  We motivate and present feature selective anchor-free (FSAF) module, a simple
and effective building block for single-shot object detectors. It can be
plugged into single-shot detectors with feature pyramid structure. The FSAF
module addresses two limitations brought up by the conventional anchor-based
detection: 1) heuristic-guided feature selection; 2) overlap-based anchor
sampling. The general concept of the FSAF module is online feature selection
applied to the training of multi-level anchor-free branches. Specifically, an
anchor-free branch is attached to each level of the feature pyramid, allowing
box encoding and decoding in the anchor-free manner at an arbitrary level.
During training, we dynamically assign each instance to the most suitable
feature level. At the time of inference, the FSAF module can work jointly with
anchor-based branches by outputting predictions in parallel. We instantiate
this concept with simple implementations of anchor-free branches and online
feature selection strategy. Experimental results on the COCO detection track
show that our FSAF module performs better than anchor-based counterparts while
being faster. When working jointly with anchor-based branches, the FSAF module
robustly improves the baseline RetinaNet by a large margin under various
settings, while introducing nearly free inference overhead. And the resulting
best model can achieve a state-of-the-art 44.6% mAP, outperforming all existing
single-shot detectors on COCO.


  We revisit classical string motion in a near pp-wave limit of
AdS$_5\times$S$^5$. It is known that the Toda lattice models are integrable.
But if the exponential potential is truncated at finite order, then the system
may become non-integrable. In particular, when the exponential potential in a
three-particle periodic Toda chain is truncated at the third order of the
dynamical variables, the resulting system becomes a well-known non-integrable
system, Henon-Heiles model. The same thing may happen in a near pp-wave limit
of AdS$_5\times$S$^5$, on which the classical string motion becomes chaotic.


  By using the full potential linear augmented plane wave (FP-LAPW) method and
full potential local orbital minimum basis (FP-LOMB) method within generalized
gradient approximation (GGA), we studied the electronic structures and magnetic
properties of nickel and chromium single dopants in polytypes of silicon
carbide (SiC). The magnetic phases of defects are found to be strongly
dependent on the external stress on the supercell. In 3C-SiC, the Ni single
dopant exhibits an anti-ferromagnetic (AFM) to ferromagnetic (FM) transition at
a moderate compressive and tensile hydrostatic strain in Si-sub and C-sub
cases. In contrast, the Ni single dopant in 4H-SiC is stably in the nonmagnetic
phase under external stress. The Cr single dopant is also insensitive to the
applied stress but stably in the magnetic phase. This strain controlled
magnetic transition makes the Ni single dopant a novel scheme of qubit.


  Medical images such as 3D computerized tomography (CT) scans and pathology
images, have hundreds of millions or billions of voxels/pixels. It is
infeasible to train CNN models directly on such high resolution images, because
neural activations of a single image do not fit in the memory of a single
GPU/TPU, and naive data and model parallelism approaches do not work. Existing
image analysis approaches alleviate this problem by cropping or down-sampling
input images, which leads to complicated implementation and sub-optimal
performance due to information loss. In this paper, we implement spatial
partitioning, which internally distributes the input and output of
convolutional layers across GPUs/TPUs. Our implementation is based on the
Mesh-TensorFlow framework and the computation distribution is transparent to
end users. With this technique, we train a 3D Unet on up to 512 by 512 by 512
resolution data. To the best of our knowledge, this is the first work for
handling such high resolution images end-to-end.


  Considering anomalies of quantum field in the (1+1)-dimensional
Achucarro-Ortiz black hole background, the stress tensor near and out of the
horizon is calculated, meanwhile, the relationship between anomalies and
Hawking radiation of the black hole is discussed.


  Quantitative predictions are presented of a depletion-induced torque and
force acting on a single colloidal hard rod immersed in a solvent of hard
spheres close to a planar hard wall. This torque and force, which are entirely
of entropic origin, may play an important role for the key-lock principle,
where a biological macromolecule (the key) is only functional in a particular
orientation with respect to a cavity (the lock).


  We theoretically demonstrate a counter-intuitive phenomenon in optical
interferometry with a thermal source: the emergence of second-order
interference between two pairs of correlated optical paths even if the time
delay imprinted by each path in one pair with respect to each path in the other
pair is much larger than the source coherence time. This fundamental effect
could be useful for experimental simulations of small-scale quantum circuits
and of $100\%$-visibility correlations typical of entangled states of a large
number of qubits, with possible applications in high-precision metrology and
imaging. As an example, we demonstrate the polarization-encoded simulation of
the operation of the quantum logic gate known as controlled-NOT gate.


  We study the reflection coefficient, the transmission coefficient and the
greybody factors for black holes with topologically non trivial transverse
sections in 4 and d-dimensions, in the limit of low energy. Considering a
massive scalar field in a topological massless black hole background, which is
non minimally coupled to the curvature and assuming the horizon geometry with a
negative constant curvature. Mainly, we show that there is range of modes which
contribute to the absorption cross section in the zero-frequency limit, at
difference of the result existing in the literature. Where, the mode with
lowest angular momentum contribute to the absorption cross section. Also we
show that the condition that the sum of the reflection coefficient and the
transmission coefficient is equal to one is always satisfied for these kind of
black holes.


  In this work, we address the problem of few-shot multi-class object counting
with point-level annotations. The proposed technique leverages a class agnostic
attention mechanism that sequentially attends to objects in the image and
extracts their relevant features. This process is employed on an adapted
prototypical-based few-shot approach that uses the extracted features to
classify each one either as one of the classes present in the support set
images or as background. The proposed technique is trained on point-level
annotations and uses a novel loss function that disentangles class-dependent
and class-agnostic aspects of the model to help with the task of few-shot
object counting. We present our results on a variety of
object-counting/detection datasets, including FSOD and MS COCO. In addition, we
introduce a new dataset that is specifically designed for weakly supervised
multi-class object counting/detection and contains considerably different
classes and distribution of number of classes/instances per image compared to
the existing datasets. We demonstrate the robustness of our approach by testing
our system on a totally different distribution of classes from what it has been
trained on.


  A summary of the work recently carried out on the morphotropic phase boundary
(MPB) of PZT is presented. By means of x-ray powder diffraction on ceramic
samples of excellent quality, the MPB has been successfully characterized by
changing temperature in a series of closely spaced compositions. As a result,
an unexpected monoclinic phase has been found to exist in between the
well-known tetragonal and rhombohedral PZT phases. A detailed structural
analysis, together with the investigation of the field effect in this region of
compositions, have led to an important advance in understanding the mechanisms
responsible for the physical properties of PZT as well as other piezoelectric
materials with similar morphotropic phase boundaries.


  We derive the leading-power singular terms at three loops for both $q_T$ and
0-jettiness, $\cal{T}_0$, for generic color-singlet processes. Our results
provide the complete set of differential subtraction terms for $q_T$ and
$\cal{T}_0$ subtractions at N$^3$LO, which are an important ingredient for
matching N$^3$LO calculations with parton showers. We obtain the full
three-loop structure of the relevant beam and soft functions, which are
necessary ingredients for the resummation of $q_T$ and $\cal{T}_0$ at
N$^3$LL$'$ and N$^4$LL order, and which constitute important building blocks in
other contexts as well. The nonlogarithmic boundary coefficients of the beam
functions, which contribute to the integrated subtraction terms, are not yet
fully known at three loops. By exploiting consistency relations between
different factorization limits, we derive results for the $q_T$ and $\cal{T}_0$
beam function coefficients at N$^3$LO in the $z\to 1$ threshold limit, and we
also estimate the size of the unknown terms beyond threshold.


  Sorting is a fundamental algorithmic pre-processing technique which often
allows to represent data more compactly and, at the same time, speeds up search
queries on it. In this paper, we focus on the well-studied problem of sorting
and indexing string sets. Since the introduction of suffix trees in 1973,
dozens of suffix sorting algorithms have been described in the literature. In
2017, these techniques were extended to sets of strings described by means of
finite automata: the theory of Wheeler graphs [Gagie et al., TCS'17] introduced
automata whose states can be totally-sorted according to the co-lexicographic
(co-lex in the following) order of the prefixes of words accepted by the
automaton. More recently, in [Cotumaccio, Prezza, SODA'21] it was shown how to
extend these ideas to arbitrary automata by means of partial co-lex orders.
This work showed that a co-lex order of minimum width (thus optimizing search
query times) on deterministic finite automata (DFAs) can be computed in $O(m^2
+ n^{5/2})$ time, $m$ being the number of transitions and $n$ the number of
states of the input DFA.
  In this paper, we exhibit new combinatorial properties of the minimum-width
co-lex order of DFAs and exploit them to design faster prefix sorting
algorithms. In particular, we describe two algorithms sorting arbitrary DFAs in
$O(mn)$ and $O(n^2\log n)$ time, respectively, and an algorithm sorting acyclic
DFAs in $O(m\log n)$ time. Within these running times, all algorithms compute
also a smallest chain partition of the partial order (required to index the
DFA). We present an experiment result to show that an optimized implementation
of the $O(n^2\log n)$-time algorithm exhibits a nearly-linear behaviour on
large deterministic pan-genomic graphs and is thus also of practical interest.


  This paper studies noise synchronisation in terms of random pullback
attractors and their instabilities. We consider an ensemble of uncoupled
lasers, each being a limit-cycle oscillator, which are driven by the same
external white Gaussian noise. As the external-noise strength increases, there
is an onset of synchronization and then subsequent loss of synchrony. Local
analysis of the laser equations shows that synchronization becomes unstable via
stochastic bifurcation to a random strange attractor. The locus of this
bifurcation is calculated in the three-dimensional parameter space defined by
the Hopf parameter, amount of amplitude-phase coupling or shear, and
external-noise strength. The analysis uncovers a square-root law for this
stochastic bifurcation.


  We discuss continuous duality transformations and the properties of classical
theories with invariant interactions between electromagnetic fields and matter.
The case of scalar fields is treated in some detail. Special discrete elements
of the continuous group are shown to be related to the Legendre transformation
with respect to the field strengths.


  There is recently a surge of interest to cut down the time it takes to change
the state of a quantum system adiabatically. We study for the time-dependent
harmonic oscillator the transient energy excitation in speed-up processes
designed to reproduce the initial populations at some predetermined final
frequency and time, providing lower bounds and examples. Implications for the
limits imposed to the process times and for the principle of unattainability of
the absolute zero, in a single expansion or in quantum refrigerator cycles, are
drawn.


