  We describe the status of the HepData database system, following a major
re-development in time for the advent of LHC data. The new HepData system
benefits from use of modern database and programming language technologies, as
well as a variety of high-quality tools for interfacing the data sources and
their presentation, primarily via the Web. The new back-end provides much more
flexible and semantic data representations than before, on which new external
applications can be built to respond to the data demands of the LHC
experimental era. The HepData re-development was largely motivated by a desire
to have a single source of reference data for Monte Carlo validation and tuning
tools, whose status and connection to HepData we also briefly review.


  We prove convergence of a finite difference approximation of the compressible
Navier--Stokes system towards the strong solution in $R^d,$ $d=2,3,$ for the
adiabatic coefficient $\gamma>1$. Employing the relative energy functional, we
find a convergence rate which is \emph{uniform} in terms of the discretization
parameters for $\gamma \geq d/2$. All results are \emph{unconditional} in the
sense that we have no assumptions on the regularity nor boundedness of the
numerical solution. We also provide numerical experiments to validate the
theoretical convergence rate. To the best of our knowledge this work contains
the first unconditional result on the convergence of a finite difference scheme
for the unsteady compressible Navier--Stokes system in multiple dimensions.


  Much of the recent success of deep reinforcement learning has been driven by
regularized policy optimization (RPO) algorithms with strong performance across
multiple domains. In this family of methods, agents are trained to maximize
cumulative reward while penalizing deviation in behavior from some reference,
or default policy. In addition to empirical success, there is a strong
theoretical foundation for understanding RPO methods applied to single tasks,
with connections to natural gradient, trust region, and variational approaches.
However, there is limited formal understanding of desirable properties for
default policies in the multitask setting, an increasingly important domain as
the field shifts towards training more generally capable agents. Here, we take
a first step towards filling this gap by formally linking the quality of the
default policy to its effect on optimization. Using these results, we then
derive a principled RPO algorithm for multitask learning with strong
performance guarantees.


  Phase transitions in nuclei, small atomic clusters and self-gravitating
systems demand the extension of thermo-statistics to ``Small'' systems. The
main obstacle is the thermodynamic limit. It is shown how the original
definition of the entropy by Boltzmann as the volume of the energy-manifold of
the N-body phase space allows a {\em geometrical} definition of the entropy as
function of the conserved quantities. Without invoking the thermodynamic limit
the whole ``zoo'' of phase transitions and critical points/lines can be
unambiguously defined. The relation to the Yang--Lee singularities of the
grand-canonical partition sum is pointed out. It is shown that just phase
transitions in non-extensive systems give the complete set of characteristic
parameters of the transition {\em including the surface tension.} Nuclear
heavy-ion collisions are an experimental playground to explore this extension
of thermo-statistics


  This paper outlines the issues related to RF MEMS packaging and low actuation
voltage. An original approach is presented concerning the modeling of
capacitive contacts using multiphysics simulation and advanced
characterization. A similar approach is used concerning packaging development
where multi-physics simulations are used to optimize the process. A devoted
package architecture is proposed featuring very low loss at microwave range.


  For multilingual sequence-to-sequence pretrained language models
(multilingual Seq2Seq PLMs), e.g. mBART, the self-supervised pretraining task
is trained on a wide range of monolingual languages, e.g. 25 languages from
CommonCrawl, while the downstream cross-lingual tasks generally progress on a
bilingual language subset, e.g. English-German, making there exists the data
discrepancy, namely domain discrepancy, and cross-lingual learning objective
discrepancy, namely task discrepancy, between the pretraining and finetuning
stages. To bridge the above cross-lingual domain and task gaps, we extend the
vanilla pretrain-finetune pipeline with extra code-switching restore task.
Specifically, the first stage employs the self-supervised code-switching
restore task as a pretext task, allowing the multilingual Seq2Seq PLMs to
acquire some in-domain alignment information. And for the second stage, we
fine-tune the model on downstream data normally. Experiments on both NLG
evaluation (12 bilingual translation tasks, 30 zero-shot translation tasks, and
2 cross-lingual summarization tasks) and NLU evaluation (7 cross-lingual
natural language inference tasks) show our model outperforms the strong
baseline mBART with standard finetuning strategy, consistently. Analyses
indicate our approach could narrow the Euclidean distance of cross-lingual
sentence representations, and improve the model generalization with trivial
computational cost. We release the code at:
https://github.com/zanchangtong/CSR4mBART.


  COnstraint-Based Reconstruction and Analysis (COBRA) provides a molecular
mechanistic framework for integrative analysis of experimental data and
quantitative prediction of physicochemically and biochemically feasible
phenotypic states. The COBRA Toolbox is a comprehensive software suite of
interoperable COBRA methods. It has found widespread applications in biology,
biomedicine, and biotechnology because its functions can be flexibly combined
to implement tailored COBRA protocols for any biochemical network. Version 3.0
includes new methods for quality controlled reconstruction, modelling,
topological analysis, strain and experimental design, network visualisation as
well as network integration of chemoinformatic, metabolomic, transcriptomic,
proteomic, and thermochemical data. New multi-lingual code integration also
enables an expansion in COBRA application scope via high-precision,
high-performance, and nonlinear numerical optimisation solvers for multi-scale,
multi-cellular and reaction kinetic modelling, respectively. This protocol can
be adapted for the generation and analysis of a constraint-based model in a
wide variety of molecular systems biology scenarios. This protocol is an update
to the COBRA Toolbox 1.0 and 2.0. The COBRA Toolbox 3.0 provides an
unparalleled depth of constraint-based reconstruction and analysis methods.


  In this letter we discuss a regularization scheme for the integration of
generic on-shell forms. The basic idea is to extend the three-particle
amplitudes to the space of unphysical helicities keeping the dimension of the
related coupling constant fixed, and construct on-shell forms out of them. We
briefly discuss the analytic structure of the extended on-shell diagrams, both
at tree level and one loop. Furthermore, we propose an integration contour
which, applied to the relevant on-shell forms, allows to extract the
four-particle amplitudes in Lorentz signature at one loop. With this contour at
hand, we explicitly apply our procedure to this case obtaining the IR
divergences as poles in the deformation parameter space, as well as the correct
functional form for the finite term. This procedure provides a natural
regularization for generic on-shell diagrams.


  We consider in this paper two different types of the weighted geometric means
of positive definite operators. We show the component-wise bijection of these
geometric means and give a geometric property of the spectral geometric mean as
a metric midpoint. Moreover, several interesting inequalities related with the
geometric means of positive definite operators will be shown. We also see the
meaning of weighted geometric means in the gyrogroup structure with finite
dimension and find the formulas of weighted geometric means of 2-by-2 positive
definite matrices and density matrices.


  In this paper, we propose a relaxation to the stochastic ruler method
originally described by Yan and Mukai in 1992 for asymptotically determining
the global optima of discrete simulation optimization problems. The `original'
version of the stochastic ruler and its variants require that a candidate for
the next estimate of the optimal solution pass a certain number of tests with
respect to the stochastic ruler to be selected as the next estimate of the
optimal solution. This requirement - that all tests need to be passed - can
lead to promising candidate solutions being rejected and can slow down the
convergence of the algorithm. Our proposed modification to the stochastic ruler
algorithm relaxes this requirement, and we show analytically that our proposed
variant of the stochastic ruler method incurs lesser computational overhead
when a new solution in the neighborhood of the current solution is a
`successful' candidate for the next estimate of the current solution. We then
show numerically that this can yield accelerated convergence to the optimal
solution via multiple numerical examples. We also provide the theoretical
grounding for the asymptotic convergence in probability of the variant to the
global optimal solution under the same set of assumptions as those underlying
the original stochastic ruler method.


  Let \( \{\varphi_i\}_{i=0}^\infty \) be a sequence of orthonormal polynomials
on the unit circle with respect to a probability measure \( \mu \). We study
zero distribution of random linear combinations of the form \[
P_n(z)=\sum_{i=0}^{n-1}\eta_i\varphi_i(z), \] where \( \eta_0,\dots,\eta_{n-1}
\) are i.i.d. standard Gaussian variables. We use the Christoffel-Darboux
formula to simplify the density functions provided by Vanderbei for the
expected number real and complex of zeros of \( P_n \). From these expressions,
under the assumption that \( \mu \) is in the Nevai class, we deduce the
limiting value of these density functions away from the unit circle. Under the
mere assumption that \( \mu \) is doubling on subarcs of \( \T \) centered at
\( 1 \) and \( -1 \), we show that the expected number of real zeros of \( P_n
\) is at most \[ (2/\pi) \log n +O(1), \] and that the asymptotic equality
holds when the corresponding recurrence coefficients decay no slower than \(
n^{-(3+\epsilon)/2} \), \( \epsilon>0 \). We conclude with providing results
that estimate the expected number of complex zeros of \( P_n \) in shrinking
neighborhoods of compact subsets of \( \T \).


  If $R$ is a rational map, the Main Result is a uniformization Theorem for the
space of decompositions of the iterates of $R$. Secondly, we show that Fatou
conjecture holds for decomposable rational maps.


  In this article, we propose a novel Bayesian multiple testing formulation for
model and variable selection in inverse setups, judiciously embedding the idea
of inverse reference distributions proposed by Bhattacharya (2013) in a mixture
framework consisting of the competing models. We develop the theory and methods
in the general context encompassing parametric and nonparametric competing
models, dependent data, as well as misspecifications. Our investigation shows
that asymptotically the multiple testing procedure almost surely selects the
best possible inverse model that minimizes the minimum Kullback-Leibler
divergence from the true model. We also show that the error rates, namely,
versions of the false discovery rate and the false non-discovery rate converge
to zero almost surely as the sample size goes to infinity. Asymptotic
{\alpha}-control of versions of the false discovery rate and its impact on the
convergence of false non-discovery rate versions, are also investigated.
  Our simulation experiments involve small sample based selection among inverse
Poisson log regression and inverse geometric logit and probit regression, where
the regressions are either linear or based on Gaussian processes. Additionally,
variable selection is also considered. Our multiple testing results turn out to
be very encouraging in the sense of selecting the best models in all the
non-misspecified and misspecified cases.


