  The unique identities of every mobile user (phone number,IMSI) and device
(IMEI) are far from secure and are increasingly vulnerable to a variety of
network-level threats. The exceedingly high reliance on the weak SIM
authentication layer does not present any notion of end-to-end security for
mobile users. We propose the design and implementation of Secure Mobile
Identities (SMI), a repetitive key-exchange protocol that uses this weak SIM
authentication as a foundation to enable mobile users to establish stronger
identity authenticity. The security guarantees of SMI are directly reliant on
the mobility of users and are further enhanced by external trusted entities
providing trusted location signatures (e.g. trusted GPS, NFC synchronization
points). In this paper, we demonstrate the efficacy of our protocol using an
implementation and analysis across standard mobility models.


  High-precision approximate analytic expressions for energies and wave
functions are found for arbitrary physical potentials. The Schr\"{o}dinger
equation is cast into nonlinear Riccati equation, which is solved analytically
in first iteration of the quasi-linearization method (QLM). The zeroth
iteration is based on general features of the exact solution near the
boundaries. The approach is illustrated on the Yukawa potential. The results
enable accurate analytical estimates of effects of parameter variations on
physical systems.


  Conversational AI systems are becoming famous in day to day lives. In this
paper, we are trying to address the following key question: To identify whether
design, as well as development efforts for search oriented conversational AI
are successful or not.It is tricky to define 'success' in the case of
conversational AI and equally tricky part is to use appropriate metrics for the
evaluation of conversational AI. We propose four different perspectives namely
user experience, information retrieval, linguistic and artificial intelligence
for the evaluation of conversational AI systems. Additionally, background
details of conversational AI systems are provided including desirable
characteristics of personal assistants, differences between chatbot and an AI
based personal assistant. An importance of personalization and how it can be
achieved is explained in detail. Current challenges in the development of an
ideal conversational AI (personal assistant) are also highlighted along with
guidelines for achieving personalized experience for users.


  An evaluation method supported by robust statistical analysis was used to
analyze historical measurements of $^{39}$Ar half-life. The method, which
combines the most frequent value (MFV) approach with bootstrap analysis,
provides a more reliable way to estimate the half-life of $^{39}$Ar. The
results show that the half-life is T1/2(MFV) = 268.2 + (3.1) - (2.9) years,
with an uncertainty corresponding to the 68% confidence level. This uncertainty
is three times smaller than the most precise re-calculated measurements by
Stoenner et al. (1965) and 2.7 times smaller than the adopted half-life value
in nuclear data sheets. Recently, the specific activity of the beta decay of
$^{39}$Ar in atmospheric argon was measured in various underground facilities.
Applying the MFV method to these measurements gives a specific activity of
SA($^{39}$Ar/Ar)(MFV) = 0.966 + (0.010) - (0.018) Bq/kg(atmAr), with an
uncertainty corresponding to the 68% confidence level. This paper also
discusses the method used to determine the half-life of $^{39}$Ar using the
specific activity of $^{39}$Ar in atmospheric argon.


  We study the question on whether the famous Golod-Shafarevich estimate, which
gives a lower bound for the Hilbert series of a (noncommutative) algebra, is
attained. This question was considered by Anick in his 1983 paper 'Generic
algebras and CW-complexes', Princeton Univ. Press., where he proved that the
estimate is attained for the number of quadratic relations $d \leq
\frac{n^2}{4}$ and $d \geq \frac{n^2}{2}$, and conjectured that this is the
case for any number of quadratic relations. The particular point where the
number of relations is equal to $ \frac{n(n-1)}{2}$ was addressed by Vershik.
He conjectured that a generic algebra with this number of relations is finite
dimensional.
  We prove that over any infinite field, the Anick conjecture holds for
  $d \geq \frac{4(n^2+n)}{9}$ and arbitrary number of generators $n$, and
confirm the Vershik conjecture over any field of characteristic 0. We give also
a series of related asymptotic results.


  Let $u$ be a solution of the Fisher-KPP equation $$ \partial_t u=\Delta
u+f(u),\quad t>0,\ x\in\mathbb{R}^N. $$ We address the following question: does
$u$ become locally planar as $t\to+\infty$ ? Namely, does $u(t_n,x_n+\cdot)$
converge locally uniformly, up to subsequences, towards a one-dimensional
function, for any sequence $((t_n,x_n))_{n\in\mathbb{N}}$ in
$(0,+\infty)\times\mathbb{R}^N$ such that $t_n\to+\infty$ as $n\to+\infty$ ?
This question is in the spirit of a conjecture of De Giorgi for stationary
solutions of Allen-Cahn equations. The answer depends on the initial datum
$u_0$ of $u$. It is known to be affirmative when the support of $u_0$ is
bounded or when it lies between two parallel half-spaces. Instead, the answer
is negative when the support of $u_0$ is "V-shaped". We prove here that $u$ is
asymptotically locally planar when the support of $u_0$ is a convex set
(satisfying in addition a uniform interior ball condition), or, more generally,
when it is at finite Hausdorff distance from a convex set. We actually derive
the result under an even more general geometric hypothesis on the support of
$u_0$. We recover in particular the aforementioned results known in the
literature. We further characterize the set of directions in which $u$ is
asymptotically locally planar, and we show that the asymptotic profiles are
monotone. Our results apply in particular when the support of $u_0$ is the
subgraph of a function with vanishing global mean.


  The `electromagnetic' $Sl(2;\bZ)$ duality group in spacetime dimension $D=4k$
can be given a Kaluza-Klein interpretation in $D=4k+2$ as the modular group of
a compactifying torus. We show how dyonic $2(k-1)$-branes in $D=4k$ can be
interpreted as self-dual $(2k-1)$-branes in $D=4k+2$ wound around the homology
cycles of the torus. In particular, dyons of the D=4 N=4 heterotic string
theory are interpreted as winding modes of a D=6 self-dual string, while D=8
dyonic membranes are interpreted as wound 3-branes of D=10 IIB superstring
theory. We also discuss the T-dual IIA interpretations of D=8 dyonic membranes.


  We show how the quantum to classical transition of the cosmological
fluctuations produced during inflation can be described by means of the
influence functional and the master equation. We split the inflaton field into
the system-field (long-wavelength modes), and the environment, represented by
its own short-wavelength modes. We compute the decoherence times for the
system-field modes and compare them with the other time scales of the model. We
present the renormalized stochastic Langevin equation for an homogeneous
system-field and then we analyze the influence of the environment on the power
spectrum for some modes in the system.


  Machine learning (ML)-based solutions are rapidly changing the landscape of
many fields, including structural engineering. Despite their promising
performance, these approaches are usually only demonstrated as proof-of-concept
in structural engineering, and are rarely deployed for real-world applications.
This paper aims to illustrate the challenges of developing ML models suitable
for deployment through two illustrative examples. Among various pitfalls, the
presented discussion focuses on model overfitting and underspecification,
training data representativeness, variable omission bias, and cross-validation.
The results highlight the importance of implementing rigorous model validation
techniques through adaptive sampling, careful physics-informed feature
selection, and considerations of both model complexity and generalizability.


  Software engineering (SE) activities have been revolutionized by the advent
of pre-trained models (PTMs), defined as large machine learning (ML) models
that can be fine-tuned to perform specific SE tasks. However, users with
limited expertise may need help to select the appropriate model for their
current task. To tackle the issue, the Hugging Face (HF) platform simplifies
the use of PTMs by collecting, storing, and curating several models.
Nevertheless, the platform currently lacks a comprehensive categorization of
PTMs designed specifically for SE, i.e., the existing tags are more suited to
generic ML categories.
  This paper introduces an approach to address this gap by enabling the
automatic classification of PTMs for SE tasks. First, we utilize a public dump
of HF to extract PTMs information, including model documentation and associated
tags. Then, we employ a semi-automated method to identify SE tasks and their
corresponding PTMs from existing literature. The approach involves creating an
initial mapping between HF tags and specific SE tasks, using a similarity-based
strategy to identify PTMs with relevant tags. The evaluation shows that model
cards are informative enough to classify PTMs considering the pipeline tag.
Moreover, we provide a mapping between SE tasks and stored PTMs by relying on
model names.


  We summarize recent work on the classification of modular invariant partition
functions that can be obtained with simple currents in theories with a center
(Z_p)^k with p prime. New empirical results for other centers are also
presented. Our observation that the total number of invariants is
monodromy-independent for (Z_p)^k appears to be true in general as well. (Talk
presented in the parallel session on string theory of the Lepton-Photon/EPS
Conference, Geneva, 1991.)


  We present measurements of Stark interference in the 6$^1S_0$ $\rightarrow$
6$^3P_1$ transition in $^{199}$Hg, a process whereby a static electric field
$E$ mixes magnetic dipole and electric quadrupole couplings into an electric
dipole transition, leading to $E$-linear energy shifts similar to those
produced by a permanent atomic electric dipole moment (EDM). The measured
interference amplitude, $a_{SI}$ = $(a_{M1} + a_{E2})$ = (5.8 $\pm$ 1.5)$\times
10^{-9}$ (kV/cm)$^{-1}$, agrees with relativistic, many-body predictions and
confirms that earlier central-field estimates are a factor of 10 too large.
More importantly, this study validates the capability of the $^{199}$Hg EDM
search apparatus to resolve non-trivial, controlled, and sub-nHz Larmor
frequency shifts with EDM-like characteristics.


  We test the performance of the semi-analytic self-consistent Just-Jahrei{\ss}
disc model (JJ model) with the astrometric data from the Tycho-Gaia Astrometric
Solution (TGAS) sub-catalogue of the first Gaia data release (Gaia DR1), as
well as the radial velocities from the fifth data release of the Radial
Velocity Experiment survey (RAVE DR5). We use a sample of 19,746 thin disc
stars from the TGAS$\times$RAVE cross-match selected in the local solar
cylinder of 300 pc radius and 1 kpc height below the Galactic plane and
simulate this sample via the forward modelling technique. First, we convert the
predicted vertical density laws of the thin disc populations into a mock
sample. Then the obtained mock populations are reddened with a 3D dust map and
are subjected to the selection criteria corresponding to the RAVE and TGAS
observational limitations as well as to additional cuts applied to the data
sample. We calculate the quantities of interest separately at different heights
above the Galactic plane taking into account the distance error effects
separately in horizontal and vertical directions. We investigate the simulated
sample in terms of the vertical number density profiles, Hess diagrams and
velocity distribution functions. Basing on a good agreement of our simulations
with the data, we conclude that our fiducial disc model confidently reproduces
the vertical trends in the thin disc stellar population properties. Thus, it
can serve as a starting point for the future extension of the JJ model to other
Galactocentric distances.