  Ultralight particles are theoretically well-motivated dark matter candidates.
In the vicinity of the solar system, these ultralight particles are described
as a superposition of plane waves, resulting in a stochastic field with
amplitude fluctuations on scales determined by the velocity dispersion of dark
matter. In this work, we systematically investigate the sensitivity of
space-based gravitational-wave interferometers to the stochastic ultralight
dark matter field within the frequentist framework. We derive the projected
sensitivity of a single detector using the time-delay interferometry and find
that the stochastic effect will only diminish the performance of the detector
marginally, unlike searches in other contexts where significant reductions are
found. Furthermore, we explore the sensitivity of detector network in two
typical configurations. We find that the well-separated configuration, where
the distance between two detectors exceeds the coherence length of dark matter,
is the optimal choice for ultralight dark matter detection due to a less chance
of missing signal. This contrasts with the detection of stochastic
gravitational-wave background, where the co-located and co-aligned
configuration is preferred. Our results may provide useful insights for
potential joint observations involving gravitational-wave detectors like LISA,
Taiji and TianQin.


  Wide-field imaging from space should not forget the dispersive dimension. We
consider the capability of space-based imaging with a slitless grism: because
of the low near-infrared background in space and the high sky-density of high
redshift emission line galaxies this makes for a very powerful redshift machine
with no moving parts. A small 1m space telescope with a 0.5 degree field of
view could measure redshifts for 10^7 galaxies at 0.5<z<2 per year, this is a
MIDEX class concept which we have dubbed `The Baryon Oscillation Probe' as the
primary science case would be constraining dark energy evolution via
measurement of the baryonic oscillations in the galaxy power spectrum. These
ideas are generalizable to other missions such as SNAP and DESTINY.


  In today's digital world, cybercrime is responsible for significant damage to
organizations, including financial losses, operational disruptions, or
intellectual property theft. Cyberattacks often start with an email, the major
means of corporate communication. Some rare, severely damaging email threats -
known as spear phishing or Business Email Compromise - have emerged. However,
the literature disagrees on their definition, impeding security vendors and
researchers from mitigating targeted attacks. Therefore, we introduce targeted
attacks. We describe targeted-attack-detection techniques as well as
social-engineering methods used by fraudsters. Additionally, we present
text-based attacks - with textual content as malicious payload - and compare
non-targeted and targeted variants.


  The variations of kinematic parameters with age are considered for a sample
of 15 402 thin-disk O--F stars with accurate $\alpha$, $\delta$, $\mu$, and
$\pi>3$ mas from the Hipparcos catalogue and radial velocities from the PCRV
catalogue. The ages have been calculated from the positions of the stars on the
Hertzsprung--Russell diagram relative to the isochrones from the Padova
database by taking into account the extinction from the previously constructed
3D analytical model and extinction coefficient $R_V$ from the 3D map of its
variations. Smooth, mutually reconciled variations of the velocity dispersions
$\sigma(U)$, $\sigma(V)$, $\sigma(W)$, solar motion components $U_{\odot}$,
$V_{\odot}$, $W_{\odot}$, Ogorodnikov--Milne model parameters, Oort constants,
and vertex deviation $lxy$ consistent with all of the extraneous results for
which the stellar ages were determined have been found. The velocity dispersion
variations are well fitted by power laws the deviations from which are
explained by the influence of predominantly radial stellar streams: Sirius,
Hyades, $\alpha$~Cet/Wolf~630, and Hercules. The accuracy of determining the
solar motion relative to the local standard of rest is shown to be
fundamentally limited due to these variations of stellar kinematics. The
deviations of our results from those of Dehnen and Binney (1998), the
Geneva--Copenhagen survey of dwarfs, and the Besancon model of the Galaxy are
explained by the use of PCRV radial velocities with corrected systematic
errors.


  We have studied the chemical potential shift in La(1-x)Sr(x)MnO(3) as a
function of doped hole concentration by core-level x-ray photoemission. The
shift is monotonous, which means that there is no electronic phase separation
on a macroscopic scale, whereas it is consistent with the nano-meter scale
cluster formation induced by chemical disorder. Comparison of the observed
shift with the shift deduced from the electronic specific heat indicates that
hole doping in La(1-x)Sr(x)MnO(3) is well described by the rigid-band picture.
In particular no mass enhancement toward the metal-insulator boundary was
implied by the chemical potential shift, consistent with the electronic
specific heat data.


  Payment channels allow transactions between participants of the blockchain to
be executed securely off-chain, and thus provide a promising solution for the
scalability problem of popular blockchains. We study the online network design
problem for payment channels, assuming a central coordinator. We focus on a
single channel, where the coordinator desires to maximize the number of
accepted transactions under given capital constraints. Despite the simplicity
of the problem, we present a flurry of impossibility results, both for
deterministic and randomized algorithms against adaptive as well as oblivious
adversaries.


  Shortcut to adiabaticity (STA) is a speed way to produce the same final state
that would result in an adiabatic, infinitely slow process. Two typical
techniques to engineer STA are developed by either introducing auxiliary
counterdiabatic fields or finding new Hamiltonians that own dynamical
invariants to constraint the system into the adiabatic paths. In this paper, a
consistent method is introduced to naturally connect the above two techniques
with a unified Lie algebraic framework, which neatly removes the requirements
of finding instantaneous states in the transitionless driving method and the
invariant quantities in the invariant-based inverse engineering approach. The
general STA schemes for different potential expansions are concisely achieved
with the aid of this method.


  In this paper we study smooth solutions to a fractional mean curvature flow
equation. We establish a comparison principle and consequences such as
uniqueness and finite extinction time for compact solutions. We also establish
evolutions equations for fractional geometric quantities that yield
preservation of certain quantities (such as positive fractional curvature) and
smoothness of graphical evolutions.


  In this paper, we propose a new Semi-Nonnegative Matrix Factorization method
for 2-dimensional (2D) data, named TS-NMF. It overcomes the drawback of
existing methods that seriously damage the spatial information of the data by
converting 2D data to vectors in a preprocessing step. In particular,
projection matrices are sought under the guidance of building new data
representations, such that the spatial information is retained and projections
are enhanced by the goal of clustering, which helps construct optimal
projection directions. Moreover, to exploit nonlinear structures of the data,
manifold is constructed in the projected subspace, which is adaptively updated
according to the projections and less afflicted with noise and outliers of the
data and thus more representative in the projected space. Hence, seeking
projections, building new data representations, and learning manifold are
seamlessly integrated in a single model, which mutually enhance other and lead
to a powerful data representation. Comprehensive experimental results verify
the effectiveness of TS-NMF in comparison with several state-of-the-art
algorithms, which suggests high potential of the proposed method for real world
applications.


  To quantify spatial protein-protein proximity (colocalization) in
fluorescence microscopic images, cross-correlation and autocorrelation
functions were decomposed into fast and slowly decaying components. The fast
component results from clusters of proteins specifically labeled and the slow
one from background/image heterogeneity. We show that the calculation of the
protein-protein proximity index and the correlation coefficient are more
reliably determined by extracting the fast-decaying component.


  Coupling of electric and magnetic responses of a scatterer known as
bianisotropy enables rich physics and unique optical phenomena, including
asymmetric absorption or reflection, one-way transparency, and photonic
topological phases. Here we demonstrate yet another feature stemming from
bianisotropic response, namely, polarization-dependent scattering of light by
bianisotropic dielectric meta-atom with broken mirror symmetry, which yields a
photonic analogue of spin Hall effect. Based on a simple dipole model, we
explain the origin of the effect confirming our conclusions by experimental
observation of photonic spin Hall effect both for a single meta-atom and for an
array of them.


  Detailed understanding of the formation and evolution of globular clusters
(GCs) has been recently advanced through a combination of numerical simulations
and analytical models. We employ a state-of-the-art model to create a
comprehensive catalogue of simulated clusters in three Milky Way (MW) and three
Andromeda (M31) analogue galaxies. Our catalogue aims to connect the chemical
and kinematic properties of GCs to the assembly histories of their host
galaxies. We apply the model to a selected sample of simulated galaxies that
closely match the virial mass, circular velocity profile, and defining assembly
events of the MW and M31. The resulting catalogue has been calibrated to
successfully reproduce key characteristics of the observed GC systems,
including total cluster mass, mass function, metallicity distribution, radial
profile, and velocity dispersion. We find that clusters in M31 span a wider
range of age and metallicity, relative to the MW, possibly due to M31's recent
major merger. Such a merger also heated up the in-situ GC population to higher
orbital energy and introduced a large number of ex-situ clusters at large
radii. Understanding the impacts of galaxy mergers and accretion on the GC
populations is crucial for uncovering the galaxy assembly histories.


  Automatic segmentation of fine-grained brain structures remains a challenging
task. Current segmentation methods mainly utilize 2D and 3D deep neural
networks. The 2D networks take image slices as input to produce coarse
segmentation in less processing time, whereas the 3D networks take the whole
image volumes to generated fine-detailed segmentation with more computational
burden. In order to obtain accurate fine-grained segmentation efficiently, in
this paper, we propose an end-to-end Feature-Fused Context-Encoding Network for
brain structure segmentation from MR (magnetic resonance) images. Our model is
implemented based on a 2D convolutional backbone, which integrates a 2D
encoding module to acquire planar image features and a spatial encoding module
to extract spatial context information. A global context encoding module is
further introduced to capture global context semantics from the fused 2D
encoding and spatial features. The proposed network aims to fully leverage the
global anatomical prior knowledge learned from context semantics, which is
represented by a structure-aware attention factor to recalibrate the outputs of
the network. In this way, the network is guaranteed to be aware of the
class-dependent feature maps to facilitate the segmentation. We evaluate our
model on 2012 Brain Multi-Atlas Labelling Challenge dataset for 134
fine-grained structure segmentation. Besides, we validate our network on 27
coarse structure segmentation tasks. Experimental results have demonstrated
that our model can achieve improved performance compared with the
state-of-the-art approaches.


