  We investigate if the degradation of a quantum directional reference frame
through repeated use can be modeled as a classical direction undergoing a
random walk on a sphere. We demonstrate that the behaviour of the fidelity for
a degrading quantum directional reference frame, defined as the average
probability of correctly determining the orientation of a test system, can be
fit precisely using such a model. Physically, the mechanism for the random walk
is the uncontrollable back-action on the reference frame due to its use in a
measurement of the direction of another system. However, we find that the
magnitude of the step size of this random walk is not given by our classical
model and must be determined from the full quantum description.


  We study $\delta$-derivations -- a construction simultaneously generalizing
derivations and centroid. First, we compute $\delta$-derivations of current Lie
algebras and of modular Zassenhaus algebra. This enables us to provide examples
of Lie algebras having 1/2-derivations which are divisors of zero, thus
answering negatively a question of Filippov. Second, we note that
$\delta$-derivations allow, in some circumstances, to construct examples of
non-semigroup gradings of Lie algebras, in addition to the recent ones
discovered by Elduque. Third, we note that utilizing the construction of the
Grassmann envelope allows to obtain results about $\delta$-(super)derivations
of Lie superalgebras from the corresponding results about Lie algebras. In this
way, we prove that prime Lie superalgebras do not possess nontrivial
$\delta$-(super)derivations, generalizing the recent result of Kaygorodov.


  This paper studies distribution-free inference in settings where the data set
has a hierarchical structure -- for example, groups of observations, or
repeated measurements. In such settings, standard notions of exchangeability
may not hold. To address this challenge, a hierarchical form of exchangeability
is derived, facilitating extensions of distribution-free methods, including
conformal prediction and jackknife+. While the standard theoretical guarantee
obtained by the conformal prediction framework is a marginal predictive
coverage guarantee, in the special case of independent repeated measurements,
it is possible to achieve a stronger form of coverage -- the "second-moment
coverage" property -- to provide better control of conditional miscoverage
rates, and distribution-free prediction sets that achieve this property are
constructed. Simulations illustrate that this guarantee indeed leads to
uniformly small conditional miscoverage rates. Empirically, this stronger
guarantee comes at the cost of a larger width of the prediction set in
scenarios where the fitted model is poorly calibrated, but this cost is very
mild in cases where the fitted model is accurate.


  We find that conjugated polymers can undergo reversible structural phase
transitions during electrochemical oxidation and ion injection. We study
poly[2,5-bis(thiophenyl)-1,4-bis(2-(2-(2-methoxyethoxy)ethoxy)ethoxy)benzene]
(PB2T-TEG), a conjugated polymer with glycolated side chains. Using grazing
incidence wide angle X-ray scattering (GIWAXS), we show that, in contrast to
previously known polymers, this polymer switches between two structurally
distinct crystalline phases associated with electrochemical oxidation/reduction
in an aqueous electrolyte. Importantly, we show that this unique phase change
behavior has important physical consequences for ion transport. Notably, using
moving front experiments visualized by both optical microscopy and
super-resolution photoinduced force microscopy (PiFM), we show that a
propagating ion front in PB2T-TEG exhibits non-Fickian transport, retaining a
sharp step-edge profile, in stark contrast to the Fickian diffusion more
commonly observed. This structural phase transition is reminiscent of those
accompanying ion uptake in inorganic materials like LiFePO$_{4}$. We propose
that engineering similar properties in future conjugated polymers may enable
the realization of new materials with superior performance in electrochemical
energy storage or neuromorphic memory applications.


  Consideration is given to thermodynamical properties of a three-dimensional
Bose-condensate of translation-invariant bipolarons (TI-bipolarons) in magnetic
field. The critical temperature of transition, critical magnetic fields,
energy, heat capacity and the transition heat of TI-bipolaron gas are
calculated. Such values as maximum magnetic field, London penetration depth and
their temperature dependencies are calculated. The results obtained are used to
explain experiments on high-temperature superconductors.


  It is well known that Nash-type inequalities for symmetric Dirichlet forms
are equivalent to on-diagonal heat kernel upper bounds for the associated
symmetric Markov semigroups. In this paper, we show that both imply (and hence
are equivalent to) off-diagonal heat kernel upper bounds under some mild
assumptions. Our approach is based on a new generalized Davies' method. Our
results extend that of \cite{CKS} for Nash-type inequalities with power order
considerably and also extend that of \cite{Gri} for second order differential
operators on a complete non-compact manifold.