  We present a method to develop a Hodge theory for tangential cohomology of
foliations by mimicing Witten's approach to ordinary Morse theory by
perturbations of the Laplacian


  Optical pump-probe spectroscopy is a powerful tool for the study of
non-equilibrium electronic dynamics and finds wide applications across a range
of fields, from physics and chemistry to material science and biology. However,
a shortcoming of conventional pump-probe spectroscopy is that photoinduced
changes in transmission, reflection and scattering can simultaneously
contribute to the measured differential spectra, leading to ambiguities in
assigning the origin of spectral signatures and ruling out quantitative
interpretation of the spectra. Ideally, these methods would measure the
underlying dielectric function (or the complex refractive index) which would
then directly provide quantitative information on the transient excited state
dynamics free of these ambiguities. Here we present and test a model
independent route to transform differential transmission or reflection spectra,
measured via conventional optical pump-probe spectroscopy, to changes in the
quantitative transient dielectric function. We benchmark this method against
changes in the real refractive index measured using time-resolved Frequency
Domain Interferometry in prototypical inorganic and organic semiconductor
films. Our methodology can be applied to existing and future pump-probe data
sets, allowing for an unambiguous and quantitative characterisation of the
transient photoexcited spectra of materials. This in turn will accelerate the
adoption of pump-probe spectroscopy as a facile and robust materials
characterisation and screening tool.


  The Centers for Disease Control and Prevention (CDC) coordinates a
labor-intensive process to measure the prevalence of autism spectrum disorder
(ASD) among children in the United States. Random forests methods have shown
promise in speeding up this process, but they lag behind human classification
accuracy by about 5%. We explore whether more recently available document
classification algorithms can close this gap. We applied 8 supervised learning
algorithms to predict whether children meet the case definition for ASD based
solely on the words in their evaluations. We compared the algorithms'
performance across 10 random train-test splits of the data, using
classification accuracy, F1 score, and number of positive calls to evaluate
their potential use for surveillance. Across the 10 train-test cycles, the
random forest and support vector machine with Naive Bayes features (NB-SVM)
each achieved slightly more than 87% mean accuracy. The NB-SVM produced
significantly more false negatives than false positives (P = 0.027), but the
random forest did not, making its prevalence estimates very close to the true
prevalence in the data. The best-performing neural network performed similarly
to the random forest on both measures. The random forest performed as well as
more recently available models like the NB-SVM and the neural network, and it
also produced good prevalence estimates. NB-SVM may not be a good candidate for
use in a fully-automated surveillance workflow due to increased false
negatives. More sophisticated algorithms, like hierarchical convolutional
neural networks, may not be feasible to train due to characteristics of the
data. Current algorithms might perform better if the data are abstracted and
processed differently and if they take into account information about the
children in addition to their evaluations.


  The link between the crystal distortions of the perovskite structure and the
magnetic exchange interaction, the single-ion anisotropy (SIA) and the
Dzyaloshinsky-Moriya (DM) interaction are investigated by means of
density-functional calculations. Using BiFeO$_3$ and LaFeO$_3$ as model
systems, we quantify the relationship between the oxygen octahedra rotations,
the ferroelectricity and the weak ferromagnetism (wFM). We recover the fact
that the wFM is due to the DM interaction induced by the oxygen octahedra
rotations. We find a simple relationship between the wFM, the oxygen rotation
amplitude and the ratio between the DM vector and the exchange parameter such
as the wFM increases with the oxygen octahedra rotation when the SIA does not
compete with the DM forces induced on the spins. Unexpectedly, we also find
that, in spite of the $d^5$ electronic configuration of Fe$^{3+}$, the SIA is
very large in some structures and is surprisingly strongly sensitive to the
chemistry of the $A$-site cation of the $A$BO$_3$ perovskite. In the ground
$R3c$ state phase we show that the SIA shape induced by the ferroelectricity
and the oxygen octahedra rotations are in competition such as it is possible to
tune the wFM "on" and "off" through the relative size of the two types of
distortion.


  By using high-quality single crystals, we quantitatively compare the
transport properties between LiFeAs and LiFeP superconductors with compensated
electron and hole carriers. The low-temperature resistivity follows the
Fermi-liquid $AT^2$ dependence with a factor of $\sim 3$ difference in the
coefficient $A$. This highlights weaker electron correlations in LiFeP, which
is consistent with its $\sim 70$ times lower upper critical field than that of
LiFeAs. Our analysis of the magneto-transport data indicates that in LiFeP the
electron carriers with lighter masses exhibit stronger temperature dependence
of inelastic scattering rate than the holes, which is the opposite to the
LiFeAs case. This stark difference in the band-dependent inelastic scattering
may be relevant to the recently reported contrasting superconducting gap
structures in these two superconductors.


  We present the size-stellar mass relations of nearby (z=0.01-0.02) Sloan
Digital Sky Survey galaxies, for samples selected by color, morphology, Sersic
index n, and specific star formation rate. Several commonly employed size
measurement techniques are used, including single Sersic fits, two-component
Sersic models, and a non-parametric method. Through simple simulations, we show
that the non-parametric and two-component Sersic methods provide the most
robust effective radius measurements, while those based on single Sersic
profiles are often overestimates, especially for massive red/early-type
galaxies. Using our robust sizes, we show for all sub-samples that the
mass-size relations are shallow at low stellar masses and steepen above ~ 3-4 x
10^{10}\msun. The mass-size relations for galaxies classified as late-type,
low-n, and star-forming are consistent with each other, while blue galaxies
follow a somewhat steeper relation. The mass-size relations of early-type,
high-n, red, and quiescent galaxies all agree with each other but are somewhat
steeper at the high-mass end than previous results. To test potential
systematics at high redshift, we artificially redshifted our sample (including
surface brightness dimming and degraded resolution) to z=1 and re-fit the
galaxies using single Serisc profiles. The sizes of these galaxies before and
after redshifting are consistent and we conclude that systematic effects in
sizes and the size-mass relation at z ~ 1 are negligible. Interestingly, since
the poorer physical resolution at high redshift washes out bright galaxy
substructures, single-Sersic fitting appears to provide more reliable and
unbiased effective radius measurements at high z than for nearby, well-resolved
galaxies.


  Knowledge distillation has recently become popular as a method of model
aggregation on the server for federated learning. It is generally assumed that
there are abundant public unlabeled data on the server. However, in reality,
there exists a domain discrepancy between the datasets of the server domain and
a client domain, which limits the performance of knowledge distillation. How to
improve the aggregation under such a domain discrepancy setting is still an
open problem. In this paper, we first analyze the generalization bound of the
aggregation model produced from knowledge distillation for the client domains,
and then describe two challenges, server-to-client discrepancy and
client-to-client discrepancy, brought to the aggregation model by the domain
discrepancies. Following our analysis, we propose an adaptive knowledge
aggregation algorithm FedD3A based on domain discrepancy aware distillation to
lower the bound. FedD3A performs adaptive weighting at the sample level in each
round of FL. For each sample in the server domain, only the client models of
its similar domains will be selected for playing the teacher role. To achieve
this, we show that the discrepancy between the server-side sample and the
client domain can be approximately measured using a subspace projection matrix
calculated on each client without accessing its raw data. The server can thus
leverage the projection matrices from multiple clients to assign weights to the
corresponding teacher models for each server-side sample. We validate FedD3A on
two popular cross-domain datasets and show that it outperforms the compared
competitors in both cross-silo and cross-device FL settings.


  A novel formalism for the evaluation of the Casimir-Polder potential in an
arbitrary gauge of vector potentials is introduced. The ground state energy of
a neutral atom in the presence of an infinite two-dimensional plane with
Chern-Simons interaction is derived at zero temperature. The essential feature
of the result is its dependence on the antisymmetric part of a dipole moment
correlation function.


  Natural (such as lunar) occultations have long been used to study sources on
small angular scales, while coronographs have been used to study high contrast
sources. We propose launching the Big Occulting Steerable Satellite (BOSS), a
large steerable occulting satellite to combine both of these techniques. BOSS
will have several advantages over standard occulting bodies. BOSS would block
all but about 4e-5 of the light at 1 micron in the region of interest around
the star for planet detections. Because the occultation occurs outside the
telescope, scattering inside the telescope does not degrade this performance.
BOSS could be combined with a space telescope at the Earth-Sun L2 point to
yield very long integration times, in excess of 3000 seconds. If placed in
Earth orbit, integration times of 160--1600 seconds can be achieved from most
major telescope sites for objects in over 90% of the sky. Applications for BOSS
include direct imaging of planets around nearby stars. Planets separated by as
little as 0.1--0.25 arcseconds from the star they orbit could be seen down to a
relative intensity as little as 1e-9 around a magnitude 8 (or brighter) star.
Other applications include ultra-high resolution imaging of compound sources,
such as microlensed stars and quasars, down to a resolution as little as 0.1
milliarcseconds.


  In this work, we report on the exciton radiative lifetimes of graphitic
carbon nitride monolayers in the triazine- (gC$_3$N$_4$-t) and heptazine-based
(gC$_3$N$_4$-h) forms, as obtained by means of ground- plus excited-state ab
initio calculations. By analysing the exciton fine structure, we highlight the
presence of dark states and show that the photo-generated electron-hole pairs
in gC$_3$N$_4$-h are remarkably long-lived, with an effective radiative
lifetime of 260 ns. This fosters the employment of gC$_3$N$_4$-h in
photocatalysis and makes it attractive for the emerging field of exciton
devices. Although very long intrinsic radiative lifetimes are an important
prerequisite for several applications, pristine carbon nitride nanosheets show
very low quantum photo-conversion efficiency, mainly due to the lack of an
efficient e-h separation mechanism. We then focus on a vertical heterostructure
made of gC$_3$N$_4$-t and gC$_3$N$_4$-h layers which shows a type-II band
alignment and looks promising for achieving net charge separation.


  The stability of topological solitary waves and pulses in one-dimensional
nonlinear Klein-Gordon systems is revisited. The linearized equation describing
small deviations around the static solution leads to a Sturm-Liouville problem,
which is solved in a systematic way for the $-l\,(l+1)\,\sech^2(x)$-potential,
showing the orthogonality and completeness relations fulfilled by the set of
its solutions for all values $l\in\mathbb{N}$. This approach allows to
determine the linear stability of kinks and pulses of certain nonlinear
Klein-Gordon equations. Two families of novel nonlinear Klein-Gordon potentials
are introduced. The exact solutions (kinks and pulses) for these potentials are
exactly calculated, even when the nonlinear potential is not explicitly known.
The kinks of the novel models are found to be stable, whereas the pulses are
unstable. The stability of the pulses is achieved by introducing certain
spatial inhomogeneities.