  Tracking multiple time-varying states based on heterogeneous observations is
a key problem in many applications. Here, we develop a statistical model and
algorithm for tracking an unknown number of targets based on the probabilistic
fusion of observations from two classes of data sources. The first class,
referred to as target-independent perception systems (TIPSs), consists of
sensors that periodically produce noisy measurements of targets without
requiring target cooperation. The second class, referred to as target-dependent
reporting systems (TDRSs), relies on cooperative targets that report noisy
measurements of their state and their identity. We present a joint TIPS-TDRS
observation model that accounts for observation-origin uncertainty, missed
detections, false alarms, and asynchronicity. We then establish a factor graph
that represents this observation model along with a state evolution model
including target identities. Finally, by executing the sum-product algorithm on
that factor graph, we obtain a scalable multitarget tracking algorithm with
inherent TIPS-TDRS fusion. The performance of the proposed algorithm is
evaluated using simulated data as well as real data from a maritime
surveillance experiment.


  Through the chemodynamical characterisation of metal-poor stars, one can
efficiently probe the early history of the Milky Way. We aim at decontaminating
a sample of $\sim$ 3M giant stars with Gaia DR3 XP-based \textit{Pristine-Gaia}
metallicities, to investigate a subset of very metal-poor stars ([Fe/H] < -1.7)
with disc-like orbits. We construct a statistically robust sample of $\sim$ 36
000 very metal-poor giants, using APOGEE and LAMOST to estimate and remove
contamination from high $V_\phi$ stars. We investigate the spatial and
kinematic properties of the decontaminated sample, using $V_\phi$ and the
action space, both powerful to disentangle stellar populations. As in previous
works, we find a pronounced asymmetry in $L_z$ and $V_\phi$ in favour of
prograde stars. This excess is mostly made of prograde-planar stars (10% of the
very metal-poor population), and contains stars with $V_\phi$ > 180 km s$^{-1}$
and $Z_{\text{max}}$ < 1.5 kpc, down to [Fe/H] = -2.9 at a 2$\sigma$ confidence
level. While the overall orbital distributions of our sample match that of a
halo, the highly prograde and planar subset (2% of the very metal-poor
population) also bears characteristics classically associated with a thick
disc, i.e., a spatial distribution compatible with a short-scaled thick disc,
and a thick disc-like $Z_{\text{max}}$ - $R_{\text{max}}$ distribution.
Additionally, assuming a stationary or prograde halo with $\overline{V_\phi}$
$\sim$ 30-40 km.s$^{-1}$ is not sufficient to suppress the kinematic signature
of the highly prograde and planar subset. These results rule out any link with
a thin disc, and instead, support a contribution from a \textit{metal-weak
thick disc}.


  In this paper we describe moral quasi-dilemmas (MQDs): situations similar to
moral dilemmas, but in which an agent is unsure whether exploring the plan
space or the world may reveal a course of action that satisfies all moral
requirements. We argue that artificial moral agents (AMAs) should be built to
handle MQDs (in particular, by exploring the plan space rather than immediately
accepting the inevitability of the moral dilemma), and that MQDs may be useful
for evaluating AMA architectures.


  We calculate the harmonic-gauge even l=1 mode of the linear metric
perturbation (MP) produced by a particle in a weak-field circular orbit around
a Schwarzschild black hole (BH). We focus on the Newtonian limit, i.e. the
limit in which the mass M of the central BH approaches zero (while fixing the
orbital radius and the small-object mass), and obtain explicit expressions for
the MP in this limit. We find that the MP are anomalous in this limit, namely,
they do not approach their standard, Coulomb-like, flat-space values. Instead,
the MP grows on approaching the BH, and this growth becomes worse as M
decreases. This anomalous behavior leads to some pathologies which we briefly
discuss. We also derive here the next-order correction (in the orbital
frequency $\Omega $) to the MP.


  We systematically classify 1/2, 1/4 and 1/8 BPS equations in SUSY gauge
theories in d=6, 5, 4, 3 and 2 with eight supercharges, with gauge groups and
matter contents being arbitrary. Instantons (strings) and vortices (3-branes)
are only allowed 1/2 BPS solitons in d=6 with N=1 SUSY. We find two 1/4 BPS
equations and the unique 1/8 BPS equation in d=6 by considering configurations
made of these field theory branes. All known BPS equations are rederived while
several new 1/4 and 1/8 BPS equations are found in dimension less than six by
dimensional reductions.


  Measurements are presented of electroweak boson production using data from
$pp$ collisions at a centre-of-mass energy of $\sqrt{s} = 8\mathrm{\,Te\kern
-0.1em V}$. The analysis is based on an integrated luminosity of
$2.0\mathrm{\,fb}^{-1}$ recorded with the LHCb detector. The bosons are
identified in the $W\rightarrow\mu\nu$ and $Z\rightarrow\mu^{+}\mu^{-}$ decay
channels. The cross-sections are measured for muons in the pseudorapidity range
$2.0 < \eta < 4.5$, with transverse momenta $p_{\rm T} > 20{\mathrm{\,Ge\kern
-0.1em V\!/}c}$ and, in the case of the $Z$ boson, a dimuon mass within $60 <
M_{\mu^{+}\mu^{-}} < 120{\mathrm{\,Ge\kern -0.1em V\!/}c^{2}}$. The results are
\begin{align*} \sigma_{W^{+}\rightarrow\mu^{+}\nu} &= 1093.6 \pm 2.1 \pm 7.2
\pm 10.9 \pm 12.7{\rm \,pb} \, , \sigma_{W^{-}\rightarrow\mu^{-}\bar{\nu}} &=
\phantom{0}818.4 \pm 1.9 \pm 5.0 \pm \phantom{0}7.0 \pm \phantom{0}9.5{\rm
\,pb} \, , \sigma_{Z\rightarrow\mu^{+}\mu^{-}} &= \phantom{00}95.0 \pm 0.3 \pm
0.7 \pm \phantom{0}1.1 \pm \phantom{0}1.1{\rm \,pb} \, , \end{align*} where the
first uncertainties are statistical, the second are systematic, the third are
due to the knowledge of the LHC beam energy and the fourth are due to the
luminosity determination. The evolution of the $W$ and $Z$ boson cross-sections
with centre-of-mass energy is studied using previously reported measurements
with $1.0\mathrm{\,fb}^{-1}$ of data at $7\mathrm{\,Te\kern -0.1em V}$.
Differential distributions are also presented. Results are in good agreement
with theoretical predictions at next-to-next-to-leading order in perturbative
quantum chromodynamics.


  We obtained a time series of spectra covering the secondary maximum in the
I-band of the bright Type Ia supernova 2014J in M82 with the TIGRE telescope.
Comparing the observations with theoretical models calculated with the time
dependent extension of the PHOENIX code, we identify the feature that causes
the secondary maximum in the I-band light curve. Fe II 3d6(3D)4s-3d6(5D)4p and
similar high excitation transitions produce a blended feature at 7500 {\AA},
which causes the rise of the light curve towards the secondary maximum. The
series of observed spectra of SN 2014J and archival data of SN 2011fe confirm
this conclusion. We further studied the plateau phase of the Rband light curve
of SN 2014J and searched for features which contribute to the flux. The
theoretical models do not clearly indicate a new feature that may cause the
Rband plateau phase. However, Co II features in the range of 6500 - 7000 {\AA}
and the Fe II feature of the I-band are clearly seen in the theoretical
spectra, but do not appear to provide all of the flux necessary for the R-band
plateau.


  The top tree data structure is an important and fundamental tool in dynamic
graph algorithms. Top trees have existed for decades, and today serve as an
ingredient in many state-of-the-art algorithms for dynamic graphs. In this
work, we give a new direct proof of the existence of top trees, facilitating
simpler and more direct implementations of top trees, based on ideas from splay
trees. This result hinges on new insights into the structure of top trees, and
in particular the structure of each root path in a top tree.


  A new phenomenology is proposed for the superfluid density of strongly
underdoped cuprate superconductors based on recent data for ultra-clean single
crystals of YBCO. The data feature a puzzling departure from Uemura scaling and
a decline of the slope as the T_c = 0 quantum critical point is approached. We
show that this behavior can be understood in terms of the renormalization of
quasiparticle effective charge by quantum fluctuations of the superconducting
phase as described by a (3+1)-dimensional XY model. We calculate the
renormalization of the superfluid density and its slope, explain the new
phenomenology, and predict its eventual demise close to the QCP.


  Fabricating high-performance and/or high-density flexible electronics on
plastic substrates is often limited by the poor dimensional stability of
polymer substrates. This can be mitigated by using glass carriers during
fabrication, but removing the plastic substrate from a large-area carrier
without damaging the electronics remains challenging. Here we present a
large-area photonic lift-off (PLO) process to rapidly separate polymer films
from rigid carriers. PLO uses a 150 microsecond pulse of broadband light from
flashlamps to lift off functional thin films from a glass carrier substrate
coated with a light-absorber layer (LAL). A 3D finite element model indicates
that the polymer/LAL interface reaches 865 degrees C during PLO, but the top
surface of the PI reaches only 118 degrees C. To demonstrate the feasibility of
this process in the production of flexible electronics, an array of indium zinc
oxide (IZO) thin-film transistors (TFTs) was fabricated on a polyimide
substrate and then photonically lifted off from the glass carrier. The TFT
mobility was 3.15 cm2V-1s-1 before and after PLO, indicating no significant
change during PLO. The flexible TFTs were mechanically robust, with no
reduction in mobility while bent. The PLO process can offer unmatched
high-throughput solutions in large-area flexible electronics production.


  We show that in the exponential $f(T)$ model studied by E. Linder
[arXiv:1005.3039, Phys.Rev.D 81, 127301 (2010)], it is impossible to have the
crossing of the phantom divide line $w_{\mathrm{DE}}=-1$.


  In this paper we propose two new algorithms based on biclustering analysis,
which can be used at the basis of a recommender system for educational
orientation of Russian School graduates. The first algorithm was designed to
help students make a choice between different university faculties when some of
their preferences are known. The second algorithm was developed for the special
situation when nothing is known about their preferences. The final version of
this recommender system will be used by Higher School of Economics.


  In the diffusive regime, we obtain the uniform in Knudsen number estimate on
the two-species Vlasov-Maxwell-Landau system with Coulomb potential around the
global equilibrium. As a consequence, we justify the limit to the two-fluid
incompressible Navier-Stokes-Fourier-Maxwell (NSFM) system with Ohm's law. This
is the first result on the global in time uniform in Knudsen number estimate on
the Boltzmann and Landau type equations with Coulomb potential coupled
Vlasov-Maxwell equations.