  The Ray--Knight theorems show that the local time processes of various path
fragments derived from a one-dimensional Brownian motion $B$ are squared Bessel
processes of dimensions $0$, $2$, and $4$. It is also known that for various
singular perturbations $X= |B| + \mu \ell$ of a reflecting Brownian motion
$|B|$ by a multiple $\mu$ of its local time process $\ell$ at $0$,
corresponding local time processes of $X$ are squared Bessel with other real
dimension parameters, both positive and negative. Here, we embed squared Bessel
processes of all real dimensions directly in the local time process of $B$.
This is done by decomposing the path of $B$ into its excursions above and below
a family of continuous random levels determined by the Harrison--Shepp
construction of skew Brownian motion as the strong solution of an SDE driven by
$B$. This embedding connects to Brownian local times a framework of point
processes of squared Bessel excursions of negative dimension and associated
stable processes, recently introduced by Forman, Pal, Rizzolo and Winkel to set
up interval partition evolutions that arise in their approach to the Aldous
diffusion on a space of continuum trees.


  In Bayesian inference, we seek to compute information about random variables
such as moments or quantiles on the basis of {available data} and prior
information. When the distribution of random variables is {intractable}, Monte
Carlo (MC) sampling is usually required. {Importance sampling is a standard MC
tool that approximates this unavailable distribution with a set of weighted
samples.} This procedure is asymptotically consistent as the number of MC
samples (particles) go to infinity. However, retaining infinitely many
particles is intractable. Thus, we propose a way to only keep a \emph{finite
representative subset} of particles and their augmented importance weights that
is \emph{nearly consistent}. To do so in {an online manner}, we (1) embed the
posterior density estimate in a reproducing kernel Hilbert space (RKHS) through
its kernel mean embedding; and (2) sequentially project this RKHS element onto
a lower-dimensional subspace in RKHS using the maximum mean discrepancy, an
integral probability metric. Theoretically, we establish that this scheme
results in a bias determined by a compression parameter, which yields a tunable
tradeoff between consistency and memory. In experiments, we observe the
compressed estimates achieve comparable performance to the dense ones with
substantial reductions in representational complexity.


  The facility location game has been studied extensively in mechanism design.
In the classical model, each agent's cost is solely determined by her distance
to the nearest facility. In this paper, we introduce a novel model where each
facility charges an entrance fee. Thus, the cost of each agent is determined by
both the distance to the facility and the entrance fee of the facility. In our
model, the entrance fee function is allowed to be an arbitrary function,
causing agents' preferences may no longer be single-peaked anymore: This
departure from the classical model introduces additional challenges. We
systematically delve into the intricacies of the model, designing strategyproof
mechanisms with favorable approximation ratios. Additionally, we complement
these ratios with nearly-tight impossibility results. Specifically, for
one-facility and two-facility games, we provide upper and lower bounds for the
approximation ratios given by deterministic and randomized mechanisms with
respect to utilitarian and egalitarian objectives.


  We present CO(1--0) observations of the high-redshift quasar SDSS
J160705+533558 ($z=3.653$) using the Karl G. Jansky Very Large Array (VLA). We
detect CO emission associated with the quasar and at $\sim16.8\,\rm kpc$
projected distance from it, separated by $\sim800\,\rm km\,s^{-1}$ in velocity.
The total molecular gas mass of this system is $\sim5\times10^{10}\,\rm
M_{\odot}$. By comparing our CO detections with previous submillimetre (submm)
observations of the source, an offset between the different emission components
is revealed: the peak of the submm emission is offset from the quasar and from
the CO companion detected in our VLA data. To explain our findings, we propose
a scenario similar to that for the Antennae galaxies: SDSS J160705+533558 might
be a merger system in which the quasar and the CO companion are the merging
galaxies, whose interaction resulted in the formation of a dusty, star-forming
overlap region between the galaxies that is dominant at the submm wavelengths.


  Sales data in a commodity market (supermarket sales to consumers) has been
analysed by studying the fluctuation spectrum and noise correlations. Three
related products (ketchup, mayonnaise and curry sauce) have been analysed. Most
noise in sales is caused by promotions, but here we focus on the fluctuations
in baseline sales. These characterise the dynamics of the market. Four hitherto
unnoticed effects have been found that are difficult to explain from simple
econometric models. These effects are: (1) the noise level in baseline sales is
much higher than can be expected for uncorrelated sales events; (2) weekly
baseline sales differences are distributed according to a broad non-Gaussian
function with fat tails; (3) these fluctuations follow a Levy distribution of
exponent alpha = 1.4, similar to financial exchange markets and in stock
markets; and (4) this noise is correlated over a period of 10 to 11 weeks, or
shows an apparent power law spectrum. The similarity to stock markets suggests
that models developed to describe these markets may be applied to describe the
collective behaviour of consumers.


