group.


  As machine learning models grow more complex and their applications become
more high-stakes, tools for explaining model predictions have become
increasingly important. This has spurred a flurry of research in model
explainability and has given rise to feature attribution methods such as LIME
and SHAP. Despite their widespread use, evaluating and comparing different
feature attribution methods remains challenging: evaluations ideally require
human studies, and empirical evaluation metrics are often data-intensive or
computationally prohibitive on real-world datasets. In this work, we address
this issue by releasing XAI-Bench: a suite of synthetic datasets along with a
library for benchmarking feature attribution algorithms. Unlike real-world
datasets, synthetic datasets allow the efficient computation of conditional
expected values that are needed to evaluate ground-truth Shapley values and
other metrics. The synthetic datasets we release offer a wide variety of
parameters that can be configured to simulate real-world data. We demonstrate
the power of our library by benchmarking popular explainability techniques
across several evaluation metrics and across a variety of settings. The
versatility and efficiency of our library will help researchers bring their
explainability methods from development to deployment. Our code is available at
https://github.com/abacusai/xai-bench.


  For any state in a $D$-dimensional Hilbert space with a choice of basis, one
can define a discrete version of the Wigner function -- a quasi-probability
distribution which represents the state on a discrete phase space. The Wigner
function can, in general, take on negative values, and the amount of negativity
in the Wigner function has an operational meaning as a resource for quantum
computation. In this note, we study the growth of Wigner negativity for a
generic initial state under time evolution with chaotic Hamiltonians. We
introduce the Krylov-Wigner function, i.e., the Wigner function defined with
respect to the Krylov basis (with appropriate phases), and show that this
choice of basis minimizes the early time growth of Wigner negativity in the
large $D$ limit. We take this as evidence that the Krylov basis (with
appropriate phases) is ideally suited for a dual, semi-classical description of
chaotic quantum dynamics at large $D$. We also numerically study the time
evolution of the Krylov-Wigner function and its negativity in random matrix
theory for an initial pure state. We observe that the negativity broadly shows
three phases: it rises gradually for a time of $O(\sqrt{D})$, then hits a sharp
ramp and finally saturates close to its upper bound of $\sqrt{D}$.


  We generalize a theorem of Tate and show that the second cohomology of the
Weil group of a global or local field with coefficients in $\C^*$ (or more
generally, with coefficients in the complex points of a tori over $\C$) vanish,
where the cohomology groups are defined using measurable cochains in the sense
of Moore. We recover a theorem of Labesse proving that admissible homomorphisms
of a Weil group to the Langlands dual of a reductive group can be lifted to an
extension of the Langlands dual group by a tori.


  Quantum phase transition occurs at a quantum critical value of a control
parameter such as the magnetic field in the Ising model in a transverse
magnetic field (ITF). Recently, it is shown that ramping across the quantum
critical point generates non-analytic behaviors in the time evolution of a
closed quantum system in the thermodynamic limit at zero temperature. The
mentioned phenomenon is called the dynamical quantum phase transition (DQPT).
Here, we consider the one-dimensional (1D) ITF model with added the
Dzyaloshinskii-Moriya interaction (DMI). Using the fermionization technique,
the Hamiltonian is exactly diagonalized. Although the DM interaction induces
chiral phase in the ground state phase diagram of the model, the study of the
rate function of the return probability has proven that the DMI does not affect
in the DQPT. We conclude accordingly that the ramping across the quantum
critical point is not a necessary and sufficient condition for DQPT.


  The connectivity aspect of connected autonomous vehicles (CAV) is beneficial
because it facilitates dissemination of traffic-related information to vehicles
through Vehicle-to-External (V2X) communication. Onboard sensing equipment
including LiDAR and camera can reasonably characterize the traffic environment
in the immediate locality of the CAV. However, their performance is limited by
their sensor range (SR). On the other hand, longer-range information is helpful
for characterizing imminent conditions downstream. By contemporaneously
coalescing the short- and long-range information, the CAV can construct
comprehensively its surrounding environment and thereby facilitate informed,
safe, and effective movement planning in the short-term (local decisions
including lane change) and long-term (route choice). In this paper, we describe
a Deep Reinforcement Learning based approach that integrates the data collected
through sensing and connectivity capabilities from other vehicles located in
the proximity of the CAV and from those located further downstream, and we use
the fused data to guide lane changing, a specific context of CAV operations. In
addition, recognizing the importance of the connectivity range (CR) to the
performance of not only the algorithm but also of the vehicle in the actual
driving environment, the paper carried out a case study. The case study
demonstrates the application of the proposed algorithm and duly identifies the
appropriate CR for each level of prevailing traffic density. It is expected
that implementation of the algorithm in CAVs can enhance the safety and
mobility associated with CAV driving operations. From a general perspective,
its implementation can provide guidance to connectivity equipment manufacturers
and CAV operators, regarding the default CR settings for CAVs or the
recommended CR setting in a given traffic environment.


  In several fields of Physics, Chemistry and Ecology, some models are
described by Liouville systems. In this article we first prove a uniqueness
result for a Liouville system in $\mathbb R^2$. Then we establish an uniform
estimate for bubbling solutions of a locally defined Liouville system near an
isolated blowup point. The uniqueness result, as well as the local uniform
estimates are crucial ingredients for obtaining a priori estimate, degree
counting formulas and existence results for Liouville systems defined on
Riemann surfaces.


  In this paper, we present TESS photometry and high-resolution spectra of the
short-period Algol EW Boo. We obtained double-lined radial velocities (RVs)
from the time-series spectra and measured the effective temperature of the
primary star as $T_{\rm{eff,1}}$ = 8560 $\pm$ 118 K. For the orbital period
study, we collected all times of minima available for over the last 30 years.
It was found that the eclipse timing variation of the system could be
represented by a periodic oscillation of 17.6 $\pm$ 0.3 years with a
semi-amplitude of 0.0041 $\pm$ 0.0001 d. The orbital and physical parameters
were derived by simultaneously analyzing the TESS light and RV curves using the
Wilson-Devinney (WD) binary star modeling code. The component masses and radii
were showed over 3% precision: $M_{1}$ = 2.67 $\pm $ 0.08 M$_{\odot}$, $M_{2}$
= 0.43 $\pm $ 0.01 M$_{\odot}$, $R_{1}$ = 2.01 $\pm $ 0.02 R$_{\odot}$, and
$R_{2}$ = 1.35 $\pm $ 0.01 R$_{\odot}$. Furthermore, multiple frequency
analyses were performed for the light-curve residuals from the WD model. As a
result, we detected 17 pressure-mode pulsations in the region of 40.15 - 52.37
d$^{-1}$. The absolute dimensions and pulsation characteristics showed that the
$\delta$ Sct pulsator was the more massive and hotter primary star of the EW
Boo.


  This paper presents a study of the performance of the muon reconstruction in
the analysis of proton-proton collisions at $\sqrt{s}$=7 TeV at the LHC,
recorded by the ATLAS detector in 2010. This performance is described in terms
of reconstruction and isolation efficiencies and momentum resolutions for
different classes of reconstructed muons. The results are obtained from an
analysis of J/$\psi$ meson and Z boson decays to dimuons, reconstructed from a
data sample corresponding to an integrated luminosity of 40~$pb^{-1}$. The
measured performance is compared to Monte Carlo predictions and deviations from
the predicted performance are discussed.


  As it has been unveiled that pre-trained language models (PLMs) are to some
extent capable of recognizing syntactic concepts in natural language, much
effort has been made to develop a method for extracting complete (binary)
parses from PLMs without training separate parsers. We improve upon this
paradigm by proposing a novel chart-based method and an effective top-K
ensemble technique. Moreover, we demonstrate that we can broaden the scope of
application of the approach into multilingual settings. Specifically, we show
that by applying our method on multilingual PLMs, it becomes possible to induce
non-trivial parses for sentences from nine languages in an integrated and
language-agnostic manner, attaining performance superior or comparable to that
of unsupervised PCFGs. We also verify that our approach is robust to
cross-lingual transfer. Finally, we provide analyses on the inner workings of
our method. For instance, we discover universal attention heads which are
consistently sensitive to syntactic information irrespective of the input
language.


  Using the ambitwistor string, we compute tree-level celestial amplitudes for
biadjoint scalars, Yang-Mills and gravity to all multiplicities. They are
presented in compact CHY-like formulas with operator-valued scattering
equations and numerators acting on a generalized hypergeometric function. With
these we extend the celestial double copy to tree-level amplitudes with
arbitrary number of external states. We also show how color-kinematics duality
is implemented in celestial amplitudes and its interpretation in terms of a
generalized twisted cohomology theory.


