  In this paper, we present a deduction of swallow water equations in the
presence of vegetation based on spatial averaging techniques starting from the
general principles of conservation of mass and momentum. For this purpose, we
worked in the hydrostatic approximation of the pressure field and we considered
certain hypotheses of kinematic and topographical nature and assumptions on the
structure of the vegetation. Some elements of differential geometry necessary
to facilitate the reading of the paper can be found in the Appendix.


  AT2018cow is the most extensively observed and widely studied fast blue
optical transient to date; its unique observational properties challenge all
existing standard models. In this paper, we model the luminosity evolution of
the optical, soft X-ray, and hard X-ray emission, as well as the X-ray spectrum
of AT2018cow with a magnetar-centered engine model. We consider a two-zone
model with a striped magnetar wind in the interior and an expanding ejecta
outside. The soft and hard X-ray emission of AT2018cow can be explained by the
leakage of high-energy photons produced by internal gradual magnetic
dissipation in the striped magnetar wind, while the luminous thermal UV/optical
emission results from the thermalization of the ejecta by the captured photons.
The two-component energy spectrum yielded by our model with a quasi-thermal
component from the optically thick region of the wind superimposed on an
optically thin synchrotron component well reproduces the X-ray spectral shape
of AT2018cow. The Markov Chain Monte Carlo fitting results suggest that in
order to explain the very short rise time to peak of the thermal optical
emission, a low ejecta mass $M_{\rm ej}\approx0.1~M_\odot$ and high ejecta
velocity $v_{\rm SN}\approx0.17c$ are required. A millisecond magnetar with
$P_0\approx3.7~\rm ms$ and $B_p\approx2.4\times10^{14}~\rm G$ is needed to
serve as the central engine of AT2018cow.


  Let $f(m,n)$ be the number of primitive lattice triangulations of $m\times n$
rectangle. We compute the limits $\lim_n f(m,n)^{1/n}$ for $m=2$ and $3$. For
$m=2$ we obtain the exact value of the limit which is equal to
$(611+\sqrt{73})/36$. For $m=3$, we express the limit in terms of certain
Fredholm's integral equation on generating functions. This provides a
polynomial time algorithm for computation of the limit with any given precision
(polynomial with respect the the number of computed digits).


  Rover localization is one of the perquisites for large scale rover
exploration. In NASA's Mars 2020 mission, the Ingenuity helicopter is carried
together with the rover, which is capable of obtaining high-resolution imagery
of Mars terrain, and it is possible to perform localization based on
aerial-to-ground (A2G) imagery correspondence. However, considering the
low-texture nature of the Mars terrain, and large perspective changes between
UAV and rover imagery, traditional image matching methods will struggle to
obtain valid image correspondence. In this paper we propose a novel pipeline
for Mars rover localization. An algorithm combing image-based rock detection
and rock distribution pattern matching is used to acquire A2G imagery
correspondence, thus establishing the rover position in a UAV-generated ground
map. Feasibility of this method is evaluated on sample data from a Mars
analogue environment. The proposed method can serve as a reliable assist in
future Mars missions.


  Black hole no-hair theorems are proven using inequalities that govern the
radial dependence of spherically symmetric configurations of matter fields. In
this paper, we analyze the analogous inequalities for geometries dual to
renormalization group flows via the AdS/CFT correspondence. These inequalities
give much useful information about the qualitative properties of such flows.
For Poincare invariant flows, we show that generic flows of relevant or
irrelevant operators lead to singular geometries. For the case of irrelevant
operators, this leads to an apparent conflict with Polchinski's decoupling
theorem, and we offer two possible resolutions to this problem.


  The Synchronic Web is a highly scalable notary infrastructure that provides
tamper-evident data provenance for historical web data. In this document, we
describe the applicability of this infrastructure for web archiving across
three envisioned stages of adoption. We codify the core mechanism enabling the
value proposition: a procedure for splitting and merging cryptographic
information fluidly across blockchain-backed ledgers. Finally, we present
preliminary performance results that indicate the feasibility of our approach
for modern web archiving scales.


  The $\phi^4$ model is coupled to an impurity in a way that preserves one-half
of the BPS property. This means that the antikink-impurity bound state is still
a BPS solution, i.e., a zero-pressure solution saturating the topological
energy bound. The kink-impurity bound state, on the other hand, does not
saturate the bound, in general. We found that, although the impurity breaks
translational invariance, it is, in some sense, restored in the BPS sector
where the energy of the antikink-impurity solution does not depend on their
mutual distance. This is reflected in the existence of a generalised
translational symmetry and a zero mode. We also investigate scattering
processes. In particular, we compare the antikink-impurity interaction close to
the BPS regime, which presents a rather smooth, elastic like nature, with other
scattering processes. However, even in this case, after exciting a sufficiently
large linear mode on the incoming antikink, we can depart from the close-to-BPS
regime. This results, for example, in a backward scattering.


  This paper formed part of a preliminary research report for a risk
consultancy and academic research. Stochastic Programming models provide a
powerful paradigm for decision making under uncertainty. In these models the
uncertainties are represented by a discrete scenario tree and the quality of
the solutions obtained is governed by the quality of the scenarios generated.
We propose a new technique to generate scenarios based on Gaussian Mixture
Hidden Markov Modelling. We show that our approach explicitly captures
important time varying dynamics of stochastic processes (such as autoregression
and jumps) as well as non-Gaussian distribution characteristics (such as
skewness and kurtosis). Our scenario generation method enables richer
robustness and scenario analysis through exploiting the tractable properties of
Markov models and Gaussian mixture distributions. We demonstrate the benefits
of our scenario generation method by conducting numerical experiments on
FTSE-100 data.


  The quality of a superconductor-normal metal-superconductor Josephson
junction (JJ) depends crucially on the transparency of the
superconductor-normal metal (S/N) interface. We demonstrate a technique for
fabricating planar JJs with perfect S/N interfaces. The technique utilizes a
strong inverse proximity effect discovered in Al/V$_5$S$_8$ bilayers, by which
the Al layer is driven into the resistive state. The highly transparent S/N
homointerface and the peculiar normal metal enable the flow of Josephson
supercurrent across a 2.9 $\mu$m long weak link. Moreover, our JJ exhibits a
giant critical current and a large product of the critical current and the
normal state resistance.


  We investigate here the gravitational collapse end states for a spherically
symmetric perfect fluid with an equation of state $p=k\rho$. It is shown that
given a regular initial data in terms of the density and pressure profiles at
the initial epoch from which the collapse develops, the black hole or naked
singularity outcomes depend on the choice of rest of the free functions
available, such as the velocities of the collapsing shells, and the dynamical
evolutions as allowed by Einstein equations. This clarifies the role that
equation of state and initial data play towards determining the final fate of
gravitational collapse.


  Absorption-line measurements of the circumgalactic medium (CGM) display a
highly non-uniform distribution of lower ionization state species accompanied
by more widespread higher ionization state material. This suggests that the CGM
is a dynamic, multiphase medium, such as arises in the presence of turbulence.
To better understand this evolution, we perform hydrodynamic and
magneto-hydrodynamic (MHD) simulations of the CGM surrounding Milky Way-like
galaxies. In both cases, the CGM is initially in hydrostatic balance in a
$10^{12}$ solar masses dark matter gravitational potential, and the simulations
include rotation in the inner halo and turbulence that decreases radially. They
also track ionizations, recombinations, and species-by-species radiative
cooling in the presence of the redshift-zero UV background, employing the
MAIHEM non-equilibrium chemistry package. We find that after 9 Gyrs of
evolution, the presence of a magnetic field leads to an overall hotter CGM,
with cool gas in the center where magnetic pressure dominates. While the
non-MHD run produces more cold clouds overall, we find similar Si IV/O VI and N
V/O VI ratios between the MHD and non-MHD runs, which are both very different
from their equilibrium values. The non-MHD halo develops cool, low angular
momentum filaments above the central disk, in comparison to the MHD run that
has more efficient angular momentum transport, especially for the cold gas
which forms a more ordered and extended disk late into its evolution.


  We report on the discovery of eight repeating fast radio burst (FRB) sources
found using the Canadian Hydrogen Intensity Mapping Experiment (CHIME)
telescope. These sources span a dispersion measure (DM) range of 103.5 to 1281
pc cm$^{-3}$. They display varying degrees of activity: six sources were
detected twice, another three times, and one ten times. These eight repeating
FRBs likely represent the bright and/or high-rate end of a distribution of
infrequently repeating sources. For all sources, we determine sky coordinates
with uncertainties of $\sim$10$^\prime$. FRB 180916.J0158+65 has a
burst-averaged DM = $349.2 \pm 0.3$ pc cm$^{-3}$ and a low DM excess over the
modelled Galactic maximum (as low as $\sim$20 pc cm$^{-3}$); this source also
has a Faraday rotation measure (RM) of $-114.6 \pm 0.6$ rad m$^{-2}$, much
lower than the RM measured for FRB 121102. FRB 181030.J1054+73 has the lowest
DM for a repeater, $103.5 \pm 0.3$ pc cm$^{-3}$, with a DM excess of $\sim$ 70
pc cm$^{-3}$. Both sources are interesting targets for multi-wavelength
follow-up due to their apparent proximity. The DM distribution of our repeater
sample is statistically indistinguishable from that of the first 12 CHIME/FRB
sources that have not repeated. We find, with 4$\sigma$ significance, that
repeater bursts are generally wider than those of CHIME/FRB bursts that have
not repeated, suggesting different emission mechanisms. Our repeater events
show complex morphologies that are reminiscent of the first two discovered
repeating FRBs. The repetitive behavior of these sources will enable
interferometric localizations and subsequent host galaxy identifications.


  Ultimately, any explanation of quantum measurement must be extendable to
relativistic quantum mechanics (RQM), since many precisely confirmed
experimental results follow from quantum field theory (QFT), which is based on
RQM. Certainly, the traditional "collapse" postulate for quantum measurement is
problematic in a relativistic context, at the very least because, as usually
formulated, it violates the relativity of simultaneity. Among alternatives to
the traditional collapse interpretation, the Everettian approach of an
unmodified, unitary quantum formalism is the only one that has been clearly
extended to RQM and QFT. However, the usual "many worlds" interpretation of
such an approach leads to to difficulty in how to even define probabilities
over different possible "worlds". The present paper addresses this difficulty
by providing a relativistic model of measurement, in which the state of the
universe is decomposed into decoherent histories of measurements recorded
within it. Zurek's concept of envariance can be generalized to this context of
relativistic spacetime, giving an objective definition of the probability of
any one of these quantum histories, consistent with Born's rule. This then
leads to the statistics of any repeated experiment also tending to follow the
Born rule as the number of repetitions increases. The wave functions that we
actually use for such experiments are local reductions of very coarse-grained
superpositions of universal eigenstates, and their "collapse" can be
re-interpreted as simply an update based on additional incremental knowledge
gained from a measurement about the "real" eigenstate of our universe.