  We study the collisional decay of a strongly driven Bose-Einstein condensate
oscillating between two momentum modes. The resulting products of the decay are
found to strongly deviate from the usual s-wave halo. Using a stochastically
seeded classical field method we simulate the collisional manifold. These
results are also explained by a model of colliding Bloch states.


  We present a new family of model selection algorithms based on the resampling
heuristics. It can be used in several frameworks, do not require any knowledge
about the unknown law of the data, and may be seen as a generalization of local
Rademacher complexities and $V$-fold cross-validation. In the case example of
least-square regression on histograms, we prove oracle inequalities, and that
these algorithms are naturally adaptive to both the smoothness of the
regression function and the variability of the noise level. Then,
interpretating $V$-fold cross-validation in terms of penalization, we enlighten
the question of choosing $V$. Finally, a simulation study illustrates the
strength of resampling penalization algorithms against some classical ones, in
particular with heteroscedastic data.


  A Gelfand-Tsetlin scheme of depth N is a triangular array with m integers at
level m, m=1,...,N, subject to certain interlacing constraints. We study the
ensemble of uniformly random Gelfand-Tsetlin schemes with arbitrary fixed N-th
row. We obtain an explicit double contour integral expression for the
determinantal correlation kernel of this ensemble (and also of its
q-deformation).
  This provides new tools for asymptotic analysis of uniformly random lozenge
tilings of polygons on the triangular lattice; or, equivalently, of random
stepped surfaces. We work with a class of polygons which allows arbitrarily
large number of sides. We show that the local limit behavior of random tilings
(as all dimensions of the polygon grow) is directed by ergodic translation
invariant Gibbs measures. The slopes of these measures coincide with the ones
of tangent planes to the corresponding limit shapes described by Kenyon and
Okounkov in arXiv:math-ph/0507007. We also prove that at the edge of the limit
shape, the asymptotic behavior of random tilings is given by the Airy process.
  In particular, our results cover the most investigated case of random boxed
plane partitions (when the polygon is a hexagon).


  In the SU(3) Einstein-Yang-Mills system sequences of static spherically
symmetric regular solutions and black hole solutions exist for both the SU(2)
and the SO(3) embedding. We construct the lowest regular solutions of the SO(3)
embedding, missed previously, and the corresponding black holes. The SO(3)
solutions are classified according to their boundary conditions and the number
of nodes of the matter functions. Both, the regular and the black hole
solutions are unstable.


  3D city models can be generated from aerial images. However, the calculated
DSMs suffer from noise, artefacts, and data holes that have to be manually
cleaned up in a time-consuming process. This work presents an approach that
automatically refines such DSMs. The key idea is to teach a neural network the
characteristics of urban area from reference data. In order to achieve this
goal, a loss function consisting of an L1 norm and a feature loss is proposed.
These features are constructed using a pre-trained image classification
network. To learn to update the height maps, the network architecture is set up
based on the concept of deep residual learning and an encoder-decoder
structure. The results show that this combination is highly effective in
preserving the relevant geometric structures while removing the undesired
artefacts and noise.


  We derive the category-theoretic backbone of quantum theory from a process
ontology. More specifically, we treat quantum theory as a theory of systems,
processes and their interactions.
  In this first part of a three-part overview, we first present a general
theory of diagrams, and in particular, of string diagrams. We discuss why
diagrams are a very natural starting point for developing scientific theories.
Then we define process theories, and define a very general notion of quantum
type. We show how our process ontology enables us to assert causality, that is,
compatibility of quantum theory and relativity theory, and we prove the
no-signalling theorem.
  Other notable contributions include new, elegant derivations of the
no-broadcasting theorem, unitarity of evolution, and Stinespring dilation, all
for any 'quantum' type in a general class of process theories.


  Full-text search engines are important tools for information retrieval. In a
proximity full-text search, a document is relevant if it contains query terms
near each other, especially if the query terms are frequently occurring words.
For each word in a text, we use additional indexes to store information about
nearby words that are at distances from the given word of less than or equal to
the MaxDistance parameter. We showed that additional indexes with
three-component keys can be used to improve the average query execution time by
up to 94.7 times if the queries consist of high-frequency occurring words. In
this paper, we present a new search algorithm with even more performance gains.
We consider several strategies for selecting multi-component key indexes for a
specific query and compare these strategies with the optimal strategy. We also
present the results of search experiments, which show that three-component key
indexes enable much faster searches in comparison with two-component key
indexes.
  This is a pre-print of a contribution "Veretennikov A.B. (2019) Proximity
Full-Text Search by Means of Additional Indexes with Multi-component Keys: In
Pursuit of Optimal Performance." published in "Manolopoulos Y., Stupnikov S.
(eds) Data Analytics and Management in Data Intensive Domains. DAMDID/RCDL
2018. Communications in Computer and Information Science, vol 1003" published
by Springer, Cham. This book constitutes the refereed proceedings of the 20th
International Conference on Data Analytics and Management in Data Intensive
Domains, DAMDID/RCDL 2018, held in Moscow, Russia, in October 2018. The 9
revised full papers presented together with three invited papers were carefully
reviewed and selected from 54 submissions. The final authenticated version is
available online at https://doi.org/10.1007/978-3-030-23584-0_7.


  Robust model fitting plays a vital role in computer vision, and research into
algorithms for robust fitting continues to be active. Arguably the most popular
paradigm for robust fitting in computer vision is consensus maximisation, which
strives to find the model parameters that maximise the number of inliers.
Despite the significant developments in algorithms for consensus maximisation,
there has been a lack of fundamental analysis of the problem in the computer
vision literature. In particular, whether consensus maximisation is "tractable"
remains a question that has not been rigorously dealt with, thus making it
difficult to assess and compare the performance of proposed algorithms,
relative to what is theoretically achievable. To shed light on these issues, we
present several computational hardness results for consensus maximisation. Our
results underline the fundamental intractability of the problem, and resolve
several ambiguities existing in the literature.


  Following the recent discussion on the puzzling nature of the interactions in
the nanotubular system Na2V3O7, we present a detailed ab-initio microscopic
analysis of its electronic and magnetic properties. By means of a non-trivial
downfolding study we propose an effective model in terms of tubes of nine-site
rings with the geometry of a spin-diamond necklace with frustrated inter-ring
interactions. We show that this model provides a quantitative account of the
observed magnetic behavior.


  During recent years the field of fine-grained complexity has bloomed to
produce a plethora of results, with both applied and theoretical impact on the
computer science community. The cornerstone of the framework is the notion of
fine-grained reductions, which correlate the exact complexities of problems
such that improvements in their running times or hardness results are carried
over. We provide a parameterized viewpoint of these reductions (PFGR) in order
to further analyze the structure of improvable problems and set the foundations
of a unified methodology for extending algorithmic results. In this context, we
define a class of problems (FPI) that admit fixed-parameter improvements on
their running time. As an application of this framework we present a truly
sub-quadratic fixed-parameter algorithm for the orthogonal vectors problem.
Finally, we provide a circuit characterization for FPI to further solidify the
notion of improvement.


  We report on deep radio images and optical spectroscopy of two BL Lac objects
that have very close compact companions. The two targets, 1ES 0502+675 and 1ES
1440+122, were selected from the HST imaging survey of 110 BL Lacs as
candidates for possible gravitational lensing. The new observations clearly
demonstrate that the companion objects are not secondary images of the active
nuclei but, in spite of the relatively low chance projection probability,
foreground Galactic stars. Gravitational lensing appears to be unimportant to
the BL Lac phenomenon. We discuss the radio properties of the BL Lac objects in
the context of standard beaming models, and show they are as expected for
beamed FRI radio galaxies.


  Consider binary system with a millisecond pulsar ejecting relativistic
particles and an optical star emitting soft photons with the energy $\omega
\simeq 1-10$ eV. These low-energy photons are scattered by the relativistic
electrons and positrons of the pulsar's wind. The scattered photons forms a
wide spectrum from hard X-ray band up to gamma band $\epsilon \simeq 1-1000$GeV
>.When the pulsar wind is isotropic the luminosity of gamma radiation $L_\gamma
=L_\gamma (\psi)$ depends heavily on the angle $\psi $ between the directions
to the optical star and to the observer from the pulsar. During the orbital
motion this angle varies periodically giving rise to the periodical change of
the observed intensity of the gamma radiation and its spectrum. We calculated
the spectral shape of the scattered hard photons. Under the assumption that the
energy losses of the relativistic particles are small we receive analytical
formulas. We apply our results to the binary system PSR B1259-63 and show that
if the wind from the Be star is accounted for then it is possible to reproduce
the observed spectrum.


  We consider a system consisting of a server, which receives updates for $N$
files according to independent Poisson processes. The goal of the server is to
deliver the latest version of the files to the user through a parallel network
of $K$ caches. We consider an update received by the user successful, if the
user receives the same file version that is currently prevailing at the server.
We derive an analytical expression for information freshness at the user. We
observe that freshness for a file increases with increase in consolidation of
rates across caches. To solve the multi-cache problem, we first solve the
auxiliary problem of a single-cache system. We then rework this auxiliary
solution to our parallel-cache network by consolidating rates to single routes
as much as possible. This yields an approximate (sub-optimal) solution for the
original problem. We provide an upper bound on the gap between the sub-optimal
solution and the optimal solution. Numerical results show that the sub-optimal
policy closely approximates the optimal policy.


  There exists an inevitable scatter in intrinsic luminosity of Gamma Ray
Bursts(GRBs). If there is relativistic beaming in the source, viewing angle
variation necessarily introduces variation in the intrinsic luminosity function
(ILF). Scatter in the ILF can cause a selection bias where distant sources that
are detected have a larger median luminosity than those detected close by.
Median luminosity divides any given population into equal halves. When the
functional form of a distribution is unknown, it can be a more robust
diagnostic than any that use trial functional forms. In this work we employ a
statistical test based on median luminosity and apply it to test a class of
models for GRBs. We assume that the GRB jet has a finite opening angle and that
the orientation of the GRB jet is random relative to the observer.We calculate
$L_{median}$ as a function of redshift by simulating GRBs empirically,
theoretically and use the luminosity vs redshift {\it Swift} data in order to
compare the theoretical results with the observed ones.
  The method accounts for the fact that at some redshifts there may be some
GRBs that go undetected. We find that $L_{median}$ is extremely insensitive to
the on-axis (i.e. maximal) luminosity of the jet.