  Can a violent process like sudden reheating after supercooling at the onset
of a first-order QCD transition improve the possibility of primordial black
hole formation? Underdensities reheat earlier than overdensities, there is a
short period of huge pressure differences, hence fluid acceleration. Density
perturbations on scales far below the Hubble radius $\lambda\ll R_{\rm H} $ get
an amplification which grows quadratically in wavenumber, the amplifications at
the horizon scale are small. Primordial black hole formation cannot be
sufficiently amplified by the QCD transition unless the initial spectrum is
fine tuned.


  Benefiting from powerful convolutional neural networks (CNNs), learning-based
image inpainting methods have made significant breakthroughs over the years.
However, some nature of CNNs (e.g. local prior, spatially shared parameters)
limit the performance in the face of broken images with diverse and complex
forms. Recently, a class of attention-based network architectures, called
transformer, has shown significant performance on natural language processing
fields and high-level vision tasks. Compared with CNNs, attention operators are
better at long-range modeling and have dynamic weights, but their computational
complexity is quadratic in spatial resolution, and thus less suitable for
applications involving higher resolution images, such as image inpainting. In
this paper, we design a novel attention linearly related to the resolution
according to Taylor expansion. And based on this attention, a network called
$T$-former is designed for image inpainting. Experiments on several benchmark
datasets demonstrate that our proposed method achieves state-of-the-art
accuracy while maintaining a relatively low number of parameters and
computational complexity. The code can be found at
\href{https://github.com/dengyecode/T-former_image_inpainting}{github.com/dengyecode/T-former\_image\_inpainting}


  This paper investigates the impact of carrier frequency offset (CFO) on the
performance of different MIMO-OFDM schemes with high spectral efficiency for
next generation of terrestrial digital TV. We show that all studied MIMO-OFDM
schemes are sensitive to CFO when it is greater than 1% of inter-carrier
spacing. We show also that the Alamouti scheme is the most sensitive MIMO
scheme to CFO


  Recombination lines involving high principal quantum numbers populate the
radio spectrum in large numbers. Low-frequency (<1 GHz) observations of radio
recombination lines (RRLs) primarily from carbon and hydrogen offer a new, if
not unique, way to probe cold, largely atomic gas and warm, ionised gas in
other galaxies. Furthermore, RRLs can be used to determine the physical state
of the emitting regions, such as temperature and density. These properties make
RRLs, potentially, a powerful tool of extragalactic ISM physics. At low radio
frequencies, its conceivable to detect RRLs out to cosmological distances when
illuminated by a strong radio continuum. However, they are extremely faint (tau
~ 1e-3 -- 1e-4) and have so far eluded detection outside of the local universe.
  With LOFAR observations of the radio quasar 3C 190 (z=1.1946), we aim to
demonstrate that the ISM can be explored out to great distances through
low-frequency RRLs.
  We report the detection of RRLs in the frequency range 112--163 MHz in the
spectrum of 3C 190. Stacking 13 a-transitions with principal quantum numbers
n=266-301, a peak 6sigma feature of optical depth, tau(peak) = (1.0 +\- 0.2) x
1e-3 and FWHM = 31.2 +/- 8.3 km/s was found at z=1.124. This corresponds to a
velocity offset of -9965 km/s with respect to the systemic redshift of 3C 190.
  We consider three interpretations of the origin of the RRL emission: an
intervening dwarf-like galaxy, an AGN-driven outflow, and the inter-galactic
medium. We argue that the RRLs most likely originate in a dwarf-like galaxy (M
~ 1e9 Msun) along the line of sight, although we cannot rule out an AGN-driven
outflow. We do find the RRLs to be inconsistent with an inter-galactic medium
origin. With this detection, we have opened up a new way to study the physical
properties of cool, diffuse gas out to cosmological distances.


  In Mixed Integer Linear Programming (MIP), a (strong) backdoor is a "small"
subset of an instance's integer variables with the following property: in a
branch-and-bound procedure, the instance can be solved to global optimality by
branching only on the variables in the backdoor. Constructing datasets of
pre-computed backdoors for widely used MIP benchmark sets or particular problem
families can enable new questions around novel structural properties of a MIP,
or explain why a problem that is hard in theory can be solved efficiently in
practice. Existing algorithms for finding backdoors rely on sampling candidate
variable subsets in various ways, an approach which has demonstrated the
existence of backdoors for some instances from MIPLIB2003 and MIPLIB2010.
However, these algorithms fall short of consistently succeeding at the task due
to an imbalance between exploration and exploitation. We propose BaMCTS, a
Monte Carlo Tree Search framework for finding backdoors to MIPs. Extensive
algorithmic engineering, hybridization with traditional MIP concepts, and close
integration with the CPLEX solver have enabled our method to outperform
baselines on MIPLIB2017 instances, finding backdoors more frequently and more
efficiently.


  We examine a 200 ks XMM-Newton observation of the narrow-line Seyfert 1
galaxy Mrk 493. The active galaxy was half as bright as in a previous 2003
snapshot observation and the current lower flux enables a study of the putative
reflection component in detail. We determine the characteristics of the 2015
X-ray continuum by first analyzing the short-term variability using
model-independent techniques. We then continue with a time-resolve analysis
including spectral fitting and modelling the fractional variability. We
determine that the variability arises from changes in the amount of primary
flux striking the accretion disk, which induces changes in the ionization
parameter and flux of the blurred reflection component. The observations seem
consistent with the picture that the primary source is of roughly constant
brightness and that variations arise from changes in the degree of light
bending happening in the vicinity of the supermassive black hole.


  By using the Kirkwood formula, the friction coefficient of a solvated
Brownian particle is determined from the integration on time of the
autocorrelation function of the force that the solvent exerts on this particle.
Extensive molecular dynamics simulations show that above a definite size of the
studied systems the value of the integral defining the friction coefficient
goes to a quasi constant value (a plateau) when the upper bound on time
increases. The minimal value of the system size where the integral exhibits
this asymptotic behavior, rises with the Brownian particle size. From the
plateau, a reliable estimate of the friction coefficient is obtained.


  A detailed study of chemical freeze-out in nucleus-nucleus collisions at beam
energy 158A GeV is presented. By analyzing hadronic multiplicities within the
statistical hadronization approach, the chemical equilibration of p-p, C-C,
Si-Si and Pb-Pb systems is studied as a function of the number of participating
nucleons in the system. Additionally, Two Component statistical hadronization
model is applied to the data and is found to be able to explain the observed
strangeness hadronic phase space under-saturation.


  The CLEAN algorithm, first published by H\"{o}gbom and its later variants
such as Multiscale CLEAN (msCLEAN) by Cornwell, has been the most popular tool
for deconvolution in radio astronomy. Interferometric imaging used in aperture
synthesis radio telescopes requires deconvolution for removal of the telescopes
point spread function from the observed images. We have compared source fluxes
produced by different implementations of H\"{o}gbom and msCLEAN (WSCLEAN, CASA)
with a prototype implementation of H\"{o}gbom and msCLEAN for the Square
Kilometer Array (SKA) on two datasets. First is a simulation of multiple point
sources of known intensity using H\"{o}gbom, where none of the software
packages detected all the simulated point sources to within 1.0% of the
simulated values. The second is of supernova remnant G055.7+3.4 taken by the
Karl G. Jansky Very Large Array (VLA) using msCLEAN, where each of the software
packages produced different images for the same settings.


  The intrinsic alignments of galaxies, i.e., the correlation between galaxy
shapes and their environment, are a major source of contamination for weak
gravitational lensing surveys. Most studies of intrinsic alignments have so far
focused on measuring and modelling the correlations of luminous red galaxies
with galaxy positions or the filaments of the cosmic web. In this work, we
investigate alignments around cosmic voids. We measure the intrinsic alignments
of luminous red galaxies detected by the Sloan Digital Sky Survey around a
sample of voids constructed from those same tracers and with radii in the
ranges: $[20-30; 30-40; 40-50]$ $h^{-1}$ Mpc and in the redshift range
$z=0.4-0.8$. We present fits to the measurements based on a linear model at
large scales, and on a new model based on the void density profile inside the
void and in its neighbourhood. We constrain the free scaling amplitude of our
model at small scales, finding no significant alignment at $1\sigma$ for either
sample. We observe a deviation from the null hypothesis, at large scales, of
2$\sigma$ for voids with radii between 20 and 30 $h^{-1}$ Mpc, and 1.5 $\sigma$
for voids with radii between 30 and 40 $h^{-1}$ Mpc and constrain the amplitude
of the model on these scales. We find no significant deviation at 1$\sigma$ for
larger voids. Our work is a first attempt at detecting intrinsic alignments of
galaxy shapes around voids and provides a useful framework for their mitigation
in future void lensing studies.


  We present a construction of the superspace of maximally supersymmetric
adS_{p+2} x S^{d-p-2} near-horizon geometry based entirely on the supergravity
constraints of which the bosonic space is a solution. Besides the geometric
superfields, i.e. the vielbeine and the spinconnection, we also derive the
isometries of the superspace together with the compensating tangent space
transformations to all orders in anticommuting superspace coordinates.


  We provide type IIB string embeddings of two axion variants of natural
inflation. We use a combination of RR 2 form axions as the inflaton field and
have its potential generated by non perturbative effects in the superpotential.
Besides giving rise to inflation, the models developed take into account the
stabilization of the compact space, both in the KKLT and large volume scenario
regimes, an essential condition for any semi-realistic model of string
inflation.


  We give short expositions of both Leighton's proof and the Bass-Kulkarni
proof of Leighton's graph covering theorem, in the context of colored graphs.
We discuss a further generalization, needed elsewhere, to "symmetry-restricted
graphs." We can prove it in some cases, for example, if the "graph of colors"
is a tree, but we do not know if it is true in general. We show that Bass's
Conjugation Theorem, which is a tool in the Bass-Kulkarni approach, does hold
in the symmetry-restricted context.