  The D^+ --> omega + pi^+ decay is studied by decomposing its amplitude into a
sum of factorizable and non-factorizable ones. Its rate is predicted as a
function of mass and width of a hypothetical hybrid meson.


  To make predictions for an eternally inflating "multiverse", one must adopt a
procedure for regulating its divergent spacetime volume. Recently, a new test
of such spacetime measures has emerged: normal observers - who evolve in pocket
universes cooling from hot big bang conditions - must not be vastly outnumbered
by "Boltzmann brains" - freak observers that pop in and out of existence as a
result of rare quantum fluctuations. If the Boltzmann brains prevail, then a
randomly chosen observer would be overwhelmingly likely to be surrounded by an
empty world, where all but vacuum energy has redshifted away, rather than the
rich structure that we observe. Using the scale-factor cutoff measure, we
calculate the ratio of Boltzmann brains to normal observers. We find the ratio
to be finite, and give an expression for it in terms of Boltzmann brain
nucleation rates and vacuum decay rates. We discuss the conditions that these
rates must obey for the ratio to be acceptable, and we discuss estimates of the
rates under a variety of assumptions.


  Recently, short channel effects (SCE) and power consumption dissipation
problems pose big challenges which need imperative actions to be taken to deal
with for field effect transistor to further scale down as semiconductor
technology enters into sub-10nm technology node. From 3nm technology node and
beyond, gate all around field effect transistor steps onto the history stage
attributed to its improved SCE suppressing ability thanks to surrounding gate
structure. Herein, we demonstrate the super electrostatic control ability of a
double-gated nanotube gate all around field effect transistor (DG NT GAAFET) in
comparison with nanotube (NT GAAFET) and nanowire gate all around field effect
transistor (NW GAAFET) with the same device parameters designed. Ion boosts of
62% and 57% have been obtained in DG NT GAAFET in comparison with those of NT
GAAFET and NW GAAFET. Besides, substantially suppressed SCEs have been obtained
in DG NT GAAFET due to enhanced electrostatic control, which are certificated
by improved Ioff, SS, and Ion/Ioff ratio obtained. On the other hand, the Ion
of NT GAAFET is comparable with that of NW GAA-FET. Whereas, its Ioff is 1
order smaller, and SS is almost 2 times smaller compared with those of NW
GAA-FET, manifesting the meliority of nanotube channel structure. In the end,
the robustness of nanotube channel structure, especially double gated one,
against Lg scaling has been verified with TCAD simulation study.


  We summarize the main features of several dark matter candidates in
extra-dimensional theories. In particular, we review Kaluza-Klein (KK)
gravitons in universal extra dimensions and branons in brane-world models. KK
gravitons are superWIMP (superweakly-interacting massive particle) dark matter,
and branons are WIMP (weakly-interacting massive particle) dark matter. Both
dark matter candidates are naturally produced in the correct amount to form
much or all of dark matter.


  The longitudinal response of single semiflexible polymers to sudden changes
in externally applied forces is known to be controlled by the propagation and
relaxation of backbone tension. Under many experimental circumstances,
realized, e.g., in nano-fluidic devices or in polymeric networks or solutions,
these polymers are effectively confined in a channel- or tube-like geometry. By
means of heuristic scaling laws and rigorous analytical theory, we analyze the
tension dynamics of confined semiflexible polymers for various generic
experimental setups. It turns out that in contrast to the well-known linear
response, the influence of confinement on the non-linear dynamics can largely
be described as that of an effective prestress. We also study the free
relaxation of an initially confined chain, finding a surprising superlinear
t^(9/8) growth law for the change in end-to-end distance at short times.


  Location-based mobile social network services such as foursquare and Gowalla
have grown exponentially over the past several years. These location-based
services utilize the geographical position to enrich user experiences in a
variety of contexts, including location-based searching and location-based
mobile advertising. To attract more users, the location-based mobile social
network services provide real-world rewards to the user, when a user checks in
at a certain venue or location. This gives incentives for users to cheat on
their locations. In this report, we investigate the threat of location cheating
attacks, find the root cause of the vulnerability, and outline the possible
defending mechanisms. We use foursquare as an example to introduce a novel
location cheating attack, which can easily pass the current location
verification mechanism (e.g., cheater code of foursquare). We also crawl the
foursquare website. By analyzing the crawled data, we show that automated large
scale cheating is possible. Through this work, we aim to call attention to
location cheating in mobile social network services and provide insights into
the defending mechanisms.


  Using a simple model of a frustrated helimagnet, the critical behavior is
numerically investigated for planar or isotropic spins, and for cases of one or
two chiral order parameters. The helical structure in this model arises from
the competition between exchange interactions of spins of the first two range
orders in one direction (in both directions) of a square lattice. The main
result is that the critical and temperature behavior is primarily determined by
topological defects that are present in all cases. In the case of planar spins,
vortices, fractional vortices and domain walls are present in the system. Their
interaction leads to the appearance of the phase of a chiral spin liquid, or
induces a single first-order transition, and in the vicinity of the Lifshitz
point vortices lead to a reentrant phase transition to the phase with a
collinear quasi-long-range order. When transitions in the chiral and continuous
order parameters are separated in temperature, they are of the 2D Ising and
Kosterlitz-Thouless types correspondingly. In the case of isotropic spins,
so-called $\mathbb{Z}_2$ vortices are present. They do not lead to the
appearance of a phase with long-range or quasi-long-range order in the case of
one chiral order parameter. However, their interaction leads to a sharp change
in the temperature dependence of the correlation length (crossover). In the
case of two chiral parameters, there are long-range chiral order of the Ising
type (chiral spin liquid) and domain walls. However, as a result of the
interaction of vortices and walls, the crossover and chiral transition occur at
the same temperature as a first-order transition.


  We propose a presentation of classical propositional tableaux elaborated by
application of methods that are noteworthy in program design, namely program
derivation with separation of concerns. We start by deriving from a
straightforward specification an algorithm given as a set of recursive
equations for computing all models of a finite set of formulae. Thereafter we
discuss the employment of data structures, mainly with regard to an easily
traceable manual execution of the algorithm. This leads to the kinds of trees
given usually as constituting the tableaux. The whole development strives at
avoiding gaps, both of logical and motivational nature.


  Spreadsheets are software programs which are typically created by end-users
and often used for business-critical tasks. Many studies indicate that errors
in spreadsheets are very common. Thus, a number of vendors offer auditing tools
which promise to detect errors by checking spreadsheets against so-called Best
Practices such as "Don't put constants in fomulae". Unfortunately, it is
largely unknown which Best Practices have which actual effects on which
spreadsheet quality aspects in which settings.
  We have conducted a controlled experiment with 42 subjects to investigate the
question whether observance of three commonly suggested Best Practices is
correlated with desired positive effects regarding correctness and
maintainability: "Do not put constants in formulae", "keep formula complexity
low" and "refer to the left and above". The experiment was carried out in two
phases which covered the creation of new and the modification of existing
spreadsheets. It was evaluated using a novel construction kit for spreadsheet
auditing tools called Spreadsheet Inspection Framework.
  The experiment produced a small sample of directly comparable spreadsheets
which all try to solve the same task. Our analysis of the obtained spreadsheets
indicates that the correctness of "bottom-line" results is not affected by the
observance of the three Best Practices. However, initially correct spreadsheets
with high observance of these Best Practices tend to be the ones whose later
modifications yield the most correct results.


  We introduce the commutators of lepton mass matrices to describe the
phenomenon of lepton flavor mixing, and establish their relations to the
effective Hamiltonians responsible for the propagation of Dirac and Majorana
neutrinos. The determinants of those commutators are invariant under matter
effects, leading to an instructive relationship between the universal
CP-violating parameters in vacuum and in matter. In the scenario of low-energy
(100 MeV \leq E \leq 1 GeV) and medium-baseline (100 km \leq L \leq 400 km)
neutrino experiments, we illustrate the features of lepton flavor mixing and CP
violation. The terrestrial matter effects on CP- and T-violating asymmetries in
\nu_\mu \to \nu_e and $\bar{\nu}_\mu \to \bar{\nu}_e neutrino oscillations are
also discussed. We demonstrate that a relatively pure signal of leptonic CP
violation at the percent level can be established from such medium-baseline
experiments with low-energy neutrino beams.


  Packet loss is a major cause of voice quality degradation in VoIP
transmissions with serious impact on intelligibility and user experience. This
paper describes a system based on a generative adversarial approach, which aims
to repair the lost fragments during the transmission of audio streams. Inspired
by the powerful image-to-image translation capability of Generative Adversarial
Networks (GANs), we propose bin2bin, an improved pix2pix framework to achieve
the translation task from magnitude spectrograms of audio frames with lost
packets, to noncorrupted speech spectrograms. In order to better maintain the
structural information after spectrogram translation, this paper introduces the
combination of two STFT-based loss functions, mixed with the traditional GAN
objective. Furthermore, we employ a modified PatchGAN structure as
discriminator and we lower the concealment time by a proper initialization of
the phase reconstruction algorithm. Experimental results show that the proposed
method has obvious advantages when compared with the current state-of-the-art
methods, as it can better handle both high packet loss rates and large gaps.


  Discriminating between competing explanatory models as to which is more
likely responsible for the growth of a network is a problem of fundamental
importance for network science. The rules governing this growth are attributed
to mechanisms such as preferential attachment and triangle closure, with a
wealth of explanatory models based on these. These models are deliberately
simple, commonly with the network growing according to a constant mechanism for
its lifetime, to allow for analytical results. We use a likelihood-based
framework on artificial data where the network model changes at a known point
in time and demonstrate that we can recover the change point from analysis of
the network. We then use real datasets and demonstrate how our framework can
show the changing importance of network growth mechanisms over time.