  In this work we analyze a non-commutativity measure of quantum correlations
recently proposed by Y. Guo [Sci. Rep. 6, 25241 (2016)]. By recourse to a
systematic survey of a two-qubit system, we detected an undesirable behavior of
such a measure related to its representation-dependence. In the case of pure
states, this dependence manifests as a non-satisfactory entanglement measure
whenever a representation other than the Schmidt's is used. In order to avoid
this dependence on the basis, we argue that a minimization procedure over the
set of all possible representations of the quantum state is required. In the
case of pure states, this minimization can be analytically performed and the
optimal basis turns out to be that of Schmidt's. In addition, the resulting
measure inherits the main properties of Guo's measure and, unlike the latter,
it reduces to a legitimate entanglement measure in the case of pure states.
Some examples involving general mixed states are also analyzed considering such
a optimization. The results show that, in most cases of interest, the use of
Guo's measure can result in a overestimation of quantum correlations. However,
since Guo's measure has the advantage of being easily computable, it might be
used as a qualitative estimator of the presence of quantum correlations.


  We develop a multimode theory of direct homodyne measurements of quantum
optical quasidistribution functions. We demonstrate that unbalanced homodyning
with appropriately shaped auxiliary coherent fields allows one to sample
point-by-point different phase space representations of the electromagnetic
field. Our analysis includes practical factors that are likely to affect the
outcome of a realistic experiment, such as non-unit detection efficiency,
imperfect mode matching, and dark counts. We apply the developed theory to
discuss feasibility of observing a loophole-free violation of Bell's
inequalities by measuring joint two-mode quasidistribution functions under
locality conditions by photon counting. We determine the range of parameters of
the experimental setup that enable violation of Bell's inequalities for two
states exhibiting entanglement in the Fock basis: a one-photon Fock state
divided by a 50:50 beam splitter, and a two-mode squeezed vacuum state produced
in the process of non-degenerate parametric down-conversion.


  We present the first suite of cosmological N-body simulations that
simultaneously include the effects of two different and theoretically
independent extensions of the standard $\Lambda$CDM cosmological scenario -
namely an $f(R)$ theory of Modified Gravity (MG) and a cosmological background
of massive neutrinos - with the aim to investigate their possible observational
degeneracies. We focus on three basic statistics of the large-scale matter
distribution, more specifically the nonlinear matter power spectrum, the halo
mass function, and the halo bias, for which we determine the deviation with
respect to the fiducial $\Lambda$CDM cosmology in the context of both separate
and combined simulations of $f(R)$ MG and massive neutrinos scenarios. Our
results show that while these two extended models separately determine very
prominent and potentially detectable features in all the three statistics, when
we allow them to be simultaneously at work these features are strongly
suppressed, resulting in much weaker deviations from the standard model's
predictions. In particular, when an $f(R)$ gravity model with $f_{R0}=-1\times
10^{-4}$ is combined with a total neutrino mass of $\Sigma _{i}m_{\nu
_{i}}=0.4$ eV, the resulting matter power spectrum, halo mass function, and
bias at z=0 are found to be consistent with the standard model's predictions at
the 10%, 20%, and 5% accuracy levels, respectively. Therefore, our results
imply an intrinsic theoretical limit to the effective discriminating power of
present and future observational data sets with respect to these widely
considered extensions of the standard cosmological scenario in the absence of
independent measurements of the neutrino masses from laboratory experiments,
even though the high-redshift evolution might still allow to partially break
the degeneracy [Abridged].


  Generally, a superconducting nanowire single-photon detector (SNSPD) is
composed of wires with a typical width of ~100 nm. Recent studies have found
that superconducting strips with a micrometer-scale width can also detect
single photons. Compared with the SNSPD, the superconducting microstrip
single-photon detector (SMSPD) has smaller kinetic inductance, higher working
current, and lower requirement in fabrication accuracy, providing potential
applications in the development of ultra-large active area detectors. However,
the study on SMSPD is still in its infancy, and the realization of its
high-performance and practical use remains an opening question. This study
demonstrates a NbN SMSPD with a saturated system detection efficiency (SDE) of
~92.2% at a dark count rate of ~200 cps, a polarization sensitivity of ~1.03,
and a minimum timing jitter of ~48 ps, at the telecom wavelength of 1550 nm
when coupled with a single mode fiber and operated at 0.84 K. Furthermore, the
detector's SDE is over 70% when operated at a 2.1-K closed-cycle cryocooler.


  We present a Bayesian analysis for a new class of realistic models of
two-phase equations of state (EoS) for hybrid stars and demonstrate that the
observation of a pair of high-mass twin stars would have a sufficient
discriminating power to favor hybrid EoS with a strong first order phase
transition over alternative EoS. Such a measurement would provide evidence for
the existence of a critical endpoint in the QCD phase diagram.


  The conflict in Yugoslavia has been a source of great concern due to the
radiological and toxic hazard posed by the alleged presence of depleted uranium
in NATO weapons. In the present study some worst-case scenaria are assumed in
order to assess the risk for Yugoslavia and its neighboring countries . The
risk is proved to be negligible for the neighboring countries while for
Yugoslavia itself evidence is given that any increase in total long-term cancer
mortality will be so low that it will remain undetected. Local radioactive
hotspots such as DU weapons fragments and abandoned battle tanks, fortified or
contaminated with DU, constitute a post-war hazard which is not studied in this
article.


  Because Fermi liquids are inherently non-interacting states of matter, all
electronic levels below the chemical potential are doubly occupied.
Consequently, the simplest way of breaking Fermi liquid theory is to engineer a
model in which some of those states are singly occupied keeping time-reversal
invariance intact. We show that breaking an overlooked local-in-momentum space
$\mathbb Z_2$ symmetry of a Fermi liquid does precisely this. As a result,
while the Mott transition from a Fermi liquid is correctly believed to obtain
without the breaking of any continuous symmetry, a discrete symmetry is broken.
This symmetry breaking serves as an organizing principle for Mott physics
whether it arises from the tractable Hatsugai-Kohmoto (HK) model or the
intractable Hubbard model. That both are controlled by the same fixed point we
establish through a renormalization group analysis. An experimental
manifestation of this fixed point is the onset of particle-hole asymmetry, a
widely observed phenomenon in strongly correlated systems. Theoretically, the
singly-occupied region of the spectrum gives rise to a surface of zeros of the
single-particle Green function, denoted as the Luttinger surface. Using
K-homology, we show that the Bott topological invariant guarantees the
stability of this surface to local perturbations. Our proof demonstrates that
the strongly coupled fixed point only corresponds to those Luttinger surfaces
with co-dimension $p+1$ with $p$ odd. We conclude that the Hubbard and HK
models both lie in the same high temperature universality class and are
controlled by the broken $\mathbb Z_2$ symmetry quartic fixed point.


  Understanding the energy transport by charge carriers and phonons in
two-dimensional (2D) van der Waals heterostructures is essential for the
development of future energy-efficient 2D nanoelectronics. Here, we performed
in situ spatially resolved Raman thermometry on an electrically biased graphene
channel and its hBN substrate to study the energy dissipation mechanism in
graphene/hBN heterostructures. By comparing the temperature profile along the
biased graphene channel with that along the hBN substrate, we found that the
thermal boundary resistance between the graphene and hBN was in the range of
(1-2) x 10^(-7) m^(2) KW^(-1) from ~100 C to the onset of graphene break-down
at ~600 C in air. Consideration of an electro-thermal transport model together
with the Raman thermometry conducted in air showed that local doping occurred
under a strong electric field played a crucial role in the energy dissipation
of the graphene/hBN device up to T ~ 600 C.


  Evidence for a re-entrant quantum paraelectric (QPE) state preceded by a
dipole glass (DG) phase with a non-classical exponent in the quantum critical
regime of SrFe12O19 is presented. It is shown that the DG transition is
accompanied with a spin glass (SG) transition and presence of a biquadratic
coupling of two diverse order parameter fields. Further, the ergodic symmetry
breaking temperatures for the DG and SG transitions coincide (TDG ~ TSG) within
+/- 1K suggesting that SrFe12O19 exhibits a canonical multiglass state. The
stability of the dipole glass state is enhanced magnetically as evidenced by
the increase in the freezing temperature with magnetic field (H). The
re-entrant QPE state, on the other hand, is found to give way to another
frequency dependent peak in the temperature dependence of dielectric constant,
most likely a DG phase, at a constant H. Further, this transition is not linked
to any magnetic transition in sharp contrast to the higher temperature
multiglass transition. The transition temperature of this phase decreases with
increasing magnetic field for a fixed frequency unlike the higher temperature
DG transition. This raises the possibility of locating a quantum critical point
(QCP) in this system at higher magnetic fields than that used in the present
work. These results are discussed in the light of quantum critical models of
multiferroic transitions. Our results highlight the need for more theoretical
studies specific to multiferroic quantum criticality in a multiglass system.


  We prove that for some universal $c$, a non-collinear set of $N>\frac{1}{c}$
points in the Euclidean plane determines at least $c \frac{N}{\log N}$ distinct
areas of triangles with one vertex at the origin, as well as at least $c
\frac{N}{\log N}$ distinct dot products.
  This in particular implies a sum-product bound $$ |A\cdot A\pm A\cdot A|\geq
c\frac{|A|^2}{\log |A|} $$ for a discrete $A \subset {\mathbb R}$.


  Production in an economy is a set of firms' activities as suppliers and
customers; a firm buys goods from other firms, puts value added and sells
products to others in a giant network of production. Empirical study is lacking
despite the fact that the structure of the production network is important to
understand and make models for many aspects of dynamics in economy. We study a
nation-wide production network comprising a million firms and millions of
supplier-customer links by using recent statistical methods developed in
physics. We show in the empirical analysis scale-free degree distribution,
disassortativity, correlation of degree to firm-size, and community structure
having sectoral and regional modules. Since suppliers usually provide credit to
their customers, who supply it to theirs in turn, each link is actually a
creditor-debtor relationship. We also study chains of failures or bankruptcies
that take place along those links in the network, and corresponding
avalanche-size distribution.