  Dimensionality reduction (DR) is a popular method for preparing and analyzing
high-dimensional data. Reduced data representations are less computationally
intensive and easier to manage and visualize, while retaining a significant
percentage of their original information. Aside from these advantages, these
reduced representations can be difficult or impossible to interpret in most
circumstances, especially when the DR approach does not provide further
information about which features of the original space led to their
construction. This problem is addressed by Interpretable Machine Learning, a
subfield of Explainable Artificial Intelligence that addresses the opacity of
machine learning models. However, current research on Interpretable Machine
Learning has been focused on supervised tasks, leaving unsupervised tasks like
Dimensionality Reduction unexplored. In this paper, we introduce LXDR, a
technique capable of providing local interpretations of the output of DR
techniques. Experiment results and two LXDR use case examples are presented to
evaluate its usefulness.


  In this article we try to present spherically symmetric isotropic strange
star model under the framework of $f(R,\mathcal{T})$ theory of gravity. To this
end, we consider that the Lagrangian density is an arbitrary linear function of
the Ricci scalar $R$ and the trace of the energy momentum tensor~$\mathcal{T}$
given as $f\left(R,\mathcal{T}\right)=R+2\chi T$. We also assume that the quark
matter distribution is governed by the simplest form of the MIT bag model
equation of state (EOS) as $p=\frac{1}{3}\left(\rho-4B\right)$, where $B$ is
the bag constant. We have obtained an exact solution of the modified form of
the the Tolman-Oppenheimer-Volkoff (TOV) equation in the framework of
$f(R,\mathcal{T})$ gravity theory and studied the dependence of different
physical properties, viz., total mass, radius, energy density and pressure on
the chosen values of $\chi$. Further, to examine physical acceptability of the
proposed stellar model in detail, we conducted different tests, viz. energy
conditions, modified TOV equation, mass-radius relation, causality condition
etc. We have precisely explained the effects arising due to the coupling of the
matter and geometry on the compact stellar system. For a chosen value of the
Bag constant we have predicted numerical values of different physical
parameters in tabular format for the different strange stars. It is found that
as the factor $\chi$ increases the strange stars shrink gradually and become
less massive to turn into a more compact stellar system. The maximum mass point
is well within the observational limits and hence our proposed model is
suitable to explain the ultra dense compact stars. For $\chi=0$ we retrieve as
usual the standard results of general relativity (GR).


  (This comment has been updated to respond to Wang and Blei's rejoinder
[arXiv:1910.07320].)
  The premise of the deconfounder method proposed in "Blessings of Multiple
Causes" by Wang and Blei [arXiv:1805.06826], namely that a variable that
renders multiple causes conditionally independent also controls for unmeasured
multi-cause confounding, is incorrect. This can be seen by noting that no fact
about the observed data alone can be informative about ignorability, since
ignorability is compatible with any observed data distribution. Methods to
control for unmeasured confounding may be valid with additional assumptions in
specific settings, but they cannot, in general, provide a checkable approach to
causal inference, and they do not, in general, require weaker assumptions than
the assumptions that are commonly used for causal inference. While this is
outside the scope of this comment, we note that much recent work on applying
ideas from latent variable modeling to causal inference problems suffers from
similar issues.


  We theoretically study the influence of the noise strength on the excitation
of the Brillouin propagation modes in a dissipative optical lattice. We show
that the excitation has a resonant behavior for a specific amount of noise
corresponding to the precise synchronization of the Hamiltonian motion on the
optical potential surfaces and the dissipative effects associated with optical
pumping in the lattice. This corresponds to the phenomenon of stochastic
resonance. Our results are obtained by numerical simulations and correspond to
the analysis of microscopic quantities (atomic spatial distributions) as well
as macroscopic quantities (enhancement of spatial diffusion and pump-probe
spectra). We also present a simple analytical model in excellent agreement with
the simulations.


  In this paper we introduce a new formalism for $K$-theory, called squares
$K$-theory. This formalism allows us to simultaneously generalize the usual
three-term relation $[B] = [A] + [C]$ for an exact sequence $A \hookrightarrow
B \twoheadrightarrow C$ or for a subtractive sequence $A\hookrightarrow B
\leftarrow C$, by defining $K_0$ of exact and subtractive categories to satisfy
a four-term relation $[A]+[D]= [C] + [B]$ for a ``good'' square diagram with
these corners. Examples that rely on this formalism are $K$-theory of smooth
manifolds of a fixed dimension and $K$-theory of (smooth and) complete
varieties. Another application we give of this theory is the construction of a
derived motivic measure taking value in the $K$-theory of homotopy sheaves.


  This work proposes a novel approach to out-of-vocabulary (OOV) keyword search
(KWS) task. The proposed approach is based on using high-level features from an
automatic speech recognition (ASR) system, so called phoneme posterior based
(PPB) features, for decoding. These features are obtained by calculating
time-dependent phoneme posterior probabilities from word lattices, followed by
their smoothing. For the PPB features we developed a special novel very fast,
simple and efficient OOV decoder. Experimental results are presented on the
Georgian language from the IARPA Babel Program, which was the test language in
the OpenKWS 2016 evaluation campaign. The results show that in terms of maximum
term weighted value (MTWV) metric and computational speed, for single ASR
systems, the proposed approach significantly outperforms the state-of-the-art
approach based on using in-vocabulary proxies for OOV keywords in the indexed
database. The comparison of the two OOV KWS approaches on the fusion results of
the nine different ASR systems demonstrates that the proposed OOV decoder
outperforms the proxy-based approach in terms of MTWV metric given the
comparable processing speed. Other important advantages of the OOV decoder
include extremely low memory consumption and simplicity of its implementation
and parameter optimization.


  This paper presents a soft earthworm robot that is capable of both efficient
locomotion and obstacle avoidance. The robot is designed to replicate the
unique locomotion mechanisms of earthworms, which enable them to move through
narrow and complex environments with ease. The robot consists of multiple
segments, each with its own set of actuators, that are connected through rigid
plastic joints, allowing for increased adaptability and flexibility in
navigating different environments. The robot utilizes proprioceptive sensing
and control algorithms to detect and avoid obstacles in real-time while
maintaining efficient locomotion. The robot uses a pneumatic actuation system
to mimic the circumnutation behavior exhibited by plant roots in order to
navigate through complex environments. The results demonstrate the capabilities
of the robot for navigating through cluttered environments, making this
development significant for various fields of robotics, including search and
rescue, environmental monitoring, and medical procedures.


  We study reflected diffusion on uniform domains where the underlying space
admits a symmetric diffusion that satisfies sub-Gaussian heat kernel estimates.
A celebrated theorem of Jones (Acta Math. 1981) states that uniform domains in
Euclidean space are extension domains for Sobolev spaces. In this work, we
obtain a similar extension property for metric spaces equipped with a Dirichlet
form whose heat kernel satisfies a sub-Gaussian estimate. We introduce a
scale-invariant version of this extension property and apply it to show that
the reflected diffusion process on such a uniform domain inherits various
properties from the ambient space, such as Harnack inequalities, cutoff energy
inequality, and sub-Gaussian heat kernel bounds. In particular, our work
extends Neumann heat kernel estimates of Gyrya and Saloff-Coste (Ast\'erisque
2011) beyond the Gaussian space-time scaling. Furthermore, our estimates on the
extension operator imply that the energy measure of the boundary of a uniform
domain is always zero. This property of the energy measure is a broad
generalization of Hino's result (PTRF 2013) that proves the vanishing of the
energy measure on the outer square boundary of the standard Sierpi\'nski carpet
equipped with the self-similar Dirichlet form.


  The broad X-ray iron line seen in the spectra of many AGN is thought to
originate from the inner regions of the putative black hole accretion disk, and
hence provides a rare probe of that central region. In principle, future high
throughput X-ray spectrometers should be able to examine the temporal response
of this fluorescent line to flares in the X-ray continuum source (which
energizes this emission line) - i.e. iron line reverberation mapping will be
possible. It has been previously found that there are robust reverberation
signatures of the black hole spin, mass and the X-ray flare location above the
accretion disk. Here, we simulate observations of a bright Seyfert nucleus with
the proposed NASA mission Constellation-X and demonstrate the feasibility of
detecting these reverberation signatures with this mission. Hence, starting
with XMM in 1999, and maturing with Constellation-X in c2010, iron line
reverberation will open a new window on the innermost regions of AGN.


  We experimentally investigate spin-orbit torques and spin pumping in NiFe/Pt
bilayers with direct and interrupted interfaces. The damping-like and
field-like torques are simultaneously measured with spin-torque ferromagnetic
resonance tuned by a dc bias current, whereas spin pumping is measured
electrically through the inverse spin Hall effect using a microwave cavity.
Insertion of an atomically thin Cu dusting layer at the interface reduces the
damping-like torque, field-like torque, and spin pumping by nearly the same
factor of ~1.4. This finding confirms that the observed spin-orbit torques
predominantly arise from diffusive transport of spin current generated by the
spin Hall effect. We also find that spin-current scattering at the NiFe/Pt
interface contributes to additional enhancement in magnetization damping that
is distinct from spin pumping.


  In this paper we study the directions of periodicity of three-dimensional
subshifts of finite type (SFTs) and in particular their slopes. A configuration
of a subshift has a slope of periodicity if it is periodic in exactly one
direction, the slope being the angle of the periodicity vectors. In this paper,
we prove that any $\Sigma^0_2$ set may be realized as a a set of slopes of an
SFT.


  We use exact diagonalisation in order to study the infinite - $U$ limit of
the two dimensional Hubbard model. As well as looking at single-particle
correlations, such as $n_{{\bf k}\sigma }=\langle c^\dagger _{{\bf k}\sigma
}c_{{\bf k}\sigma } \rangle $, we also study {\it N-particle correlation
functions} which compare the relative positions of {\it all} the particles in
different models. In particular we study 16 and 18-site clusters and compare
the charge correlations in the Hubbard model with those of spinless fermions
and hard-core bosons. We find that although low densities of holes favour a
`locally-ferromagnetic' fermionic description, the correlations at larger
densities resemble those of pure hard-core bosons surprisingly well .


  The recent discoveries of strikingly large zero-field Hall and Nernst effects
in antiferromagnets Mn$_3$$X$, ($X$ = Sn, Ge) have brought the study of
magnetic topological states to the forefront of condensed matter research and
technological innovation. These effects are considered fingerprints of Weyl
nodes residing near the Fermi energy, promoting Mn$_3$$X$, ($X$ = Sn, Ge) as a
fascinating platform to explore the elusive magnetic Weyl fermions. In this
review, we provide recent updates on the insights drawn from experimental and
theoretical studies of Mn$_3$$X$, ($X$ = Sn, Ge) by combining previous reports
with our new, comprehensive set of transport measurements of high-quality
Mn$_3$Sn and Mn$_3$Ge single crystals. In particular, we report
magnetotransport signatures specific to chiral anomalies in Mn$_3$Ge and planar
Hall effect in Mn$_3$Sn, which have not yet been found in earlier studies. The
results summarized here indicate the essential role of magnetic Weyl fermions
in producing the large transverse responses in the absence of magnetization.