  Small object detection (SOD) in optical images and videos is a challenging
problem that even state-of-the-art generic object detection methods fail to
accurately localize and identify such objects. Typically, small objects appear
in real-world due to large camera-object distance. Because small objects occupy
only a small area in the input image (e.g., less than 10%), the information
extracted from such a small area is not always rich enough to support decision
making. Multidisciplinary strategies are being developed by researchers working
at the interface of deep learning and computer vision to enhance the
performance of SOD deep learning based methods. In this paper, we provide a
comprehensive review of over 160 research papers published between 2017 and
2022 in order to survey this growing subject. This paper summarizes the
existing literature and provide a taxonomy that illustrates the broad picture
of current research. We investigate how to improve the performance of small
object detection in maritime environments, where increasing performance is
critical. By establishing a connection between generic and maritime SOD
research, future directions have been identified. In addition, the popular
datasets that have been used for SOD for generic and maritime applications are
discussed, and also well-known evaluation metrics for the state-of-the-art
methods on some of the datasets are provided.


  For an effective AdS theory, we present a simple prescription to compute the
renormalization of its dual boundary field theory. In particular, we define
anomalous dimension holographically as the dependence of the wave-function
renormalization factor on the radial cutoff in the Poincare patch of AdS. With
this definition, the anomalous dimensions of both single- and double- trace
operators are calculated. Three different dualities are considered with the
field theory being CFT, CFT with a double-trace deformation and spontaneously
broken CFT. For the second dual pair, we compute scaling corrections at the UV
and IR fixed points of the RG flow triggered by the double-trace deformation.
For the last case, we discuss whether our prescription is sensitive to the AdS
interior or equivalently, the IR physics of the dual field theory.


  This paper evaluates the performance of multi-user massive multiple-input
multiple-output (MIMO) systems in which the base station is equipped with a
dynamic metasurface antenna (DMA). Due to the physical implementation of DMAs,
conventional models widely-used in MIMO are no longer valid, and
electromagnetic phenomena such as mutual coupling, insertion losses and
reflections inside the waveguides need to be considered. Hence, starting from a
recently proposed electromagnetic model for DMAs, we formulate a zero-forcing
optimization problem, yielding an unconstrained objective function with known
gradient. The performance is compared with that of full-digital and hybrid
massive MIMO, focusing on the impact of insertion losses and mutual coupling.


  Radiopure materials for detector components in rare event searches may be
contaminated after manufacturing with long-lived $^{210}$Pb produced by the
decay of atmospheric radon. Charged radon daughters deposited on the surface or
implanted in the bulk of detector materials have the potential to cause
noticeable backgrounds within dark matter regions of interest. Understanding
the mechanics governing these background signals is therefore a paramount
concern in dark matter experiments in order to distinguish a real signal from
internal detector backgrounds. Teflon ($i.e.$ PTFE) is a specific material of
interest because it makes up the walls of the inner detector of many liquid
noble detectors such as the LUX-ZEPLIN experiment. The rate of radon daughter
plate-out onto Teflon can be orders of magnitude larger than the plate-out rate
onto other materials. Mitigation of plate-out onto Teflon and steel by
proximity to other materials is demonstrated.


  Let $X$ be a complex manifold, $\pi: E \rightarrow X$ a locally trivial
holomorphic fibration with fiber $F$, and $\mathfrak{g}$ a Lie algebra with an
invariant symmetric form. We associate to this data a holomorphic
prefactorization algebra $\mathcal{F}_{\mathfrak{g}, \pi}$ on $X$ in the
formalism of Costello-Gwilliam. When $X=\mathbb{C}$, $\mathfrak{g}$ is simple,
and $F$ is a smooth affine variety, we extract from $\mathcal{F}_{\mathfrak{g},
\pi}$ a vertex algebra which is a vacuum module for the universal central
extension of the Lie algebra $\mathfrak{g} \otimes H^{0}(F,
\mathcal{O})[z,z^{-1}]$. As a special case, when $F$ is an algebraic torus
$(\mathbb{C}^{*})^n$, we obtain a vertex algebra naturally associated to an
$(n+1)$--toroidal algebra, generalizing the affine vacuum module.


  Despite recent advances, large scale visual artifacts are still a common
occurrence in images generated by GANs. Previous work has focused on improving
the generator's capability to accurately imitate the data distribution
$p_{data}$. In this paper, we instead explore methods that enable GANs to
actively avoid errors by manipulating the input space. The core idea is to
apply small changes to each noise vector in order to shift them away from areas
in the input space that tend to result in errors. We derive three different
architectures from that idea. The main one of these consists of a simple
residual module that leads to significantly less visual artifacts, while only
slightly decreasing diversity. The module is trivial to add to existing GANs
and costs almost zero computation and memory.


  We analyze the relation between the emission radii of twin kilohertz
quasi-periodic oscillations (kHz QPOs) and the co-rotation radii of the 12
neutron star low mass X-ray binaries (NS-LMXBs) which are simultaneously
detected with the twin kHz QPOs and NS spins. We find that the average
co-rotation radius of these sources is r_co about 32 km, and all the emission
positions of twin kHz QPOs lie inside the corotation radii, indicating that the
twin kHz QPOs are formed in the spin-up process. It is noticed that the upper
frequency of twin kHz QPOs is higher than NS spin frequency by > 10%, which may
account for a critical velocity difference between the Keplerian motion of
accretion matter and NS spin that is corresponding to the production of twin
kHz QPOs. In addition, we also find that about 83% of twin kHz QPOs cluster
around the radius range of 15-20 km, which may be affected by the hard surface
or the local strong magnetic field of NS. As a special case, SAX J1808.4-3658
shows the larger emission radii of twin kHz QPOs of r about 21-24 km, which may
be due to its low accretion rate or small measured NS mass (< 1.4 solar mass).


  A photon's observed wavelength tells an astronomical detector about the
amount of position information obtained by observing that photon. This amount
of position information may depend on time in a way which, to first order over
distances small compared to the size of the universe, might account for the
cosmological redshift.


  Moir\'e superlattices of two-dimensional (2D) materials with a small twist
angle are thought to exhibit appreciable flexoelectric effect, though
unambiguous confirmation of their flexoelectricity is challenging due to
artifacts associated with commonly used piezoresponse force microscopy (PFM).
For example, unexpectedly small phase contrast ($\sim$$8^{\circ}$) between
opposite flexoelectric polarizations was reported in twisted bilayer graphene
(tBG), though theoretically predicted value is $180^{\circ}$. Here we developed
a methodology to extract intrinsic moir\'e flexoelectricity using twisted
double bilayer graphene (tDBG) as a model system, probed by lateral PFM. For
small twist angle samples, we found that a vectorial decomposition is essential
to recover the small intrinsic flexoelectric response at domain walls from a
large background signal. The obtained three-fold symmetry of commensurate
domains with significant flexoelectric response at domain walls is fully
consistent with our theoretical calculations. Incommensurate domains in tDBG
with relatively large twist angles can also be observed by this technique. Our
work provides a general strategy for unraveling intrinsic flexoelectricity in
van der Waals moir\'e superlattices while providing insights into engineered
symmetry breaking in centrosymmetric materials.


  We study the compressible Euler equations in the isentropic nozzle flow. The
global existence of an $L^{\infty}$ solution has been proved in (Tsuge in
Nonlinear Anal. Real World Appl. 209: 217-238 (2017)) for large data and
general nozzle. However, unfortunately, this solution does not possess
finiteness of energy. Although the modified Godunov scheme is introduced in
this paper, we cannot deduce the energy inequality for the approximate
solutions. Therefore, our aim in the present paper is to derive the energy
inequality for an $L^{\infty}$ solution. To do this, we introduce the modified
Lax Friedrichs scheme, which has a recurrence formula consisting of discretized
approximate solutions. We shall first deduce from the formula the energy
inequality. Next, applying the compensated compactness method, the approximate
solution converges to a weak solution. The energy inequality also holds for the
solution as the limit. As a result, since our solutions are $L^{\infty}$, they
possess finite energy and propagation, which are essential to physics.


  Using high--sensitivity radon (Rn-222) portable detectors (passive electronic
devices of the type RADIM3), the airborne Rn-222 concentration in the interior
of various Cypriot buildings and dwellings was measured. For each preselected
building and dwelling, a calibrated detector was put into a closed room, and
the Rn-222 concentration was registered in sampling intervals of 2 to 4 hours
for a total counting time of typically 48 hours. Rn-222 activity concentrations
were found to be in the range of 6.2 to 102.8 Bq/m**3, with an overall
arithmetic mean value of (19.3 +- 14.7) Bq/m**3. This value is by a factor of
two below the world average (population-weighted) value of 39 Bq/m**3. The
total annual effective dose equivalent to the Cypriot population was calculated
to be between 0.16 and 2.6 mSv with an overall arithmetic mean value of (0.49
+- 0.37) mSv.