  Despite the benefits of personalizing items and information tailored to
users' needs, it has been found that recommender systems tend to introduce
biases that favor popular items or certain categories of items, and dominant
user groups. In this study, we aim to characterize the systematic errors of a
recommendation system and how they manifest in various accountability issues,
such as stereotypes, biases, and miscalibration. We propose a unified framework
that distinguishes the sources of prediction errors into a set of key measures
that quantify the various types of system-induced effects, both at the
individual and collective levels. Based on our measuring framework, we examine
the most widely adopted algorithms in the context of movie recommendation. Our
research reveals three important findings: (1) Differences between algorithms:
recommendations generated by simpler algorithms tend to be more stereotypical
but less biased than those generated by more complex algorithms. (2) Disparate
impact on groups and individuals: system-induced biases and stereotypes have a
disproportionate effect on atypical users and minority groups (e.g., women and
older users). (3) Mitigation opportunity: using structural equation modeling,
we identify the interactions between user characteristics (typicality and
diversity), system-induced effects, and miscalibration. We further investigate
the possibility of mitigating system-induced effects by oversampling
underrepresented groups and individuals, which was found to be effective in
reducing stereotypes and improving recommendation quality. Our research is the
first systematic examination of not only system-induced effects and
miscalibration but also the stereotyping issue in recommender systems.


  Randomized Aggregatable Privacy-Preserving Ordinal Response, or RAPPOR, is a
technology for crowdsourcing statistics from end-user client software,
anonymously, with strong privacy guarantees. In short, RAPPORs allow the forest
of client data to be studied, without permitting the possibility of looking at
individual trees. By applying randomized response in a novel manner, RAPPOR
provides the mechanisms for such collection as well as for efficient,
high-utility analysis of the collected data. In particular, RAPPOR permits
statistics to be collected on the population of client-side strings with strong
privacy guarantees for each client, and without linkability of their reports.
This paper describes and motivates RAPPOR, details its differential-privacy and
utility guarantees, discusses its practical deployment and properties in the
face of different attack models, and, finally, gives results of its application
to both synthetic and real-world data.


  This work developed a numerical procedure for a system of partial
differential equations (PDEs) describing the propagation of solitons in ideal
optical fibers. The validation of the procedure was implemented from the
numerical comparison between the known analytical solutions of the PDEs system
and those obtained by using the numerical procedure developed. It was
discovered that the procedure, based on the finite difference method and
relaxation Gauss-Seidel method, was adequate in describing the propagation of
soliton waves in ideals optical fibers.


  We represent minimal upper gradients of Newtonian functions, in the range
$1\le p<\infty$, by maximal directional derivatives along "generic" curves
passing through a given point, using plan-modulus duality and disintegration
techniques. As an application we introduce the notion of $p$-weak charts and
prove that every Newtonian function admits a differential with respect to such
charts, yielding a linear approximation along $p$-almost every curve. The
differential can be computed curvewise, is linear, and satisfies the usual
Leibniz and chain rules.
  The arising $p$-weak differentiable structure exists for spaces with finite
Hausdorff dimension and agrees with Cheeger's structure in the presence of a
Poincar\'e inequality. It is moreover compatible with, and gives a geometric
interpretation of, Gigli's abstract differentiable structure, whenever it
exists. The $p$-weak charts give rise to a finite dimensional $p$-weak
cotangent bundle and pointwise norm, which recovers the minimal upper gradient
of Newtonian functions and can be computed by a maximization process over
generic curves. As a result we obtain new proofs of reflexivity and density of
Lipschitz functions in Newtonian spaces, as well as a characterization of
infinitesimal Hilbertianity in terms of the pointwise norm.


  We show that for every symmetric space G/K of compact type with K connected,
the K-action on G/K by left translations is equivariantly formal.


  3D object reconstruction is a fundamental task of many robotics and AI
problems. With the aid of deep convolutional neural networks (CNNs), 3D object
reconstruction has witnessed a significant progress in recent years. However,
possibly due to the prohibitively high dimension of the 3D object space, the
results from deep CNNs are often prone to missing some shape details. In this
paper, we present an approach which aims to preserve more shape details and
improve the reconstruction quality. The key idea of our method is to leverage
object mask and pose estimation from CNNs to assist the 3D shape learning by
constructing a probabilistic single-view visual hull inside of the network. Our
method works by first predicting a coarse shape as well as the object pose and
silhouette using CNNs, followed by a novel 3D refinement CNN which refines the
coarse shapes using the constructed probabilistic visual hulls. Experiment on
both synthetic data and real images show that embedding a single-view visual
hull for shape refinement can significantly improve the reconstruction quality
by recovering more shapes details and improving shape consistency with the
input image.


  We summarize how the approach to the black--disk regime (BDR) of strong
interactions at TeV energies influences rapidity gap survival in exclusive hard
diffraction pp--> p + H + p (H =dijet, \bar Q Q, Higgs). Employing a recently
developed partonic description of such processes, we discuss (a) the
suppression of diffraction at small impact parameters by soft spectator
interactions in the BDR; (b) further suppression by inelastic interactions of
hard spectator partons in the BDR; (c) effects of correlations between hard and
soft interactions, as suggested by various models of proton structure (color
fluctuations, spatial correlations of partons). Hard spectator interactions in
the BDR substantially reduce the rapidity gap survival probability at LHC
energies compared to previously reported estimates.


  In this paper we present results from a method of community detection using
label propagation in undirected, unweighted graphs which incorporates elements
of neural computing and spike-based data. Using a fully connected,
edge-weighted system of spiking neurons driven by external currents, we
generate spike responses that are decoded into a binary signal. The similarity
between pairs of signals is quantified using a Hamming-distance based metric
and is used to classify vertices into communities. We test our approach on a
set of graph instances, each with 128 vertices and either homogeneous or
heterogeneous community size distributions. We present our method as a
candidate for a split-computing workflow that incorporates neuromorphic
hardware and does not require extensive pre-training of network parameters.


  This manuscript is a research resource description and presents a large and
novel Electronic Health Records (EHR) data resource, American Family Cohort
(AFC). The AFC data is derived from Centers for Medicare and Medicaid Services
(CMS) certified American Board of Family Medicine (ABFM) PRIME registry. The
PRIME registry is the largest national Qualified Clinical Data Registry (QCDR)
for Primary Care. The data is converted to a popular common data model, the
Observational Health Data Sciences and Informatics (OHDSI) Observational
Medical Outcomes Partnership (OMOP) Common Data Model (CDM).
  The resource presents approximately 90 million encounters for 7.5 million
patients. All 100% of the patients present age, gender, and address
information, and 73% report race. Nealy 93% of patients have lab data in LOINC,
86% have medication data in RxNorm, 93% have diagnosis in SNOWMED and ICD, 81%
have procedures in HCPCS or CPT, and 61% have insurance information. The
richness, breadth, and diversity of this research accessible and research ready
data is expected to accelerate observational studies in many diverse areas. We
expect this resource to facilitate research in many years to come.


  In the paper "Control Design for UAV Quadrotors via Embedded Model Control"
[1], the authors designed a complete control unit for a UAV Quadrotor, based on
the Embedded Model Control (EMC) methodology, in combination with the Feedback
Linearization (FL); when applied to non-linear systems. Specifically, [1]
proposes to use the FL as a novel way to design the internal model for the EMC
state and disturbance predictor. To support the treatise in [1], in this report
the feedback-linearized model of the UAV quadrotor leveraged in [1] is
step-by-step derived.


  In this work, we consider the problem of secure multi-party computation
(MPC), consisting of $\Gamma$ sources, each has access to a large private
matrix, $N$ processing nodes or workers, and one data collector or master. The
master is interested in the result of a polynomial function of the input
matrices. Each source sends a randomized functions of its matrix, called as its
share, to each worker. The workers process their shares in interaction with
each other, and send some results to the master such that it can derive the
final result. There are several constraints: (1) each worker can store a
function of each input matrix, with the size of $\frac{1}{m}$ fraction of that
input matrix, (2) up to $t$ of the workers, for some integer $t$, are adversary
and may collude to gain information about the private inputs or can do
malicious actions to make the final result incorrect. The objective is to
design an MPC scheme with the minimum number the workers, called the recovery
threshold, such that the final result is correct, workers learn no information
about the input matrices, and the master learns nothing beyond the final
result. In this paper, we propose an MPC scheme that achieves the recovery
threshold of $3t+2m-1$ workers, which is order-wise less than the recovery
threshold of the conventional methods. The challenge in dealing with this set
up is that when nodes interact with each other, the malicious messages that
adversarial nodes generate propagate through the system, and can mislead the
honest nodes. To deal with this challenge, we design some subroutines that can
detect erroneous messages, and correct or drop them.


  We present metallicities for 487 red giants in the Carina dwarf spheroidal
(dSph) galaxy that were obtained from FLAMES low-resolution Ca triplet (CaT)
spectroscopy. We find a mean [Fe/H] of -1.91 dex with an intrinsic dispersion
of 0.25 dex, whereas the full spread in metallicities is at least one dex. The
analysis of the radial distribution of metallicities reveals that an excess of
metal poor stars resides in a region of larger axis distances. These results
can constrain evolutionary models and are discussed in the context of chemical
evolution in the Carina dSph.


  Stone-type duality theorems, which relate algebraic and
relational/topological models, are important tools in logic because -- in
addition to elegant abstraction -- they strengthen soundness and completeness
to a categorical equivalence, yielding a framework through which both algebraic
and topological methods can be brought to bear on a logic. We give a systematic
treatment of Stone-type duality for the structures that interpret bunched
logics, starting with the weakest systems, recovering the familiar BI and
Boolean BI (BBI), and extending to both classical and intuitionistic Separation
Logic. We demonstrate the uniformity and modularity of this analysis by
additionally capturing the bunched logics obtained by extending BI and BBI with
modalities and multiplicative connectives corresponding to disjunction,
negation and falsum. This includes the logic of separating modalities (LSM), De
Morgan BI (DMBI), Classical BI (CBI), and the sub-classical family of logics
extending Bi-intuitionistic (B)BI (Bi(B)BI). We additionally obtain as
corollaries soundness and completeness theorems for the specific Kripke-style
models of these logics as presented in the literature: for DMBI, the
sub-classical logics extending BiBI and a new bunched logic, Concurrent Kleene
BI (connecting our work to Concurrent Separation Logic), this is the first time
soundness and completeness theorems have been proved. We thus obtain a
comprehensive semantic account of the multiplicative variants of all standard
propositional connectives in the bunched logic setting. This approach
synthesises a variety of techniques from modal, substructural and categorical
logic and contextualizes the "resource semantics" interpretation underpinning
Separation Logic amongst them.