  We consider two families of spaces, $X$ : the closed orientable Riemann
surfaces of genus $g>0$ and the classifying spaces of right-angled Artin
groups. In both cases we compare the depth of the fundamental group with the
depth of an associated Lie algebra, $L$, that can be determined by the minimal
Sullivan algebra. For these spaces we prove that $$ \mbox{depth} \,\mathbb
Q[\pi_1(X)] = \mbox{depth}\, {L}\,$$ and give precise formulas for the depth.


  We study the relation between a heterotic T^6/Z6 orbifold model and a
compactification on a smooth Voisin-Borcea Calabi-Yau three-fold with
non-trivial line bundles. This orbifold can be seen as a Z2 quotient of T^4/Z3
x T^2. We consider a two-step resolution, whose intermediate step is (K3 x
T^2)/Z2. This allows us to identify the massless twisted states which
correspond to the geometric Kaehler and complex structure moduli. We work out
the match of the two models when non-zero expectation values are given to all
twisted geometric moduli. We find that even though the orbifold gauge group
contains an SO(10) factor, a possible GUT group, the subgroup after higgsing
does not even include the standard model gauge group. Moreover, after higgsing,
the massless spectrum is non-chiral under the surviving gauge group.


  Dynamic convolution learns a linear mixture of n static kernels weighted with
their input-dependent attentions, demonstrating superior performance than
normal convolution. However, it increases the number of convolutional
parameters by n times, and thus is not parameter efficient. This leads to no
research progress that can allow researchers to explore the setting n>100 (an
order of magnitude larger than the typical setting n<10) for pushing forward
the performance boundary of dynamic convolution while enjoying parameter
efficiency. To fill this gap, in this paper, we propose KernelWarehouse, a more
general form of dynamic convolution, which redefines the basic concepts of
``kernels", ``assembling kernels" and ``attention function" through the lens of
exploiting convolutional parameter dependencies within the same layer and
across neighboring layers of a ConvNet. We testify the effectiveness of
KernelWarehouse on ImageNet and MS-COCO datasets using various ConvNet
architectures. Intriguingly, KernelWarehouse is also applicable to Vision
Transformers, and it can even reduce the model size of a backbone while
improving the model accuracy. For instance, KernelWarehouse (n=4) achieves
5.61%|3.90%|4.38% absolute top-1 accuracy gain on the
ResNet18|MobileNetV2|DeiT-Tiny backbone, and KernelWarehouse (n=1/4) with
65.10% model size reduction still achieves 2.29% gain on the ResNet18 backbone.
The code and models are available at https://github.com/OSVAI/KernelWarehouse.


  Many applications require to learn, mine, analyze and visualize large-scale
graphs. These graphs are often too large to be addressed efficiently using
conventional graph processing technologies. Many applications have requirements
to analyze, transform, visualize and learn large scale graphs. These graphs are
often too large to be addressed efficiently using conventional graph processing
technologies. Recent literatures convey that graph sampling/random walk could
be an efficient solution. In this paper, we propose, to the best of our
knowledge, the first GPU-based framework for graph sampling/random walk. First,
our framework provides a generic API which allows users to implement a wide
range of sampling and random walk algorithms with ease. Second, offloading this
framework on GPU, we introduce warp-centric parallel selection, and two
optimizations for collision migration. Third, towards supporting graphs that
exceed GPU memory capacity, we introduce efficient data transfer optimizations
for out-of-memory sampling, such as workload-aware scheduling and batched
multi-instance sampling. In its entirety, our framework constantly outperforms
the state-of-the-art projects. First, our framework provides a generic API
which allows users to implement a wide range of sampling and random walk
algorithms with ease. Second, offloading this framework on GPU, we introduce
warp-centric parallel selection, and two novel optimizations for collision
migration. Third, towards supporting graphs that exceed the GPU memory
capacity, we introduce efficient data transfer optimizations for out-of-memory
and multi-GPU sampling, such as workload-aware scheduling and batched
multi-instance sampling. Taken together, our framework constantly outperforms
the state of the art projects in addition to the capability of supporting a
wide range of sampling and random walk algorithms.


  Only a causal class among the 199 Lorentzian ones, which do not exists in the
Newtonian spacetime, is privileged to construct a generic, gravity free and
immediate (non retarded) relativistic positioning system. This is the causal
class of the null emission coordinates. Emission coordinates are defined and
generated by four emitters broadcasting their proper times. The emission
coordinates are covariant (frame independent) and hence valid for any user. Any
observer can obtain the values of his(her) null emission coordinates from the
emitters which provide him his(her) trajectory.


  In this paper, we mainly study structure of multiplicative simple Hom-Jordan
algebras. We talk about equivalent conditions for multiplicative Hom-Jordan
algebras being solvable, simple and semi-simple. As an application, we give a
theorem about classification of multiplicative simple Hom-Jordan algebras.
Moreover, some propositions about bimodules of multiplicative Hom-Jordan
algebras are also displayed.


  Given a causal graph representing the data-generating process shared across
different domains/distributions, enforcing sufficient graph-implied conditional
independencies can identify domain-general (non-spurious) feature
representations. For the standard input-output predictive setting, we
categorize the set of graphs considered in the literature into two distinct
groups: (i) those in which the empirical risk minimizer across training domains
gives domain-general representations and (ii) those where it does not. For the
latter case (ii), we propose a novel framework with regularizations, which we
demonstrate are sufficient for identifying domain-general feature
representations without a priori knowledge (or proxies) of the spurious
features. Empirically, our proposed method is effective for both (semi)
synthetic and real-world data, outperforming other state-of-the-art methods in
average and worst-domain transfer accuracy.


  A few years ago a connection between the elliptic genus of the K3 manifold
and the largest Mathieu group M$_{24}$ was proposed. We study the elliptic
genera for Calabi-Yau manifolds of larger dimensions and discuss potential
connections between the expansion coefficients of these elliptic genera and
sporadic groups. While the Calabi-Yau 3-fold case is rather uninteresting, the
elliptic genera of certain Calabi-Yau $d$-folds for $d>3$ have expansions that
could potentially arise from underlying sporadic symmetry groups. We explore
such potential connections by calculating twined elliptic genera for a large
number of Calabi-Yau 5-folds that are hypersurfaces in weighted projected
spaces, for a toroidal orbifold and two Gepner models.


  In a framework where galaxies form hierarchically, extended stellar haloes
are predicted to be an ubiquitous feature around Milky Way-like galaxies and to
consist mainly of the shredded stellar component of smaller galactic systems.
The type of accreted stellar systems are expected to vary according to the
specific accretion and merging history of a given galaxy, and so is the
fraction of stars formed in-situ versus accreted. Analysis of the chemical
properties of Milky Way halo stars out to large Galactocentric radii can
provide important insights into the properties of the environment in which the
stars that contributed to the build-up of different regions of the Milky Way
stellar halo formed. In this work we focus on the outer regions of the Milky
Way stellar halo, by determining chemical abundances of halo stars with large
present-day Galactocentric distances, $>$15 kpc. The data-set we acquired
consists of high resolution HET/HRS, Magellan/MIKE and VLT/UVES spectra for 28
red giant branch stars covering a wide metallicity range, $-3.1
\lesssim$[Fe/H]$\lesssim -0.6$. We show that the ratio of $\alpha$-elements
over Fe as a function of [Fe/H] for our sample of outer halo stars is not
dissimilar from the pattern shown by MW halo stars from solar neighborhood
samples. On the other hand, significant differences appear at [Fe/H]$\gtrsim
-1.5$ when considering chemical abundance ratios such as [Ba/Fe], [Na/Fe],
[Ni/Fe], [Eu/Fe], [Ba/Y]. Qualitatively, this type of chemical abundance trends
are observed in massive dwarf galaxies, such as Sagittarius and the Large
Magellanic Cloud. This appears to suggest a larger contribution in the outer
halo of stars formed in an environment with high initial star formation rate
and already polluted by asymptotic giant branch stars with respect to inner
halo samples.


  Drug dosing is an important application of AI, which can be formulated as a
Reinforcement Learning (RL) problem. In this paper, we identify two major
challenges of using RL for drug dosing: delayed and prolonged effects of
administering medications, which break the Markov assumption of the RL
framework. We focus on prolongedness and define PAE-POMDP (Prolonged Action
Effect-Partially Observable Markov Decision Process), a subclass of POMDPs in
which the Markov assumption does not hold specifically due to prolonged effects
of actions. Motivated by the pharmacology literature, we propose a simple and
effective approach to converting drug dosing PAE-POMDPs into MDPs, enabling the
use of the existing RL algorithms to solve such problems. We validate the
proposed approach on a toy task, and a challenging glucose control task, for
which we devise a clinically-inspired reward function. Our results demonstrate
that: (1) the proposed method to restore the Markov assumption leads to
significant improvements over a vanilla baseline; (2) the approach is
competitive with recurrent policies which may inherently capture the prolonged
effect of actions; (3) it is remarkably more time and memory efficient than the
recurrent baseline and hence more suitable for real-time dosing control
systems; and (4) it exhibits favorable qualitative behavior in our policy
analysis.


  Neutrinos produced in gamma-ray bursters (GRBers) may provide a unique probe
for the physics of these extreme astrophysical systems. Here we discuss
neutrino production in inelastic neutron-proton collisions within the
relativistic outflows associated with GRBers. We consider both the widely used
fireball model and a recently proposed magneto-hydrodynamic (MHD) model for the
GRB outflow.


  We show that certain products of Whittaker functions and Schwartz functions
on a general linear group extend to Whittaker functions on a larger general
linear group. This generalizes results of Cogdell--Piatetski-Shapiro \cite{CPS}
and Jacquet--Piatetski-Shapiro--Shalika \cite{JPSS83}. As a consequence, we
prove that the Rankin--Selberg $L$-factor of the product of a discrete series
representation and the Zelevinsky dual of a discrete series representation is
given by a single Rankin--Selberg integral.