  Coronary angiography is the gold standard imaging technique for studying and
diagnosing coronary artery disease. However, the resulting 2D X-ray projections
lose 3D information and exhibit visual ambiguities. In this work, we aim to
establish dense correspondence in multi-view angiography, serving as a
fundamental basis for various clinical applications and downstream tasks. To
overcome the challenge of unavailable annotated data, we designed a data
simulation pipeline using 3D Coronary Computed Tomography Angiography (CCTA).
We formulated the problem of dense correspondence estimation as a query
matching task over all points of interest in the given views. We established
point-to-point query matching and advanced it to curve-to-curve correspondence,
significantly reducing errors by minimizing ambiguity and improving topological
awareness. The method was evaluated on a set of 1260 image pairs from different
views across 8 clinically relevant angulation groups, demonstrating compelling
results and indicating the feasibility of establishing dense correspondence in
multi-view angiography.


  A powerful result from behavioral systems theory known as the fundamental
lemma allows for predictive control akin to Model Predictive Control (MPC) for
linear time invariant (LTI) systems with unknown dynamics purely from data.
While most of data-driven predictive control literature focuses on robustness
with respect to measurement noise, only few works consider exploiting
probabilistic information of disturbances for performance-oriented control as
in stochastic MPC. In this work, we propose a novel data-driven stochastic
predictive control scheme for chance-constrained LTI systems subject to
measurement noise and additive stochastic disturbances. In order to render the
otherwise stochastic and intractable optimal control problem deterministic, our
approach leverages ideas from tube-based MPC by decomposing the state into a
deterministic nominal state driven by inputs and a stochastic error state
affected by disturbances. By tightening constraints probabilistically with
respect to the additive disturbance and robustly with respect to the
measurement noise, satisfaction of original chance-constraints is guaranteed.
The resulting data-driven receding horizon optimal control problem is
lightweight and recursively feasible, and renders the closed loop
input-to-state stable with respect to both additive disturbances and
measurement noise. We demonstrate the effectiveness of the proposed approach in
a simulation example.


  In this paper, we prove the Iwasawa main conjecture of totally real fields
for certain specific non-commutative $p$-adic Lie extensions, using the
integral logarithms introduced by Oliver and Taylor. Our result gives certain
generalization of Kazuya Kato's proof of the main conjecture for Galois
extensions of Heisenberg type.


  We computed the abundance of refractory elements in planetary bodies formed
in stellar systems with solar chemical composition by combining models for
chemical composition and planet formation. We also consider the formation of
refractory organic compounds, which have been ignored in previous studies on
this topic. We used the commercial software package HSC Chemistry in order to
compute the condensation sequence and chemical composition of refractory
minerals incorporated into planets. The problem of refractory organic material
is approached with two distinct model calculations: the first considers that
the fraction of atoms used in the formation of organic compounds is removed
from the system (i.e. organic compounds are formed in the gas phase and are
nonreactive); and the second assumes that organic compounds are formed by the
reaction between different compounds that had previously condensed from the gas
phase. Results show that refractory material represents more than 50 wt % of
the mass of solids accreted by the simulated planets, with up to 30 wt % of the
total mass composed of refractory organic compounds. Carbide and silicate
abundances are consistent with C/O and Mg/Si elemental ratios of 0.5 and 1.02
for the Sun. Less than 1 wt % of carbides; pyroxene and olivine in similar
quantities are formed. The model predicts planets that are similar in
composition to those of the Solar system. It also shows that, starting from a
common initial nebula composition, a wide variety of chemically different
planets can form, which means that the differences in planetary compositions
are due to differences in the planetary formation process. We show that a model
in which refractory organic material is absent from the system is more
compatible with observations. The use of a planet formation model is essential
to form a wide diversity of planets in a consistent way.


  New results of the NA49 collaboration on strange particle production are
presented. Rapidity and transverse mass spectra as well as total multiplicities
are discussed. The study of their evolution from AGS over SPS to the highest
RHIC energy reveals a couple of interesting features. These include a sudden
change in the energy dependence of the mt-spectra and of the yields of strange
hadrons around 30 AGeV. Both are found to be difficult to be reproduced in a
hadronic scenario, but might be an indication for a phase transition to a quark
gluon plasma.


  AIMS: We aim to evaluate the near-infrared colors of brown dwarfs as observed
with four major infrared imaging space observatories: the Hubble Space
Telescope (HST), the James Webb Space Telescope (JWST), the Euclid mission, and
the WFIRST telescope.
  METHODS: We used the SPLAT SPEX/ISPEX spectroscopic library to map out the
colors of the M-, L-, and T-type dwarfs. We have identified which color-color
combination is optimal for identifying broad type and which single color is
optimal to then identify the subtype (e.g., T0-9). We evaluated each
observatory separately as well as the narrow-field (HST and JWST) and
wide-field (Euclid and WFIRST) combinations.
  RESULTS: The Euclid filters perform poorly typing brown dwarfs and WFIRST
performs only marginally better, despite a wider selection of filters. WFIRST's
W146 and F062 combined with Euclid's Y-band discriminates somewhat better
between broad brown dwarf categories. However, subtyping with any combination
of Euclid and WFIRST observations remains uncertain due to the lack of medium
or narrow-band filters. We argue that a medium band added to the WFIRST filter
selection would greatly improve its ability to preselect brown dwarfs its
imaging surveys.
  CONCLUSIONS: The HST filters used in high-redshift searches are close to
optimal to identify broad stellar type. However, the addition of F127M to the
commonly used broad filter sets would allow for unambiguous subtyping. An
improvement over HST is one of two broad and medium filter combinations on
JWST: pairing F140M with either F150W or F162M discriminates very well between
subtypes.


  We report the discovery of a pair of extremely reddened classical Cepheid
variable stars located in the Galactic plane behind the bulge, using
near-infrared time-series photometry from the VVV Survey. This is the first
time that such objects have ever been found in the opposite side of the
Galactic plane. The Cepheids have almost identical periods, apparent
brightnesses and colors. From the near-infrared Leavitt law, we determine their
distances with ~1.5% precision and ~8% accuracy. We find that they have a same
total extinction of A(V)~32 mag, and are located at the same heliocentric
distance of <d>=11.4+/-0.9 kpc, and less than 1 pc from the true Galactic
plane. Their similar periods indicate that the Cepheids are also coeval, with
an age of ~48+/-3 Myr, according to theoretical models. They are separated by
an angular distance of only 18.3", corresponding to a projected separation of
~1 pc. Their position coincides with the expected location of the Far 3 kpc Arm
behind the bulge. Such a tight pair of similar classical Cepheids indicates the
presence of an underlying young open cluster, that is both hidden behind heavy
extinction and disguised by the dense stellar field of the bulge. All our
attempts to directly detect this "invisible cluster" have failed, and deeper
observations are needed.


  A III-V compound semiconductor nanowire is an attractive material for a novel
hybrid quantum interface that interconnects photons, electrons, and phonons
through a wavelength-tunable quantum structure embedded in its free-standing
structure. In such a nanomechanical element, however, a challenge is how to
detect and manipulate a small number of phonons via its tiny mechanical motion.
A solution would be to couple an optical cavity to a nanowire by introducing
the ``cavity optomechanics'' framework, but the typical size difference between
them becomes a barrier to achieving this. Here, we demonstrate near-field
coupling of a silica microsphere cavity and an epitaxially grown InP/InAs
free-standing nanowire. The evanescent optomechanical coupling enables not only
fine probing of the mechanical motion by balanced homodyne interferometry but
also tuning of the resonance frequency, linewidth, Duffing nonlinearity, and
vibration axis in the nanowire. Combining this cavity optomechanics with
epitaxial nanowire engineering opens the way to novel quantum metrology and
information processing.


  The bimodality in observed present-day galaxy colours has long been a
challenge for hierarchical galaxy formation models, as it requires some
physical process to quench (and keep quenched) star formation in massive
galaxies. Here we examine phenomenological models of quenching by
post-processing the star formation histories of galaxies from cosmological
hydrodynamic simulations that reproduce observations of star-forming galaxies
reasonably well. We consider recipes for quenching based on major mergers, halo
mass thresholds, gas temperature thresholds, and variants thereof. We compare
the resulting simulated star formation histories to observed g-r
colour-magnitude diagrams and red and blue luminosity functions from SDSS. The
merger and halo mass quenching scenarios each yield a distinct red sequence and
blue cloud of galaxies that are in broad agreement with data, albeit only under
rather extreme assumptions. In detail, however, the simulated red sequence
slope and amplitude in each scenario is somewhat discrepant, perhaps traceable
to low metallicities in simulated galaxies. Merger quenching produces more
massive blue galaxies, earlier quenching, and more frosting of young stars;
comparing to relevant data tends to favor merger over halo mass quenching.
Although physically-motivated quenching models can produce a red sequence,
interesting generic discrepancies remain that indicate that additional physics
is required to reproduce the star formation and enrichment histories of red and
dead galaxies.


  We consider the Laplace operator with Dirichlet boundary conditions on a
domain in R^d and study the effect that performing a scaling in one direction
has on the eigenvalues and corresponding eigenfunctions as a function of the
scaling parameter around zero. This generalizes our previous results in two
dimensions and, as in that case, allows us to obtain an approximation for
Dirichlet eigenvalues for a large class of domains, under very mild
assumptions. As an application, we derive a three--term asymptotic expansion
for the first eigenvalue of d-dimensional ellipsoids.


  We consider the asymmetric simple exclusion process with Langmuir kinetics on
a periodic lattice. We analytically obtain the exact time evolution of
correlation functions with arbitrary length starting from the initial state
with no particle in the system. The exact stationary state of this model has
been known for the totally asymmetric case. We propose a basis transformation
which simplifies the proof of the stationarity of this state and enables the
generalization to the partially asymmetric case. Moreover, we construct
low-energy excitations and obtain the exact relaxation time.


  The present paper analyses the formal parallelism existing between the laws
of thermodynamics and some economic principles. Based on previous works, we
shall show how the existence in Economics of principles analogous to those in
thermodynamics involves the occurrence of economic events that remind of
well-known phenomenological thermodynamic paradigms (i.e., the magnetocaloric
effect and population inversion). We shall also show how the phase transition
and renormalization theory provides a natural framework to understand and
predict trend changes in stock markets. Finally, current negotiation strategies
in financial markets are briefly reviewed.