  We present several entanglement conditions in order to detect bound entangled
states in continuous variable systems. Specifically, Werner and Wolf [Phys.
Rev. Lett. 86, 3658 (2001)] and Horodecki and Lewenstein [Phys. Rev. Lett. 85,
2657 (2000)] have proposed examples of bound entangled Gaussian state and bound
entangled non-Gaussian state, respectively, of which entanglement can be
detected by using our entanglement conditions.


  We analyze quasi-stationary distributions
$\{\mu^{\varepsilon}\}_{\varepsilon>0}$ of a family of Markov chains
$\{X^{\varepsilon}\}_{\varepsilon>0}$ that are random perturbations of a
bounded, continuous map $F:M\to M$, where $M$ is a closed subset of
$\mathbb{R}^k$. Consistent with many models in biology, these Markov chains
have a closed absorbing set $M_0\subset M$ such that $F(M_0)=M_0$ and
$F(M\setminus M_0)=M\setminus M_0$. Under some large deviations assumptions on
the random perturbations, we show that, if there exists a positive attractor
for $F$ (i.e., an attractor for $F$ in $M\setminus M_0$), then the weak* limit
points of $\mu_{\varepsilon}$ are supported by the positive attractors of $F$.
To illustrate the broad applicability of these results, we apply them to
nonlinear branching process models of metapopulations, competing species,
host-parasitoid interactions and evolutionary games.


  We present a detailed analysis of the velocity distribution and orientation
of orbits of subhaloes in high resolution cosmological simulations of dark
matter haloes. We find a trend for substructure to preferentially revolve in
the same direction as the sense of rotation of the host halo: there is an
excess of prograde satellite haloes. Throughout our suite of nine host haloes
(eight cluster sized objects and one galactic halo) there are on average 59% of
the satellites corotating with the host. Even when including satellites out to
five virial radii of the host, the signal still remains pointing out the
relation of the signal with the infall pattern of subhaloes. However, the
fraction of prograde satellites weakens to about 53% when observing the data
along a (random) line-of-sight and deriving the distributions in a way an
observer would infer them. This decrease in the observed prograde fraction has
its origin in the technique used by the observer to determine the sense of
rotation, which results in a possible misclassification of non-circular orbits.
We conclude that the existence of satellites on corotating orbits is another
prediction of the cold dark matter structure formation scenario, although there
will be difficulties to verify it observationally. Since the galactic halo
simulation gave the same result as the cluster-sized simulations, we assume
that the fraction of prograde orbits is independent of the scale of the system,
though more galactic simulations would be necessary to confirm this.


  The exactly solvable scalar hairy black hole model (originated from the
modern high-energy theory) is proposed. It turns out that the existence of
black holes (BH) is strongly correlated to global scalar field, in a sense that
they mutually impose bounds upon their physical parameters like the BH mass
(lower bound) or the cosmological constant (upper bound). We consider the same
model also as a cosmological one and show that it agrees with recent
experimental data; additionally, it provides a unified quintessence-like
description of dark energy and dark matter.


  Pressure effects on the charge and spin dynamics in the bilayer manganite
compounds $La_{2-2x}Sr_{1+2x}Mn_2O_7$ are studied theoretically by taking into
account the orbital degrees of freedom. The orbital degrees are active in the
layered crystal structure, and applied hydrostatic pressure stabilizes the
$3d_{x^2-y^2}$ orbital in comparison with $3d_{3z^2-r^2}$. The change of the
orbital states weakens the interlayer charge and spin couplings, and suppresses
the three dimensional ferromagnetic transition. Numerical results, based on an
effective Hamiltonian which includes the energy level difference of the
orbitals, show that the applied pressure controls the dimensionality of the
spin and charge dynamics through changes of the orbital states.


  Based on a new large, homogeneous photometric database of 35 Galactic
globular clusters (GGCs), a set of distance and reddening independent relative
age indicators has been measured. The observed D(V-I)_2.5 and D(V)(HB-TO) vs.
metallicity relations have been compared with the relations predicted by two
recent updated libraries of isochrones. Using these models and two independent
methods, we have found that self-consistent relative ages can be estimated for
our GGC sample. Based on the relative age vs. metallicity distribution, we
conclude that: (a) there is no evidence of an age spread for clusters with
[Fe/H]<-1.2, all the clusters of our sample in this range being old and coeval;
(b) for the intermediate metallicity group (-1.2<=[Fe/H]<-0.9) there is a clear
evidence of age dispersion, with clusters up to ~25% younger than the older
members; and (c) the clusters within the metal rich group ([Fe/H]>=-0.9) seem
to be coeval within the uncertainties (except Pal12), but younger (~17%) than
the bulk of the Galactic globulars. The latter result is totally model
dependent. From the distribution of the GGC ages with the Galactocentric
distance, we can present a possible scenario for the Milky Way formation: The
GC formation process started at the same zero age throughout the halo, at least
out to ~20 kpc from the Galactic center. According to the present stellar
evolution models, the metal-rich globulars are formed at a later time (~ 17%
lower age). And finally, significantly younger halo GGCs are found at any
R(GC)>8 kpc. For these, a possible scenario associated with mergers of dwarf
galaxies to the Milky Way is suggested.


  Trustworthy deployment of deep learning medical imaging models into
real-world clinical practice requires that they be calibrated. However, models
that are well calibrated overall can still be poorly calibrated for a
sub-population, potentially resulting in a clinician unwittingly making poor
decisions for this group based on the recommendations of the model. Although
methods have been shown to successfully mitigate biases across subgroups in
terms of model accuracy, this work focuses on the open problem of mitigating
calibration biases in the context of medical image analysis. Our method does
not require subgroup attributes during training, permitting the flexibility to
mitigate biases for different choices of sensitive attributes without
re-training. To this end, we propose a novel two-stage method: Cluster-Focal to
first identify poorly calibrated samples, cluster them into groups, and then
introduce group-wise focal loss to improve calibration bias. We evaluate our
method on skin lesion classification with the public HAM10000 dataset, and on
predicting future lesional activity for multiple sclerosis (MS) patients. In
addition to considering traditional sensitive attributes (e.g. age, sex) with
demographic subgroups, we also consider biases among groups with different
image-derived attributes, such as lesion load, which are required in medical
image analysis. Our results demonstrate that our method effectively controls
calibration error in the worst-performing subgroups while preserving prediction
performance, and outperforming recent baselines.


  The Cherenkov Telescope Array Observatory (CTAO) is the next generation of
observatories employing the imaging air Cherenkov technique for the study of
very high energy gamma rays. The deployment of deep learning methods for the
reconstruction of physical attributes of incident particles has evinced
promising outcomes when conducted on simulations. However, the transition of
this approach to observational data is accompanied by challenges, as deep
learning-based models are susceptible to domain shifts. In this paper, we
integrate domain adaptation in the physics-based context of the CTAO and shed
light on the gain in performance that these techniques bring using LST-1 real
acquisitions.


  We develop deterministic approximation algorithms for the minimum dominating
set problem in the CONGEST model with an almost optimal approximation
guarantee. For $\epsilon>1/{\text{{poly}}}\log \Delta$ we obtain two algorithms
with approximation factor $(1+\epsilon)(1+\ln (\Delta+1))$ and with runtimes
$2^{O(\sqrt{\log n \log\log n})}$ and $O(\Delta\cdot\text{poly}\log \Delta
+\text{poly}\log \Delta \log^{*} n)$, respectively. Further we show how
dominating set approximations can be deterministically transformed into a
connected dominating set in the \CONGEST model while only increasing the
approximation guarantee by a constant factor. This results in a deterministic
$O(\log \Delta)$-approximation algorithm for the minimum connected dominating
set with time complexity
  $2^{O(\sqrt{\log n \log\log n})}$.


  Numerous activities in our daily life, including transactions, access to
services and transportation, require us to verify who we are by showing our ID
documents containing face images, e.g. passports and driver licenses. An
automatic system for matching ID document photos to live face images in real
time with high accuracy would speedup the verification process and remove the
burden on human operators. In this paper, by employing the transfer learning
technique, we propose a new method, DocFace, to train a domain-specific network
for ID document photo matching without a large dataset. Compared with the
baseline of applying existing methods for general face recognition to this
problem, our method achieves considerable improvement. A cross validation on an
ID-Selfie dataset shows that DocFace improves the TAR from 61.14% to 92.77% at
FAR=0.1%. Experimental results also indicate that given more training data, a
viable system for automatic ID document photo matching can be developed and
deployed.


  We analyze STIS spectra in the 1150-1700 Angstrom wavelength range obtained
for six early B supergiants in the neighboring galaxy M31. Because of their
likely high (nearly solar) abundance, these stars were originally chosen to be
directly comparable to their Galactic counterparts, and represent a much-needed
addition to our current sample of B-type supergiants, in our efforts to study
the dependence of the Wind Momentum-Luminosity Relationship on spectral type
and metallicity. As a first step to determine wind momenta we fit the P-Cygni
profiles of the resonance lines of N V, Si IV and C IV with standard methods,
and derive terminal velocities for all of the STIS targets. From these lines we
also derive ionic stellar wind column densities. Our results are compared with
those obtained previously in Galactic supergiants, and confirm earlier claims
of `normal' wind line intensities and terminal velocities in M31. For half of
the sample we find evidence for an enhanced maximum turbulent velocity when
compared to Galactic counterparts.


  Perception of artificial agents is one the grand challenges of AI research.
Deep Learning and data-driven approaches are successful on constrained problems
where perception can be learned using supervision, but do not scale to
open-worlds. In such case, for autonomous embodied agents with first-person
sensors, perception can be learned end-to-end to solve particular tasks.
However, literature shows that perception is not a purely passive compression
mechanism, and that actions play an important role in the formulation of
abstract representations. We propose to study perception for these embodied
agents, under the mathematical formalism of group theory in order to make the
link between perception and action. In particular, we consider the commutative
properties of continuous action sequences with respect to sensory information
perceived by such an embodied agent. We introduce the Sensory Commutativity
Probability (SCP) criterion which measures how much an agent's degree of
freedom affects the environment in embodied scenarios. We show how to compute
this criterion in different environments, including realistic robotic setups.
We empirically illustrate how SCP and the commutative properties of action
sequences can be used to learn about objects in the environment and improve
sample-efficiency in Reinforcement Learning.