  We present a detailed spectroscopic analysis of 61 low mass white dwarfs and
provide precise atmospheric parameters, masses, and updated binary system
parameters based on our new model atmosphere grids and the most recent
evolutionary model calculations. For the first time, we measure systematic
abundances of He, Ca and Mg for metal-rich extremely low mass white dwarfs and
examine the distribution of these abundances as a function of effective
temperature and mass. Based on our preliminary results, we discuss the
possibility that shell flashes may be responsible for the presence of the
observed He and metals. We compare stellar radii derived from our spectroscopic
analysis to model-independent measurements and find good agreement except for
those white dwarfs with Teff < 10,000 K. We also calculate the expected
gravitational wave strain for each system and discuss their significance to the
eLISA space-borne gravitational wave observatory. Finally, we provide an update
on the instability strip of extremely low mass white dwarf pulsators.


  Context. Ceres is the most massive body of the asteroid belt and contains
about 25 wt.% (weight percent) of water. Understanding its thermal evolution
and assessing its current state are major goals of the Dawn Mission.
Constraints on internal structure can be inferred from various observations.
Especially, detailed knowledge of the rotational motion can help constrain the
mass distribution inside the body, which in turn can lead to information on its
geophysical history. Aims. We investigate the signature of the interior on the
rotational motion of Ceres and discuss possible future measurements performed
by the spacecraft Dawn that will help to constrain Ceres' internal structure.
Methods. We compute the polar motion, precession-nutation, and length-of-day
variations. We estimate the amplitudes of the rigid and non-rigid response for
these various motions for models of Ceres interior constrained by recent shape
data and surface properties. Results. As a general result, the amplitudes of
oscillations in the rotation appear to be small, and their determination from
spaceborne techniques will be challenging. For example, the amplitudes of the
semi-annual and annual nutations are around ~364 and ~140 milli-arcseconds, and
they show little variation within the parametric space of interior models
envisioned for Ceres. This, combined with the very long-period of the
precession motion, requires very precise measurements. We also estimate the
timescale for Ceres' orientation to relax to a generalized Cassini State, and
we find that the tidal dissipation within that object was probably too small to
drive any significant damping of its obliquity since formation. However,
combining the shape and gravity observations by Dawn offers the prospect to
identify departures of non-hydrostaticity at the global and regional scale,
which will be instrumental in constraining Ceres' past and current thermal
state. We also discuss the existence of a possible Chandler mode in the
rotational motion of Ceres, whose potential excitation by endogenic and/or
exogenic processes may help detect the presence of liquid reservoirs within the
asteroid.


  Evolutionary techniques driven by behavioural diversity, such as novelty
search, have shown significant potential in evolutionary robotics. These
techniques rely on priorly specified behaviour characterisations to estimate
the similarity between individuals. Characterisations are typically defined in
an ad hoc manner based on the experimenter's intuition and knowledge about the
task. Alternatively, generic characterisations based on the sensor-effector
values of the agents are used. In this paper, we propose a novel approach that
allows for systematic derivation of behaviour characterisations for
evolutionary robotics, based on a formal description of the agents and their
environment. Systematically derived behaviour characterisations (SDBCs) go
beyond generic characterisations in that they can contain task-specific
features related to the internal state of the agents, environmental features,
and relations between them. We evaluate SDBCs with novelty search in three
simulated collective robotics tasks. Our results show that SDBCs yield a
performance comparable to the task-specific characterisations, in terms of both
solution quality and behaviour space exploration.


  A new $H(\textrm{divdiv})$-conforming finite element is presented, which
avoids the need for super-smoothness by redistributing the degrees of freedom
to edges and faces. This leads to a hybridizable mixed method with
superconvergence for the biharmonic equation. Moreover, new finite element
divdiv complexes are established. Finally, new weak Galerkin and $C^0$
discontinuous Galerkin methods for the biharmonic equation are derived.


  In this paper, we present a novel siamese motion-aware network (SiamMan) for
visual tracking, which consists of the siamese feature extraction subnetwork,
followed by the classification, regression, and localization branches in
parallel. The classification branch is used to distinguish the foreground from
background, and the regression branch is adopt to regress the bounding box of
target. To reduce the impact of manually designed anchor boxes to adapt to
different target motion patterns, we design the localization branch, which aims
to coarsely localize the target to help the regression branch to generate
accurate results. Meanwhile, we introduce the global context module into the
localization branch to capture long-range dependency for more robustness in
large displacement of target. In addition, we design a multi-scale learnable
attention module to guide these three branches to exploit discriminative
features for better performance. The whole network is trained offline in an
end-to-end fashion with large-scale image pairs using the standard SGD
algorithm with back-propagation. Extensive experiments on five challenging
benchmarks, i.e., VOT2016, VOT2018, OTB100, UAV123 and LTB35, demonstrate that
SiamMan achieves leading accuracy with high efficiency. Code can be found at
https://isrc.iscas.ac.cn/gitlab/research/siamman.


  We present the results of a search for nuclear X-ray activity in nearby
galaxies using Chandra archival data in a sample of 62 galaxies from the
Spitzer Infrared Nearby Galaxy Survey (SINGS). We detect 37 nuclear X-ray
sources; seven of these are new detections. Most of the nuclear X-ray sources
are likely to be AGNs. The fraction of galaxies hosting AGNs is thus about 60%,
much higher than that found with optical searches, and demonstrates the
efficacy of X-ray observations to find hidden AGNs in optically normal
galaxies. We find that the nuclear X-ray sources are preferentially present in
earlier type galaxies. Unlike what is observed at high redshift, we do not find
a strong correlation between the AGN luminosity and the 24 micron luminosity of
the host galaxy; we find a strong correlation with the 3.6 micron luminosity
instead. This suggests that at the present epoch the accretion rate depends on
the total mass of the galaxy, as perhaps does the black hole mass.


  We consider spontaneous symmetry breaking transitions of strongly interacting
two-dimensional Dirac fermions minimally coupled to mass and emergent gauge
field order parameters. Using a renormalization group analysis, we show that
the presence of gauge fields leads to novel fermion induced quantum
(multi-)criticality where the putative emergent Lorentz invariance is violated.
We illustrate this with the example of translational symmetry breaking due to
charge-density wave order on the honeycomb lattice. Finally, we identify that
topological phase transitions are well described by this effective field
theory.


  We apply the methods of algebraic reliability to the study of percolation on
trees. To a complete $k$-ary tree $T_{k,n}$ of depth $n$ we assign a monomial
ideal $I_{k,n}$ on $\sum_{i=1}^n k^i$ variables and $k^n$ minimal monomial
generators. We give explicit recursive formulae for the Betti numbers of
$I_{k,n}$ and their Hilbert series, which allow us to study explicitly
percolation on $T_{k,n}$. We study bounds on this percolation and study its
asymptotical behavior with the mentioned commutative algebra techniques.


  We study the three-body charmed baryonic decays $\bar{B}^0\to\Sigma_c^{++}
\bar{p}\pi^-$ and $\bar{B}^0\to\Sigma_c^{0}\bar{p}\pi^+$ in the four-body final
state $\bar{B}^0\to\Lambda_c^{+}\bar{p}\pi^+\pi^-$, using a data sample of 357
fb$^{-1}$ accumulated at the $\Upsilon(4S)$ resonance with the Belle detector
at the KEKB asymmetric-energy $e^+e^-$ collider. We measure the branching
fractions ${\cal B}
(\bar{B}^0\to\Sigma_c(2455)^{++}\bar{p}\pi^-)$=$(2.1\pm0.2\pm0.3\pm0.5)\times
10^{-4}$, ${\cal
B}(\bar{B}^0\to\Sigma_c(2455)^{0}\bar{p}\pi^+)$=$(1.4\pm0.2\pm0.2\pm0.4)\times1
0^{-4}$, ${\cal B}(\bar{B}^0\to\Sigma_c(2520)^{++}
\bar{p}\pi^-)$=$(1.2\pm\0.1\pm0.2\pm0.3)\times10^{-4}$ with statistical
significances of 13.1, 9.5 and 7.2 standard deviations, respectively. The
errors are statistical, systematic, and due to the uncertainty in ${\cal
B}(\Lambda_c^+\to{p}K^-\pi^+)$, respectively. We also set an upper limit ${\cal
B}(\bar{B}^0\to\Sigma_c(2520)^{0}\bar{p}\pi^+)<0.38\times10^{-4}$ at the 90%
confidence level. In addition, we obtain a non-resonant branching fraction of
$(6.4\pm0.4\pm\0.9\pm1.7)\times10^{-4}$, and a total branching fraction of
$(11.2\pm0.5\pm1.4\pm2.9)\times10^{-4}$ for
$\bar{B}^0\to\Lambda_c^{+}\bar{p}\pi^+\pi^-$.


  The results of the AMS01 experiment are reviewed. The proton flux measured
below the geomagnetic cutoff is interpreted. Some Physics prospects for AMS02
on the International Space Station are outlined.