  It has long been known that large grounded conducting networks on the surface
of Earth are affected by solar activity and geomagnetic storms. Power networks
are such extensive grounded conductors and are susceptible to geomagnetically
induced currents (GICs). GICs at any specific node in a power network are
assumed to be linearly related to the horizontal vector components of an
induced plane-wave geoelectric field by a pair of network parameters. These
network parameters are not easily measured in the network, but may be estimated
empirically. In this work, we present a new approach of using an ensemble of
network parameters estimates. The ensembles include a huge number of parameter
pair estimates calculated from simultaneously solving pairs of time instances
of the governing GIC equation. Each individual estimate is not the true state
of the system, but a possible state. Taking the ensemble as a whole though
gives the most probable parameter estimate. The most probable parameter
estimate for both network parameters, as defined by their respective ensembles,
is used directly in the modelling of GICs. The ensembles themselves however
allow for further analysis into the nature of GICs. An improvement is seen when
comparing the out-of-sample performance of the ensemble estimates with previous
GIC modelling in the South African power network during the Halloween Storm of
2003. For the first time, it is shown that errors in the GIC modelling chain
are absorbed into the network parameter estimates. Using a range of estimates
from the ensemble, a GIC prediction band is produced. This band corresponds to
an error estimate for predicted GIC. Furthermore, it has been explicitly shown
that estimated network parameters vary with GIC magnitude during an event. This
behaviour is then used to refine the parameter estimation further and allow for
real time dynamic network parameter estimation.


  This report was prepared on behalf of three Energy Frontier Topical Groups of
the Snowmass 2021 Community Planning Exercise. It summarizes the status and
implications of studies of strong interactions in high-energy experiments and
QCD theory. We emphasize the rich landscape and broad impact of these studies
in the decade ahead. Hadronic interactions play a central role in the
high-luminosity Large Hadron Collider (LHC) physics program, and strong
synergies exist between the (HL-)LHC and planned or proposed experiments at the
U.S. Electron-Ion Collider, CERN forward physics experiments, high-intensity
facilities, and future TeV-range lepton and hadron colliders. Prospects for
precision determinations of the strong coupling and a variety of
nonperturbative distribution and fragmentation functions are examined. We also
review the potential of envisioned tests of new dynamical regimes of QCD in
high-energy and high-density scattering processes with nucleon, ion, and photon
initial states. The important role of the high-energy heavy-ion program in
studies of nuclear structure and the nuclear medium, and its connections with
QCD involving nucleons are summarized. We address ongoing and future
theoretical advancements in multi-loop QCD computations, lattice QCD, jet
substructure, and event generators. Cross-cutting connections between
experimental measurements, theoretical predictions, large-scale data analysis,
and high-performance computing are emphasized.


  I present an exactly solvable model of a pseudogap with two zero-energy
fermion modes coupled to each other by a classical source of frequency omega_0
and strength |Delta|. A suitably defined fermion propagator has an infinite
number of poles at frequencies that are multiple integers of omega_0. In the
adiabatic limit, omega_0 << |\Delta|, the situation is qualitatively different
from the static case omega_0=0: the residue of the pole at omega=0 (a remnant
of the bare fermion) vanishes linearly with omega_0, a result that could not be
anticipated by perturbation theory; the multiple poles of the propagator
coalesce into a continuum instead of forming two single poles at +-|Delta|,
which should be interpreted as inhomogeneous broadening of the Bogoliubov
quasiparticles.


  It is shown that the variety of transposed Poisson algebras coincides with
the variety of Gelfand-Dorfman algebras in which the Novikov multiplication is
commutative. The Gr\"obner-Shirshov basis for the transposed Poisson operad is
calculated up to degree 4. Furthermore, we demonstrate that every transposed
Poisson algebra is F-manifold. We verify that the special identities of
GD-algebras hold in transposed Poisson algebras. Finally, we propose a
conjecture stating that every transposed Poisson algebra is special, i.e., can
be embedded into a differential Poisson algebra.


  The repeating FRB 20121102A was localized to a star-forming region in a dwarf
galaxy and found to be co-located with a persistent radio source (PRS). FRB
20190520B is only the second known source sharing phenomenology akin to FRB
20121102A's, with similar burst activity, host galaxy properties, as well as
being associated with a PRS. PRS emission is potentially a calorimeter,
allowing us to estimate the energy output of the central FRB engine.
Independently of FRB studies, PRSs have been found in dwarf galaxies and
interpreted as intermediate mass black holes. To improve our understanding of
such sources associated with dwarf galaxies, it is imperative to increase the
known sample size. Here, we present a search for compact radio sources
coincident with dwarf galaxies, discuss source candidates and planned
strategies to differentiate them between candidate FRB hosts and intermediate
mass black holes.


  We study the gas distribution and kinematics of the inner kpc of six
moderately luminous (43.43$\leq$log$L_{\rm bol}\leq$44.83) nearby ($0.004 \leq
z \leq 0.014$) Seyfert galaxies observed with the Near-infrared Integral Field
Spectrograph (NIFS) in the J(1.25$\mu$m) and K(2.2$\mu$m) bands. We analyse the
most intense emission lines detected on these spectral wavebands: [Fe II]
1.2570 $\mu$m and Pa$\beta$, which trace the ionised gas in the partially and
fully ionised regions, and H$_2$2.1218$\mu$m, that traces the hot ($\sim 2000$
K) molecular gas. The dominant kinematic component is rotation in the disc of
the galaxies, except for the ionised gas in NGC 5899 which shows only weak
signatures of a disc component. We find ionised gas outflow in four galaxies,
while signatures of H$_2$ outflows are seen in three galaxies. The ionised gas
outflows display velocities of a few hundred km\,s$^{-1}$, and their
mass-outflow rates are in the range $0.005 - 12.49$M$_{\odot}$yr$^{-1}$ . Their
kinetic powers correspond to $0.005-0.7$ per cent of the AGN bolometric
luminosities. Besides rotation and outflows signatures in some cases, the H 2
kinematics reveals also inflows in three galaxies. The inflow velocities are
$50-80$km\,s$^{-1}$ and the mass inflow rates are in the range $1 - 9 \times
10^{-4}$M$_{\odot}$yr$^{-1}$ for hot molecular gas. These inflows might be only
the hot skin of the total inflowing gas, which is expected to be dominated by
colder gas. The mass inflow rates are lower than the current accretion rates to
the AGN, and the ionised outflows are apparently disturbing the gas in the
inner kpc.


  One applies the symmetry group theory for study the partial differential
equations of Tzitzeica surfaces theory. One finds infinitesimal symmetries,
Lagrangians and a new solution of Titzeica equation.


  We consider the large time asymptotic behavior of the global solutions to the
initial value problem for the nonlinear damped wave equation with slowly
decaying initial data. When the initial data decay fast enough, it is known
that the solution to this problem converges to the self-similar solution to the
Burgers equation called a nonlinear diffusion wave and its optimal asymptotic
rate is obtained. In this paper, we focus on the case that the initial data
decay more slowly than previous works and derive the corresponding asymptotic
profiles. Moreover, we investigate how the change of the decay rate of the
initial values affect its asymptotic rate.


  We propose an effective online background subtraction method, which can be
robustly applied to practical videos that have variations in both foreground
and background. Different from previous methods which often model the
foreground as Gaussian or Laplacian distributions, we model the foreground for
each frame with a specific mixture of Gaussians (MoG) distribution, which is
updated online frame by frame. Particularly, our MoG model in each frame is
regularized by the learned foreground/background knowledge in previous frames.
This makes our online MoG model highly robust, stable and adaptive to practical
foreground and background variations. The proposed model can be formulated as a
concise probabilistic MAP model, which can be readily solved by EM algorithm.
We further embed an affine transformation operator into the proposed model,
which can be automatically adjusted to fit a wide range of video background
transformations and make the method more robust to camera movements. With using
the sub-sampling technique, the proposed method can be accelerated to execute
more than 250 frames per second on average, meeting the requirement of
real-time background subtraction for practical video processing tasks. The
superiority of the proposed method is substantiated by extensive experiments
implemented on synthetic and real videos, as compared with state-of-the-art
online and offline background subtraction methods.


  We prove that the regular von Neumann subalgebras $B$ of the hyperfinite II_1
factor $R$ satisfying the condition $B'\cap R=Z(B)$ are completely classified
(up to conjugacy by an automorphism of $R$) by the associated discrete measured
groupoid $G$. We obtain a similar classification result for triple inclusions
$A\subset B \subset R$, where $A$ is a Cartan subalgebra in $R$ and the
intermediate von Neumann algebra $B$ is regular in $R$. A key step in proving
these results is to show the vanishing cohomology for the associated cocycle
actions of $G$ on $B$. We in fact prove two very general vanishing cohomology
results for free cocycle actions of amenable discrete measured groupoids on
arbitrary tracial von Neumann algebras $B$, resp. Cartan inclusions $A\subset
B$. Our work provides a unified approach and generalizations to many known
vanishing cohomology and classification results [CFW81], [O85], [ST84], [BG84],
[FSZ88], [P18], etc.


  Many problems in quantum information theory can be vied as interconversion
between resources. In this talk, we apply this view point to state estimation
theory, motivated by the following observations.
  First, a monotone metric takes value between SLD and RLD Fisher metric. This
is quite analogous to the fact that entanglement measures are sandwiched by
distillable entanglement and entanglement cost. Second, SLD add RLD are
mutually complement via purification of density matrices, but its operational
meaning was not clear.
  To find a link between these observations, we define reverse estimation
problem, or simulation of quantum state family by probability distribution
family, proving that RLD Fisher metric is a solution to local reverse
estimation problem of quantum state family with 1-dim parameter. This result
gives new proofs of some known facts and proves one new fact about monotone
distances.
  We also investigate information geometry of RLD, and reverse estimation
theory of a multi-dimensional parameter family.


  The Alber equation is a phase-averaged second-moment model for the statistics
of a sea state, which recently has been attracting renewed attention. We extend
it in two ways: firstly, we derive a generalized Alber system starting from a
system of nonlinear Schr\"odinger equations, which contains the classical Alber
equation as a special case but can also describe crossing seas, i.e. two
wavesystems with different wavenumbers crossing. (These can be two completely
independent wavenumbers, i.e. in general different directions and different
moduli.) We also derive the associated 2-dimensional scalar instability
condition. This is the first time that a modulation instability condition
applicable to crossing seas has been systematically derived for general
spectra. Secondly, we use the classical Alber equation and its associated
instability condition to quantify how close a given non-parametric spectrum is
to being modulationally unstable. We apply this to a dataset of 100
non-parametric spectra provided by the Norwegian Meteorological Institute, and
find the vast majority of realistic spectra turn out to be stable, but three
extreme sea states are found to be unstable (out of 20 sea states chosen for
their severity). Moreover, we introduce a novel "proximity to instability"
(PTI) metric, inspired by the stability analysis. This is seen to correlate
strongly with the steepness and Benjamin-Feir Index (BFI) for the sea states in
our dataset (>85% Spearman rank correlation). Furthermore, upon comparing with
phase-resolved broadband Monte Carlo simulations, the kurtosis and probability
of rogue waves for each sea state are also seen to correlate well with its PTI
(>85% Spearman rank correlation).