  For a connected, reductive group $G$ over a finite field endowed with a
cocharacter $\mu$, we define the zip cone of $(G,\mu)$ as the cone of all
possible weights of mod $p$ automorphic forms on the stack of $G$-zips. This
cone is conjectured to coincide with the cone of weights of characteristic $p$
automorphic forms for Hodge-type Shimura varieties of good reduction. We prove
in full generality that the cone of weights of characteristic $0$ automorphic
forms is contained in the zip cone, which gives further evidence to this
conjecture. Furthermore, we determine exactly when the zip cone is generated by
the weights of partial Hasse invariants, which is a group-theoretical
generalization of a result of Diamond--Kassaei and Goldring--Koskivirta.


  The junction conditions for the most general gravitational theory with a
Lagrangian containing terms quadratic in the curvature are derived. We include
the cases with a possible concentration of matter on the joining hypersurface
-termed as thin shells, domain walls or braneworlds in the literature- as well
as the proper matching conditions where only finite jumps of the
energy-momentum tensor are allowed. In the latter case we prove that the
matching conditions are more demanding than in General Relativity. In the
former case, we show that generically the shells/domain walls are of a new kind
because they possess, in addition to the standard energy-momentum tensor, a
double layer energy-momentum contribution which actually induces an external
energy flux vector and an external scalar pressure/tension on the shell. We
prove that all these contributions are necessary to make the entire
energy-momentum tensor divergence-free, and we present the field equations
satisfied by these energy-momentum quantities. The consequences of all these
results are briefly analyzed.


  We demonstrate that the recently proposed pruned-enriched Rosenbluth method
(P. Grassberger, Phys. Rev. E 56 (1997) 3682) leads to extremely efficient
algorithms for the folding of simple model proteins. We test them on several
models for lattice heteropolymers, and compare to published Monte Carlo
studies. In all cases our algorithms are faster than all previous ones, and in
several cases we find new minimal energy states. In addition to ground states,
our algorithms give estimates for the partition sum at finite temperatures.


  We present a statistical mechanical calculation of the thermodynamical
properties of (non rotating) isolated horizons. The introduction of Planck
scale allows for the definition of an universal horizon temperature
(independent of the mass of the black hole) and a well-defined notion of energy
(as measured by suitable local observers) proportional to the horizon area in
Planck units. The microcanonical and canonical ensembles associated with the
system are introduced. Black hole entropy and other thermodynamical quantities
can be consistently computed in both ensembles and results are in agreement
with Hawking's semiclassical analysis for all values of the Immirzi parameter.


  The category-valued trace assigns to a bimodule category over a linear
monoidal category a linear category. It generalizes Drinfeld centers of
monoidal categories and the relative Deligne product of bimodule categories. In
this article, we study bimodule categories that are given as categories of
bicomodules over a Hopf algebra. Our main result is a representation-theoretic
realization of the category-valued trace as a category of generalized Hopf
bimodules.


  Encouraging progress has been made towards Visual Question Answering (VQA) in
recent years, but it is still challenging to enable VQA models to adaptively
generalize to out-of-distribution (OOD) samples. Intuitively, recompositions of
existing visual concepts (\ie, attributes and objects) can generate unseen
compositions in the training set, which will promote VQA models to generalize
to OOD samples. In this paper, we formulate OOD generalization in VQA as a
compositional generalization problem and propose a graph generative
modeling-based training scheme (X-GGM) to implicitly model the problem. X-GGM
leverages graph generative modeling to iteratively generate a relation matrix
and node representations for the predefined graph that utilizes
attribute-object pairs as nodes. Furthermore, to alleviate the unstable
training issue in graph generative modeling, we propose a gradient distribution
consistency loss to constrain the data distribution with adversarial
perturbations and the generated distribution. The baseline VQA model (LXMERT)
trained with the X-GGM scheme achieves state-of-the-art OOD performance on two
standard VQA OOD benchmarks, \ie, VQA-CP v2 and GQA-OOD. Extensive ablation
studies demonstrate the effectiveness of X-GGM components. Code is available at
\url{https://github.com/jingjing12110/x-ggm}.


  We construct the universal sl(2)-tangle cohomology using an approach with
webs and dotted foams. This theory depends on two parameters, and for the case
of links it is a categorification of the unnormalized Jones polynomial of the
link.


  The nonrelativistic standard model for a continuous, one-parameter diffusion
process in position space is the Wiener process. As well-known, the Gaussian
transition probability density function (PDF) of this process is in conflict
with special relativity, as it permits particles to propagate faster than the
speed of light. A frequently considered alternative is provided by the
telegraph equation, whose solutions avoid superluminal propagation speeds but
suffer from singular (non-continuous) diffusion fronts on the light cone, which
are unlikely to exist for massive particles. It is therefore advisable to
explore other alternatives as well. In this paper, a generalized Wiener process
is proposed that is continuous, avoids superluminal propagation, and reduces to
the standard Wiener process in the non-relativistic limit. The corresponding
relativistic diffusion propagator is obtained directly from the nonrelativistic
Wiener propagator, by rewriting the latter in terms of an integral over
actions. The resulting relativistic process is non-Markovian, in accordance
with the known fact that nontrivial continuous, relativistic Markov processes
in position space cannot exist. Hence, the proposed process defines a
consistent relativistic diffusion model for massive particles and provides a
viable alternative to the solutions of the telegraph equation.


  The gluino-induced contributions to the decay b-> s gamma are investigated in
supersymmetric frameworks with generic sources of flavour violation. It is
shown that, when QCD corrections are taken into account, the relevant operator
basis of the Standard Model effective Hamiltonian gets enlarged to contain: i)
magnetic and chromomagnetic operators with a factor of alpha_s and weighted by
a quark mass m_b or m_c; ii) magnetic and chromomagnetic operators of lower
dimensionality, also containing alpha_s; iii) four-quark operators weighted by
a factor alpha_s^2. Numerical results are given, showing the effects of the
leading order QCD corrections on the inclusive branching ratio for b-> s gamma.
Constraints on supersymmetric sources of flavour violation are derived.


  Loosely speaking, the Navier-Stokes-$\alpha$ model and the Navier-Stokes
equations differ by a spatial filtration parametrized by a scale denoted
$\alpha$. Starting from a strong two-dimensional solution to the
Navier-Stokes-$\alpha$ model driven by a multiplicative noise, we demonstrate
that it generates a strong solution to the stochastic Navier-Stokes equations
under the condition $\alpha$ goes to 0. The initially introduced probability
space and the Wiener process are maintained throughout the investigation,
thanks to a local monotonicity property that abolishes the use of Skorokhod's
theorem. High spatial regularity a priori estimates for the fluid velocity
vector field are carried out within periodic boundary conditions.


  In this note, we study the expander decomposition problem in a more general
setting where the input graph has positively weighted edges and nonnegative
demands on its vertices. We show how to extend the techniques of Chuzhoy et al.
(FOCS 2020) to this wider setting, obtaining a deterministic algorithm for the
problem in almost-linear time.


  Video and image quality assessment has long been projected as a regression
problem, which requires predicting a continuous quality score given an input
stimulus. However, recent efforts have shown that accurate quality score
regression on real-world user-generated content (UGC) is a very challenging
task. To make the problem more tractable, we propose two new methods - binary,
and ordinal classification - as alternatives to evaluate and compare
no-reference quality models at coarser levels. Moreover, the proposed new tasks
convey more practical meaning on perceptually optimized UGC transcoding, or for
preprocessing on media processing platforms. We conduct a comprehensive
benchmark experiment of popular no-reference quality models on recent
in-the-wild picture and video quality datasets, providing reliable baselines
for both evaluation methods to support further studies. We hope this work
promotes coarse-grained perceptual modeling and its applications to efficient
UGC processing.


  We use measurements from the Rosetta plasma consortium (RPC) Langmuir probe
(LAP) and mutual impedance probe (MIP) to study the spatial distribution of
low-energy plasma in the near-nucleus coma of comet 67P/Churyumov-Gerasimenko.
The spatial distribution is highly structured with the highest density in the
summer hemisphere and above the region connecting the two main lobes of the
comet, i.e. the neck region. There is a clear correlation with the neutral
density and the plasma to neutral density ratio is found to be about 1-2x10^-6,
at a cometocentric distance of 10 km and at 3.1 AU from the sun. A clear 6.2 h
modulation of the plasma is seen as the neck is exposed twice per rotation. The
electron density of the collisonless plasma within 260 km from the nucleus
falls of with radial distance as about 1/r. The spatial structure indicates
that local ionization of neutral gas is the dominant source of low-energy
plasma around the comet.


  Large language models (LLMs) with Chain-of-thought (CoT) have recently
emerged as a powerful technique for eliciting reasoning to improve various
downstream tasks. As most research mainly focuses on English, with few
explorations in a multilingual context, the question of how reliable this
reasoning capability is in different languages is still open. To address it
directly, we study multilingual reasoning consistency across multiple
languages, using popular open-source LLMs. First, we compile the first
large-scale multilingual math reasoning dataset, mCoT-MATH, covering eleven
diverse languages. Then, we introduce multilingual CoT instruction tuning to
boost reasoning capability across languages, thereby improving model
consistency. While existing LLMs show substantial variation across the
languages we consider, and especially low performance for lesser resourced
languages, our 7B parameter model mCoT achieves impressive consistency across
languages, and superior or comparable performance to close- and open-source
models even of much larger sizes.


  In order to efficiently provide demand side management (DSM) in smart grid,
carrying out pricing on the basis of real-time energy usage is considered to be
the most vital tool because it is directly linked with the finances associated
with smart meters. Hence, every smart meter user wants to pay the minimum
possible amount along with getting maximum benefits. In this context, usage
based dynamic pricing strategies of DSM plays their role and provide users with
specific incentives that help shaping their load curve according to the
forecasted load. However, these reported real-time values can leak privacy of
smart meter users, which can lead to serious consequences such as spying, etc.
Moreover, most dynamic pricing algorithms charge all users equally irrespective
of their contribution in causing peak factor. Therefore, in this paper, we
propose a modified usage based dynamic pricing mechanism that only charges the
users responsible for causing peak factor. We further integrate the concept of
differential privacy to protect the privacy of real-time smart metering data.
To calculate accurate billing, we also propose a noise adjustment method.
Finally, we propose Demand Response enhancing Differential Pricing (DRDP)
strategy that effectively enhances demand response along with providing dynamic
pricing to smart meter users. We also carry out theoretical analysis for
differential privacy guarantees and for cooperative state probability to
analyze behavior of cooperative smart meters. The performance evaluation of
DRDP strategy at various privacy parameters show that the proposed strategy
outperforms previous mechanisms in terms of dynamic pricing and privacy
preservation.