  We report J-band MOSFIRE spectroscopy of a low-mass
(log$(M_*/M_\odot)=8.62^{+0.10}_{-0.06}$) star-forming galaxy at $z=0.997$
showing the detection of [NII] and [SII] alongside a strong H$\alpha$ line. We
derive a gas-phase metallicity of
log$(\text{O}/\text{H})=7.99^{+0.13}_{-0.23}$, placing this object in a region
of $M_* - Z$ space that is sparsely populated at this redshift. Furthermore,
many existing metallicity measurements in this $M_* - z$ regime are derived
from only [NII]/H$\alpha$ (N2), a diagnostic widely used in high-redshift
metallicity studies despite the known strong degeneracy with the ionization
parameter and resulting large systematic uncertainty. We demonstrate that even
in a regime where [NII] and [SII] are at the detection limit and the
measurement uncertainty associated with the [NII]/[SII] ratio is high (S/N~3),
the more sophisticated Dopita et al. diagnostic provides an improved constraint
compared to N2 by reducing the systematic uncertainty due to the ionization
parameter. This approach does not, however, dispel uncertainty associated with
stochastic or systematic variations in the nitrogen-to-oxygen abundance ratio.
While this approach improves upon N2, future progress in extending metallicity
studies into this low-mass regime will require larger samples to allow for
stochastic variations, as well as careful consideration of the global trends
among dwarf galaxies in all physical parameters, not just metallicity.


  We report on the photometric properties of faculae and network as observed in
full-disk, scattered-light corrected images from the Helioseismic Magnetic
Imager. We use a Lucy-Richardson deconvolution routine that corrects an image
in less than one second. Faculae are distinguished from network through
proximity to active regions. This is the first report that full-disk
observations, including center-to-limb variations, reproduce the photometric
properties of faculae and network observed previously only in sub-arcsecond
resolution, small field-of-view studies, i.e. that network, as defined by
distance from active regions, exhibit higher photometric contrasts.
Specifically, for magnetic flux values larger than approximately 300 G, the
network is brighter than faculae and the contrast differences increases toward
the limb, where the network contrast is about twice the facular one. For lower
magnetic flux values, network appear darker than faculae. Contrary to reports
from previous full-disk observations, we also found that network exhibits a
higher center-to-limb variation. Our results are in agreement with reports from
simulations that indicate magnetic flux alone is a poor proxy of the
photometric properties of magnetic features. We estimate that the contribution
of faculae and network to Total Solar Irradiance variability of the current
Cycle 24 is overestimated by at least 11\% due to the photometric properties of
network and faculae not being recognized as different. This estimate is
specific to the method employed in this study to reconstruct irradiance
variations, so caution should be paid when extending it to other techniques.


  Why do Social Media Corporations (SMCs) engage in state-linked information
operations? Social media can significantly influence the global political
landscape, allowing governments and other political entities to engage in
concerted information operations, shaping or manipulating domestic and foreign
political agendas. In response to state-linked political manipulation tactics
on social media, Twitter and Meta carried out take-down operations against
propaganda networks, accusing them of interfering foreign elections, organizing
disinformation campaigns, manipulating political debates and many other issues.
This research investigates the two SMCs' policy orientation to explain which
factors can affect these two companies' reaction against state-linked
information operations. We find that good governance indicators such as
democracy are significant elements of SMCs' country-focus. This article also
examines whether Meta and Twitter's attention to political regime
characteristics is influenced by international political alignments. This
research illuminates recent trends in SMCs' take-down operations and
illuminating interplay between geopolitics and domestic regime characteristics.


  In this paper, we propose a new distributed energy beamforming and
information transfer (DEBIT) scheme for realizing simultaneous wireless
information and power transfer (SWIPT) in multiway relay networks (MWRNs),
where multiple single-antenna users exchange information via an
energy-constrained single-antenna relay node. We investigate the optimal
transceiver designs to maximize the achievable sum-rate or the harvested power.
The resultant sum-rate maximization problem is non-convex and the global
optimal solution can be obtained through a three-dimensional search in
combination with conventional convex optimization. To reduce the computation
complexity, a suboptimal DEBIT scheme is also proposed, for which the
optimization problem becomes linear programming. The achievable sum-rate
performance is analyzed and a closed-form lower bound is derived for the MWRN
with a large number of users. Furthermore, we consider the harvested-power
maximization problem under a target sum-rate constraint, and derive a lower
bound of the average harvested power for MWRNs with a large number of users.
Numerical results show that the DEBIT scheme significantly outperforms the
conventional SWIPT and the derived lower bounds are tight.


  We consider both the co-ordinates and momenta to be non-commutative and
define a non-commutative version of Lorentz symmetry which has a smooth limit
to the standard Lorentz symmetry. The Poincar\acute{e} algebra in this
spacetime has also been discussed.


  We study collisions between two strongly interacting atomic Fermi gas clouds.
We observe exotic nonlinear hydrodynamic behavior, distinguished by the
formation of a very sharp and stable density peak as the clouds collide and
subsequent evolution into a box-like shape. We model the nonlinear dynamics of
these collisions using quasi-1D hydrodynamic equations. Our simulations of the
time-dependent density profiles agree very well with the data and provide clear
evidence of shock wave formation in this universal quantum hydrodynamic system.


  We derive the equations for calculating the high-frequency asymptotics of the
local two-particle vertex function for a multi-orbital impurity model. These
relate the asymptotics for a general local interaction to equal-time
two-particle Green's functions, which we sample using continuous-time quantum
Monte Carlo simulations with a worm algorithm. As specific examples we study
the single-orbital Hubbard model and the three $t_{2g}$ orbitals of SrVO$_3$
within dynamical mean field theory (DMFT). We demonstrate how the knowledge of
the high-frequency asymptotics reduces the statistical uncertainties of the
vertex and further eliminates finite box size effects. The proposed method
benefits the calculation of non-local susceptibilities in DMFT and diagrammatic
extensions of DMFT.


  Recent and upcoming stabilized spectrographs are pushing the frontier for
Doppler spectroscopy to detect and characterize low-mass planets.
Specifications for these instruments are so impressive that intrinsic stellar
variability is expected to limit their Doppler precision for most target stars
(Fischer et al. 2016). To realize their full potential, astronomers must
develop new strategies for distinguishing true Doppler shifts from intrinsic
stellar variability. Stellar variability due to star spots, faculae and other
rotationally-linked variability are particularly concerning, as the stellar
rotation period is often included in the range of potential planet orbital
periods. To robustly detect and accurately characterize low-mass planets via
Doppler planet surveys, the exoplanet community must develop statistical models
capable of jointly modeling planetary perturbations and intrinsic stellar
variability. Towards this effort, this note presents simulations of extremely
high resolution, solar-like spectra created with SOAP 2.0 (arXiv:1409.3594)
that includes multiple evolving star spots. We anticipate this data set will
contribute to future studies developing, testing, and comparing statistical
methods for measuring physical radial velocities amid contamination by stellar
variability.


  We derive in full generality the equations that govern the time dependence of
the energy ${\mathcal E}$ of the decay electrons in a muon $g-2$ experiment. We
include both electromagnetic and gravitational effects and we estimate possible
systematics on the measurements of $g-2\equiv 2(1+a)$, whose experimental
uncertainty will soon reach $\Delta a/a\approx 10^{-7}$. In addition to the
standard modulation of ${\mathcal E}$ when the motion is orthogonal to a
constant magnetic field $B$, with angular frequency $\omega_a=e a |B|/m$, we
study effects due to: (1) a non constant muon $\gamma$ factor, in presence of
electric fields $E$, (2) a correction due to a component of the muon velocity
along $B$ (the `pitch correction'), (3) corrections to the precession rate due
to $E$ fields, (4) non-trivial spacetime metrics. Oscillations along the radial
and vertical directions of the muon lead to oscillations in ${\mathcal E}$ with
a relative size of order $10^{-6}$, for the BNL $g-2$ experiment. We then find
a subleading effect in the `pitch' correction, leading to a frequency shift of
$\Delta \omega_a/\omega_a \approx {\cal O}(10^{-9})$ and subleading effects of
about $\Delta \omega_a/\omega_a \approx {\rm few} \times {\cal
O}(10^{-8}-10^{-9})$ due to $E$ fields. Finally we show that GR effects are
dominated by the Coriolis force, due to the Earth rotation with angular
frequency $\omega_T$, leading to a correction of about $\Delta
\omega_a/\omega_a \approx \omega_T/(\gamma \omega_a) \approx {\cal
O}(10^{-12})$. A similar correction might be more appreciable for future
electron $g-2$ experiments, being of order $\Delta \omega_a/\omega_{a, {\rm
el}} \approx \omega_T/(\omega_{a, {\rm el}}) \approx 7\times 10^{-13}$,
compared to the present experimental uncertainty, $\Delta a_{\rm el}/a_{\rm
el}\approx 10^{-10}$, and forecasted to reach soon $\Delta a_{\rm el}/a_{\rm
el}\approx 10^{-11}$.


  Natural convection in porous media is a highly nonlinear multiphysical
problem relevant to many engineering applications (e.g., the process of
$\mathrm{CO_2}$ sequestration). Here, we present a non-intrusive reduced order
model of natural convection in porous media employing deep convolutional
autoencoders for the compression and reconstruction and either radial basis
function (RBF) interpolation or artificial neural networks (ANNs) for mapping
parameters of partial differential equations (PDEs) on the corresponding
nonlinear manifolds. To benchmark our approach, we also describe linear
compression and reconstruction processes relying on proper orthogonal
decomposition (POD) and ANNs. We present comprehensive comparisons among
different models through three benchmark problems. The reduced order models,
linear and nonlinear approaches, are much faster than the finite element model,
obtaining a maximum speed-up of $7 \times 10^{6}$ because our framework is not
bound by the Courant-Friedrichs-Lewy condition; hence, it could deliver
quantities of interest at any given time contrary to the finite element model.
Our model's accuracy still lies within a mean squared error of 0.07 (two-order
of magnitude lower than the maximum value of the finite element results) in the
worst-case scenario. We illustrate that, in specific settings, the nonlinear
approach outperforms its linear counterpart and vice versa. We hypothesize that
a visual comparison between principal component analysis (PCA) or t-Distributed
Stochastic Neighbor Embedding (t-SNE) could indicate which method will perform
better prior to employing any specific compression strategy.