  Co-infecting parasites and pathogens remain a leading challenge for global
public health due to their consequences for individual-level infection risk and
disease progression. However, a clear understanding of the population-level
consequences of co-infection is lacking. Here, we constructed a model that
includes three individual-level effects of co-infection: mortality, fecundity,
and transmission. We used the model to investigate how these individual-level
consequences of co-infection scale up to produce population-level infection
patterns. To parameterize this model, we conducted a four-year cohort study in
African buffalo to estimate the individual-level effects of co-infection with
two bacterial pathogens, bovine tuberculosis (BTB) and brucellosis, across a
range of demographic and environmental contexts. At the individual-level, our
empirical results identified BTB as a risk factor for acquiring brucellosis,
but we found no association between brucellosis and the risk of acquiring BTB.
Both infections were associated with reductions in survival and neither
infection was associated with reductions in fecundity. Results of the model
reproduce co-infection patterns in the data and predict opposite impacts of
co-infection at individual and population scales: whereas BTB facilitated
brucellosis infection at the individual-level, our model predicts the presence
of brucellosis to have a strong negative impact on BTB at the population-level.
In modeled populations where brucellosis is present, the endemic prevalence and
basic reproduction number (Ro) of BTB were lower than in populations without
brucellosis. Therefore, these results provide a data-driven example of
competition between co-infecting pathogens that occurs when one pathogen
facilitates secondary infections at the individual level.


  This short talk summarizes some important issues relevant to a new Minkowski
space formulation of nonperturbative contributions to quantum scattering.
Details may be found in hep-ph/9403353. (To appear in Proceedings of 1994 NATO
Advanced Research Workshop)


  We define the topological Dirac equation describing the evolution of a
topological wave function on networks or on simplicial complexes. On networks,
the topological wave function describes the dynamics of topological signals or
cochains, i.e. dynamical signals defined both on nodes and on links. On
simplicial complexes the wave function is also defined on higher-dimensional
simplices. Therefore the topological wave function satisfies a relaxed
condition of locality as it acquires the same value along simplices of
dimension larger than zero. The topological Dirac equation defines eigenstates
whose dispersion relation is determined by the spectral properties of the Dirac
(or chiral) operator defined on networks and generalized network structures
including simplicial complexes and multiplex networks. On simplicial complexes
the Dirac equation leads to multiple energy bands. On multiplex networks the
topological Dirac equation can be generalized to distinguish between different
mutlilinks leading to a natural definition of rotations of the topological
spinor. The topological Dirac equation is here initially formulated on a
spatial network or simplicial complex for describing the evolution of the
topological wave function in continuous time. This framework is also extended
to treat the topological Dirac equation on $1+d$ spaces describing a discrete
space-time with one temporal dimension and $d$ spatial dimensions with $d\in
\{1,2,3\}$. This work includes also the discussion of numerical results
obtained by implementing the topological Dirac equation on simplicial complex
models and on real simple and multiplex network data.


  We present results from an all-sky search for unmodeled gravitational-wave
bursts in the data collected by the LIGO, GEO 600 and Virgo detectors between
November 2006 and October 2007. The search is performed by three different
analysis algorithms over the frequency band 50-6000 Hz. Data are analyzed for
times with at least two of the four LIGO-Virgo detectors in coincident
operation, with a total live time of 266 days. No events produced by the search
algorithms survive the selection cuts. We set a frequentist upper limit on the
rate of gravitational-wave bursts impinging on our network of detectors. When
combined with the previous LIGO search of the data collected between November
2005 and November 2006, the upper limit on the rate of detectable
gravitational-wave bursts in the 64-2048 Hz band is 2.0 events per year at 90%
confidence. We also present event rate versus strength exclusion plots for
several types of plausible burst waveforms. The sensitivity of the combined
search is expressed in terms of the root-sum-squared strain amplitude for a
variety of simulated waveforms and lies in the range 6x10^-22 1/sqrt(Hz) to
2x10^-20 1/sqrt(Hz). This is the first untriggered burst search to use data
from the LIGO and Virgo detectors together, and the most sensitive untriggered
burst search performed so far.


  A $\vee$-complement of a subgroup $H \leqslant \mathbb{F}_n$ is a subgroup $K
\leqslant \mathbb{F}_n$ such that $H \vee K = \mathbb{F}_n$. If we also ask $K$
to have trivial intersection with $H$, then we say that $K$ is a
$\oplus$-complement of $H$. The minimum possible rank of a $\vee$-complement
(resp. $\oplus$-complement) of $H$ is called the $\vee$-corank (resp.
$\oplus$-corank) of $H$. We use Stallings automata to study these notions and
the relations between them. In particular, we characterize when complements
exist, compute the $\vee$-corank, and provide language-theoretical descriptions
of the sets of cyclic complements. Finally, we prove that the two notions of
corank coincide on subgroups that admit cyclic complements of both kinds.


  We estimate the relative likelihood of success in the searches for primitive
versus intelligent life on other planets. Taking into account the larger search
volume for detectable artificial electromagnetic signals, we conclude that both
searches should be performed concurrently, albeit with significantly more
funding dedicated to primitive life. Based on the current federal funding
allocated to the search for biosignatures, our analysis suggests that the
search for extraterrestrial intelligence (SETI) may merit a federal funding
level of at least $\$10$ million per year, assuming that the average lifetime
of technological species exceeds a millennium.


  Monolayer transition metal dichalcogenides (TMDC) grown by chemical vapor
deposition (CVD) are plagued by a significantly lower optical quality compared
to exfoliated TMDC. In this work we show that the optical quality of CVD-grown
MoSe$_2$ is completely recovered if the material is sandwiched in
MoS$_2$/MoSe$_2$/MoS$_2$ trilayer van der Waals heterostructures. We show by
means of density-functional theory that this remarkable and unexpected result
is due to defect healing: S atoms of the more reactive MoS$_2$ layers are
donated to heal Se vacancy defects in the middle MoSe$_2$ layer. In addition,
the trilayer structure exhibits a considerable charge-transfer mediated valley
polarization of MoSe$_2$ without the need for resonant excitation. Our
fabrication approach, relying solely on simple flake transfer technique, paves
the way for the scalable production of large-area TMDC materials with excellent
optical quality.


  A simple model for the dust media describing evolution of the system like
spiral galaxy is considered. In contrast to previous considerations we show
that the initial density fold should be quasi-one-dimensional (bar-like)
instead of disc-like. The disc component of the galaxies appears only during
the evolution. The model naturally reproduces some essential features of the
galaxies. In particular, it reproduces all the observed typical forms of the
rotation curves for the spiral galaxies with a characteristic minimum and
plateau. It appears that the plateau corresponds to escaping the matter
(external spiral arms, due to initial conditions, have too large velocities to
be confined by the gravitational field of the galaxy). Such a scenario of the
galaxy evolution leads to the conclusion that the hypothesis of the dark matter
is not necessary (at least, for the spiral galaxies).


  This paper presents a new methodology for clustering multivariate time series
leveraging optimal transport between copulas. Copulas are used to encode both
(i) intra-dependence of a multivariate time series, and (ii) inter-dependence
between two time series. Then, optimal copula transport allows us to define two
distances between multivariate time series: (i) one for measuring
intra-dependence dissimilarity, (ii) another one for measuring inter-dependence
dissimilarity based on a new multivariate dependence coefficient which is
robust to noise, deterministic, and which can target specified dependencies.


  We present consistent optimization for single stage object detection.
Previous works of single stage object detectors usually rely on the regular,
dense sampled anchors to generate hypothesis for the optimization of the model.
Through an examination of the behavior of the detector, we observe that the
misalignment between the optimization target and inference configurations has
hindered the performance improvement. We propose to bride this gap by
consistent optimization, which is an extension of the traditional single stage
detector's optimization strategy. Consistent optimization focuses on matching
the training hypotheses and the inference quality by utilizing of the refined
anchors during training. To evaluate its effectiveness, we conduct various
design choices based on the state-of-the-art RetinaNet detector. We demonstrate
it is the consistent optimization, not the architecture design, that yields the
performance boosts. Consistent optimization is nearly cost-free, and achieves
stable performance gains independent of the model capacities or input scales.
Specifically, utilizing consistent optimization improves RetinaNet from 39.1 AP
to 40.1 AP on COCO dataset without any bells or whistles, which surpasses the
accuracy of all existing state-of-the-art one-stage detectors when adopting
ResNet-101 as backbone. The code will be made available.


  Meetings typically involve multiple participants and lengthy conversations,
resulting in redundant and trivial content. To overcome these challenges, we
propose a two-step framework, Reconstruct before Summarize (RbS), for effective
and efficient meeting summarization. RbS first leverages a self-supervised
paradigm to annotate essential contents by reconstructing the meeting
transcripts. Secondly, we propose a relative positional bucketing (RPB)
algorithm to equip (conventional) summarization models to generate the summary.
Despite the additional reconstruction process, our proposed RPB significantly
compressed the input, leading to faster processing and reduced memory
consumption compared to traditional summarization methods. We validate the
effectiveness and efficiency of our method through extensive evaluations and
analysis. On two meeting summarization datasets, AMI and ICSI, our approach
outperforms previous state-of-the-art approaches without relying on large-scale
pre-training or expert-grade annotating tools.


  In this paper we survey some finiteness results of the deformation classes of
hyperk\"ahler Lagrangian fibrations, and we prove finiteness for stable
Lagrangian fibrations with a given discriminant divisor.