  We investigate to what extent the theory of N\'eron models of jacobians and
of abel-jacobi maps extends to relative curves over base schemes of dimension
greater than 1. We give a necessary and sufficient criterion for the existence
of a N\'eron model. We use this to show that, in general, N\'eron models do not
exist even after making a modification or even alteration of the base. On the
other hand, we show that N\'eron models do exist outside some codimension-2
locus.


  Despite tremendous success in many application scenarios, deep learning faces
serious intellectual property (IP) infringement threats. Considering the cost
of designing and training a good model, infringements will significantly
infringe the interests of the original model owner. Recently, many impressive
works have emerged for deep model IP protection. However, they either are
vulnerable to ambiguity attacks, or require changes in the target network
structure by replacing its original normalization layers and hence cause
significant performance drops. To this end, we propose a new passport-aware
normalization formulation, which is generally applicable to most existing
normalization layers and only needs to add another passport-aware branch for IP
protection. This new branch is jointly trained with the target model but
discarded in the inference stage. Therefore it causes no structure change in
the target model. Only when the model IP is suspected to be stolen by someone,
the private passport-aware branch is added back for ownership verification.
Through extensive experiments, we verify its effectiveness in both image and 3D
point recognition models. It is demonstrated to be robust not only to common
attack techniques like fine-tuning and model compression, but also to ambiguity
attacks. By further combining it with trigger-set based methods, both black-box
and white-box verification can be achieved for enhanced security of deep
learning models deployed in real systems. Code can be found at
https://github.com/ZJZAC/Passport-aware-Normalization.


  We investigate the stellar populations of a sample of Tidal Dwarf Galaxies,
combining observations and evolutionary synthesis models to try and reveal
their formation mechanism. On optical images we select a first sample of TDGs
for which optical spectroscopy is used to measure metallicities and velocity
structure. Finally, we estimate ages, burst strengths, and stellar masses from
near-infrared imaging in comparison with a dedicated grid of evolutionary
synthesis models, to assess if Tidal Dwarfs are formed out of collapsing gas
clouds or by an accumulation of old stars from the parent galaxy or by a
combination of both.


  We present extensive observations and analysis of supernova (SN) 2021dbg,
utilizing optical photometry and spectroscopy. For approximately 385 days
following the explosion, SN 2021dbg exhibited remarkable luminosity, surpassing
most SNe II. This initial high luminosity is potentially attributed to the
interaction between the ejected material and the surrounding circumstellar
material (CSM), as evidenced by the pronounced interaction signatures observed
in its spectra. The subsequent high luminosity is primarily due to the
significant $^{56}$Ni ($0.17 \pm 0.05$ M$_{\odot}$) produced in the explosion.
Based on the flux of flash emission lines detected in the initial spectra, we
estimate that the CSM mass near the progenitor amounted to $\sim$(1.0--2.0)
$\times 10^{-3}$ M$_{\odot}$, likely resulting from intense stellar wind
activity 2--3 yr preceding the explosion. Considering the bolometric light
curve, nebular spectrum modeling, and mass-loss rate, we suggest that the
progenitor of SN 2021dbg was a red supergiant (RSG) with a mass of $\sim 20$
M$_{\odot}$ and a radius of 1200 R$_{\odot}$. This RSG featured a thick
hydrogen shell, which may have contained a region with a sharp decrease in
material density, electron density, and temperature, contributing to its
layered structure. This object demonstrates mixed features of SNe IIP and SNe
IIL, making it as a transitional event linking the above two subclasses of SNe
II.


  Podcast recommendation is a growing area of research that presents new
challenges and opportunities. Individuals interact with podcasts in a way that
is distinct from most other media; and primary to our concerns is distinct from
music consumption. We show that successful and consistent recommendations can
be made by viewing users as moving through the podcast library sequentially.
Recommendations for future podcasts are then made using the trajectory taken
from their sequential behavior. Our experiments provide evidence that user
behavior is confined to local trends, and that listening patterns tend to be
found over short sequences of similar types of shows. Ultimately, our approach
gives a450%increase in effectiveness over a collaborative filtering baseline.


  Chemical non-equilibrium version of the statistical hadronization model
combined with a single-freeze-out scenario is used to analyze the
transverse-momentum spectra of pions, kaons and protons produced in heavy-ion
collisions at sqrt(sNN) = 2.76 TeV. With the statistical parameters found in
earlier studies of hadronic ratios and two new geometric parameters determined
by the absolute normalization and slopes of the spectra, we obtain a very good
agreement between the data and the model predictions. In particular, the
enhancement of pions observed at the very low transverse-momenta is very well
reproduced. In the chemical non-equilibrium approach, this effect may be
naturally interpreted as the onset of pion condensation in heavy-ion
collisions. We further stress that the chemical non-equilibrium explains not
only the proton yield but the proton spectra as well.


  Spiking Neural Networks (SNN) are energy-efficient computing architectures
that exchange spikes for processing information, unlike classical Artificial
Neural Networks (ANN). Due to this, SNNs are better suited for real-life
deployments. However, similar to ANNs, SNNs also benefit from deeper
architectures to obtain improved performance. Furthermore, like the deep ANNs,
the memory, compute and power requirements of SNNs also increase with model
size, and model compression becomes a necessity. Knowledge distillation is a
model compression technique that enables transferring the learning of a large
machine learning model to a smaller model with minimal loss in performance. In
this paper, we propose techniques for knowledge distillation in spiking neural
networks for the task of image classification. We present ways to distill
spikes from a larger SNN, also called the teacher network, to a smaller one,
also called the student network, while minimally impacting the classification
accuracy. We demonstrate the effectiveness of the proposed method with detailed
experiments on three standard datasets while proposing novel distillation
methodologies and loss functions. We also present a multi-stage knowledge
distillation technique for SNNs using an intermediate network to obtain higher
performance from the student network. Our approach is expected to open up new
avenues for deploying high performing large SNN models on resource-constrained
hardware platforms.


  The integration of a massive number of large-scale wind turbines brought
about urgent technical challenge to power transmission network operators in
terms of secure power supply and energy dispatching optimization. In this
paper, an optimal framework is proposed for transmission expansion planning in
a deregulated power market environment. The level of congestion in the network
is utilized as the driving signal for the need of network expansion. A
compromise between the congestion cost and the investment cost is used to
determine the optimal expansion scheme. The long-term network expansion problem
is formed as the decoupled combination of: 1) the master problem (minimization
of investment costs subject to investment constraints and the Benders cuts
generated by the operational problem (power pool) and 2) the operational
problem, whose solution provides congestion details and associated multipliers.
A proper power-pool model is developed and solved for congestion cost,
congestion revenue, and transmission shadow prices. Also, we proposed to use a
set of metrics to rate the effect of the expansion on the generators, demands,
and the system as a whole. The proposed model is applied to the Garver six-bus
system and to the IEEE 24-bus Reliability Test System.


  The direct sum of irreducible level one integrable representations of affine
Kac-Moody Lie algebra of (affine) type $ADE$ carries a structure of
$P/Q$-graded vertex operator algebra. There exists a filtration on this direct
sum studied by Kato and Loktev such that the corresponding graded vector space
is a direct sum of global Weyl modules. The associated graded space with
respect to the dual filtration is isomorphic to the homogenous coordinate ring
of semi-infinite flag variety. We describe the ring structure in terms of
vertex operators and endow the homogenous coordinate ring with a structure of
$P/Q$-graded vertex operator algebra. We use the vertex algebra approach to
derive semi-infinite Pl\"ucker-type relations in the homogeneous coordinate
ring.


  MoSe2-WSe2 heterostructures host strongly bound interlayer excitons (IXs)
which exhibit bright photoluminescence (PL) when the twist-angle is near
0{\deg} or 60{\deg}. Over the past several years, there have been numerous
reports on the optical response of these heterostructures but no unifying model
to understand the dynamics of IXs and their temperature dependence. Here, we
perform a comprehensive study of the temperature, excitation power, and
time-dependent PL of IXs. We observe a significant decrease in PL intensity
above a transition temperature that we attribute to a transition from localized
to delocalized IXs. Astoundingly, we find a simple inverse relationship between
the IX PL energy and the transition temperature, which exhibits opposite power
dependent behaviors for near 0{\deg} and 60{\deg} samples. We conclude that
this temperature dependence is a result of IX-IX exchange interactions, whose
effect is suppressed by the moir\'e potential trapping IXs at low temperature.


  This report presents results from a background measurement campaign for the
CODEX-b proposal undertaken in August, 2018. The data were recorded in the
DELPHI side of the LHCb cavern behind a 3.2~m concrete shield wall, during
Run~2 proton-proton collisions with the goal of calibrating the simulation for
the full CODEX-b detector. The maximum flux rate in the DELPHI side of the
cavern was found to be around 0.6~mHz/cm$^2$ across a vertical plane just
behind the shield wall, parallel to the beam line. A detailed simulation under
development within the LHCb {\tt Gauss} framework is described. This includes
shielding elements pertinent for CODEX-b's acceptance -- the LHCb detector, the
shield wall and cavern infrastructure. Additional flux from tracks not in the
line of sight from the interaction point, but bent by the magnetic fields, are
incorporated. Overall, the simulation overestimates the background flux
compared to the measurement. Several cross-checks and avenues for further
investigations are described.


  Bound states in superconductors are expected to exhibit a spatially resolved
electron-hole asymmetry which is the hallmark of their quantum nature. This
asymmetry manifests as oscillations at the Fermi wavelength, which is usually
tiny and thus washed out by thermal broadening or by scattering at defects.
Here we demonstrate theoretically and confirm experimentally that, when coupled
to magnetic impurities, bound states in a vortex core exhibit an emergent axial
electron-hole asymmetry on a much longer scale, set by the coherence length. We
study vortices in 2H-NbSe$_2$ and in 2H-NbSe$_{1.8}$S_{0.2}$ with magnetic
impurities, characterizing these with detailed Hubbard-corrected density
functional calculations. We find that the induced electron-hole imbalance
depends on the band character of the superconducting material. Our results open
interesting prospects for the study of coupled superconducting bound states.