  The field theory of self-avoiding tethered membranes still poses major
challenges. In this article, we report progress on the toy-model of a manifold
repelled by a single point. Our approach allows to sum the perturbation
expansion in the strength g_0 of the interaction exactly in the limit of
internal dimension D -> 2, yielding an analytic solution for the
strong-coupling limit. This analytic solution is the starting point for an
expansion in 2-D, which aims at connecting to the well studied case of polymers
(D=1). We give results to fourth order in 2-D, where the dependence on g_0 is
again summed exactly. As an application, we discuss plaquette density
functions, and propose a Monte-Carlo experiment to test our results. These
methods should also allow to shed light on the more complex problem of
self-avoiding manifolds.


  To assist surgeons in the operating theatre, surgical phase recognition is
critical for developing computer-assisted surgical systems, which requires
comprehensive understanding of surgical videos. Although existing studies made
great progress, there are still two significant limitations worthy of
improvement. First, due to the compromise of resource consumption, frame-wise
visual features are extracted by 2D networks and disregard spatial and temporal
knowledge of surgical actions, which hinders subsequent inter-frame modeling
for phase prediction. Second, these works simply utilize ordinary
classification loss with one-hot phase labels to optimize the phase
predictions, and cannot fully explore surgical videos under inadequate
supervision. To overcome these two limitations, we propose a Surgical Temporal
Action-aware Network with sequence Regularization, named STAR-Net, to recognize
surgical phases more accurately from input videos. Specifically, we propose an
efficient multi-scale surgical temporal action (MS-STA) module, which
integrates visual features with spatial and temporal knowledge of surgical
actions at the cost of 2D networks. Moreover, we devise the dual-classifier
sequence regularization (DSR) to facilitate the training of STAR-Net by the
sequence guidance of an auxiliary classifier with a smaller capacity. Our
STAR-Net with MS-STA and DSR can exploit visual features of surgical actions
with effective regularization, thereby leading to the superior performance of
surgical phase recognition. Extensive experiments on a large-scale gastrectomy
surgery dataset and the public Cholec80 benchmark prove that our STAR-Net
significantly outperforms state-of-the-arts of surgical phase recognition.


  Detecting social bias in text is challenging due to nuance, subjectivity, and
difficulty in obtaining good quality labeled datasets at scale, especially
given the evolving nature of social biases and society. To address these
challenges, we propose a few-shot instruction-based method for prompting
pre-trained language models (LMs). We select a few class-balanced exemplars
from a small support repository that are closest to the query to be labeled in
the embedding space. We then provide the LM with instruction that consists of
this subset of labeled exemplars, the query text to be classified, a definition
of bias, and prompt it to make a decision. We demonstrate that large LMs used
in a few-shot context can detect different types of fine-grained biases with
similar and sometimes superior accuracy to fine-tuned models. We observe that
the largest 530B parameter model is significantly more effective in detecting
social bias compared to smaller models (achieving at least 13% improvement in
AUC metric compared to other models). It also maintains a high AUC (dropping
less than 2%) when the labeled repository is reduced to as few as $100$
samples. Large pretrained language models thus make it easier and quicker to
build new bias detectors.


  We have studied the nature and origin of the soft X-ray excess detected in
the interesting changing-look AGN (CLAGN) Mrk~590 using two decades of
multi-wavelength observations from \xmm{}, \suzaku{}, \swift{} and \nustar{}.
In the light of vanishing soft excess in this CLAGN, we test two models, "the
warm Comptonization" and "the ionized disk reflection" using extensive UV/X-ray
spectral analysis. Our main findings are: (1) the soft X-ray excess emission,
last observed in 2004, vanished in 2011, and never reappeared in any of the
later observations, (2) we detected a significant variability ($\sim300\%$) in
the observed optical-UV and power-law flux between observations with the lowest
state ($L_{\rm bol} = 4.4\times 10^{43}\, erg\, s^{-1}$, in 2016) and the
highest state ($L_{\rm bol} = 1.2\times 10^{44}\, erg\, s^{-1}$, in 2018), (3)
the UV and power-law fluxes follow same temporal pattern, (4) the photon index
showed a significant variation ($\Gamma=1.88^{+0.02}_{-0.08}$ and
$\Gamma=1.58^{+0.02}_{-0.03}$ in 2002 and 2021 respectively) between
observations, (5) no Compton hump was detected in the source spectra but a
narrow Fe$K_{\alpha}$ line is present in all observations, (6) we detected a
high-energy cut-off in power-law continuum ($92^{+55}_{-25} \rm keV$ and
$60^{+10}_{-08} \rm keV$) with the latest \nustar{} observations, (7) the warm
Comptonization model needs an additional diskbb component to describe the
source UV bump, (8) there is no correlation between the Eddington rate and the
soft excess as found in other changing-look AGNs. We conclude that given the
spectral variability in UV/X-rays, the ionized disk reflection or the warm
Comptonization models may not be adequate to describe the vanishing soft excess
feature observed in Mrk~590.


  This communication deals with a theoretical study of the hot spot onset (HSO)
in cellular bipolar power transistors. This well-known phenomenon consists of a
current crowding within few cells occurring for high power conditions, which
significantly decreases the forward safe operating area (FSOA) of the device.
The study was performed on a virtual sample by means of a fast, fully
analytical electro-thermal simulator operating in the steady state regime and
under the condition of imposed input base current. The purpose was to study the
dependence of the phenomenon on several thermal and geometrical factors and to
test suitable countermeasures able to impinge this phenomenon at higher biases
or to completely eliminate it. The power threshold of HSO and its localization
within the silicon die were observed as a function of the electrical bias
conditions as for instance the collector voltage, the equivalent thermal
resistance of the assembling structure underlying the silicon die, the value of
the ballasting resistances purposely added in the emitter metal
interconnections and the thickness of the copper heat spreader placed on the
die top just to the aim of making more uniform the temperature of the silicon
surface.


  The goal of audio captioning is to translate input audio into its description
using natural language. One of the problems in audio captioning is the lack of
training data due to the difficulty in collecting audio-caption pairs by
crawling the web. In this study, to overcome this problem, we propose to use a
pre-trained large-scale language model. Since an audio input cannot be directly
inputted into such a language model, we utilize guidance captions retrieved
from a training dataset based on similarities that may exist in different
audio. Then, the caption of the audio input is generated by using a pre-trained
language model while referring to the guidance captions. Experimental results
show that (i) the proposed method has succeeded to use a pre-trained language
model for audio captioning, and (ii) the oracle performance of the pre-trained
model-based caption generator was clearly better than that of the conventional
method trained from scratch.


  Screen recordings are becoming increasingly important as rich software
artifacts that inform mobile application development processes. However, the
amount of manual effort required to extract information from these graphical
artifacts can hinder resource-constrained mobile developers. This paper
presents Video2Scenario (V2S), an automated tool that processes video
recordings of Android app usages, utilizes neural object detection and image
classification techniques to classify the depicted user actions, and translates
these actions into a replayable scenario. We conducted a comprehensive
evaluation to demonstrate V2S's ability to reproduce recorded scenarios across
a range of devices and a diverse set of usage cases and applications. The
results indicate that, based on its performance with 175 videos depicting 3,534
GUI-based actions, V2S is accurate in reproducing $\approx$89\% of actions from
collected videos.


  SimRank, proposed by Jeh and Widom, provides a good similarity measure that
has been successfully used in numerous applications. While there are many
algorithms proposed for computing SimRank, their computational costs are very
high. In this paper, we propose a new computational technique, "SimRank
linearization," for computing SimRank, which converts the SimRank problem to a
linear equation problem. By using this technique, we can solve many SimRank
problems, such as single-pair compuation, single-source computation, all-pairs
computation, top k searching, and similarity join problems, efficiently.


  We re-analyze the flavor decomposition of the pion-nucleon $\sigma$-term in
the framework of baryon chiral perturbation to fourth order. We employ a
covariant and the heavy baryon framework including also the low-lying decuplet.
Using only continuum data, we find a small strangeness content of the proton.
The uncertainties are, however, large and might be overcome by dedicated
lattice QCD calculations.


  We compare the 3D clustering of old passively-evolving and dusty star-forming
z~1 EROs from the K20 survey. With detailed simulations of clustering, the
comoving correlation length of dusty star-forming EROs is constrained to be
less than r_0~2.5 Mpc/h. In contrast, the old EROs are much more positively
correlated, with 5.5<~r_0/(Mpc/h)<~16, consistent with previous claims for z~1
field early-type galaxies based on analyses of ERO angular clustering. The low
level of clustering of dusty star-forming EROs does not support these to be
major mergers building up an elliptical galaxy, or typical counterparts of
SCUBA sources, but it is instead consistent with the weak clustering of high
redshift blue galaxies and of luminous local IRAS galaxies. Current
hierarchical merging models can explain the large r_0 for z~1 field early-type
galaxies, but fail in matching their high number density and overall old ages.


  Typical semiconductor chips include thousands of mostly small memories. As
memories contribute an estimated 25% to 40% to the overall power, performance,
and area (PPA) of a chip, memories must be designed carefully to meet the
system's requirements. Memory arrays are highly uniform and can be described by
approximately 10 parameters depending mostly on the complexity of the
periphery. Thus, to improve PPA utilization, memories are typically generated
by memory compilers. A key task in the design flow of a chip is to find optimal
memory compiler parametrizations which on the one hand fulfill system
requirements while on the other hand optimize PPA. Although most compiler
vendors also provide optimizers for this task, these are often slow or
inaccurate. To enable efficient optimization in spite of long compiler run
times, we propose training fully connected feed-forward neural networks to
predict PPA outputs given a memory compiler parametrization. Using an
exhaustive search-based optimizer framework which obtains neural network
predictions, PPA-optimal parametrizations are found within seconds after chip
designers have specified their requirements. Average model prediction errors of
less than 3%, a decision reliability of over 99% and productive usage of the
optimizer for successful, large volume chip design projects illustrate the
effectiveness of the approach.