  LoRa lacks the sensing capabilities of channel status. Received signal
strength indicator (RSSI) decreases due to collision, interference, and
near-far effect while for signal-to-noise ratio (SNR), the packets are rejected
by decreasing the transmission power (TP) at a higher spreading factor (SF). To
overcome these challenges in the case of electric shelf label (ESL) to minimize
the dependency on retransmission and acknowledgment, the end devices (EDs) are
allocated around gateways (GWs) based on machine clustering with dynamic SF for
SNR while dynamic TP for RSSI. The experimental results determined that the
RSSI approach is more dominant than SNR because of determining the exact
locality of the ED that diminished the capture effect. Arithmetic distribution
of EDs for various GWs in different clusters helps to minify the near-far
effect. The resultant received power (RP) at each cluster is higher for most of
the connected EDs than the threshold RP.


  In some parameter and solution regimes, a minimally coupled nonrelativistic
quantum particle in 1d is isomorphic to a much heavier, vibrating, very thin
Euler-Bernoulli rod in 3d, with ratio of bending modulus to linear density
$(\hbar/2m)^2$. For $m=m_e$, this quantity is comparable to that of a
microtubule. Axial forces and torques applied to the rod play the role of
scalar and vector potentials, respectively, and rod inextensibility plays the
role of normalization. We show how an uncertainty principle $\Delta x\Delta
p_x\gtrsim\hbar$ governs transverse deformations propagating down the
inextensible, force and torque-free rod, and how orbital angular momentum
quantized in units of $\hbar$ or $\hbar/2$ (depending on calculation method)
emerges when the force and torque-free inextensible rod is formed into a ring.
For torqued rings with large wavenumbers, a ``twist quantum'' appears that is
somewhat analogous to the magnetic flux quantum. These and other results are
obtained from a purely classical treatment of the rod, i.e., without quantizing
any classical fields.


  The parquet decomposition of the self-energy into classes of diagrams, those
associated with specific scattering processes, can be exploited for different
scopes. In this work, the parquet decomposition is used to unravel the
underlying physics of non-perturbative numerical calculations. We show the
specific example of dynamical mean field theory (DMFT) and its cluster
extensions (DCA) applied to the Hubbard model at half-filling and with hole
doping: These techniques allow for a simultaneous determination of two-particle
vertex functions and self-energies, and hence, for an essentially "exact"
parquet decomposition at the single-site or at the cluster level. Our
calculations show that the self-energies in the underdoped regime are dominated
by spin scattering processes, consistent with the conclusions obtained by means
of the fluctuation diagnostics approach [Phys. Rev. Lett. 114, 236402 (2015)].
However, differently from the latter approach, the parquet procedure displays
important changes with increasing interaction: Even for relatively moderate
couplings, well before the Mott transition, singularities appear in different
terms, with the notable exception of the predominant spin-channel. We explain
precisely how these singularities, which partly limit the utility of the
parquet decomposition, and - more generally - of parquet-based algorithms, are
never found in the fluctuation diagnostics procedure. Finally, by a more
refined analysis, we link the occurrence of the parquet singularities in our
calculations to a progressive suppression of charge fluctuations and the
formation of an RVB state, which are typical hallmarks of a pseudogap state in
DCA.


  The widely used nonrelativistic QCD (NRQCD) factorization theory now
encounters some notable difficulties in describing quarkonium production. This
may be due to the inadequate treatment of soft hadrons emitted in the
hadronization process, which causes bad convergence of velocity expansion in
NRQCD. In this paper, starting from QCD we propose a rigorously defined
factorization approach, soft gluon factorization (SGF), to better deal with the
effects of soft hadrons. After a careful velocity expansion, the SGF can be as
simple as the NRQCD factorization in phenomenological studies, but has a much
better convergence. The SGF may provide a new insight to understand the
mechanisms of quarkonium production and decay.


  The behavior of small samples in very short and intense hard x-ray pulses is
studied by molecular dynamics type calculations. The main emphasis is put on
the effect of various tamper layers about the sample. This is discussed from
the point of view of structural imaging of single particles, including not only
the distortion of the structure but also the background conditions. A detailed
picture is given about the Coulomb explosion, with explanation of the tampering
mechanism. It is shown that a thin water layer is efficient in slowing down the
distortion of the atomic structure, but it gives a significant contribution to
the background.


  We revisit Hopcroft's problem and related fundamental problems about
geometric range searching. Given $n$ points and $n$ lines in the plane, we show
how to count the number of point-line incidence pairs or the number of
point-above-line pairs in $O(n^{4/3})$ time, which matches the conjectured
lower bound and improves the best previous time bound of
$n^{4/3}2^{O(\log^*n)}$ obtained almost 30 years ago by Matou\v{s}ek.
  We describe two interesting and different ways to achieve the result: the
first is randomized and uses a new 2D version of fractional cascading for
arrangements of lines; the second is deterministic and uses decision trees in a
manner inspired by the sorting technique of Fredman (1976). The second approach
extends to any constant dimension.
  Many consequences follow from these new ideas: for example, we obtain an
$O(n^{4/3})$-time algorithm for line segment intersection counting in the
plane, $O(n^{4/3})$-time randomized algorithms for bichromatic closest pair and
Euclidean minimum spanning tree in three or four dimensions, and a randomized
data structure for halfplane range counting in the plane with $O(n^{4/3})$
preprocessing time and space and $O(n^{1/3})$ query time.


  The $J/\Psi$ and $\Psi'$ experiments at the Beijing Electron Positron
Collider (BEPC) play a unique role in many aspects of light hadron
spectroscopy, such as hunting for glueballs and hybrids, extracting $u\bar
u+d\bar d$ and $s\bar s$ components of mesons, and studying excited nucleons
and hyperons, i.e., $N^*$, $\Lambda^*$, $\Sigma^*$ and $\Xi^*$ resonances.
Physics objectives, recent results and future prospects of light hadron
spectroscopy at BEPC are presented.


  Room-temperature ferromagnetism is observed in (110) oriented ZnO films
containing 5 at % of Sc, Ti, V, Fe, Co or Ni, but not Cr, Mn or Cu ions. There
are large moments, 1.9 and 0.5 muB/atom for Co- and Ti-substituted oxides,
respectively. Sc-substituted ZnO shows also a moment of 0.3 muB/Sc.
Magnetization is very anisotropic, with variations of up to a factor three
depending on the orientation of the applied field relative to the R-cut
sapphire substrates. Results are interpreted in terms of a spin-split donor
impurity band model, which can account for ferromagnetism in insulating or
conducting high-k oxides with concentrations of magnetic ions that lie far
below the percolation threshold. The variation of the ferromagnetism with
oxygen pressure used during film growth is evidence of a link between
ferromagnetism and defect concentration.


  We consider "unphysical", kinematic observables that do not commute with the
constraints of a gauge system in the context of an extension of the system. We
show that these observables, while not predictable, can nevertheless be said to
have a physical interpretation. They implement Rovelli's concept of partial and
relational observables. We investigate the propositional structure of these
observables and point out interpretational issues. We find that to make
relational statements in the quantum theory one must deal directly with these
observables. In particular we argue that in this scenario the spectra of
kinematic observables are what is experimentally accessible.


  In this work, we assess the internal dynamics of particles in liquid-solid
fluidized beds using an unresolved CFD-DEM model. We use the Nearest Neighbors
Method (NNM) and the mixing index based on the principal component analysis
proposed by Doucet et al. [1] to quantify the bed mixing for several flow
regimes and particle properties. Discussions on the advantages and drawbacks of
each method are provided. Using results for several inlet flow rates, we show
that the dimensionless mixing time reaches a plateau and does not increase
significantly with the inlet velocity. The principal component analysis shows
that the studied fluidized bed has no preferential mixing component.
Additionally, we show that, except for the sliding friction coefficient, the
collision properties have almost negligible influence on the mixing behavior.


  We give two different, statistically consistent definitions of the length l
of a prime knot tied into a polymer ring. In the good solvent regime the
polymer is modelled by a self avoiding polygon of N steps on cubic lattice and
l is the number of steps over which the knot ``spreads'' in a given
configuration. An analysis of extensive Monte Carlo data in equilibrium shows
that the probability distribution of l as a function of N obeys a scaling of
the form p(l,N) ~ l^(-c) f(l/N^D), with c ~ 1.25 and D ~ 1. Both D and c could
be independent of knot type. As a consequence, the knot is weakly localized,
i.e. <l> ~ N^t, with t=2-c ~ 0.75. For a ring with fixed knot type, weak
localization implies the existence of a peculiar characteristic length l^(nu) ~
N^(t nu). In the scaling ~ N^(nu) (nu ~0.58) of the radius of gyration of the
whole ring, this length determines a leading power law correction which is much
stronger than that found in the case of unrestricted topology. The existence of
such correction is confirmed by an analysis of extensive Monte Carlo data for
the radius of gyration. The collapsed regime is studied by introducing in the
model sufficiently strong attractive interactions for nearest neighbor sites
visited by the self-avoiding polygon. In this regime knot length determinations
can be based on the entropic competition between two knotted loops separated by
a slip link. These measurements enable us to conclude that each knot is
delocalized (t ~ 1).