  In this manuscript, we investigate the oscillatory behaviour of the
anisotropy in the diagonal Bianchi-I spacetimes. Our starting point is a
simplification of Einstein's equations using only observable or physical
variables. As a consequence, we are able to: (a) Prove general results
concerning the existence of oscillations of the anisotropy in the primordial
and the late-time universe. For instance, in the expanding scenario, we show
that a past weakly mixmaster behaviour (oscillations as we approach the Kasner
solutions) might appear even with no violation of the usual energy conditions,
while in the future, the pulsation (oscillations around isotropic solutions)
seems to be most favored; (b) Determine a large scheme for deriving classes of
physically motivated exact solutions, and we give some (including the general
barotropic perfect fluid and the magnetic one); (c) Understand the physical
conditions for the occurrence of the isotropization or anisotropization during
the cosmological evolution; (d) Understand how anisotropy and energy density
are converted one into another. In particular, we call attention to the
presence of a residue in the energy density in a late-time isotropic universe
coming from its past anisotropic behaviour.


  Machine learning in medical imaging during clinical routine is impaired by
changes in scanner protocols, hardware, or policies resulting in a
heterogeneous set of acquisition settings. When training a deep learning model
on an initial static training set, model performance and reliability suffer
from changes of acquisition characteristics as data and targets may become
inconsistent. Continual learning can help to adapt models to the changing
environment by training on a continuous data stream. However, continual manual
expert labelling of medical imaging requires substantial effort. Thus, ways to
use labelling resources efficiently on a well chosen sub-set of new examples is
necessary to render this strategy feasible.
  Here, we propose a method for continual active learning operating on a stream
of medical images in a multi-scanner setting. The approach automatically
recognizes shifts in image acquisition characteristics - new domains -, selects
optimal examples for labelling and adapts training accordingly. Labelling is
subject to a limited budget, resembling typical real world scenarios. To
demonstrate generalizability, we evaluate the effectiveness of our method on
three tasks: cardiac segmentation, lung nodule detection and brain age
estimation. Results show that the proposed approach outperforms other active
learning methods, while effectively counteracting catastrophic forgetting.


  We consider the scaling laws, second-order statistics and entropy of the
consumed energy of metropolis cities which are hybrid complex systems
comprising social networks, engineering systems, agricultural output, economic
activity and energy components. We abstract a city in terms of two fundamental
variables; $s$ resource cells (of unit area) that represent energy-consuming
geographic or spatial zones (e.g. land, housing or infrastructure etc.) and a
population comprising $n$ mobile units that can migrate between these cells. We
show that with a constant metropolis area (fixed $s$), the variance and entropy
of consumed energy initially increase with $n$, reach a maximum and then
eventually diminish to zero as saturation is reached. These metrics are
indicators of the spatial mobility of the population. Under certain situations,
the variance is bounded as a quadratic function of the mean consumed energy of
the metropolis. However, when population and metropolis area are endogenous,
growth in the latter is arrested when $n\leq\frac{s}{2}\log(s)$ due to
diminished population density. Conversely, the population growth reaches
equilibrium when $n\geq {s}\log{n}$ or equivalently when the aggregate of both
over-populated and under-populated areas is large. Moreover, we also draw the
relationship between our approach and multi-scalar information, when economic
dependency between a metropolis's sub-regions is based on the entropy of
consumed energy. Finally, if the city's economic size (domestic product etc.)
is proportional to the consumed energy, then for a constant population density,
we show that the economy scales linearly with the surface area (or $s$).


  Let $X$ be a real or complex Banach space and $T_t:X\to X$ is a power bounded
operator (or a $C_0$-semigroup). If there exists a "occasionally" attracting
compact subset K (for each x$ in unit ball $\liminf_n \rho(T^n x, K)=0$ then
there exists attracting finite-dimensional subspace $L$ (for each x in X
$\lim_n \rho(T^n x, L)=0$. Also we define the compact-supercyclicity. Each
infinity-dimentional $X$ has no compact-supercyclic isometries. If $T$ is a
supercyclic and power bounded that $T^nx$ vanishes for each $x$.


  Any continuous action of SL(n,Z), where n > 2, on a r-dimensional mod 2
homology sphere factors through a finite group action if r < n - 1. In
particular, any continuous action of SL(n+2,Z) on the n-dimensional sphere
factors through a finite group action.


  Instruction tuning enables language models to more effectively generalize and
better follow user intent. However, obtaining instruction data is costly and
challenging. Prior work employs methods such as expensive human annotation,
crowd-sourced datasets with alignment issues, and generating noisy examples via
LLMs. We introduce the LongForm-C dataset, which is created by reverse
instructions. We generate instructions via LLMs for human-written corpus
examples using reverse instructions. First we select a diverse set of
human-written documents from corpora such as C4 and Wikipedia; then we generate
instructions for these documents via LLMs. This approach provides a cheaper and
cleaner instruction-tuning dataset with natural output and one suitable for
long text generation. Our models outperform 10x larger language models without
instruction tuning on tasks such as story/recipe generation and long-form
question answering. Moreover, LongForm models outperform prior
instruction-tuned models such as FLAN-T5 and Alpaca by a large margin, and
improve language understanding capabilities further. Finally, our models can
effectively follow and answer multilingual instructions; we demonstrate this
for news generation. We publicly release our data and models:
https://github.com/akoksal/LongForm.


  We introduce a picture to analyze the density matrix renormalization group
(DMRG) numerical method from a quantum information perspective. This leads us
to introduce some modifications for problems with periodic boundary conditions
in which the results are dramatically improved. The picture also explains some
features of the method in terms of entanglement and teleportation.


  Extended gauge models and the Randall-Sundrum model with extra-dimension
predict the existence of TeV-mass resonances. The LHC potential for a five
sigma level discovery was investigated as described in this document. Final
states containing large invariant mass di-muons from ${Z}^{\prime}$ and the RS1
graviton were studied. The possibility of discriminating between different
${Z}^{\prime}$ model by measuring the muon forward-backward asymmetry was
investigated. The determination of the spin of the resonance is also discussed.


  We study the fully non-adiabatic tidal response of a uniformly rotating
unevolved 20 Msun star to the dominant l=m=2 component of the companion's
perturbing potential. This is done numerically with a 2D implicit finite
difference scheme. We assume the star is rotating slowly, so that the
centrifugal force can be neglected, but the Coriolis force is taken fully into
account. We study the low frequency `inertial' regime where the tidal
oscillation frequency in the frame corotating with the star is less than twice
the stellar spin rate. In this frequency range inertial modes are excited in
the convective core which can interact with rotationally modified g- or r-modes
in the radiative envelope and cause significant strengthening of the tidal
interaction. Resonant interaction with quasi-toroidal (r-)modes in slightly
super-synchronous stars causes efficient spin down towards corotation.


  Motivated by the recent investigations given in [25] and the fact that
Bernoulli probability-type models were often used in the study on some problems
in theory of compressive sensing, here we define and study the complex-valued
discrete random variables $\widetilde{X}_l(m,N)$ ($0\le l\le N-1$, $1\le m\le
N$). Each of these random variables is defined as a linear combination of $N$
independent identically distributed $0-1$ Bernoulli random variables. We prove
that for $l\not=0$, $\widetilde{X}_l(m,N)$ is the zero-mean random variable,
and we also determine the variance of $\widetilde{X}_l(m,N)$ and its real and
imaginary parts. Notice that $\widetilde{X}_l(m,N)$ belongs to the class of
sub-Gaussian random variables that are significant in some areas of theory of
compressive sensing. In particular, we prove some probability estimates for the
mentioned random variables. These estimates are used to establish the upper
bounds of the sub-Gaussian norm of their real and imaginary parts. We believe
that our results should be implemented in certain applications of sub-Gaussian
random variables for solving some problems in compressive sensing of sparse
signals.


  We study the spectral properties of a charged particle confined to a
two-dimensional plane and submitted to homogeneous magnetic and electric fields
and an impurity potential. We use the method of complex translations to prove
that the life-times of resonances induced by the presence of electric field are
at least Gaussian long as the electric field tends to zero.


  Sizeable primordial curvature perturbations needed to seed a population of
primordial black holes (PBHs) will be accompanied by a scalar-induced
gravitational wave signal that can be detectable by pulsar timing arrays (PTA).
We derive conservative bounds on the amplitude of the scalar power spectrum at
the PTA frequencies and estimate the implied constraints on the PBH abundance.
We show that only a small fraction of dark matter can consist of stellar mass
PBHs when the abundance is calculated using threshold statistics. The strength
and the shape of the constraint depend on the shape of the power spectrum and
the nature of the non-Gaussianities. We find that constraints on the PBH
abundance arise in the mass range $0.1-10^3\, M_{\odot}$, with the sub-solar
mass range being constrained only for narrow curvature power spectra. These
constraints are softened when positive non-Gaussianity is introduced and can be
eliminated when $f_{\rm NL} \gtrsim 5$. On the other hand, if the PBH abundance
is computed via the theory of peaks, the PTA constraints on PBHs are
significantly relaxed, signalling once more the theoretical uncertainties in
assessing the PBH abundance. We further discuss how strong positive
non-Gaussianites can allow for heavy PBHs to potentially seed supermassive BHs.


  We study the collisional processes that can lead to thermalization in
one-dimensional systems. For two body collisions excitations of transverse
modes are the prerequisite for energy exchange and thermalzation. At very low
temperatures excitations of transverse modes are exponentially suppressed,
thermalization by two body collisions stops and the system should become
integrable. In quantum mechanics virtual excitations of higher radial modes are
possible. These virtually excited radial modes give rise to effective
three-body velocity-changing collisions which lead to thermalization. We show
that these three-body elastic interactions are suppressed by pairwise quantum
correlations when approaching the strongly correlated regime. If the relative
momentum $k$ is small compared to the two-body coupling constant $c$ the
three-particle scattering state is suppressed by a factor of $(k/c)^{12}$,
which is proportional to $\gamma ^{12}$, that is to the square of the
three-body correlation function at zero distance in the limit of the
Lieb-Liniger parameter $\gamma \gg 1$. This demonstrates that in one
dimensional quantum systems it is not the freeze-out of two body collisions but
the strong quantum correlations which ensures absence of thermalization on
experimentally relevant time scales.