  We prove the following two results relating real mutually unbiased bases and
representations of finite groups of odd order. Let $q$ be a power of 2 and $r$
a positive integer. Then we can find a $q^{2r}\times q^{2r}$ real orthogonal
matrix $D$, say, of multiplicative order $q^{2r-1}+1$, whose $q^{2r-1}+1$
powers $D$, \dots, $D^{q^{2r-1}+1}=I$ define $q^{2r-1}+1$ mutually unbiased
bases in $\mathbb{R}^{q^{2r}}$. Thus the scaled matrices $q^rD$, \dots,
$q^rD^{q^{2r-1}}$ are $q^{2r-1}$ different Hadamard matrices. When we take
$q=2$, we achieve the maximum number of real mutually unbiased bases in
dimension $2^{2r}$ using the elements of a cyclic group. We also prove the
following. Let $G$ be an arbitrary finite group of odd order $2k+1$, where
$k\geq 3$. Then $G$ has a real representation $R$, say, of degree $2^{2^{k-1}}$
such that the elements $R(\sigma)$, $\sigma\in G$, define $|G|$ mutually
unbiased bases in $\mathbb{R}^{d}$, where $d= 2^{2^{k-1}}$. In addition, a
group of order 5 defines five real mutually unbiased bases in $\mathbb{R}^{16}$
and a group of order 3 defines three real mutually unbiased bases in
$\mathbb{R}^{4}$. Thus, an arbitrary group of odd order has a faithful
representation by real scaled Hadamard matrices of 2-power size.


  We present dynamic density functional theory (DDFT) incorporating general
inhomogeneous, incompressible, time dependent background flows and inertia,
describing externally driven passive colloidal systems out of equilibrium. We
start by considering the underlying nonequilibrium Langevin dynamics, including
the effect of the local velocity of the surrounding liquid bath, to obtain the
nonlinear, nonlocal partial differential equations governing the evolution of
the (coarse--grained) density and velocity fields describing the dynamics of
colloids. Additionally, we show both with heuristic arguments, and by numerical
solution, that our equations and solutions agree with existing DDFTs in the
overdamped (high friction) limit. We provide numerical solutions that model the
flow of hard spheres, in both unbounded and confined domains, and compare to
previously--derived DDFTs with and without the background flow.


  Recent calculations with an effective isospin dependent contact interaction
show the possibility of the crossover from superfluidity of neutron Cooper
pairs in $^1S_0$ pairing channel to Bose-Einstein condensation (BEC) of
di-neutron bound states in dilute nuclear matter. The density and spin
correlation functions are calculated for a di-neutron condensate in asymmetric
nuclear matter with the aim to find the possible features of the BCS-BEC
crossover. It is shown that the zero-momentum transfer spin correlation
function satisfies the sum rule at zero temperature. In symmetric nuclear
matter, the density correlation function changes sign at low momentum transfer
across the BCS-BEC transition and this feature can be considered as a signature
of the crossover. At finite isospin asymmetry, this criterion gives too large
value for the critical asymmetry $\alpha_c^d\sim0.9$, at which the BEC state is
quenched. Therefore, it can be trusted for the description of the
density-driven BCS-BEC crossover of neutron pairs only at small isospin
asymmetry.
  This result generalizes the conclusion of the study in Phys. Rev. Lett. {\bf
95}, 090402 (2005), where the change of sign of the density correlation
function at low momentum transfer in two-component quantum fermionic atomic gas
with the balanced populations of fermions of different species was considered
as an unambiguous signature of the BCS-BEC transition.


  Schubert polynomials are refined by the key polynomials of
Lascoux-Sch\"{u}tzenberger, which in turn are refined by the fundamental slide
polynomials of Assaf-Searles. In this paper we determine which fundamental
slide polynomial refinements of key polynomials, indexed by strong
compositions, are multiplicity free. We also give a recursive algorithm to
determine all terms in the fundamental slide polynomial refinement of a key
polynomial indexed by a strong composition. From here, we apply our results to
begin to classify which fundamental slide polynomial refinements, indexed by
weak compositions, are multiplicity free. We completely resolve the cases when
the weak composition has at most two nonzero parts or the sum has at most two
nonzero terms.


  Pareto Front Learning (PFL) was recently introduced as an efficient method
for approximating the entire Pareto front, the set of all optimal solutions to
a Multi-Objective Optimization (MOO) problem. In the previous work, the mapping
between a preference vector and a Pareto optimal solution is still ambiguous,
rendering its results. This study demonstrates the convergence and completion
aspects of solving MOO with pseudoconvex scalarization functions and combines
them into Hypernetwork in order to offer a comprehensive framework for PFL,
called Controllable Pareto Front Learning. Extensive experiments demonstrate
that our approach is highly accurate and significantly less computationally
expensive than prior methods in term of inference time.


  Registration is a fundamental task in medical robotics and is often a crucial
step for many downstream tasks such as motion analysis, intra-operative
tracking and image segmentation. Popular registration methods such as ANTs and
NiftyReg optimize objective functions for each pair of images from scratch,
which are time-consuming for 3D and sequential images with complex
deformations. Recently, deep learning-based registration approaches such as
VoxelMorph have been emerging and achieve competitive performance. In this
work, we construct a test-time training for deep deformable image registration
to improve the generalization ability of conventional learning-based
registration model. We design multi-scale deep networks to consecutively model
the residual deformations, which is effective for high variational
deformations. Extensive experiments validate the effectiveness of multi-scale
deep registration with test-time training based on Dice coefficient for image
segmentation and mean square error (MSE), normalized local cross-correlation
(NLCC) for tissue dense tracking tasks. Two videos are in
https://www.youtube.com/watch?v=NvLrCaqCiAE and
https://www.youtube.com/watch?v=pEA6ZmtTNuQ


  We present a prototype for the first tracking detector consisting of 250
micron thin scintillating fibers and silicon photomultiplier (SiPM) arrays. The
detector has a modular design, each module consists of a mechanical support
structure of 10mm Rohacell foam between two 100 micron thin carbon fiber skins.
Five layers of scintillating fibers are glued to both top and bottom of the
support structure. SiPM arrays with a channel pitch of 250 micron are placed in
front of the fibers. We show the results of the first module prototype using
multiclad fibers of types Bicron BCF-20 and Kuraray SCSF-81M that were read out
by novel 32-channel SiPM arrays from FBK-irst/INFN Perugia as well as
32-channel SiPM arrays produced by Hamamatsu. A spatial resolution of 88 micron
+/- 6 micron at an average yield of 10 detected photons per minimal ionizig
particle has been achieved.


  We study a simple model of vector dark matter that couples to Standard Model
particles via magnetic dipole interactions. In this scenario, the cosmological
abundance arises through the freeze-in mechanism and depends on the dipole
coupling, the vector mass, and the reheat temperature. To ensure cosmological
metastability, the vector must be lighter than the fermions to which it
couples, but rare decays can still produce observable 3$\gamma$ final states;
two-body decays can also occur at one-loop with additional weak suppression,
but are subdominant if the vector couples mainly to light fermions. For
sufficiently heavy vectors, induced kinetic mixing with the photon can also
yield additional two body decays to lighter fermions and predict indirect
detection signals through final state radiation. We explore the implications of
couplings to various flavors of visible particles and emphasize leptophilic
dipoles involving electrons, muons, and taus, which offer the most promising
indirect detection signatures through 3$\gamma$, $e^+ e^- \gamma$, and $\mu^+
\mu^- \gamma$ decay channels. We also present constraints from current and past
telescopes, and sensitivity projections for future missions including
e-ASTROGAM and AMEGO.


  We discuss the evolution of the magnetic field of an accreting white dwarf.
We first show that the timescale for ohmic decay in the liquid interior is 8 to
12 billion years for a dipole field, and 4 to 6 billion years for a quadrupole
field. We then compare the timescales for ohmic diffusion and accretion at
different depths in the star, and for a simplified field structure and
spherical accretion, calculate the time-dependent evolution of the global
magnetic field at different accretion rates. In this paper, we neglect mass
loss by classical nova explosions and assume the white dwarf mass increases
with time. In this case, the field structure in the outer layers of the white
dwarf is significantly modified for accretion rates above the critical rate
(1-5) x 10^(-10) solar masses per year. We consider the implications of our
results for observed systems. We propose that accretion-induced magnetic field
changes are the missing evolutionary link between AM Her systems and
intermediate polars. The shorter ohmic decay time for accreting white dwarfs
provides a partial explanation of the lack of accreting systems with 10^9 G
fields. In rapidly accreting systems such as supersoft X-ray sources,
amplification of internal fields by compression may be important for Type Ia
supernova ignition and explosion. Finally, spreading matter in the polar cap
may induce complexity in the surface magnetic field, and explain why the more
strongly accreting pole in AM Her systems has a weaker field. We conclude with
speculations about the field evolution when classical nova explosions cause the
white dwarf mass to decrease with time.


  We have developed a modular system for high-resolution microscopy at high
hydrostatic pressure. The system consists of a pressurised cell of volume ~100
microlitres, a temperature controlled holder, a ram and a piston. We have made
each of these components in several versions which can be interchanged to allow
a wide range of applications. Here, we report two pressure cells with pressure
ranges 0.1-700MPa and 0.1-100MPa, which can be combined with hollow or solid
rams and pistons. Our system is designed to work with fluorescent samples
(using a confocal or epifluorescence microscope), but also allows for
transmitted light microscopy via the hollow ram and piston. The system allows
precise control of pressure and temperature [-20-70C], as well as rapid
pressure quenching. We demonstrate its performance and versatility with two
applications: time-resolved imaging of colloidal phase transitions caused by
pressure changes between 0.1MPa and 101MPa, and imaging the growth of
Escherichia coli bacteria at 50MPa. We also show that the isotropic-nematic
phase transition of pentyl-cyanobiphenyl (5CB) liquid crystal provides a
simple, convenient and accurate method for calibrating pressure in the range
0.1-200MPa.