  It was proved that accelerated motion of a linear dielectric causes its
polarization. Accelerated translational motion of a dielectric's plate leads to
the positive charge of the surface facing the direction of motion. Metal plates
of a capacitor were used to register polarized charges on a dielectric's
surface. Potential difference between the capacitor plates is proportional to
acceleration, when acceleration is constant potential difference grows with the
increase of a dielectric's area, of its permittivity and is hardly dependant on
a dielectric's thickness


  Any polyhedron accommodates a type of potential theoretic skeleton called a
mother body. The study of such mother bodies was originally from Mathematical
Physics, initiated by Zidarov and developed by Bj\"{o}rn Gustafson and Makoto
Sakai. In this paper, we attempt to apply the brilliant idea of mother body to
Electrostatics to compute the potentials of electric fields.


  A Large Ion Collider Experiment (ALICE) is the dedicated heavy-ion experiment
at the Large Hadron Collider (LHC). In addition to its heavy-ion physics
program, it also has a rich proton-proton physics program benefiting from a
detector with a low momentum cut-off (pT about 50 MeV/c) and a small material
budget (about 11% of a radiation length until the outer wall of the main
tracking detector, the Time-Projection Chamber). ALICE has excellent means of
particle identification (PID) with methods ranging from specific energy loss
and time of flight to transition and Cherenkov radiation. The good primary and
secondary vertex resolution allows for measurements of strangeness and heavy
flavor with low backgrounds. ALICE has taken proton-proton collision data at
0.9, 2.36, and 7 TeV. In this article results of the first minimum-bias and
soft-QCD measurements are presented. Inclusive pseudorapidity, multiplicity,
and transverse momentum distributions are discussed as well as distributions of
identified particles including strange particles. Further, results on two-pion
Bose-Einstein correlations and the antiproton-to-proton ratio in collisions at
the LHC are shown.


  Knowledge Graph Embedding methods aim at representing entities and relations
in a knowledge base as points or vectors in a continuous vector space. Several
approaches using embeddings have shown promising results on tasks such as link
prediction, entity recommendation, question answering, and triplet
classification. However, only a few methods can compute low-dimensional
embeddings of very large knowledge bases without needing state-of-the-art
computational resources. In this paper, we propose KG2Vec, a simple and fast
approach to Knowledge Graph Embedding based on the skip-gram model. Instead of
using a predefined scoring function, we learn it relying on Long Short-Term
Memories. We show that our embeddings achieve results comparable with the most
scalable approaches on knowledge graph completion as well as on a new metric.
Yet, KG2Vec can embed large graphs in lesser time by processing more than 250
million triples in less than 7 hours on common hardware.


  The band gaps of isostructural Bi2OS2 and LaOBiS2 were examined using optical
absorption and discussed with the band structures calculated based on the
crystal structures determined using synchrotron X-ray diffraction. The Bi 6p
and S 3p orbitals in the Bi-S plane were computationally predicted to
constitute the bands near the Fermi level. The optical reflectance spectra of
Bi2OS2 and LaOBiS2 showed optical band gaps of ca. 1.0 eV, which were close to
the computationally calculated direct band gaps of ca. 0.8 eV. Our results show
that Bi2OS2 and LaOBiS2 are semiconductors containing direct band gaps of
0.8-1.0 eV, and they are suggested to be candidates for optoelectronic
materials in the near-infrared region without highly toxic elements.


  Numerical simulation is used to analyze statistical characteristics of vortex
beams propagating in the atmosphere. The cumulative distribution function and
the probability density function of intensity fluctuations are compared for
Gaussian beams and vortex beams. It is shown that for propagation conditions in
the turbulent atmosphere corresponding to weak fluctuations (Rytov parameter
much smaller than unity), intensity fluctuations at the axis of the Gaussian
beam have the lognormal distribution, whereas the probability density
distribution of the radiation intensity fluctuations at the axis of the vortex
beams is well approximated by the exponential distribution characteristic of
conditions of saturated fluctuations (Rytov parameter much larger than unity)


  Starting from the collisional Boltzmann equation, we derive for the first
time and from first principles the Boltzmann hierarchy for neutrinos including
interactions with a scalar particle. Such interactions appear, for example, in
majoron-like models of neutrino mass generation. We study two limits of the
scalar mass: (i) An extremely massive scalar whose only role is to mediate an
effective 4-fermion neutrino-neutrino interaction, and (ii) a massless scalar
that can be produced in abundance and thus demands its own Boltzmann hierarchy.
In contrast to, e.g., the first-order Boltzmann hierarchy for
Thomson-scattering photons, our interacting neutrino/scalar Boltzmann
hierarchies contain additional momentum-dependent collision terms arising from
a non-negligible energy transfer in the neutrino-neutrino and neutrino-scalar
interactions. This necessitates that we track each momentum mode of the phase
space distributions individually, even if the particles were massless.
Comparing our hierarchy with the commonly used $(c_{\rm eff}^2,c_{\rm
vis}^2)$-parameterisation, we find no formal correspondence between the two
approaches, which raises the question of whether the latter parameterisation
even has an interpretation in terms of particle scattering. Lastly, although we
have invoked majoron-like models as a motivation for our study, our treatment
is in fact generally applicable to all scenarios in which the neutrino and/or
other ultrarelativistic fermions interact with scalar particles.


  We propose a simple geometric interpretation for gauge/gravity duality that
relates the large-$N$ limit of gauge theory to the second quantization of
string theory.


  With the increasing sensitivity of gravitational-wave detectors, we expect to
observe multiple binary neutron-star systems through gravitational waves in the
near future. The combined analysis of these gravitational-wave signals offers
the possibility to constrain the neutron-star radius and the equation of state
of dense nuclear matter with unprecedented accuracy. However, it is crucial to
ensure that uncertainties inherent in the gravitational-wave models will not
lead to systematic biases when information from multiple detections are
combined. To quantify waveform systematics, we perform an extensive simulation
campaign of binary neutron-star sources and analyse them with a set of four
different waveform models. Based on our analysis with about 38 simulations, we
find that statistical uncertainties in the neutron-star radius decrease to $\pm
250\rm m$ ($2\%$ at $90\%$ credible interval) but that systematic differences
between currently employed waveform models can be twice as large. Hence, it
will be essential to ensure that systematic biases will not become dominant in
inferences of the neutron-star equation of state when capitalizing on future
developments.


  Automatic code transformation in which transformations are tuned for specific
applications and contexts are difficult to achieve in an accessible manner. In
this paper, we present an approach to build application specific code
transformations. Our approach is based on analysis of the abstract syntax
representation of exemplars of the essential change to the code before and
after the transformation is applied. This analysis entails a sequence of steps
to identify the change, determine how to generalize it, and map it to term
rewriting rules for the Stratego term rewriting system. The methods described
in this paper assume programs are represented in a language-neutral term
format, allowing tools based on our methods to be applied to programs written
in the major languages used by computational scientists utilizing high
performance computing systems.


  We consider the motion of an incompressible shear-thickening power-law-like
non-Newtonian fluid in $R^3$ with a variable power-law index. This system of
nonlinear partial differential equations arises in mathematical models of
electrorheological fluids. The aim of this paper is to investigate the
large-time behaviour of the difference $u-\tilde{u}$ where $u$ is a strong
solution of the given equations with the initial data $u_0$ and $\tilde{u}$ is
the strong solution of the same equations with perturbed initial data
$u_0+w_0$. The initial perturbation $w_0$ is not required to be small, but is
assumed to satisfy certain decay condition. In particular, we can show that
$(1+t)^{-\frac{\gamma}{2}}\lesssim
\|u(t)-\tilde{u}(t)\|_2\lesssim(1+t)^{-\frac{\gamma}{2}}$, for sufficiently
large $t>0$, where $\gamma\in(2,\frac{5}{2})$. The proof is based on the
observation that the solution of the linear heat equation describes the
asymptotic behaviour of the solutions of the electrorheological fluids well for
sufficiently large time $t>0$, and the generalized Fourier splitting method
with an iterative argument. Furthermore, it will also be discussed that the
argument used in the present paper can improve the previous results for the
generalized Newtonian fluids with a constant power-law index.