  Given functions $f$ and $g$ defined on the subset lattice of order $n$, their
min-sum subset convolution, defined for all $S \subseteq [n]$ as \[
  (f \star g)(S) = \min_{T \subseteq S}\:\big(f(T) + g(S \setminus T)\big), \]
lies at the heart of several NP-hard optimization problems, such as
minimum-cost $k$-coloring, the prize-collecting Steiner tree, and many others
in computational biology. Despite its importance, its na\"ive $O(3^n)$-time
evaluation remains the fastest known, the other alternative being an $\tilde
O(2^n M)$-time algorithm for instances where the input functions have a bounded
integer range $\{-M, \ldots, M\}$.
  We study for the first time the $(1 + \varepsilon)$-approximate min-sum
subset convolution and present both a weakly- and strongly-polynomial
approximation algorithm, running in time $\tilde O(2^n \log M / \varepsilon)$
and $\tilde O(2^\frac{3n}{2} / \sqrt{\varepsilon})$, respectively. To
demonstrate the applicability of our work, we present the first
exponential-time $(1 + \varepsilon)$-approximation schemes for the above
optimization problems.
  Our algorithms lie at the intersection of two lines of research that have
been so far considered separately: $\textit{sequence}$ and $\textit{subset}$
convolutions in semi-rings. We also extend the recent framework of Bringmann,
K\"unnemann, and W\k{e}grzycki [STOC 2019] to the context of subset
convolutions.


  We apply The Batalin-Tyutin constraint formalism of converting a second class
system into a first class system for the rotational quantisation of the SU(2)
Skyrme model. We obtain the first class constraint and the Hamiltonian in the
extended phase space. The vacuum functional is constructed and evaluated in the
unitary gauge and a multiplier dependent gauge. Finally, we discuss the
spectrum of the extended theory. The use of the BT formalism on the collective
coordinates quantisation of the SU(2) Skyrme model leads an additional term in
the usual quantum Hamiltonian that can improve the phenomenology predicted by
the Skyrme model.


  An analytical solution for time evolution of the gravitational wave damping
in the early Universe due to freely streaming neutrinos is found in the late
time regime. The solution is represented by a convergent series of spherical
Bessel functions of even order and was possible with the help of a new compact
formula for the convolution of spherical Bessel functions of integer order.


  Interaction-driven topological phase transitions in Dirac semimetals are
investigated by means of large-scale quantum Monte Carlo (QMC) simulations. The
interaction among Dirac fermions is introduced by coupling them to Ising spins
that realize the quantum dynamics of the two-dimensional transverse field Ising
model. The ground state phase diagram, in which the tuning parameters are the
transverse field and the coupling between fermion and Ising spins, is
determined. At weak and intermediate coupling, a second-order Ising quantum
phase transition and a first-order topological phase transition between two
topologically distinct Dirac semimetals are observed. Interestingly, at the
latter, the Dirac points smear out to form nodal lines in the Brillouin zone,
and collective bosonic fluctuations with SO(4) symmetry are strongly enhanced.
At strong coupling, these two phase boundaries merge into a first-order
transition.


  How can we compute the pseudoinverse of a sparse feature matrix efficiently
and accurately for solving optimization problems? A pseudoinverse is a
generalization of a matrix inverse, which has been extensively utilized as a
fundamental building block for solving linear systems in machine learning.
However, an approximate computation, let alone an exact computation, of
pseudoinverse is very time-consuming due to its demanding time complexity,
which limits it from being applied to large data. In this paper, we propose
FastPI (Fast PseudoInverse), a novel incremental singular value decomposition
(SVD) based pseudoinverse method for sparse matrices. Based on the observation
that many real-world feature matrices are sparse and highly skewed, FastPI
reorders and divides the feature matrix and incrementally computes low-rank SVD
from the divided components. To show the efficacy of proposed FastPI, we apply
them in real-world multi-label linear regression problems. Through extensive
experiments, we demonstrate that FastPI computes the pseudoinverse faster than
other approximate methods without loss of accuracy. %and uses much less memory
compared to full-rank SVD based approach. Results imply that our method
efficiently computes the low-rank pseudoinverse of a large and sparse matrix
that other existing methods cannot handle with limited time and space.


  We investigate the nature of a $Z_2$-invariant XY ring-exchange interaction
with a frustrated Ising coupling on the triangular lattice. In the limit of
pure XY ring-exchange interaction, we show that the classical ground state is
degenerate resulting from the $Z_2$-invariance of the Hamiltonian. Quantum
fluctuations lift these classical degenerate ground states and produce an
unusual state whose excitation spectrum exhibits a gapped maximum quadratic
dispersion near ${\bf k}=0$ and vanishes at the midpoints of each side of the
Brillouin zone. This result is in contrast to a gapless quadratic dispersion
near ${\bf k}=0$ in the U(1)-invariant counterpart. We also study the effects
of frustration when competing with a classically frustrated Ising interaction.
We provide a glimpse into the possible quantum phases that could emerge. A
comprehensive understanding of this Hamiltonian, however, cannot be elucidated
analytically and requires an explicit numerical simulation.


  This paper studies three fundamental aspects of an OS that impact the
performance and energy efficiency of network processing: 1) batching, 2)
processor energy settings, and 3) the logic and instructions of the OS
networking paths. A network device's interrupt delay feature is used to induce
batching and processor frequency is manipulated to control the speed of
instruction execution. A baremetal library OS is used to explore OS path
specialization. This study shows how careful use of batching and interrupt
delay results in 2X energy and performance improvements across different
workloads. Surprisingly, we find polling can be made energy efficient and can
result in gains up to 11X over baseline Linux. We developed a methodology and a
set of tools to collect system data in order to understand how energy is
impacted at a fine-grained granularity. This paper identifies a number of other
novel findings that have implications in OS design for networked applications
and suggests a path forward to consider energy as a focal point of systems
research.


  It is proposed that the Higgs vacuum possesses a small-scale structure that
can explain the large discrepancy between the predicted electroweak vacuum
energy density and the observed cosmological constant. An effective Lagrangian
description is employed to obtain modifications to the Standard Model
predictions that can be tested at collider experiments.


  We obtain a result in the spirit of the well-known W. Schachermeyer and H. P.
Rosenthal research about the equivalence between Radon-Nikodym and Krein-Milman
properties, by showing that, for closed, bounded and convex subsets C of a
separable Banach space, under Krein-Milman property for $C$, one has the
equivalence between convex point of continuity property and strong regularity
both defined for every locally convex topology on C, containing the weak
topology on C. Then, under Krein-Milman property, not only the classical convex
point of continuity property and strong regularity are equivalent, but also
when they are defined for an arbitrary locally convex topology containing the
weak topology. We also show that while the unit ball $B$ of $c_0$ fails convex
point of continuity property and strong regularity (both defined for the weak
topology), threre is a locally convex topology $\tau$ on $B$, containing the
weak topology on $B$, such that $B$ still fails convex point of continuity
property for $\tau$, but $B$ surprisingly enjoys strong regularity for
$\tau$-open sets. Moreover, $B$ satisfies the diameter two property for the
topology $\tau$, that is, every nonempty $\tau$-open subset of $B$ has diameter
two even though every $\tau$-open subset of $B$ contains convex combinations of
relative $\tau$-open subsets with arbitrarily small diameter, that is, $B$
fails the strong diameter two property for the topology $\tau$. This stresses
the known extreme differences up to now between those diameter two properties
from a topological point of view.


  We recently showed that dispersion-correcting potentials (DCPs),
atom-centered Gaussian-type functions developed for use with B3LYP (J. Phys.
Chem. Lett. 2012, 3, 1738-1744) greatly improved the ability of the underlying
functional to predict non-covalent interactions. However, the application of
B3LYP-DCP for the {\beta}-scission of the cumyloxyl radical led a calculated
barrier height that was over-estimated by ca. 8 kcal/mol. We show in the
present work that the source of this error arises from the previously developed
carbon atom DCPs, which erroneously alters the electron density in the C-C
covalent-bonding region. In this work, we present a new C-DCP with a form that
was expected to influence the electron density farther from the nucleus. Tests
of the new C-DCP, with previously published H-, N- and O-DCPs, with
B3LYP-DCP/6-31+G(2d,2p) on the S66, S22B, HSG-A, and HC12 databases of
non-covalently interacting dimers showed that it is one of the most accurate
methods available for treating intermolecular interactions, giving mean
absolute errors (MAEs) of 0.19, 0.27, 0.16, and 0.18 kcal/mol, respectively.
Additional testing on the S12L database of complexation systems gave an MAE of
2.6 kcal/mol, showing that the B3LYP-DCP/6-31+G(2d,2p) approach is one of the
best-performing and feasible methods for treating large systems dominated by
non-covalent interactions. Finally, we showed that C-C making/breaking
chemistry is well-predicted using the newly developed DCPs. In addition to
predicting a barrier height for the {\beta}-scission of the cumyloxyl radical
that is within 1.7 kcal/mol of the high-level value, application of
B3LYP-DCP/6-31+G(2d,2p) to 10 databases that include reaction barrier heights
and energies, isomerization energies and relative conformation energies gives
performance that is amongst the best of all available dispersion-corrected
density-functional theory approaches.


  Thanks to Pfaffian techniques, we study the R\'enyi entanglement entropies
and the entanglement spectrum of large subsystems for two-dimensional
Rokhsar-Kivelson wave functions constructed from a dimer model on the
triangular lattice. By including a fugacity $t$ on some suitable bonds, one
interpolates between the triangular lattice (t=1) and the square lattice (t=0).
The wave function is known to be a massive $\mathbb Z_2$ topological liquid for
$t>0$ whereas it is a gapless critical state at t=0. We mainly consider two
geometries for the subsystem: that of a semi-infinite cylinder, and the
disk-like setup proposed by Kitaev and Preskill [Phys. Rev. Lett. 96, 110404
(2006)]. In the cylinder case, the entropies contain an extensive term --
proportional to the length of the boundary -- and a universal sub-leading
constant $s_n(t)$. Fitting these cylinder data (up to a perimeter of L=32
sites) provides $s_n$ with a very high numerical accuracy ($10^{-9}$ at t=1 and
$10^{-6}$ at $t=0.5$). In the topological $\mathbb{Z}_2$ liquid phase we find
$s_n(t>0)=-\ln 2$, independent of the fugacity $t$ and the R\'enyi parameter
$n$. At t=0 we recover a previously known result, $s_n(t=0)=-(1/2)\ln(n)/(n-1)$
for $n<1$ and $s_n(t=0)=-\ln(2)/(n-1)$ for $n>1$. In the disk-like geometry --
designed to get rid of the boundary contributions -- we find an entropy $s^{\rm
KP}_n(t>0)=-\ln 2$ in the whole massive phase whatever $n>0$, in agreement with
the result of Flammia {\it et al.} [Phys. Rev. Lett. 103, 261601 (2009)]. Some
results for the gapless limit $R^{\rm KP}_n(t\to 0)$ are discussed.