  AA Dor is an eclipsing, close, post common-envelope binary consisting of a
sdOB primary star and an unseen secondary with an extraordinary small mass -
formally a brown dwarf. The brown dwarf may have been a former planet which
survived a common envelope phase and has even gained mass.
  A recent determination of the components' masses from results of NLTE
spectral analysis and subsequent comparison to evolutionary tracks shows a
discrepancy to masses derived from radial-velocity and the eclipse curves.
Phase-resolved high-resolution and high-SN spectroscopy was carried out in
order to investigate on this problem.
  We present results of a NLTE spectral analysis of the primary, an analysis of
its orbital parameters, and discuss possible evolutionary scenarios.


  The brane world based on the 6D gravitational model is examined. It is
regarded as a higher dimensional version of the 5D model by Randall and Sundrum
>. The obtained analytic solution is checked by the numerical method. The mass
hierarchy is examined. Especially the {\it geometrical see-saw} mass relation,
between the Planck mass, the cosmological constant, and the neutrino mass, is
suggested. Comparison with the 5D model is made.


  Current fog systems rely on centralized and strongly consistent services for
configuration management originally designed for cloud systems. In the
geo-distributed fog, such systems can exhibit high communication latency or
become unavailable in case of network partition. In this paper, we examine the
drawbacks of strong consistency for fog configuration management and propose an
alternative based on CRDTs. We prototypically implement our approach for the
FReD fog data management platform. Early results show reductions of server
response times of up to 50\%.


  In this paper, we show that any solution of the nonlinear Schr{{\"o}}dinger
equation $iu\_t+\Delta u\pm|u|^\frac{4}{N}u=0,$ which blows up in finite time,
satisfies a mass concentration phenomena near the blow-up time. Our proof is
essentially based on the Bourgain's one~\cite{MR99f:35184}, which has
established this result in the bidimensional spatial case, and on a
generalization of Strichartz's inequality, where the bidimensional spatial case
was proved by Moyua, Vargas and Vega~\cite{MR1671214}. We also generalize to
higher dimensions the results in Keraani~\cite{MR2216444} and Merle and
Vega~\cite{MR1628235}.


  The paper presents linear predictors and causal filters for discrete time
signals featuring some different kinds of spectrum degeneracy. These predictors
and filters are based on approximation of ideal non-causal transfer functions
by causal transfer functions represented by polynomials of Z-transform of the
unit step signal.


  In this paper, we study the additive complexity $\rho^{+}_{\mathbf{t}}(n)$ of
a Thue-Morse like sequence $\mathbf{t}=\sigma^{\infty}(0)$ with the morphism
$\sigma: 0\to 01, 1\to 12, 2\to 20$. We show that
$\rho^{+}_{\mathbf{t}}(n)=2\lfloor\log_2(n)\rfloor+3$ for all integers $n\geq
1$. Consequently, $(\rho_{\mathbf{t}}(n))_{n\geq 1}$ is a $2$-regular sequence.


  In supersymmetric theories a field can develop a vacuum expectation value $M
\gg 10^3\,{\rm GeV}$, even though its mass $m$ is of order $10^2$ to
$10^3\,{\rm GeV}$. The finite temperature in the early Universe can hold such a
field at zero, corresponding to a false vacuum with energy density $ V_0 \sim
m^2 M^2 $. When the temperature falls below $V_0^{1/4}$, the thermal energy
density becomes negligible and an era of thermal inflation begins. It ends when
the field rolls away from zero at a temperature of order $m$, corresponding to
of order 10 $e$-folds of inflation which does not affect the density
perturbation generated during ordinary inflation. Thermal inflation can solve
the Polonyi/moduli problem if $M$ is within one or two orders of magnitude of
$10^{12}\,{\rm GeV}$.


  The main aim of this present paper is to present a new extension of the
fractional derivative operator by using the extension of Beta function recently
defined by Shadab et al.[19]. Moreover, we establish some results related to
the newly defined modified fractional derivative operator such as Mellin
transform and relations to extended hypergeometric and Appell's function via
generating functions.


  S. Brodsky, F.J. Llanes-Estrada, and A. Szczepaniak formulated the $J=0$
fixed pole universality hypothesis for (deeply) virtual Compton scattering. We
show that in the Bjorken limit this hypothesis is equivalent to the validity of
the inverse moment sum rule for the $D$-term form factor. However, any
supplementary $D$-term added to a generalized parton distribution (GPD) results
in an additional $J=0$ fixed pole contribution that violates universality.
Unfortunately, one can not provide any reliable theoretical argument excluding
the existence of such supplementary $D$-term. Moreover, the violation of $J=0$
fixed pole universality was revealed in field theoretical GPD models.
Therefore, $J=0$ fixed pole universality hypothesis remains just an external
assumption and probably will never be proven theoretically.


  Tournaments are graphs obtained by assigning a direction for every edge in an
undirected complete graph. We give a formula for the number of isomorphism
classes of vertex-transitive tournaments with prime order. For that, we
introduce Cayley tournaments, which are special Cayley digraphs, and show that
there is a one to one identification between the isomorphism classes of
vertex-transitive tournaments with prime order and the isomorphism classes of
Cayley tournaments with prime order.


  We develop a theory for interacting fermions in the presence of spin-orbit
coupling and Zeeman fields, and show that many new superfluids phases, which
are topological in nature, emerge. Depending on values of spin-orbit coupling,
Zeeman fields, and interactions, initially gapped s-wave superfluids acquire
p-wave, d-wave, f-wave and higher angular momentum components, which produce
zeros in the excitation spectrum, rendering the superfluid gapless. Several
multi-critical points, which separate topological superfluid phases from normal
or non-uniform, are accessible depending on spin-orbit coupling, Zeeman fields
or interactions, setting the stage for the study of tunable topological
superfluids.


  Incremental learning of semantic segmentation has emerged as a promising
strategy for visual scene interpretation in the open- world setting. However,
it remains challenging to acquire novel classes in an online fashion for the
segmentation task, mainly due to its continuously-evolving semantic label
space, partial pixelwise ground-truth annotations, and constrained data
availability. To ad- dress this, we propose an incremental learning strategy
that can fast adapt deep segmentation models without catastrophic forgetting,
using a streaming input data with pixel annotations on the novel classes only.
To this end, we develop a uni ed learning strategy based on the
Expectation-Maximization (EM) framework, which integrates an iterative
relabeling strategy that lls in the missing labels and a rehearsal-based
incremental learning step that balances the stability-plasticity of the model.
Moreover, our EM algorithm adopts an adaptive sampling method to select
informative train- ing data and a class-balancing training strategy in the
incremental model updates, both improving the e cacy of model learning. We
validate our approach on the PASCAL VOC 2012 and ADE20K datasets, and the
results demonstrate its superior performance over the existing incremental
methods.


  In this study, we characterize the cross-platform mobilization of YouTube and
BitChute videos on Twitter during the 2020 U.S. Election fraud discussions.
Specifically, we extend the VoterFraud2020 dataset to describe the prevalence
of content supplied by both platforms, the mobilizers of that content, the
suppliers of that content, and the content itself. We find that while BitChute
videos promoting election fraud claims were linked to and engaged with in the
Twitter discussion, they played a relatively small role compared to YouTube
videos promoting fraud claims. This core finding points to the continued need
for proactive, consistent, and collaborative content moderation solutions
rather than the reactive and inconsistent solutions currently being used.
Additionally, we find that cross-platform disinformation spread from video
platforms was not prominently from bot accounts or political elites, but rather
average Twitter users. This finding supports past work arguing that research on
disinformation should move beyond a focus on bots and trolls to a focus on
participatory disinformation spread.


  We investigate a single scalar neutrino production at the upgraded HERA with
high luminosity in the framework of an R-parityviolating supersymmetric model.
We find that the scalar neutrino with mass around 100GeV could be observed
through investigating the multilepton production process e- p -> mu-
sneutrino(tau) X -> mu- (e- mu+) X. The signal would be characterized by mu+
and e- with high transverse momentum as well as a sharp peak in the invariant
mass M(e-,mu+) distribution.


  We investigate the variation of current star formation in galaxies as a
function of distance along three supercluster filaments, each joining pairs of
rich clusters, in the Pisces-Cetus supercluster, which is part of the 2dFGRS.
We find that even though there is a steady decline in the rate of star
formation, as well as in the fraction of star forming galaxies, as one
approaches the core of a cluster at an extremity of such a filament, there is
an increased activity of star formation in a narrow distance range between
3-4/h_70 Mpc, which is 1.5-2 times the virial radius of the clusters involved.
This peak in star formation is seen to be entirely due to the dwarf galaxies
(-20<M_B<-17.5). The position of the peak does not seem to depend on the
velocity dispersion of the nearest cluster, undermining the importance of the
gravitational effect of the clusters involved. We find that this enhancement in
star formation occurs at the same place for galaxies which belong to groups
within these filaments, while group members elsewhere in the 2dFGRS do not show
this effect. We conclude that the most likely mechanism for this enhanced star
formation is galaxy-galaxy harassment, in the crowded infall region of rich
clusters at the extremities of filaments, which induces a burst of star
formation in galaxies, before they have been stripped of their gas in the
denser cores of clusters. The effects of strangulation in the cores of
clusters, as well as excess star formation in the infall regions along the
filaments, are more pronounced in dwarfs since they more vulnerable to the
effects of strangulation and harassment than giant galaxies.


  We calculate the QCD moments of the pion structure function using Drell-Yan
data on the quark distributions in the pion and a phenomenological model for
the resonance region. The extracted higher twist corrections are found to be
larger than those for the nucleon, contributing around 50% of the lowest moment
at Q^2=1 GeV^2.


  With the popularity of smartphones, users are heavily dependent on mobile
applications for daily work and entertainments. However, mobile apps are
becoming more and more complicated with more features and increasing size, part
of which may be redundant to users. Due to the limitation of current
installation mechanism, users have to download full-size applications instead
of enjoy only the wanted features. Such full-size apps may consume more
resources, including CPU, memory, and energy, which may hurt users' enthusiasm
for further installation. We first conduct an empirical study to characterize
used features when users interact with mobile applications, and find that users
only consume a small set features of target apps. To address this problem, we
present AppStarscream, which offers to decompose and run Android apps with
app-level virtualization. We have implemented a prototype system and evaluated
it with real-world apps showing that AppStarscream is efficient and practical.