  We compute the triply graded Khovanov-Rozansky homology of a family of links,
including positive torus links and $\operatorname{Sym}^l$-colored torus knots.


  Very compact 70 MeV pulse race-track microtron is under construction now. To
acquire outputs of beam-current transformers on every orbit and pulses of high
voltage and RF field a distributed multi-channel beam diagnostic system was
developed. Each acquisition controller consists of four fast differential
amplifiers and one DSP-based micro-controller with on-chip ADC and CAN-bus
controller. Each amplifier is coupled with beam-current transformer and has
bandwidth of up to 150MHz and gain of up to 10. One of four channels is
acquired during a measurement cycle. Another channel could be selected between
two following pulses. All the controllers are connected via optically coupled
CAN-bus with a host diskless PC running under Linux with the RTLinux extension.
Dedicated software of the system consists of low level acquisition software for
DSP, network software for controllers and host PC, application software for PC
to present date for operator and control system. Standard CAN application
layers were considered but refused because of the closed character of the whole
system and centralised synchronisation of the whole system. Dedicated software
of the system consists from low level acquisition software for DSP, network
software for controllers and host PC, application software for PC to present
date for operator and control system. Standard CAN application layers were
considered but refused because of closed character of the whole system and
centralised synchronisation of the whole system.


  Reionization, the only phase transition in the Universe since recombination,
is a key event in the cosmic history of baryonic matter. We derive, in the
context of the large-scale bias expansion, the imprints of the epoch of
reionization in the large-scale distribution of galaxies, and identify two
contributions of particular importance. First, the Compton scattering of CMB
photons off the free electrons lead to a drag force on the baryon fluid. This
drag induces a relative velocity between baryons and CDM which is of the same
order of magnitude as the primordially-induced relative velocity, and enters in
the evolution of the relative velocity as calculated by Boltzmann codes. This
leads to a unique contribution to galaxy bias involving the matter velocity
squared. The second important effect is a modulation of the galaxy density by
the ionizing radiation field through radiative-transfer effects, which is
captured in the bias expansion by so-called higher-derivative terms. We
constrain both of these imprints using the power spectrum of the BOSS DR12
galaxy sample. While they do not lead to a shift in the baryon acoustic
oscillation scale, including these terms is important for unbiased cosmology
constraints from the shape of the galaxy power spectrum.


  We introduce Yetter-Drinfeld modules over a weak Hopf algebra $H$, and show
that the category of Yetter-Drinfeld modules is isomorphic to the center of the
category of $H$-modules. The categories of left-left, left-right, right-left
and right-right Yetter-Drinfeld modules are isomorphic as braided monoidal
categories. Yetter-Drinfeld modules can be viewed as weak Doi-Hopf modules,
and, a fortiori, as weak entwined modules. If $H$ is finitely generated and
projective, then we introduce the Drinfeld double using duality results between
entwining structures and smash product structures, and show that the category
of Yetter-Drinfeld modules is isomorphic to the category of modules over the
Drinfeld double.


  We present the analytic computation of all the planar master integrals which
contribute to the two-loop scattering amplitudes for Higgs$\to 3$ partons, with
full heavy-quark mass dependence. These are relevant for the NNLO corrections
to fully inclusive Higgs production and to the NLO corrections to Higgs
production in association with a jet, in the full theory. The computation is
performed using the differential equations method. Whenever possible, a basis
of master integrals that are pure functions of uniform weight is used. The
result is expressed in terms of one-fold integrals of polylogarithms and
elementary functions up to transcendental weight four. Two integral sectors are
expressed in terms of elliptic functions. We show that by introducing a
one-dimensional parametrization of the integrals the relevant second order
differential equation can be readily solved, and the solution can be expressed
to all orders of the dimensional regularization parameter in terms of iterated
integrals over elliptic kernels. We express the result for the elliptic sectors
in terms of two and three-fold iterated integrals, which we find suitable for
numerical evaluations. This is the first time that four-point multiscale
Feynman integrals have been computed in a fully analytic way in terms of
elliptic functions.


  We discuss the recent derivation of the three-loop ${\cal O}(\alpha\alpha_s)$
contribution to the Higgs boson production cross section via gluon fusion
arising from diagrams with light quarks, using an effective theory approach. We
show results for the updated prediction of this process accounting for all the
new theoretical calculations and the newest MSTW PDFs.


  We investigate the impact of realistic 3D hydrodynamical model stellar
atmospheres on the determination of elemental abundances in the carbon-rich,
hyper iron-poor stars HE0107-5240 and HE1327-2326. We derive the chemical
compositions of the two stars by means of a detailed 3D analysis of spectral
lines under the assumption of local thermodynamic equilibrium (LTE). The lower
temperatures of the line-forming regions of the hydrodynamical models cause
changes in the predicted spectral line strengths. In particular we find the 3D
abundances of C, N, and O to be lower by ~ -0.8 dex (or more) than estimated
from a 1D analysis. The 3D abundances of iron-peak elements are also decreased
but by smaller factors (~ -0.2 dex). We caution however that the neglected
non-LTE effects might actually be substantial for these metals. We finally
discuss possible implications for studies of early Galactic chemical evolution.


  Improving and extending recent results of the author, we conditionally
estimate exponential sums with Dirichlet coefficients of L-functions, both over
all integers and over all primes in an interval. In particular, we establish
new conditional results on exponential sums with Hecke eigenvalues and squares
of Hecke eigenvalues over primes. We employ these estimates to improve our
recent result on squares of Hecke eigenvalues at Piatetski-Shapiro primes under
the Riemann Hypothesis for symmetric square L-functions for Hecke eigenforms.


  The limited velocity in a geometry of Lorentzian signature, seem to prevent
the universe to reach thermodynamic equilibrium as suggested by the cosmic
microwave background. Thus it was suggested that the universe which was
initially minuscule has reached a more considerable radius in a short duration
by a process known as cosmic inflation. However, to drive such a process have
led to the suggestion of an ad-hoc scalar field the inflaton, which has no
purpose in nature other than driving the cosmic inflation field and then
stopping it once the universe reached the right size. In a recent paper it was
shown that rapid expansion can occur without postulating an inflation by
following Hawking's suggestion and assuming that primordially the metric of the
universe had an Euclidean signature, in which case velocity is not limited and
thermalization and rapid expansion are derived without the need to assume an
ad-hoc field. However, while in the previous work emphasis was put on the
dynamics and physical statistics of the particles in a Euclidean space vs.
Lorentzian space in which both spaces were given. No mathematical model was
given regarding the development of current Lorentzian space-time from the early
Euclidean space-time, and how fundamental problems such as the space-time
singularity and the homogeneity of the CMB can be solved in the hybrid
Euclidean-Lorentzian picture. This lacuna is to be rectified in the current
paper.


  The interplay of non-trivial band topology and magnetism gives rise to a
series of exotic quantum phenomena, such as the emergent quantum anomalous Hall
(QAH) effect and topological magnetoelectric effect. Many of these quantum
phenomena have local manifestations when the global symmetry is broken. Here,
we report local signatures of the thickness dependent topology in intrinsic
magnetic topological insulator MnBi$_2$Te$_4$(MBT), using scanning tunneling
microscopy and spectroscopy on molecular beam epitaxy grown MBT thin films. A
thickness-dependent band gap with an oscillatory feature is revealed, which we
reproduce with theoretical calculations. Our theoretical results indicate a
topological quantum phase transition beyond a film thickness of one monolayer,
with alternating QAH and axion insulating states for even and odd layers,
respectively. At an even-odd layer step, a localized gapped electronic state is
observed, in agreement with an axion insulator edge state that results from a
phase transition across the step. The demonstration of thickness-dependent
topological properties highlights the role of nanoscale control over novel
quantum states, reinforcing the necessity of thin film technology in quantum
information science applications.


  Adsorption of 1/3 monolayer of Sn on a heavily-doped p-type Si(111) substrate
results in the formation of a hole-doped Mott insulator, with electronic
properties that are remarkably similar to those of the high-Tc copper oxide
compounds. In this work, we show that the maximum hole-density of this system
increases with decreasing domain size as the area of the Mott insulating
domains approaches the nanoscale regime. Concomitantly, scanning tunneling
spectroscopy data at 4.4 K reveal an increasingly prominent zero bias anomaly
(ZBA). We consider two different scenarios as potential mechanisms for this
ZBA: chiral d_(x^2 -y^2 )+ id_xy wave superconductivity and a dynamical Coulomb
blockade (DCB) effect. The latter arises due to the formation of a resistive
depletion layer between the nano-domains and the substrate. Both models fit the
tunneling spectra with weaker ZBAs, while the DCB model clearly fits better to
spectra recorded at higher temperatures or from the smallest domains with the
strongest ZBA. Consistently, STS spectra from the lightly-doped substrates
display oscillatory behavior that can be attributed to conventional Coulomb
staircase behavior, which becomes stronger for smaller sized domains. We
conclude that the ZBA is predominantly due to a DCB effect, while a
superconducting instability is absent or a minor contributing factor.


  We report on the magnetoelectric dynamics in the linear magnetoelectric
antiferromagnet TbPO$_4$ studied by broadband dielectric spectroscopy. For the
phase transition into the magnetoelectric antiferromagnetic phase at $T_{N}
\approx 2.3$ K, a finite magnetic field $H$ induces critical behavior in the
quasi-static permittivity $\varepsilon'$. Plotting the corresponding anomaly as
function of $T/T_N(H)$, we observe the scaling behavior $\Delta \varepsilon'
\propto H^2$, a clear fingerprint of linear magnetoelectric antiferromagnets.
Above the phase transition, we find a critical slowing down of the ferroic
fluctuations in finite magnetic field. This behaviour can be understood via a
magnetic-field-induced relaxational response that resembles the soft-mode
behaviour in canonical ferroelectrics and multiferroics.


  We consider a distributed learning setup where a network of agents
sequentially access realizations of a set of random variables with unknown
distributions. The network objective is to find a parametrized distribution
that best describes their joint observations in the sense of the
Kullback-Leibler divergence. Apart from recent efforts in the literature, we
analyze the case of countably many hypotheses and the case of a continuum of
hypotheses. We provide non-asymptotic bounds for the concentration rate of the
agents' beliefs around the correct hypothesis in terms of the number of agents,
the network parameters, and the learning abilities of the agents. Additionally,
we provide a novel motivation for a general set of distributed Non-Bayesian
update rules as instances of the distributed stochastic mirror descent
algorithm.