  This paper improves the algorithms based on supporting halfspaces and
quadratic programming for convex set intersection problems in our earlier paper
in several directions. First, we give conditions so that much smaller quadratic
programs (QPs) and approximate projections arising from partially solving the
QPs are sufficient for multiple-term superlinear convergence for nonsmooth
problems. Second, we identify additional regularity, which we call the second
order supporting hyperplane property (SOSH), that gives multiple-term quadratic
convergence. Third, we show that these fast convergence results carry over for
the convex inequality problem. Fourth, we show that infeasibility can be
detected in finitely many operations. Lastly, we explain how we can use the
dual active set QP algorithm of Goldfarb and Idnani to get useful iterates by
solving the QPs partially, overcoming the problem of solving large QPs in our
algorithms.


  Direct optimal control theory for quantum dynamical problems presents itself
as an interesting alternative to the traditional indirect optimal control. The
method relies on the first discretize and then optimize paradigm, where a
discretization of the dynamical equations leads to a nonlinear optimization
problem. It has been applied successfully to the control of a bistable system
where the wavepacket had been approximated by a parameterized Gaussian, leading
to a semiclassical set of equations of motion (A. R. Ramos Ramos, O. K\"uhn,
Front. Phys. 9 (2021) 615168). Motivated by these results, in the present paper
we extend the application of the method to the case of exact wavepacket
propagation using the example of a generic Fermi-resonance model. In particular
we address the question how population of the involved overtone state can be
avoided such as to reduce the effect of intramolecular vibrational energy
redistribution. A methodological advantage is that direct optimal control
theory offers flexibility when choosing the running cost, since there is no
need to compute functional derivatives and coupling terms as in the case of
indirect optimal control. We exploit this fact to include state populations in
the running cost, which allows their optimization.


  Supersymmetric standard model has a parity violation in QCD through chiral
quark-squark-gluino interactions with non-degenerate masses between left-handed
and right-handed squarks. Since experiments have not show any parity violations
in QCD yet, a bound for the mass degeneracy between left-handed and
right-handed squarks should exist. In this paper we try to obtain this bound
for each squark. At first, we investigate a non-degeneracy bound between
$m_{\tilde{c}_L}$ and $m_{\tilde{c}_R}$ from experimental data of charmonium
decay. Next, we estimate the non-degeneracy bounds for $\tilde{u}$ and
$\tilde{d}$ from nucleon-meson scattering data, and comment on other squarks.


  We present the results of a search for rapidly evolving transients in the
Dark Energy Survey Supernova Programme. These events are characterized by fast
light curve evolution (rise to peak in $\lesssim 10$ d and exponential decline
in $\lesssim30$ d after peak). We discovered 72 events, including 37 transients
with a spectroscopic redshift from host galaxy spectral features. The 37 events
increase the total number of rapid optical transients by more than factor of
two. They are found at a wide range of redshifts ($0.05<z<1.56$) and peak
brightnesses ($-15.75>M_\mathrm{g}>-22.25$). The multiband photometry is well
fit by a blackbody up to few weeks after peak. The events appear to be hot
($T\approx10000-30000$ K) and large ($R\approx 10^{14}-2\cdot10^{15}$ cm) at
peak, and generally expand and cool in time, though some events show evidence
for a receding photosphere with roughly constant temperature. Spectra taken
around peak are dominated by a blue featureless continuum consistent with hot,
optically thick ejecta. We compare our events with a previously suggested
physical scenario involving shock breakout in an optically thick wind
surrounding a core-collapse supernova (CCSNe), we conclude that current models
for such a scenario might need an additional power source to describe the
exponential decline. We find these transients tend to favor star-forming host
galaxies, which could be consistent with a core-collapse origin. However, more
detailed modeling of the light curves is necessary to determine their physical
origin.


  We prove that, for any $B \subset \mathbb R$, the Cartesian product set $B
\times B$ determines $\Omega(|B|^{2+c})$ distinct angles.