  A simple yet general method for constructing basis sets for molecular
electronic structure calculations is presented. These basis sets consist of
atomic natural orbitals from a multi-configurational self-consistent field
calculation supplemented with primitive functions, chosen such that the
asymptotics are appropriate for the potential of the system. Primitives are
optimized for the homonuclear diatomic molecule to produce a balanced basis
set. Two general features that facilitate this basis construction are
demonstrated. First, weak coupling exists between the optimal exponents of
primitives with different angular momenta. Second, the optimal primitive
exponents for a chosen system depend weakly on the particular level of theory
employed for optimization. The explicit case considered here is a basis set
appropriate for the Burkatzki-Filippi-Dolg pseudopotentials. Since these
pseudopotentials are finite at nuclei and have a Coulomb tail, the recently
proposed Gauss-Slater functions are the appropriate primitives. Double- and
triple-zeta bases are developed for elements hydrogen through argon. These new
bases offer significant gains over the corresponding Burkatzki-Filippi-Dolg
bases at various levels of theory. Using a Gaussian expansion of the basis
functions, these bases can be employed in any electronic structure method.
Quantum Monte Carlo provides an added benefit: expansions are unnecessary since
the integrals are evaluated numerically.


  Recent work has shown that the properties of multiple populations within
massive stellar clusters (i.e., in the extent of their abundance variations as
well as the fraction of stars that show the anomalous chemistry) depend on the
mass as well as the age of the host cluster. Such correlations are largely
unexpected in current models for the formation of multiple populations and
hence provide essential insight into their origin. Here we extend or previous
study into the presence or absence of multiple populations using integrated
light spectroscopy of the $\sim600$~Myr, massive ($\sim10^7 - 10^8$~\msun)
clusters, W3 and W30, in the galactic merger remnant, NGC 7252. Due to the
extreme mass of both clusters, the expectation is that they should host rather
extreme abundance spreads, manifested through, e.g., high mean [Na/Fe]
abundances. However, we do not find evidence for a strong [Na/Fe] enhancement,
with the observations being consistent with the solar value. This suggests that
age is playing a key role, or alternatively that multiple populations only
manifest below a certain stellar mass, as the integrated light at all ages
above $\sim100$~Myr is dominated by stars near or above the main sequence
turn-off.


  In the present paper we report comprehensive analysis of the thermodynamic
properties of novel hydrogen dominant potassium hydride superconductor
(KH$_{6}$). Our computations are conducted within the Eliashberg theory which
yields quantitative estimations of the most important thermodynamic properties
of superconducting phase. In particular, we observe, that together with the
increasing pressure all the thermodynamic properties decrease, e.g. $T_{C} \in
\left< 72.91 , 55.50 \right>$ K for $p \in \left< 166 , 300 \right>$ GPa. It is
predicted that such decreasing behavior corresponds to the decreasing hydrogen
lattice molecularization with increasing pressure value. Futhermore, by
calculating the dimensionless thermodynamic ratios, familiar in the
Bardeen-Cooper-Schrieffer theory (BCS), it is proved that KH$_{6}$ material is
a strong-coupling superconductor and cannot be quantitatively described within
the BCS theory.


  Haptic feedback can improve safety of teleoperated robots when situational
awareness is limited or operators are inattentive. Standard potential field
approaches increase haptic resistance as an obstacle is approached, which is
desirable when the operator is unaware of the obstacle but undesirable when the
movement is intentional, such as when the operator wishes to inspect or
manipulate an object. This paper presents a novel haptic teleoperation
framework that estimates the operator's attentiveness to obstacles and dampens
haptic feedback for intentional movement. A biologically-inspired attention
model is developed based on computational working memory theories to integrate
visual saliency estimation with spatial mapping. The attentiveness map is
generated in real-time, and our system renders lower haptic forces for
obstacles that the operator is estimated to be aware of. Experimental results
in simulation show that the proposed framework outperforms haptic teleoperation
without attentiveness estimation in terms of task performance, robot safety,
and user experience.


  We present in this paper a rigorous theoretical framework to show stability,
convergence and accuracy of improved edge-based and face-based smoothed finite
element methods (bESFEM and bFS-FEM) for nearly-incompressible elasticity
problems. The crucial idea is that the space of piecewise linear polynomials
used for the displacements is enriched with bubble functions on each element,
while the pressure is a piecewise constant function. The meshes of triangular
or tetrahedral elements required by these methods can be generated
automatically. The enrichment induces a softening in the bilinear form allowing
the weakened weak (W2)procedure to produce a high-quality solution, free from
locking and that does not oscillate. We prove theoretically that both methods
confirm the uniform inf-sup and convergence conditions. Four numerical examples
are given to validate the reliability of the bES-FEM and bFS-FEM.


  Superstrings and topological strings with supermanifolds as target space play
a central role in the recent developments in string theory. Nevertheless the
rules for higher-genus computations are still unclear or guessed in analogy
with bosonic and fermionic strings. Here we present a common geometrical
setting to develop systematically the prescription for amplitude computations.
The geometrical origin of these difficulties is the theory of integration of
superforms. We provide a translation between the theory of supermanifolds and
topological strings with supertarget space. We show how in this formulation one
can naturally construct picture changing operators to be inserted in the
correlation functions to soak up the zero modes of commuting ghost and we
derive the amplitude prescriptions from the coupling with an extended
topological gravity on the worldsheet. As an application we consider a simple
model on R^(3|2) leading to super-Chern-Simons theory.


  We show that Brodsky-Lepage evolution equation for the leading twist spin 3/2
baryon distribution amplitude is completely integrable and reduces to the
three-particle XXX_{s=-1} Heisenberg spin chain. Trajectories of the anomalous
dimensions are identified and calculated using the 1/N expansion. Extending
this result, we prove integrability of the evolution equations for twist 3
quark-gluon operators in the large N_c limit and derive explicit expressions
for the corresponding integrals of motion.


  Forty-five years after the discovery of the peculiar quantum effect known as
`probability backflow', and twenty years after the greatest possible size of
the effect was characterized, an experiment has been proposed recently to
observe the effect in a Bose-Einstein condensate. Here the history is described
in non-technical terms.


  We classify all possible charge lattices and 1-form symmetry groups for
$\mathcal{N}=2$ SCFTs with characteristic dimension $\varkappa \neq \{1,2\}$.
For rank-$r$ SCFTs that are not stacks of lower rank theories the order of the
1-form symmetry group can be 1,2,3,4 and $r+1$. As an application of the
classification we show that $\mathcal{N}=2$ $S$-folds and Minahan-Nemeschansky
SCFTs have trivial 1-form symmetry. We find two sporadic lattices compatible
with the Coulomb branch geometries $\mathbb{C}^5/G_{33}$ and
$\mathbb{C}^6/G_{34}$ that are not realized by any known SCFT. The former, if
realized, would have a $\mathbb{Z}_2$ 1-form symmetry and a non-invertible
topological defect.


  The Search for Extraterrestrial Intelligence (SETI) has thus far failed to
provide a convincing detection of intelligent life. In the wake of this null
signal, many "contact pessimistic" hypotheses have been formulated, the most
famous of which is the Rare Earth Hypothesis. It postulates that although
terrestrial planets may be common, the exact environmental conditions that
Earth enjoys are rare, perhaps unique. As a result, simple microbial life may
be common, but complex metazoans (and hence intelligence) will be rare. This
paper uses Monte Carlo Realisation Techniques to investigate the Rare Earth
Hypothesis, in particular the environmental criteria considered imperative to
the existence of intelligence on Earth.
  By comparing with a less restrictive, more optimistic hypothesis, the data
indicates that if the Rare Earth hypothesis is correct, intelligent
civilisation will indeed be relatively rare. Studying the separations of pairs
of civilisations shows that most intelligent civilisation pairs (ICPs) are
unconnected: that is, they will not be able to exchange signals at lightspeed
in the limited time that both are extant. However, the few ICPs that are
connected are strongly connected, being able to participate in numerous
exchanges of signals. This may provide encouragement for SETI researchers:
although the Rare Earth Hypothesis is in general a contact-pessimistic
hypothesis, it may be a "soft" or "exclusive" hypothesis, i.e. it may contain
facets that are latently contact-optimistic.


  We use the known renormalon structure of Bjorken polarised sum rule (BSR)
${\overline \Gamma}_1^{p-n}(Q^2)$ to evaluate the leading-twist part of that
quantity. In addition, we include $D=2$ and $D=4$ Operator Product Expansion
(OPE) terms and fit this expression to available experimental data for
inelastic BSR. Since we use perturbative QCD (pQCD) coupling, which fails at
low squared spacelike momenta $Q^2 \lesssim 1 \ {\rm GeV}^2$ due to Landau
singularities, the fit is performed for $Q^2 \geq Q^2_{\rm min}$ where
$Q^2_{\rm min} \approx (1.7 \pm 0.3) \ {\rm GeV}^2$. Due to large BSR
experimental uncertainties, the extracted value of the pQCD coupling has very
large uncertainties, especially when $Q^2_{\rm min}$ is varied. However, when
we fix the pQCD coupling to the known world average values, the $D=2$ and $D=4$
residue parameters can be determined within large but reasonable uncertainties.


  An optimisation scheme is developed to accurately represent the sub-grid
scale forcing of a high dimensional chaotic ocean system. Using a simple
parameterisation scheme, the velocity components of a 30km resolution shallow
water ocean model are optimised to have the same climatological mean and
variance as that of a less viscous 7.5km resolution model. The 5 day
lag-covariance is also optimised, leading to a more accurate estimate of the
high resolution response to forcing using the low resolution model.
  The system considered is an idealised barotropic double gyre that is chaotic
at both resolutions. Using the optimisation scheme, we find and apply the
constant in time, but spatially varying, forcing term that is equal to the time
integrated forcing of the sub-mesoscale eddies. A linear stochastic term,
independent of the large-scale flow, with no spatial correlation but a
spatially varying amplitude and time scale is used to represent the transient
eddies. The climatological mean, variance and 5 day lag-covariance of the
velocity from a single high resolution integration is used to provide an
optimisation target. No other high resolution statistics are required.
Additional programming effort, for example to build a tangent linear or adjoint
model, is not required either.
  The focus of this paper is on the optimisation scheme and the accuracy of the
optimised flow. The method can be applied in future investigations into the
physical processes that govern barotropic turbulence and it can perhaps be
applied to help understand and correct biases in the mean and variance of a
more realistic coarse or eddy-permitting ocean model. The method is
complementary to current parameterisations and can be applied at the same time
without modification.