  Gauge symmetries play a central role, both in the mathematical foundations as
well as the conceptual construction of modern (particle) physics theories.
However, it is yet unclear whether they form a necessary component of theories,
or whether they can be eliminated. It is also unclear whether they are merely
an auxiliary tool to simplify (and possibly localize) calculations or whether
they contain independent information. Therefore their status, both in physics
and philosophy of physics, remains to be fully clarified.
  In this overview we review the current state of affairs on both the
philosophy and the physics side. In particular, we focus on the circumstances
in which the restriction of gauge theories to gauge invariant information on an
observable level is warranted, using the Brout-Englert-Higgs theory as an
example of particular current importance. Finally, we determine a set of yet to
be answered questions to clarify the status of gauge symmetries.


  We report experiments on convection driven by a radial electrical force in
suspended annular smectic A liquid crystal films. In the absence of an
externally imposed azimuthal shear, a stationary one-dimensional (1D) pattern
consisting of symmetric vortex pairs is formed via a supercritical transition
at the onset of convection. Shearing reduces the symmetries of the base state
and produces a traveling 1D pattern whose basic periodic unit is a pair of
asymmetric vortices. For a sufficiently large shear, the primary bifurcation
changes from supercritical to subcritical. We describe measurements of the
resulting hysteresis as a function of the shear at radius ratio $\eta \sim
0.8$. This simple pattern forming system has an unusual combination of
symmetries and control parameters and should be amenable to quantitative
theoretical analysis.


  In this short note, we provide an explicit formula to compute every colored
double Tornheim's series by using double polylogarithm values at roots of
unity. When the colors are given by $\pm 1$ our formula is different from that
of Tsumura [On alternating analogues of Tornheim's double series II, Ramanujan
J. 18 (2009), 81-90] even though numerical data confirm both are correct in
almost all the cases. This agreement can also be checked rigorously by using
regularized double shuffle relations of the alternating double zeta values in
weights less than eight.


  In this review article, we present a unified approach to solving discrete,
integrable, possibly non-commutative, dynamical systems, including the $Q$- and
$T$-systems based on $A_r$. The initial data of the systems are seen as cluster
variables in a suitable cluster algebra, and may evolve by local mutations. We
show that the solutions are always expressed as Laurent polynomials of the
initial data with non-negative integer coefficients. This is done by
reformulating the mutations of initial data as local rearrangements of
continued fractions generating some particular solutions, that preserve
manifest positivity. We also show how these techniques apply as well to
non-commutative settings.


  We study information-theoretic limits for simultaneous wireless information
and power transfer (SWIPT) systems employing nonlinear radio frequency (RF)
energy harvesting (EH) receivers (Rxs). In particular, we consider a SWIPT
system with one transmitter that broadcasts a common signal to an information
decoding (ID) Rx and multiple EH Rxs. Owing to the nonlinearity of the EH Rxs'
circuitry, the efficiency of wireless power transfer depends on the waveform of
the transmitted signal. We aim to answer the following fundamental question:
What is the optimal input distribution of the transmit signal waveform that
maximizes the information transfer rate at the ID Rx conditioned on individual
minimum required direct-current (DC) powers to be harvested at the EH Rxs?
Specifically, we study the conditional capacity problem of a SWIPT system
impaired by additive white Gaussian noise subject to average-power (AP) and
peak power (PP) constraints at the transmitter and nonlinear EH constraints at
the EH Rxs. To this end, we develop a novel nonlinear EH model that captures
the saturation of the harvested DC power by taking into account the reverse
breakdown current of the rectifying diode. We derive a novel semiclosed-form
expression for the harvested DC power, which simplifies to closed form for low
input RF powers. The derived analytical expressions are shown to closely match
circuit simulation results. We solve the conditional capacity problem for real-
and complex-valued signalling and prove that the optimal input distribution
that maximizes the rate-energy (R-E) region is unique and discrete with a
finite number of mass points. Furthermore, we show that the boundary of the R-E
region saturates for high PP constraints due to the saturation of the harvested
DC power for high input RF powers. In addition, we devise a suboptimal input
distribution whose R-E tradeoff performance is close to optimal.


  The Lorentz invariant $CPT$ violation by using non-local interactions is
naturally incorporated in the Higgs coupling to neutrinos in the Standard
Model, without spoiling the basic $SU(2)_{L}\times U(1)$ gauge symmetry. The
neutrino--antineutrino mass splitting is thus realized by the mechanism which
was proposed recently, assuming the neutrino masses to be predominantly
Dirac-type in the Standard Model.


  We investigate the chiral mass splitting of parity-doubled J=0,1 states for c
\bar{s} and c \bar{n} meson systems in the \tilde{U}(12)_{SF}-classification
scheme of hadrons, using the linear sigma model to describe the light-quark
pseudoscalar and scalar mesons together with the spontaneous breaking of chiral
symmetry, and consequently predict the masses of as-yet-unobserved
(0^{+},1^{+}) c \bar{n} mesons. We also mention some indications of their
existence in the recent published data from the Belle and BABAR Collaborations.


  Terzan5 is the globular cluster (GC)-like stellar system harboring the
largest known population of MSPs. Using the Multi-Conjugate Adaptive Optics
demonstrator MAD at the ESO - VLT, we recently obtained a superb (K, J - K)
color-magnitude diagram, which has revealed the existence of two horizontal
branches (HBs) well separated in magnitude and colour (Ferraro et al. 2009,
Nature,462, 483). A prompt spectroscopic follow-up with NIRSPEC@Keck has shown
that the two populations have (1) significantly different iron content ([Fe/H]=
-0.2 and +0.3 for the faint and the bright HB, respectively), (2) distinct
[alpha/Fe] abundance patterns and (3) no evidence of the Al-O anti-correlation
commonly observed in GCs. All these properties suggest that Ter 5 is far from
being a genuine globular. Instead it has experienced the explosion of a huge
number of supernovae (SNe), thus accounting for its high metal content and it
should have been much more massive in the past than today, thus to retain the
SN ejecta within its potential well. The many type II SNe should have also
produced a large number of neutron stars (NSs), which could finally explain its
exceptionally large population of MSPs.


  One of the fundamental questions in science is how scientific disciplines
evolve and sustain progress in society. No studies to date allows us to explain
the endogenous processes that support the evolution of scientific disciplines
and emergence of new scientific fields in applied sciences of physics. This
study confronts this problem here by investigating the evolution of
experimental physics to explain and generalize some characteristics of the
dynamics of applied sciences. Empirical analysis suggests properties about the
evolution of experimental physics and in general of applied sciences, such as:
a) scientific fission, the evolution of scientific disciplines generates a
process of division into two or more research fields that evolve as autonomous
entities over time; b) ambidextrous drivers of science, the evolution of
science via scientific fission is due to scientific discoveries or new
technologies; c) new driving research fields, the drivers of scientific
disciplines are new research fields rather than old ones; d) science driven by
development of general purpose technologies, the evolution of experimental
physics and applied sciences is due to the convergence of experimental and
theoretical branches of physics associated with the development of computer,
information systems and applied computational science. Results also reveal that
average duration of the upwave of scientific production in scientific fields
supporting experimental physics is about 80 years. Overall, then, this study
begins the process of clarifying and generalizing, as far as possible, some
characteristics of the evolutionary dynamics of scientific disciplines that can
lay a foundation for the development of comprehensive properties explaining the
evolution of science as a whole for supporting fruitful research policy
implications directed to advancement of science and technological progress in
society.


  The excitation spectrum of a two-component Bose-Einstein condensate has been
discussed by Ref \cite{alex2comp} using the Bogoliubov equations. Here we make
the additional contributions of the linear response function and dielectric
function for a two-component CBG in the condensation phase as well as the
confirmation of the plasmon excitation spectrum using the Gross-Pitaevskii
(G-P) equations.


  We consider the Schr\"odinger partial differential equation of a rotating
symmetric rigid molecule (symmetric rotor) driven by a z-linearly polarized
electric field, as prototype of degenerate infinite-dimensional bilinear
control system. By introducing an abstract perturbative criterium, we classify
its simultaneous approximate controllability; based on this insight, we
numerically perform an orientational selective transfer of rotational
population.


  Traditional face editing methods often require a number of sophisticated and
task specific algorithms to be applied one after the other --- a process that
is tedious, fragile, and computationally intensive. In this paper, we propose
an end-to-end generative adversarial network that infers a face-specific
disentangled representation of intrinsic face properties, including shape (i.e.
normals), albedo, and lighting, and an alpha matte. We show that this network
can be trained on "in-the-wild" images by incorporating an in-network
physically-based image formation module and appropriate loss functions. Our
disentangling latent representation allows for semantically relevant edits,
where one aspect of facial appearance can be manipulated while keeping
orthogonal properties fixed, and we demonstrate its use for a number of facial
editing applications.


  For the 3-component dispersionless Boussinesq-type system, we construct two
compatible nontrivial finite deformations for the Lie algebra structure in the
symmetry algebra.


  We prove that the existential theory of any function field $K$ of
characteristic $p> 0$ is undecidable in the language of rings provided that the
constant field does not contain the algebraic closure of a finite field. We
also extend the undecidability proof for function fields of higher
transcendence degree to characteristic 2 and show that the first-order theory
of {\bf any} function field of positive characteristic is undecidable in the
language of rings without parameters.


  Firstly we provide new characterizations for doubly warped product manifolds.
Then we consider several types of gradient solitons on them such as Riemann,
Ricci, Yamabe and conformal and examine the effect of a gradient soliton on a
doubly warped product to its factor manifolds. Finally we investigate the
concircularly flat and conharmonically flat cases of doubly warped products.


  The looked for V-binomials recurrence for Lucas companion to $U_n$ sequence
$V_n$ is delivered


  The 2H(e,e'p)n cross section was measured in Hall A of the Thomas Jefferson
National Accelerator Facility (JLab) in quasielastic kinematics (x=0.96) at a
four-momentum transfer squared, Q^2=0.67 (GeV/c)^2. The experiment was
performed in fixed electron kinematics for recoil momenta from zero to 550
MeV/c. Though the measured cross section deviates by 1-2 sigma from a
state-of-the-art calculation at low recoil momenta, it agrees at high recoil
momenta where final state interactions (FSI) are predicted to be large.