  Given a function $f(n)$ periodic of period $q\geq 1$ and an irrational number
$0<\alpha\leq 1$, Chatterjee and Gun proved that the series
$F(s,f,\alpha)=\sum_{n=0}^{\infty}\frac{f(n)}{(n+\alpha)^s}$ has infinitely
many zeros for $\sigma>1$ when $\alpha$ is transcendental and $F(s,f,\alpha)$
has a pole at $s=1$, or when $\alpha$ is algebraic irrational and
$c=\frac{\max{f(n)}}{\min{f(n)}}<1.15$. In this note, we prove that the result
holds in full generality.


  The chemical elements are created in nuclear fusion processes in the hot and
dense cores of stars. The energy generated through nucleosynthesis allows stars
to shine for billions of years. When these stars explode as massive supernovae,
the newly made elements are expelled, chemically enriching the surrounding
regions. Subsequent generations of stars are formed from gas that is slightly
more element enriched than that from which previous stars formed. This chemical
evolution can be traced back to its beginning soon after the Big Bang by
studying the oldest and most metal-poor stars still observable in the Milky Way
today. Through chemical analysis, they provide the only available tool for
gaining information about the nature of the short-lived first stars and their
supernova explosions more than thirteen billion years ago. These events set in
motion the transformation of the pristine universe into a rich cosmos of
chemically diverse planets, stars, and galaxies.


  We show that for a Steinhaus random multiplicative function
$f:\mathbb{N}\to\mathbb{D}$ and any polynomial $P(x)\in\mathbb{Z}[x]$ of
$\text{deg}\ P\ge 2$ which is not of the form $w(x+c)^{d}$ for some $w\in
\mathbb{Z}$, $c\in \mathbb{Q}$, we have \[\frac{1}{\sqrt{x}}\sum_{n\le x}
f(P(n)) \xrightarrow{d} \mathcal{CN}(0,1),\] where $\mathcal{CN}(0,1)$ is the
standard complex Gaussian distribution with mean $0$ and variance $1.$ This
confirms a conjecture of Najnudel in a strong form. We further show that there
almost surely exist arbitrary large values of $x\ge 1,$ such that $$|\sum_{n\le
x} f(P(n))| \gg_{\text{deg}\ P} \sqrt{x} (\log \log x)^{1/2},$$ for any
polynomial $P(x)\in\mathbb{Z}[x]$ with $\text{deg}\ P\ge 2,$ which is not a
product of linear factors (over $\mathbb{Q}$). This matches the bound predicted
by the law of the iterated logarithm. Both of these results are in contrast
with the well-known case of linear phase $P(n)=n,$ where the partial sums are
known to behave in a non-Gaussian fashion and the corresponding sharp
fluctuations are speculated to be $O(\sqrt{x}(\log \log
x)^{\frac{1}{4}+\varepsilon})$ for any $\varepsilon>0$.


  We quantify the spatial distribution of stars for two subclusters centred
around the massive/intermediate mass stars S Mon and IRS1/2 in the NGC2264
star-forming region. We find that both subclusters are have neither a
substructured, nor a centrally concentrated distribution according to the
Q-parameter. Neither subcluster displays mass segregation according to the
$\Lambda_{\rm MSR}$ ratio, but the most massive stars in IRS1/2 have higher
relative surface densities according to the $\Sigma_{\rm LDR}$ ratio. We then
compare these quantities to the results of N-body simulations to constrain the
initial conditions of NGC2264, which are consistent with having been dense
($\tilde{\rho} \sim 10^4$M$_\odot$pc$^{-3}$), highly substructured and
subvirial. These initial conditions were also derived from a separate analysis
of the runaway and walkaway stars in the region, and indicate that star-forming
regions within 1kpc of the Sun likely have a broad range of initial stellar
densities. In the case of NGC2264, its initial stellar density could have been
high enough to cause the destruction or truncation of protoplanetary discs and
fledgling planetary systems due to dynamical encounters between stars in the
early stages of its evolution.