  We present a protocol for quantum fingerprinting that is ready to be
implemented with current technology and is robust to experimental errors. The
basis of our scheme is an implementation of the signal states in terms of a
coherent state in a superposition of time-bin modes. Experimentally, this
requires only the ability to prepare coherent states of low amplitude, and to
interfere them in a balanced beam splitter. The states used in the protocol are
arbitrarily close in trace distance to states of $\mathcal{O}(\log_2 n)$
qubits, thus exhibiting an exponential separation in communication complexity
compared to the classical case. The protocol uses a number of optical modes
that is proportional to the size $n$ of the input bit-strings, but a total mean
photon number that is constant and independent of $n$. Given the expended
resources, our protocol achieves a task that is provably impossible using
classical communication only. In fact, even in the presence of realistic
experimental errors and loss, we show that there exist a large range of input
sizes for which our quantum protocol requires communication that can be more
than two orders of magnitude smaller than a classical fingerprinting protocol.


  Controversy exists on whether differentiable neural architecture search
methods discover wiring topology effectively. To understand how wiring topology
evolves, we study the underlying mechanism of several existing differentiable
NAS frameworks. Our investigation is motivated by three observed searching
patterns of differentiable NAS: 1) they search by growing instead of pruning;
2) wider networks are more preferred than deeper ones; 3) no edges are selected
in bi-level optimization. To anatomize these phenomena, we propose a unified
view on searching algorithms of existing frameworks, transferring the global
optimization to local cost minimization. Based on this reformulation, we
conduct empirical and theoretical analyses, revealing implicit inductive biases
in the cost's assignment mechanism and evolution dynamics that cause the
observed phenomena. These biases indicate strong discrimination towards certain
topologies. To this end, we pose questions that future differentiable methods
for neural wiring discovery need to confront, hoping to evoke a discussion and
rethinking on how much bias has been enforced implicitly in existing NAS
methods.


  Transition metal impurities such as nickel, copper, and iron, in solid-state
materials like silicon have a significant impact on the electrical performance
of integrated circuits and solar cells. To study the impact of copper
impurities inside bulk silicon on the electrical properties of the material,
one needs to understand the configurational space of copper atoms incorporated
inside the silicon lattice. In this work, we performed ReaxFF reactive force
field based molecular dynamics simulations, studying different configurations
of individual and crystalline copper atoms inside bulk silicon by looking at
the diffusional behavior of copper in silicon. The ReaxFF Cu/Si parameter set
was developed by training against DFT data, including the energy barrier for an
individual Cu-atom inside a silicon lattice. We found that the diffusion of
copper atoms has a direct relationship with the temperature. Moreover, it is
also shown that individual copper atoms start to clusterize inside bulk silicon
at elevated temperatures. Our simulation results provide a comprehensive
picture of the effects of temperature and copper concentration on the
crystallization of individual copper inside silicon lattice. Finally, the
stress-strain relationship of Cu/Si compounds under uniaxial tensile loading
have been obtained. Our results indicate a decrease in the elastic modulus with
increasing level of Cu-impurity concentration. We observe spontaneous
microcracking of the Si during the stress-strain tests as a consequence of the
formation of a small Cu clusters adjacent to the Si surface.


  Knowledge graphs (KGs) have emerged as a prominent data representation and
management paradigm. Being usually underpinned by a schema (e.g., an ontology),
KGs capture not only factual information but also contextual knowledge. In some
tasks, a few KGs established themselves as standard benchmarks. However, recent
works outline that relying on a limited collection of datasets is not
sufficient to assess the generalization capability of an approach. In some
data-sensitive fields such as education or medicine, access to public datasets
is even more limited. To remedy the aforementioned issues, we release PyGraft,
a Python-based tool that generates highly customized, domain-agnostic schemas
and KGs. The synthesized schemas encompass various RDFS and OWL constructs,
while the synthesized KGs emulate the characteristics and scale of real-world
KGs. Logical consistency of the generated resources is ultimately ensured by
running a description logic (DL) reasoner. By providing a way of generating
both a schema and KG in a single pipeline, PyGraft's aim is to empower the
generation of a more diverse array of KGs for benchmarking novel approaches in
areas such as graph-based machine learning (ML), or more generally KG
processing. In graph-based ML in particular, this should foster a more holistic
evaluation of model performance and generalization capability, thereby going
beyond the limited collection of available benchmarks. PyGraft is available at:
https://github.com/nicolas-hbt/pygraft.


  We report the results on Big Bang Nucleosynthesis (BBN) based on an updated
code, with accuracy of the order of 0.1% on He4 abundance, compared with the
predictions of other recent similar analysis. We discuss the compatibility of
the theoretical results, for vanishing neutrino chemical potentials, with the
observational data. Bounds on the number of relativistic neutrinos and baryon
abundance are obtained by a likelihood analysis. We also analyze the effect of
large neutrino chemical potentials on primordial nucleosynthesis, motivated by
the recent results on the Cosmic Microwave Background Radiation spectrum. The
BBN exclusion plots for electron neutrino chemical potential and the effective
number of relativistic neutrinos are reported. We find that the standard BBN
seems to be only marginally in agreement with the recent BOOMERANG and MAXIMA-1
results, while the agreement is much better for degenerate BBN scenarios for
large effective number of neutrinos, N_\nu \sim 10.


  We combined the bond order length strength and bond charge models and the
topological concept to obtain the nonbonding, bonding, and antibonding states
of the T type WTe$_2$/MoS$_2$ heterostructure.The energy band projection method
and electronic information entropy are remarkable approaches for analyzing the
electronic properties of various structures based on DFT calculations. This
study provides a new way to describe the electronic properties of T type
heterostructures and calculate the electron and bonding state probabilities.


  We present an adaptive-order positivity-preserving conservative
finite-difference scheme that allows a high-order solution away from shocks and
discontinuities while guaranteeing positivity and robustness at
discontinuities. This is achieved by monitoring the relative power in the
highest mode of the reconstructed polynomial and reducing the order when the
polynomial series no longer converges. Our approach is similar to the
multidimensional optimal order detection (MOOD) strategy, but differs in
several ways. The approach is a priori and so does not require retaking a time
step. It can also readily be combined with positivity-preserving flux limiters
that have gained significant traction in computational astrophysics and
numerical relativity. This combination ultimately guarantees a physical
solution both during reconstruction and time stepping. We demonstrate the
capabilities of the method using a standard suite of very challenging 1d, 2d,
and 3d general relativistic magnetohydrodynamics test problems.


  This is the first in a series of papers that deals with duality statements
such as Mukai-duality (T-duality, from algebraic geometry) and the Baum-Connes
conjecture (from operator $K$-theory). These dualities are expressed in terms
of categories of modules. In this paper, we develop a general framework needed
to describe these dualities. In various geometric contexts, e.g. complex
geometry, generalized complex geometry, and noncommutative geometry, the
geometric structure is encoded in a certain differential graded algebra. We
develop the module theory of such differential graded algebras in such a way
that we can recover the derived category of coherent sheaves on a complex
manifold. In this paper and ones to follow we apply this to stating and proving
the duality statements mentioned above. After developing the general framework,
we look at a (complex) Lie algebroid $\A\to T_\cx X$. One can then consider our
analogue of the derived category of coherent sheaves, integrable with respect
to the Lie algebroid. We then establish a (Serre) duality theorem for
"elliptic" Lie algebroids and for noncommutative tori.


  As artificial intelligence (AI) continues advancing, ensuring positive
societal impacts becomes critical, especially as AI systems become increasingly
ubiquitous in various aspects of life. However, developing "AI for good" poses
substantial challenges around aligning systems with complex human values.
Presently, we lack mature methods for addressing these challenges. This article
presents and evaluates the Positive AI design method aimed at addressing this
gap. The method provides a human-centered process to translate wellbeing
aspirations into concrete practices. First, we explain the method's four key
steps: contextualizing, operationalizing, optimizing, and implementing
wellbeing supported by continuous measurement for feedback cycles. We then
present a multiple case study where novice designers applied the method,
revealing strengths and weaknesses related to efficacy and usability. Next, an
expert evaluation study assessed the quality of the resulting concepts, rating
them moderately high for feasibility, desirability, and plausibility of
achieving intended wellbeing benefits. Together, these studies provide
preliminary validation of the method's ability to improve AI design, while
surfacing areas needing refinement like developing support for complex steps.
Proposed adaptations such as examples and evaluation heuristics could address
weaknesses. Further research should examine sustained application over multiple
projects. This human-centered approach shows promise for realizing the vision
of 'AI for Wellbeing' that does not just avoid harm, but actively benefits
humanity.


  Small bodies in the solar system are conventionally classified into asteroids
and comets. However, it is recently found that a small number of objects can
exhibit properties of both asteroids and comets. Some are more consistent with
asteroids despite episodic ejections and are labeled as "active asteroids",
while some might be aging comets with depleting volatiles. Ejecta produced by
active asteroids and/or dormant comets are potentially detectable as meteor
showers at the Earth if they are in Earth-crossing orbits, allowing us to
retrieve information about the historic activities of these objects. Meteor
showers from small bodies with low and/or intermittent activities are usually
weak, making shower confirmation and parent association challenging. We show
that statistical tests are useful for identifying likely parent-shower pairs.
Comprehensive analyses of physical and dynamical properties of meteor showers
can lead to deepen understanding on the history of their parents. Meteor
outbursts can trace to recent episodic ejections from the parents, and "orphan"
showers may point to historic disintegration events. The flourish of NEO and
meteor surveys during the past decade has produced a number of high-confidence
parent-shower associations, most have not been studied in detail. More work is
needed to understand the formation and evolution of these parent-shower pairs.


  A controlled sweeping process with prox-regular set, $W^{1,2}$-controls, and
separable endpoints constraints is considered in this paper. Existence of
optimal solutions is established and local optimality conditions are derived
via strong converging continuous approximations that entirely reside in the
interior of the prox-regular set. Consequently, these results are expressed in
terms of new subdifferentials for the original data that are strictly smaller
than the standard Clarke and Mordukhovich subdifferentials.