  Given a system that does not work as expected, Sequential Diagnosis (SD) aims
at suggesting a series of system measurements to isolate the true explanation
for the system's misbehavior from a potentially exponential set of possible
explanations. To reason about the best next measurement, SD methods usually
require a sample of possible fault explanations at each step of the iterative
diagnostic process. The computation of this sample can be accomplished by
various diagnostic search algorithms. Among those, Reiter's HS-Tree is one of
the most popular due its desirable properties and general applicability.
Usually, HS-Tree is used in a stateless fashion throughout the SD process to
(re)compute a sample of possible fault explanations in each iteration, each
time given the latest (updated) system knowledge including all so-far collected
measurements. At this, the built search tree is discarded between two
iterations, although often large parts of the tree have to be rebuilt in the
next iteration, involving redundant operations and calls to costly reasoning
services.
  As a remedy to this, we propose DynamicHS, a variant of HS-Tree that
maintains state throughout the diagnostic session and additionally embraces
special strategies to minimize the number of expensive reasoner invocations. In
this vein, DynamicHS provides an answer to a longstanding question posed by
Raymond Reiter in his seminal paper from 1987.
  Extensive evaluations on real-world diagnosis problems prove the
reasonability of the DynamicHS and testify its clear superiority to HS-Tree
wrt. computation time. More specifically, DynamicHS outperformed HS-Tree in 96%
of the executed sequential diagnosis sessions and, per run, the latter required
up to 800% the time of the former. Remarkably, DynamicHS achieves these
performance improvements while preserving all desirable properties as well as
the general applicability of HS-Tree.


  This paper studies the fundamental limits of availability and throughput for
independent and heterogeneous demands of a limited resource. Availability is
the probability that the demands are below the capacity of the resource.
Throughput is the expected fraction of the resource that is utilized by the
demands. We offer a concentration inequality generator that gives lower bounds
on feasible availability and throughput pairs with a given capacity and
independent but not necessarily identical distributions of up-to-unit demands.
We show that availability and throughput cannot both be poor. These bounds are
analogous to tail inequalities on sums of independent random variables, but
hold throughout the support of the demand distribution. This analysis gives
analytically tractable bounds supporting the unit-demand characterization of
Chawla, Devanur, and Lykouris (2023) and generalizes to up-to-unit demands. Our
bounds also provide an approach towards improved multi-unit prophet
inequalities (Hajiaghayi, Kleinberg, and Sandholm, 2007). They have
applications to transaction fee mechanism design (for blockchains) where high
availability limits the probability of profitable user-miner coalitions (Chung
and Shi, 2023).


  The dynamic response of power grids to small events or persistent stochastic
disturbances influences their stable operation. Low-frequency inter-area
oscillations are of particular concern due to insufficient damping. This paper
studies the effect of the operating point on the linear time-invariant dynamics
of power networks. A pertinent metric based on the frequency response of grid
dynamics is proposed to quantify power system's stability against inter-area
oscillations. We further put forth an optimal power flow formulation to yield a
grid dispatch that optimizes this novel stability metric. A semidefinite
program (SDP) relaxation is employed to yield a computationally tractable
convex problem. Numerical tests on the IEEE-39 bus system demonstrate that the
SDP relaxation is exact yielding a rank-1 solution. The relative trade-off of
the proposed small-signal stability metric versus the generation cost is also
studied.


  A power allocation to active and reactive power in stochastic resonance is
discussed for energy harvesting from mechanical noise. It is confirmed that
active power can be increased at stochastic resonance, in the same way of the
relationship between energy and phase at an appropriate setting in resonance.


  In this paper, it is established that quantum nilpotent algebras (also known
as CGL extensions) are catenary, i.e., all saturated chains of inclusions of
prime ideals between any two given prime ideals $P \subsetneq Q$ have the same
length. This is achieved by proving that the prime spectra of these algebras
have normal separation, and then establishing the mild homological conditions
necessary to apply a result of Lenagan and the first author. The work also
recovers the Tauvel height formula for quantum nilpotent algebras, a result
that was first obtained by Lenagan and the authors through a different
approach.


  Following up on the linear transformer part of the article from Katharopoulos
et al., that takes this idea from Shen et al., the trick that produces a linear
complexity for the attention mechanism is re-used and extended to a
second-order approximation of the softmax normalization.


  Crunchbase is an online platform collecting information about startups and
technology companies, including attributes and relations of companies, people,
and investments. Data contained in Crunchbase is, to a large extent, not
available elsewhere, making Crunchbase to a unique data source. In this paper,
we present how to bring Crunchbase to the Web of Data so that its data can be
used in the machine-readable RDF format by anyone on the Web. First, we give
insights into how we developed and hosted a Linked Data API for Crunchbase and
how sameAs links to other data sources are integrated. Then, we present our
method for crawling RDF data based on this API to build a custom Crunchbase RDF
knowledge graph. We created an RDF data set with over 347 million triples,
including 781k people, 659k organizations, and 343k investments. Our Crunchbase
Linked Data API is available online at http://linked-crunchbase.org.


  In this paper, we continue to construct stationary classical solutions of the
incompressible Euler equation approximating singular stationary solutions of
this equation.
  This procedure now is carried out by constructing solutions to the following
elliptic problem \[
  {cases} -\ep^2 \Delta
u=(u-q-\frac{\kappa}{2\pi}\ln\frac{1}{\ep})_+^p-(q-\frac{\kappa}{2\pi}\ln\frac{1}{\ep}-u)_+^p,
\quad & x\in\Omega, u=0, \quad & x\in\partial\Omega, {cases} \] where $p>1$,
$\Omega\subset\mathbb{R}^2$ is a bounded domain, $q$ is a harmonic function.
  We showed that if $\Omega$ is a simply-connected smooth domain, then for any
given non-degenerate critical point of Kirchhoff-Routh function
$\mathcal{W}(x_1^+,...,x_m^+,x_1^-,...,x_n^-)$ with
$\kappa^+_i=\kappa>0\,(i=1,...,m)$ and $\kappa^-_j=-\kappa\,(j=1,...,n)$, there
is a stationary classical solution approximating stationary $m+n$ points vortex
solution of incompressible Euler equations with total vorticity $(m-n)\kappa$.


  We study tropical geometry in the global setting using Berkovich's
deformation retraction. We state and prove the generalized balancing conditions
in this setting. Starting with a strictly semi-stable formal scheme, we
calculate certain sheaves of vanishing cycles using analytic \'etale
cohomology, then we interpret the tropical weights via these cycles. We obtain
the balancing condition for tropical curves on the skeleton associated to the
formal scheme in terms of the intersection theory on the special fiber. Our
approach works over any complete discrete valuation field.


  In cryptanalysis, security of ciphers vis-a-vis attacks is gauged against
three criteria of complexities, i.e., computations, memory and time. Some
features may not be so apparent in a particular domain, and their analysis in a
transformed domain often reveals interesting patterns. Moreover, the complexity
criteria in different domains are different and performance improvements are
often achieved by transforming the problem in an alternate domain. Owing to the
results of coding theory and signal processing, Discrete Fourier Transform
(DFT) based attacks have proven to be efficient than algebraic attacks in terms
of their computational complexity. Motivated by DFT based attacks, we present a
transform domain analysis of Linear Feedback Shift Register(LFSR) based
sequence generators. The time and frequency domain behavior of non-linear
filter and combiner generators is discussed along with some novel observations
based on the Chinese Remainder Theorem (CRT). CRT is exploited to establish
patterns in LFSR sequences and underlying cyclic structures of finite fields.
Application of DFT spectra attacks on combiner generators is also demonstrated.
Our proposed method saves on the last stage computations of selective DFT
attacks for combiner generators. The proposed approach is demonstrated on some
examples of combiner generators and is scalable to general configuration of
combiner generators.


  Optical continuous glucose monitoring (CGM) systems are emerging for
personalized glucose management owing to their lower cost and prolonged
durability compared to conventional electrochemical CGMs. Here, we report a
computational CGM system, which integrates a biocompatible
phosphorescence-based insertable biosensor and a custom-designed
phosphorescence lifetime imager (PLI). This compact and cost-effective PLI is
designed to capture phosphorescence lifetime images of an insertable sensor
through the skin, where the lifetime of the emitted phosphorescence signal is
modulated by the local concentration of glucose. Because this phosphorescence
signal has a very long lifetime compared to tissue autofluorescence or
excitation leakage processes, it completely bypasses these noise sources by
measuring the sensor emission over several tens of microseconds after the
excitation light is turned off. The lifetime images acquired through the skin
are processed by neural network-based models for misalignment-tolerant
inference of glucose levels, accurately revealing normal, low (hypoglycemia)
and high (hyperglycemia) concentration ranges. Using a 1-mm thick skin phantom
mimicking the optical properties of human skin, we performed in vitro testing
of the PLI using glucose-spiked samples, yielding 88.8% inference accuracy,
also showing resilience to random and unknown misalignments within a lateral
distance of ~4.7 mm with respect to the position of the insertable sensor
underneath the skin phantom. Furthermore, the PLI accurately identified larger
lateral misalignments beyond 5 mm, prompting user intervention for
re-alignment. The misalignment-resilient glucose concentration inference
capability of this compact and cost-effective phosphorescence lifetime imager
makes it an appealing wearable diagnostics tool for real-time tracking of
glucose and other biomarkers.


  The spectral action on noncommutative torus is obtained, using a
Chamseddine--Connes formula via computations of zeta functions. The importance
of a Diophantine condition is outlined. Several results on holomorphic
continuation of series of holomorphic functions are obtained in this context.