  Leaky integrate-and-fire (LIF) encoding is a model of neuron transfer
function in biology that has recently attracted the attention of the signal
processing and neuromorphic computing communities as a technique of event-based
sampling for data acquisition. While LIF enables the implementation of
analog-circuit signal samplers of lower complexity and higher accuracy
simultaneously, the core difficulty of this technique is the retrieval of an
input from its LIF-encoded output. In this article, we study this problem in
the context of bandlimited inputs, by extracting the most abstract features of
an LIF encoder as a generalized nonuniform sampler. In this view, the LIF
output is seen as the transformation of the input by a known linear operator.
We show that the signal reconstruction method of projection onto convex sets
(POCS) converges to a weighted pseudo-inverse of this operator. This allows
perfect recovery under uniqueness of reconstruction, minimum-norm
reconstruction under incomplete sampling, as well as a noise shaping of time
quantization that outperforms standard pseudo-inversion. On the practical side,
a single iteration of the POCS method can be used to improve any estimate whose
LIF samples are not consistent with those of the input, and a rigorous
discrete-time implementation of this iteration is proposed that does not
require a Nyquist-rate representation of the signals.


  Schmidt decomposition is a widely employed tool of quantum theory which plays
a key role for distinguishable particles in scenarios such as entanglement
characterization, theory of measurement and state purification. Yet, it is held
not to exist for identical particles, an open problem forbidding its
application to analyze such many-body quantum systems. Here we prove, using a
newly developed approach, that the Schmidt decomposition exists for identical
particles and is thus universal. We find that it is affected by single-particle
measurement localization and state overlap. We study paradigmatic two-particle
systems where identical qubits and qutrits are located in the same place or in
separated places. For the case of two qutrits in the same place, we show that
their entanglement behavior, whose physical interpretation is given, differs
from that obtained before by different methods. Our results are generalizable
to multiparticle systems and open the way for further developments in quantum
information theory when particle identity counts as a resource.


  The functional integral method can be used in quantum mechanics to find the
scattering amplitude for particles in the external field. We will obtain the
potential scattering amplitude form the complete Green function in the
corresponding external field through solving the Schrodinger equation, after
being separated from the poles on the mass shell, which takes the form of an
eikonal (Glauber) representation in the high energy region and the small
scattering angles. Consider specific external potentials such as the Yukawa or
Gaussian potential, we will find the corresponding differential scattering
cross-sections.


  Kernel phase imaging (KPI) enables the direct detection of substellar
companions and circumstellar dust close to and below the classical (Rayleigh)
diffraction limit. We present a kernel phase analysis of JWST NIRISS full pupil
images taken during the instrument commissioning and compare the performance to
closely related NIRISS aperture masking interferometry (AMI) observations. For
this purpose, we develop and make publicly available the custom "Kpi3Pipeline"
enabling the extraction of kernel phase observables from JWST images. The
extracted observables are saved into a new and versatile kernel phase FITS file
(KPFITS) data exchange format. Furthermore, we present our new and publicly
available "fouriever" toolkit which can be used to search for companions and
derive detection limits from KPI, AMI, and long-baseline interferometry
observations while accounting for correlated uncertainties in the model fitting
process. Among the four KPI targets that were observed during NIRISS instrument
commissioning, we discover a low-contrast (~1:5) close-in (~1 $\lambda/D$)
companion candidate around CPD-66~562 and a new high-contrast (~1:170)
detection separated by ~1.5 $\lambda/D$ from 2MASS~J062802.01-663738.0. The
5-$\sigma$ companion detection limits around the other two targets reach ~6.5
mag at ~200 mas and ~7 mag at ~400 mas. Comparing these limits to those
obtained from the NIRISS AMI commissioning observations, we find that KPI and
AMI perform similar in the same amount of observing time. Due to its 5.6 times
higher throughput if compared to AMI, KPI is beneficial for observing faint
targets and superior to AMI at separations >325 mas. At very small separations
(<100 mas) and between ~250-325 mas, AMI slightly outperforms KPI which suffers
from increased photon noise from the core and the first Airy ring of the
point-spread function.


  Currently existing energy-stable parametric finite element methods for
surface diffusion flow and other flows are usually limited to first-order
accuracy in time. Designing a high-order algorithm for geometric flows that can
also be theoretically proven to be energy-stable poses a significant challenge.
Motivated by the new scalar auxiliary variable approach [F.Huang, J.Shen,
Z.Yang, SIAM J. SCI. Comput., 42 (2020), pp. A2514-A2536], we propose novel
energy-stable parametric finite element approximations for
isotropic/anisotropic surface diffusion flows, achieving both first-order and
second-order accuracy in time. Additionally, we apply the algorithms to
simulate the solid-state dewetting of thin films. Finally, extensive numerical
experiments validate the accuracy, energy stability, and efficiency of our
developed numerical methods. The designed algorithms in this work exhibit
strong versatility, as they can be readily extended to other high-order time
discretization methods (e.g., BDFk schemes). Meanwhile, the algorithms achieve
remarkable computational efficiency and maintain excellent mesh quality. More
importantly, the algorithm can be theoretically proven to possess unconditional
energy stability, with the energy nearly equal to the original energy.