  We derive the axion-nucleon interaction Lagrangian in heavy baryon chiral
perturbation theory up to next-to-next-to-leading order. The effective
axion-nucleon coupling is calculated to a few percent accuracy.


  There is a serious problem with one of the assumptions made in the security
proof of the SURF scheme. This problem turns out to be easy in the regime of
parameters needed for the SURF scheme to work.
  We give afterwards the old version of the paper for the reader's convenience.


  We construct a version of Dijkgraaf-Witten theory based on a compact abelian
Lie group within the formalism of Turaev's homotopy quantum field theory. As an
application we show that the 2+1-dimensional theory based on U(1) classifies
lens spaces up to homotopy type.


  We prove using invariance under the modular $S$- and $ST$-transformations
that every unitary two-dimensional conformal field theory (CFT) of only
even-spin operators (with no extended chiral algebra and with central charges
$c,\tilde{c}>1$) contains a primary operator with dimension $\Delta_1$
satisfying $0 < \Delta_1 < (c+\tilde{c})/24 + 0.09280...$ After deriving both
analytical and numerical bounds, we discuss how to extend our methods to bound
higher conformal dimensions before deriving lower and upper bounds on the
number of primary operators in a given energy range. Using the AdS$_3$/CFT$_2$
dictionary, the bound on $\Delta_1$ proves the lightest massive excitation in
appropriate theories of 3D matter and gravity with cosmological constant
$\Lambda < 0$ can be no heavier than $1/(8G_N)+O(\sqrt{-\Lambda})$; the bounds
on the number operators are related via AdS/CFT to the entropy of states in the
dual gravitational theory. In the flat-space approximation, the limiting mass
is exactly that of the lightest BTZ black hole.


  Equilibrium statistics of Hamiltonian systems is correctly described by the
microcanonical ensemble, whereas canonical ones fail in the most interesting,
mostly inhomogeneous, situations like phase separations or away from the
thermodynamic ``limit'' (e.g. self-gravitating systems and small quantum
systems). A new derivation of the Second Law is presented that respects these
fundamental complications. Our ``geometric foundation of Thermo-Statistics''
opens the fundamental (axiomatic) application of Thermo-Statistics to
non-diluted systems or to ``non-simple'' systems which are not similar to
(homogeneous) fluids. Supprisingly, but also understandably, a so far open
problem c.f. Uffink: cond-mat/0005327, page 50 and page 72.


  We define a generalized likelihood function based on uncertainty measures and
show that maximizing such a likelihood function for different measures induces
different types of classifiers. In the probabilistic framework, we obtain
classifiers that optimize the cross-entropy function. In the possibilistic
framework, we obtain classifiers that maximize the interclass margin.
Furthermore, we show that the support vector machine is a sub-class of these
maximum-margin classifiers.


  We have studied modification of the fluorescence spectra of a
room-temperature atomic rubidium vapor in the region of $^{85}$Rb and $^{87}$Rb
D$_2$ line while changing the temporal rate of linear (triangular) scanning of
laser radiation frequency. Increase of the ramping speed over certain value
($\approx$ 10$^6$ MHz/s) results in essential modification of magnitudes of
individual atomic transitions, different on rising and falling slopes, which
characterize transition from a steady-state interaction regime to a transient
one. Our experimental results are well consistent with the developed
theoretical model. The obtained results can be used for determination of atomic
system parameters such as ground-state relaxation rate. Possible follow-up
actions on addressed control of atomic levels population is discussed.


  In this article we study a general class of non-rotating thin-shell wormholes
with cylindrical symmetry. We consider two physically sound definitions of the
flare-out condition and we show that the less restrictive one allows for the
construction of wormholes with positive energy density at the throat. We also
analyze the mechanical stability of these objects under perturbations
preserving the symmetry, proving that previous results are particular cases of
a general property. We present examples of wormholes corresponding to
Einstein-Maxwell spacetimes.


  The understanding of the halo current properties during disruptions is key to
design and operate large scale tokamaks in view of the large thermal and
electromagnetic loads that they entail. For the first time, we present a fully
self-consistent model for halo current simulations including neutral particles
and sheath boundary conditions. The model is used to simulate Vertical
Displacement Events (VDEs) occurring in the COMPASS tokamak. Recent COMPASS
experiments have shown that the parallel halo current density at the
plasma-wall interface is limited by the ion saturation current during
VDE-induced disruptions. We show that usual MHD boundary conditions can lead to
the violation of this physical limit and we implement this current density
limitation through a boundary condition for the electrostatic potential. Sheath
boundary conditions for the density, the heat flux, the parallel velocity and a
realistic parameter choice (e.g. Spitzer $\eta$ and Spitzer-H\"arm
$\chi_\parallel$ values) extend present VDE simulations beyond the state of the
art. Experimental measurements of the current density, temperature and heat
flux profiles at the COMPASS divertor are compared with the results obtained
from axisymmetric simulations. Since the ion saturation current density
($J_{sat}$) is shown to be essential to determine the halo current profile,
parametric scans are performed to study its dependence on different quantities
such as the plasma resistivity and the particle and heat diffusion
coefficients. In this respect, the plasma resistivity in the halo region
broadens significantly the $J_{sat}$ profile, increasing the halo width at a
similar total halo current.


  Left-invariant Hermitian and Gauduchon connections are studied on an
arbitrary Lie group $G$ equipped with an arbitrary left-invariant almost
Hermitian structure $(\langle\cdot,\cdot\rangle,J)$. The space of
left-invariant Hermitian connections is shown to be in one-to-one
correspondence with the space $\wedge^{(1,1)}\mathfrak{g}^\ast\otimes
\mathfrak{g}$ of left-invariant 2-forms of type (1,1) (with respect to $J$)
with values in $\mathfrak{g}:=\mbox{Lie}(G)$. Explicit formulas are obtained
for the torsion components of every Hermitian and Gauduchon connection with
respect to a convenient choice of left-invariant frame on $G$. The curvature of
Gauduchon connections is studied for the special case $G=H\times A$, where $H$
is an arbitrary $n$-dimensional Lie group, $A$ is an arbitrary $n$-dimensional
abelian Lie group, and the almost complex structure is totally real with
respect to $\mathfrak{h}:=\mbox{Lie}(H)$. When $H$ is compact, it is shown that
$H\times A$ admits a left-invariant (strictly) almost Hermitian structure
$(\langle\cdot,\cdot\rangle,J)$ such that the Gauduchon connection
corresponding to the Strominger (or Bismut) connection in the integrable case
is precisely the trivial left-invariant connection and, in addition, has
totally skew-symmetric torsion. The almost Hermitian structure
$(\langle\cdot,\cdot\rangle,J)$ on $H\times A$ is shown to satisfy the
\textit{strong K\"{a}hler with torsion} condition. Furthermore, the affine line
of Gauduchon connections on $H\times A$ with the aforementioned almost
Hermitian structure is also shown to contain a (nontrivial) flat connection.


  It has been recently reported that a granular mixture in which grains differ
in their restitution coefficients presents segregation: the more inelastic
particles sink to the bottom. When other segregation mechanisms as buoyancy and
the Brazil nut effect are present, the inelasticity induced segregation can
compete with them. First, a detailed analysis, based on numerical simulations
of two dimensional systems, of the competition between buoyancy and the
inelasticity induced segregation is presented, finding that there is a
transition line in the parameter space that determines which mechanism is
dominant. In the case of neutrally buoyant particles having different sizes the
inelasticity induced segregation can compete with the Brazil nut effect (BNE).
Reverse Brazil nut effect (RBNE) could be obtained at large inelasticities of
the intruder. At intermediate values, BNE and RBNE coexist and large inelastic
particles are found both near the bottom and at the top of the system.


  We study the long time behavior of solutions of the non-autonomous
Reaction-Diffusion equation defined on the entire space R^n when external terms
are unbounded in a phase space. The existence of a pullback global attractor
for the equation is established in L^2(R^n) and H^1(R^n), respectively. The
pullback asymptotic compactness of solutions is proved by using uniform a
priori estimates on the tails of solutions outside bounded domains.


  Models with an Axion Like Particle (ALP) can provide an explanation for the
discrepancy between experimental measurement of the muon anomalous magnetic
moment $(g-2)_\mu$ and the Standard Model prediction. This explanation relies
on the couplings of the ALP to the muon and the photon. We also include more
general couplings to the electroweak gauge bosons and incorporate them in the
calculations up to the 2-loop order. We investigate the existing experimental
constraints and find that they do not rule out the ALP model under
consideration as a possible explanation for the $(g-2)_\mu$ anomaly. At the
same time, we find the future Tera-$Z$ and Higgs factories, such as the CEPC
and FCC-ee, can completely cover the relevant parameter space through searches
with final states $(\gamma \gamma) \gamma$, $(\mu^+ \mu^-) \gamma$ and $(\mu^+
\mu^-) \mu^+ \mu^-$.


  In this paper we consider spatial networks that realize a balance between an
infrastructure cost (the cost of wire needed to connect the network in space)
and communication efficiency, measured by average shortest pathlength. A global
optimization procedure yields network topologies in which this balance is
optimized. These are compared with network topologies generated by a
competitive process in which each node strives to optimize its own
cost-communication balance. Three phases are observed in globally optimal
configurations for different cost-communication trade-offs: (i) regular small
worlds, (ii) star-like networks and (iii) trees with a centre of interconnected
hubs. In the latter regime, i.e. for very expensive wire, power laws in the
link length distributions $P(w)\propto w^{-\alpha}$ are found, which can be
explained by a hierarchical organization of the networks. In contrast, in the
local optimization process the presence of sharp transitions between different
network regimes depends on the dimension of the underlying space. Whereas for
$d=\infty$ sharp transitions between fully connected networks, regular small
worlds and highly cliquish periphery-core networks are found, for $d=1$ sharp
transitions are absent and the power law behaviour in the link length
distribution persists over a much wider range of link cost parameters. The
measured power law exponents are in agreement with the hypothesis that the
locally optimized networks consist of multiple overlapping sub-optimal
hierarchical trees.