  We report the control of vertical magnetization shift (VMS) and exchange bias
through spin-orbit torque (SOT) in Pt/Co/Ir25Mn75/Co heterostructure device.
The exchange bias accompanying with a large relative VMS of about 30 % is
observed after applying a single pulse 40 mA in perpendicular field of 2 kOe.
Furthermore, the field-free SOT-induced variations of VMS and exchange bias is
also observed, which would be related to the effective built-in out-of-plane
field due to unequal upward and downward interfacial spin populations. The
SOT-induced switched fraction of out-of-plane interfacial spins shows a linear
dependence on relative VMS, indicating the number of uncompensated pinned spins
are proportional to the switched interfacial spins. Our finding offers a
comprehensive understanding for electrically manipulating interfacial spins of
AFM materials.


  To our knowledge, the existing measure approximation theory requires the
diffusion term of the stochastic delay differential equations (SDDEs) to be
globally Lipschitz continuous. Our work is to develop a new explicit numerical
method for SDDEs with the nonlinear diffusion term and establish the measure
approximation theory. Precisely, we construct a function-valued explicit
truncated Euler-Maruyama segment process (TEMSP) and prove that it admits a
unique ergodic numerical invariant measure. We also prove that the numerical
invariant measure converges to the underlying one of SDDE in the Fortet-Mourier
distance. Finally, we give an example and numerical simulations to support our
theory.


  With the advancement of computer vision and natural language processing,
text-to-video generation, enabled by text-to-video diffusion models, has become
more prevalent. These models are trained using a large amount of data from the
internet. However, the training data often contain copyrighted content,
including cartoon character icons and artist styles, private portraits, and
unsafe videos. Since filtering the data and retraining the model is
challenging, methods for unlearning specific concepts from text-to-video
diffusion models have been investigated. However, due to the high computational
complexity and relative large optimization scale, there is little work on
unlearning methods for text-to-video diffusion models. We propose a novel
concept-unlearning method by transferring the unlearning capability of the text
encoder of text-to-image diffusion models to text-to-video diffusion models.
Specifically, the method optimizes the text encoder using few-shot unlearning,
where several generated images are used. We then use the optimized text encoder
in text-to-video diffusion models to generate videos. Our method costs low
computation resources and has small optimization scale. We discuss the
generated videos after unlearning a concept. The experiments demonstrates that
our method can unlearn copyrighted cartoon characters, artist styles, objects
and people's facial characteristics. Our method can unlearn a concept within
about 100 seconds on an RTX 3070. Since there was no concept unlearning method
for text-to-video diffusion models before, we make concept unlearning feasible
and more accessible in the text-to-video domain.


  We study the dynamics of a class-B semiconductor microring laser coupled to a
neutral microring resonator for common fabrication parameters. For zero
detuning between the resonators, we identify five dynamical regions controlled
by the normalized pump rate of the laser and coupling strength between the
resonators. These regions show stable lasing with phase locking for either
sufficiently small or large coupling strength parameter values. Multistability
and chaos arise in between these stable regions where at least one fixed point
is attractive. The transition from stable to unstable lasing regions in the
parameter space phase diagram is a crossover.


  Recent studies have demonstrated the power of recurrent neural networks for
machine translation, image captioning and speech recognition. For the task of
capturing temporal structure in video, however, there still remain numerous
open research questions. Current research suggests using a simple temporal
feature pooling strategy to take into account the temporal aspect of video. We
demonstrate that this method is not sufficient for gesture recognition, where
temporal information is more discriminative compared to general video
classification tasks. We explore deep architectures for gesture recognition in
video and propose a new end-to-end trainable neural network architecture
incorporating temporal convolutions and bidirectional recurrence. Our main
contributions are twofold; first, we show that recurrence is crucial for this
task; second, we show that adding temporal convolutions leads to significant
improvements. We evaluate the different approaches on the Montalbano gesture
recognition dataset, where we achieve state-of-the-art results.


  Organizations use diverse types of security solutions to prevent
cyberattacks. Multiple vendors provide security solutions developed using
heterogeneous technologies and paradigms. Hence, it is a challenging rather
impossible to easily make security solutions to work an integrated fashion.
Security orchestration aims at smoothly integrating multivendor security tools
that can effectively and efficiently interoperate to support security staff of
a Security Operation Centre (SOC). Given the increasing role and importance of
security orchestration, there has been an increasing amount of literature on
different aspects of security orchestration solutions. However, there has been
no effort to systematically review and analyze the reported solutions. We
report a Multivocal Literature Review that has systematically selected and
reviewed both academic and grey (blogs, web pages, white papers) literature on
different aspects of security orchestration published from January 2007 until
July 2017. The review has enabled us to provide a working definition of
security orchestration and classify the main functionalities of security
orchestration into three main areas: unification, orchestration, and
automation. We have also identified the core components of a security
orchestration platform and categorized the drivers of security orchestration
based on technical and socio-technical aspects. We also provide a taxonomy of
security orchestration based on the execution environment, automation strategy,
deployment type, mode of task and resource type. This review has helped us to
reveal several areas of further research and development in security
orchestration.


  In robotics, simulation has the potential to reduce design time and costs,
and lead to a more robust engineered solution and a safer development process.
However, the use of simulators is predicated on the availability of good
models. This contribution is concerned with improving the quality of these
models via calibration, which is cast herein in a Bayesian framework. First, we
discuss the Bayesian machinery involved in model calibration. Then, we
demonstrate it in one example: calibration of a vehicle dynamics model that has
low degree of freedom count and can be used for state estimation, model
predictive control, or path planning. A high fidelity simulator is used to
emulate the ``experiments'' and generate the data for the calibration. The
merit of this work is not tied to a new Bayesian methodology for calibration,
but to the demonstration of how the Bayesian machinery can establish
connections among models in computational dynamics, even when the data in use
is noisy. The software used to generate the results reported herein is
available in a public repository for unfettered use and distribution.


  Past experiments about hydrogen absorption in niobium have revealed specific
properties about interactions between interstitial hydrogen atoms. It has been
reported that there are long-range attractive and short-range repulsive
interactions between interstitial hydrogen atoms in niobium. It has also been
reported that these interactions are of many-body nature. While previous
understanding of these interactions is based on experimental inferences from
past experiments, through these calculations, for the first time, we can
understand the nature of the interactions at a fundamental level. In this work,
we use Density Functional Theory calculations to study the interactions of
interstitial hydrogen atoms in niobium. We report here that these interactions
are a combination of an attractive, indirect image interaction and a repulsive,
direct interaction. Through our calculations, we also infer here that these
interactions indeed have many-body characteristics.


  Deep learning methods have gained increased attention in various applications
due to their outstanding performance. For exploring how this high performance
relates to the proper use of data artifacts and the accurate problem
formulation of a given task, interpretation models have become a crucial
component in developing deep learning-based systems. Interpretation models
enable the understanding of the inner workings of deep learning models and
offer a sense of security in detecting the misuse of artifacts in the input
data. Similar to prediction models, interpretation models are also susceptible
to adversarial inputs. This work introduces two attacks, AdvEdge and
AdvEdge$^{+}$, that deceive both the target deep learning model and the coupled
interpretation model. We assess the effectiveness of proposed attacks against
two deep learning model architectures coupled with four interpretation models
that represent different categories of interpretation models. Our experiments
include the attack implementation using various attack frameworks. We also
explore the potential countermeasures against such attacks. Our analysis shows
the effectiveness of our attacks in terms of deceiving the deep learning models
and their interpreters, and highlights insights to improve and circumvent the
attacks.


  We include a generalized infinite class of quark-gluon vertex dressing
diagrams in a study of how dynamics beyond the ladder-rainbow truncation
influences the Bethe-Salpeter description of light quark pseudoscalar and
vector mesons. The diagrammatic specification of the vertex is mapped into a
corresponding specification of the Bethe-Salpeter kernel, which preserves
chiral symmetry. This study adopts the algebraic format afforded by the simple
interaction kernel used in previous work on this topic. The new feature of the
present work is that in every diagram summed for the vertex and the
corresponding Bethe-Salpeter kernel, each quark-gluon vertex is required to be
the self-consistent vertex solution. We also adopt from previous work the
effective accounting for the role of the explicitly non-Abelian three gluon
coupling in a global manner through one parameter determined from recent
lattice-QCD data for the vertex. With the more consistent vertex used here, the
error in ladder-rainbow truncation for vector mesons is never more than 10% as
the current quark mass is varied from the u/d region to the b region.


  We study strongly supercooled cosmological phase transitions. We perform
numerical lattice simulations of two-bubble collisions and demonstrate that,
depending on the scalar potential, in the collision the field can either bounce
to a false vacuum or remain oscillating around the true vacuum. We study if
these cases can be distinguished from their gravitational wave signals and
discuss the possibility of black hole formation in the bubble collisions.


  In this article, we use Lindstr\"om Gessel Viennot Lemma to give a short,
combinatorial, visualizable proof of the identity of Schur polynomials -- the
sum of monomials of Young tableaux equals to the quotient of determinants. As a
by-product, we have a proof of Vandermonde determinant without words. We also
prove the cauchy identity. In the remarks, we discuss factorial Schur
polynomials, dual Cauchy identity and the relation beteen Newton interpolation
formula.


  In the present article we describe a few simple and efficient finite volume
type schemes on moving grids in one spatial dimension combined with appropriate
predictor-corrector method to achieve higher resolution. The underlying finite
volume scheme is conservative and it is accurate up to the second order in
space. The main novelty consists in the motion of the grid. This new dynamic
aspect can be used to resolve better the areas with large solution gradients or
any other special features. No interpolation procedure is employed, thus
unnecessary solution smearing is avoided, and therefore, our method enjoys
excellent conservation properties. The resulting grid is completely
redistributed according the choice of the so-called monitor function. Several
more or less universal choices of the monitor function are provided. Finally,
the performance of the proposed algorithm is illustrated on several examples
stemming from the simple linear advection to the simulation of complex shallow
water waves. The exact well-balanced property is proven. We believe that the
techniques described in our paper can be beneficially used to model tsunami
wave propagation and run-up.