  Hoffman proved that for a simple graph $G$, the chromatic number $\chi(G)$
obeys $\chi(G) \le 1 - \frac{\lambda_1}{\lambda_{n}}$ where $\lambda_1$ and
$\lambda_n$ are the maximal and minimal eigenvalues of the adjacency matrix of
$G$ respectively. Lov\'asz later showed that $\chi(G) \le 1 -
\frac{\lambda_1}{\lambda_{n}}$ for any (perhaps negatively) weighted adjacency
matrix.
  In this paper, we give a probabilistic proof of Lov\'asz's theorem, then
extend the technique to derive generalizations of Hoffman's theorem when
allowed a certain proportion of edge-conflicts. Using this result, we show that
if a 3-uniform hypergraph is 2-colorable, then $\bar d \le
-\frac{3}{2}\lambda_{\min}$ where $\bar d$ is the average degree and
$\lambda_{\min}$ is the minimal eigenvalue of the underlying graph. We
generalize this further for $k$-uniform hypergraphs, for the cases $k=4$ and
$5$, by considering several variants of the underlying graph.


  Extending gr-qc/0502074, we show that in order to avoid a breakdown of
general covariance and gauge invariance at the quantum level the total flux of
charge and energy in each outgoing partial wave of a charged quantum field in a
Reissner-Nordstrom black hole background must be equal to that of a (1+1)
dimensional blackbody at the Hawking temperature with the appropriate chemical
potential.


  From a supersymmetry covariant source extension of N=2 SYM we study
non-trivial thermodynamical limits thereof. Using an argument by one of us
about the solution of the strong CP problem and the uniqueness of the QCD
ground state we find that the dependence of the effective potential on the
defining field operators is severely restricted. In contrast to the solution by
Seiberg and Witten an acceptable infrared behavior only exists for broken
supersymmetry while the gauge symmetry remains unbroken.


  In this work, we develop a computational method that to provide realtime
detection for water bottom topography based on observations on surface
measurements, and we design an inverse problem to achieve this task. The
forward model that we use to describe the feature of water surface is the
truncated KdV equation, and we formulate the inversion mechanism as an online
parameter estimation problem, which is solved by a direct filter method.
Numerical experiments are carried out to show that our method can effectively
detect abrupt changes of water depth.


  In this work we explore the effect of pion cloud contributions to the mass of
the nucleon and the delta baryon. To this end we solve a coupled system of
Dyson-Schwinger equations for the quark propagator, a Bethe-Salpeter equation
for the pion and a three-body Faddeev equation for the baryons. In the
quark-gluon interaction we explicitly resolve the term responsible for the
back-coupling of the pion onto the quark, representing rainbow-ladder like pion
cloud effects in bound states. We study the dependence of the resulting baryon
masses on the current quark mass and discuss the internal structure of the
baryons in terms of a partial wave decomposition. We furthermore determine
values for the nucleon and delta sigma-terms.


  Unambiguous unitary maps and unambiguous unitary quantum channels are
introduced and some of their properties are derived. These properties ensure
certain simple form for the measurements involved in realizing an unambiguous
unitary quantum channel. Error correction and unambiguous error correction with
nonzero probability are discussed in terms of unambiguous unitary quantum
channels. We not only re-derive the well-known condition for a set of errors to
be correctable with certainty, but also obtain a necessary and sufficient
condition for the errors caused by a noisy channel to be correctable with any
nonzero probability. Dense coding with a partially entangled state can also be
viewed as an unambiguous unitary quantum channel when all messages are required
to be transmitted with equal probability of success, the maximal achievable
probability of success is derived and the optimum protocol is also obtained.


  To obtain a generalized wave equation for a field in general covariant form,
one must define covariant differentiation of a generalized wave function
describing particles with arbitrary spin. Gel'fand and Iaglom, Dirac, and Fierz
and Pauli have studied the generalized wave equation in the special theory of
relativity. In this paper, the Gel'fand-Iaglom field equation was generalized
to the curved space based on the veilbein framework. The general covariant
field equations for arbitrary spin were obtained. More importantly, in this
work, we introduced the gauge covariant derivative with the local Lorentz
transformation, which is the foundation for a gauge theory of gravitation.


  We investigate the Meissner effect in a parametrically driven superconductor
using a semiclassical $U(1)$ lattice gauge theory. Specifically, we
periodically drive the $z$-axis tunneling, which leads to an enhancement of the
imaginary part of the $z$-axis conductivity at low frequencies if the driving
frequency is blue-detuned from the plasma frequency. This has been proposed as
a possible mechanism for light-enhanced interlayer transport in
YBa$_2$C$_3$O$_{7-\delta}$ (YBCO). In contrast to this enhancement of the
conductivity, we find that the screening of magnetic fields is less effective
than in equilibrium for blue-detuned driving, while it displays a tendency to
be enhanced for red-detuned driving.


  The influence of the reduced mass on the results of the approximation by the
Morse function of the ground electronic state term potential U(r) of hydrogen
molecule nH2 for seven symmetrical isotopologues n = 1-7 is investigated. For
each isotopologue, two alternative model solutions of the Schroedinger equation
are obtained, namely, M1(r) and M2(r) functions, which differ by the selection
of the primary fitting parameters in the Morse approximation. The U(r) - M(r)
functions are shown to clearly visualize the differences between the shapes of
the potential at its approximation. The concept of systematic deviation of
Morse functions from the real potential is introduced. This deviation is always
present in the approximation of simple terms, for which U(r) curve lies between
M1(r) and M2(r) without crossings. In case of nH2, for M1(r) the systematic
monotonous deviation increases, reaching 1700-2770 cm-1 (for 7H2-1H2) at the
level of the asymptote. For M2(r) the systematic deviation decreases at larger
distances: it is dome-shaped with a maximum of ca. 1500 cm-1 in the upper part
of the term, after which it falls to zero. The M2(r) curves for different
isotopologues diverge by less than 20 cm-1. There are also anomalies, where
M1(r) and M2(r) cross U(r), called "Herzberg anomaly". For example, at around r
= 1.08 A the U(r) - M2(r) function shows anomalous negative values ranging from
-125 cm-1 (for 1H2) to -142 cm-1 (for 7H2). The diagnostic value of Herzberg
anomaly and anharmonicities for various isotopologues is discussed.


  Event cameras, characterized by high temporal resolution, high dynamic range,
low power consumption, and high pixel bandwidth, offer unique capabilities for
object detection in specialized contexts. Despite these advantages, the
inherent sparsity and asynchrony of event data pose challenges to existing
object detection algorithms. Spiking Neural Networks (SNNs), inspired by the
way the human brain codes and processes information, offer a potential solution
to these difficulties. However, their performance in object detection using
event cameras is limited in current implementations. In this paper, we propose
the Spiking Fusion Object Detector (SFOD), a simple and efficient approach to
SNN-based object detection. Specifically, we design a Spiking Fusion Module,
achieving the first-time fusion of feature maps from different scales in SNNs
applied to event cameras. Additionally, through integrating our analysis and
experiments conducted during the pretraining of the backbone network on the
NCAR dataset, we delve deeply into the impact of spiking decoding strategies
and loss functions on model performance. Thereby, we establish state-of-the-art
classification results based on SNNs, achieving 93.7\% accuracy on the NCAR
dataset. Experimental results on the GEN1 detection dataset demonstrate that
the SFOD achieves a state-of-the-art mAP of 32.1\%, outperforming existing
SNN-based approaches. Our research not only underscores the potential of SNNs
in object detection with event cameras but also propels the advancement of
SNNs. Code is available at https://github.com/yimeng-fan/SFOD.


  The spectrum of the integrable spin-S Heisenberg chains is completely
characterized in terms of spin-1/2 spinons. In the continuum limit they form a
quasi-particle basis to the higher level SU(2) Wess-Zumino-Witten (WZW) models.
Enumerating the spinon states in finite systems we obtain effective single
particle distribution functions for these objects which generalize Haldane's
generalized exclusion principle to quasi-particles with non-Abelian exchange
statistics.


  Electronic health record (EHR) data has emerged as a valuable resource for
analyzing patient health status. However, the prevalence of missing data in EHR
poses significant challenges to existing methods, leading to spurious
correlations and suboptimal predictions. While various imputation techniques
have been developed to address this issue, they often obsess unnecessary
details and may introduce additional noise when making clinical predictions. To
tackle this problem, we propose SMART, a Self-Supervised Missing-Aware
RepresenTation Learning approach for patient health status prediction, which
encodes missing information via elaborated attentions and learns to impute
missing values through a novel self-supervised pre-training approach that
reconstructs missing data representations in the latent space. By adopting
missing-aware attentions and focusing on learning higher-order representations,
SMART promotes better generalization and robustness to missing data. We
validate the effectiveness of SMART through extensive experiments on six EHR
tasks, demonstrating its superiority over state-of-the-art methods.