  For $g \geq 2$ and $h \geq 3$, we give small improvements on the maximum size
of a $B_h[g]$-set contained in the interval $\{1,2, \dots , N \}$. In
particular, we show that a $B_3[g]$-set in $\{1,2, \dots , N \}$ has at most
$(14.3 g N)^{1/3}$ elements. The previously best known bound was $(16
gN)^{1/3}$ proved by Cilleruelo, Ruzsa, and Trujillo. We also introduce a
related optimization problem that may be of independent interest.


  The physical mechanisms of the laser-induced periodic surface structures
(LIPSS) formation are studied in this paper for single-pulse irradiation
regimes. The change in the LIPSS period with wavelength of incident laser
radiation is investigated experimentally, using a picosecond laser system,
which provides 7-ps pulses in near-IR, visible, and UV spectral ranges. The
experimental results are compared with predictions made under the assumption
that the surface-scattered waves are involved in the LIPSS formation.
Considerable disagreement suggests that hydrodynamic mechanisms can be
responsible for the observed pattern periodicity.


  Estimating the level set of a signal from measurements is a task that arises
in a variety of fields, including medical imaging, astronomy, and digital
elevation mapping. Motivated by scenarios where accurate and complete
measurements of the signal may not available, we examine here a simple
procedure for estimating the level set of a signal from highly incomplete
measurements, which may additionally be corrupted by additive noise. The
proposed procedure is based on box-constrained Total Variation (TV)
regularization. We demonstrate the performance of our approach, relative to
existing state-of-the-art techniques for level set estimation from compressive
measurements, via several simulation examples.


  We consider the two weight problem for the Hilbert transform, namely the
question of finding real-variable characterization of those pair of weights for
which the Hilbert transform acts boundedly on $ L ^2 $ of the weights. Such a
characterization is known subject to certain side conditions. We give a new
proof, simpler in many details, of the best such result. In addition, we
analyze underlying assumptions in the proof, especially in terms of two
alternate side conditions. A new characterization in the case of one doubling
weight is given.


  This is a survey of results on the construction of holomorphic cusp forms on
tube domains originally initiated by Ikeda. Besides a survey it includes
conjectures and possible applications of our work.


  Circumbinary disks have been hypothesized to exist around a number of binary
post-AGB stars. Although most of the circumbinary disks have been inferred
through the near IR excess, a few of them are strong emitters of molecular
emission. Here we present high angular resolution observations of the emission
of $^{12}$CO and its isotopomer $^{13}$CO J=2--1 line from the circumstellar
envelope around the binary post-AGB star IRAS 08544$-$4431, which is one of the
most prominent members of this class of objects. We find that the envelope is
resolved in our observations and two separate components can be identified: (a)
a central extended and strong component with very narrow linewidth between 2 -
6 \kms; (b) a weak bipolar outflow with expansion velocity up to 8 \kms. The
central compact component possesses low and variable $^{12}$CO/$^{13}$CO J=2--1
line ratio, indicating optically thick emission of the main isotope. We
estimate a molecular gas mass of 0.0047 M$_\odot$ for this component based on
the optically thinner $^{13}$CO J=2--1 line. We discuss the relation of the
molecular envelope and the circumbinary disk inferred from near IR excess and
compare with other known cases where the distribution of molecular gas has been
imaged at high angular resolution.


  Question-answer driven Semantic Role Labeling (QA-SRL) was proposed as an
attractive open and natural flavour of SRL, potentially attainable from laymen.
Recently, a large-scale crowdsourced QA-SRL corpus and a trained parser were
released. Trying to replicate the QA-SRL annotation for new texts, we found
that the resulting annotations were lacking in quality, particularly in
coverage, making them insufficient for further research and evaluation. In this
paper, we present an improved crowdsourcing protocol for complex semantic
annotation, involving worker selection and training, and a data consolidation
phase. Applying this protocol to QA-SRL yielded high-quality annotation with
drastically higher coverage, producing a new gold evaluation dataset. We
believe that our annotation protocol and gold standard will facilitate future
replicable research of natural semantic annotations.


  One of the key tasks in the economy is forecasting the economic agents'
expectations of the future values of economic variables using mathematical
models. The behavior of mathematical models can be irregular, including
chaotic, which reduces their predictive power. In this paper, we study the
regimes of behavior of two economic models and identify irregular dynamics in
them. Using these models as an example, we demonstrate the effectiveness of
evolutionary algorithms and the continuous deep Q-learning method in
combination with Pyragas control method for deriving a control action that
stabilizes unstable periodic trajectories and suppresses chaotic dynamics. We
compare qualitative and quantitative characteristics of the model's dynamics
before and after applying control and verify the obtained results by numerical
simulation. Proposed approach can improve the reliability of forecasting and
tuning of the economic mechanism to achieve maximum decision-making efficiency.


  We report inelastic light scattering studies on Ca(Fe0.97Co0.03)2As2 in a
wide spectral range of 120-5200 cm-1 from 5K to 300K, covering the tetragonal
to orthorhombic structural transition as well as magnetic transition at Tsm ~
160K. The mode frequencies of two first-order Raman modes B1g and Eg, both
involving displacement of Fe atoms, show sharp increase below Tsm.
Concomitantly, the linewidths of all the first-order Raman modes show anomalous
broadening below Tsm, attributed to strong spin-phonon coupling. The high
frequency modes observed between 400-1200 cm-1 are attributed to the electronic
Raman scattering involving the crystal field levels of d-orbitals of Fe2+. The
splitting between xz and yz d-orbital levels is shown to be ~ 25 meV which
increases as temperature decreases below Tsm. A broad Raman band observed at ~
3200 cm-1 is assigned to two-magnon excitation of the itinerant Fe 3d
antiferromagnet.


  We give a systematical study on the recently reported excited charm and
charm-strange mesons with potential $1^-$ spin-parity, including the
$D^*_{s1}(2700)^+$, $D^*_{s1}(2860)^+$, $D^*(2600)^0$, $D^*(2650)^0$,
$D^*_1(2680)^0$ and $D^*_1(2760)^0$. The main strong decay properties are
obtained by the framework of Bethe-Salpeter (BS) methods. Our results reveal
that the two $1^-$ charm-strange mesons can be well described by the further
$2^3\!S_1$-$1^3\!D_1$ mixing scheme with a mixing angle of $8.7^{+3.9}_{-3.2}$
degrees. The predicted decay ratio $\frac{\mathcal{B}(D^*K)}{\mathcal{B}(D~K)}$
for $D^*_{s1}(2860)$ is $0.62^{+0.22}_{-0.12}$.~$D^*(2600)^0$ can also be
explained as the $2^3\!S_1$ predominant state with a mixing angle of
$-(7.5^{+4.0}_{-3.3})$ degrees. Considering the mass range, $D^*(2650)^0$ and
$D^*_1(2680)^0$ are more likely to be the $2^3\!S_1$ predominant states,
although the total widths under both the $2^3\!S_1$ and $1^3\!D_1$ assignments
have no great conflict with the current experimental data. The calculated width
for LHCb $D^*_1(2760)^0$ seems about 100 \si{MeV} larger than experimental
measurement if taking it as $1^3\!D_1$ or $1^3\!D_1$ dominant state $c\bar u$.
The comparisons with other calculations and several important decay ratios are
also present. For the identification of these $1^-$ charm mesons, further
experimental information, such as
$\frac{\mathcal{B}(D\pi)}{\mathcal{B}(D^*\pi)}$ are necessary.


  In this paper, We have presented a new general function photonic crystals
(GFPCs), which refractive indexes are line functions of space position in two
mediums $A$ and $B$, and obtain new results: (1) when the line function of
refractive indexes is up or down, the transmissivity can be far larger or
smaller than 1. (2) when the refractive indexes function increase or decrease
along the direction of incident light, the light intensity should be magnified
or weaken, which can be made optical magnifier or attenuator. (3) The GFPCs can
be made optical diode when the light positive and negative incident the GFPCs.


  A library for reading and writing data in the SUSY Les Houches Accord format
is presented. The implementation is in native Fortran 77. The data are
contained in a single array conveniently indexed by preprocessor statements.


  We present data from the Supernova Cosmology Project for five high redshift
Type Ia supernovae (SNe Ia) that were obtained using the NICMOS infrared camera
on the Hubble Space Telescope. We add two SNe from this sample to a rest-frame
I-band Hubble diagram, doubling the number of high redshift supernovae on this
diagram. This I-band Hubble diagram is consistent with a flat universe
(Omega_Matter, Omega_Lambda= 0.29, 0.71). A homogeneous distribution of large
grain dust in the intergalactic medium (replenishing dust) is incompatible with
the data and is excluded at the 5 sigma confidence level, if the SN host galaxy
reddening is corrected assuming R_V=1.75. We use both optical and infrared
observations to compare photometric properties of distant SNe Ia with those of
nearby objects. We find generally good agreement with the expected color
evolution for all SNe except the highest redshift SN in our sample (SN 1997ek
at z=0.863) which shows a peculiar color behavior. We also present spectra
obtained from ground based telescopes for type identification and determination
of redshift.


  Drawing upon a body of research on the evolution of creativity, this paper
proposes a theory of how, when, and why the forward-thinking story-telling
abilities of humans evolved, culminating in the visionary abilities of science
fiction writers. The ability to recursively chain thoughts together evolved
approximately two million years ago. Language abilities, and the ability to
shift between different modes of thought, evolved approximately 100,000 years
ago. Science fiction dates to at least the second Century AD. It is suggested
that well before this time, but after 100,000 years ago, and concurrent with
the evolution of a division of labour between creators and imitators there
arose a division of labour between past, present, and future thinkers.
Agent-based model research suggests there are social benefits to the evolution
of individual differences in creativity such that there is a balance between
novelty-generating creators and continuity-perpetuating imitators. A balance
between individuals focused on the past, present, and future would be expected
to yield similar adaptive benefits.


  The statement of problem is motivated by the idea of modeling the classical
turbulence with a set of chaotic quantized vortex filaments in superfluids.
Among various arguments supporting the idea of quasi-classic behavior of
quantum turbulence, the strongest, probably, is the $k$ dependence of the
spectra of energy, $E(k)\propto k^{-5/3}$ obtained in numerical simulations and
experiments. At the same time the mechanism of classical vs quantum turbulence
(QT) is not clarified and the source of the $k^{-5/3}$ dependence is unclear.
In this work we concentrated on the nonuniform vortex vortex bundles. This
choice is related to actively discussed question concerning a role of collapses
in the vortex dynamics in formation of turbulent spectra. We demonstrate that
the nonuniform vortex vortex bundles, which appear in result of nonlinear
vortex dynamics generates the energy spectrum, which close to the Kolmogorov
dependence $\propto k^{-5/3}$.