  R-matrix analyses of the 12C + alpha elastic-scattering phase shifts deduced
from a recent high-precision measurement of the differential cross sections are
performed. The l=0 phase shifts constrain the R-matrix radius a around 5.85 fm,
while the l=2 phase shifts lead to a strong constrain neither on a nor on the
asymptotic normalization constant C of the 2+ subthreshold state (except for a
loose upper limit). This contradicts previous R-matrix analyses of the 12C +
alpha elastic scattering and explains the incompatibility between values of C
obtained in these analyses.


  We report on the detection of a pulsating Fe Ka line in the High Mass X-ray
Binary (HMXB) GX 301-2, from a 40-ks Chandra observation near periastron. The
pulsations in the Fe Ka emission appeared only in the first 7 ks of the
observation, with a period and phase profile similar to those of the continuum.
The presence of pulsed fluorescent lines is an unusual property in HMXBs. After
7 ks, the continuum flux increased by a factor of three, the Fe Ka flux
increased only by about 10\%, and the pulsating signal in the line disappeared.
Finally, in the second half of the observation, both the continuum and the line
flux dropped by a similar factor of 2. We suggest that the pulsating component
of the Fe Ka line is coming from a transient non-isotropic distribution of
dense gas around the neutron star, for example an accretion stream induced by
periastron passage, or from the illuminated surface of the donor star.


  Recent observational and theoretical work suggests that the formation of the
Galactic stellar halo involved both dissipative processes and the accretion of
subfragments. With present data, the fraction of the halo for which an
accretion origin can be substantiated is small, of order 10 percent. The
kinematics of the best halo field star samples show evidence for both
dissipative and dissipationless formation processes. Models of star-forming
dissipative collapse, in a cosmological context and including feedback from
star formation, do not confirm the simple relations between metallicity,
rotation velocity, and orbital eccentricity for halo stars as originally
predicted. The new model predictions are much closer to the observed
distributions, which have generally been interpreted as evidence for an
accretion origin. These results are broadly consistent with a hierarchical
galaxy formation model, but the details remain to be worked out.


  We have detected new HD absorption systems at high redshifts, z_abs=2.626 and
z_abs=1.777, identified in the spectra of the quasars J0812+3208 and Q1331+170,
respectively. Each of these systems consists of two subsystems. The HD column
densities have been determined: log(N(HD),A)=15.70+/-0.07 for z_A=2.626443(2)
and log(N(HD),B)=12.98+/-0.22 for z_B=2.626276(2) in the spectrum of J0812+3208
and log(N(HD),C)=14.83+/-0.15 for z_C=1.77637(2) and log(N(HD),D)=14.61+/-0.20
for z_D=1.77670(3) in the spectrum of Q1331+170. The measured HD/H2 ratio for
three of these subsystems has been found to be considerably higher than its
values typical of clouds in our Galaxy. We discuss the problem of determining
the primordial deuterium abundance, which is most sensitive to the baryon
density of the Universe \Omega_{b}. Using a well-known model for the chemistry
of a molecular cloud, we have estimated the isotopic ratio
D/H=HD/2H_2=(2.97+/-0.55)x10^{-5} and the corresponding baryon density
\Omega_{b}h^2=0.0205^{+0.0025}_{-0.0020}. This value is in good agreement with
\Omega_{b}h^2=0.0226^{+0.0006}_{-0.0006} obtained by analyzing the cosmic
microwave background radiation anisotropy. However, in high-redshift clouds,
under conditions of low metallicity and low dust content, hydrogen may be
incompletely molecularized even in the case of self-shielding. In this
situation, the HD/2H_2 ratio may not correspond to the actual D/H isotopic
ratio. We have estimated the cloud molecularization dynamics and the influence
of cosmological evolutionary effects on it.


  The task of detecting whether a person wears a face mask from speech is
useful in modelling speech in forensic investigations, communication between
surgeons or people protecting themselves against infectious diseases such as
COVID-19. In this paper, we propose a novel data augmentation approach for mask
detection from speech. Our approach is based on (i) training Generative
Adversarial Networks (GANs) with cycle-consistency loss to translate unpaired
utterances between two classes (with mask and without mask), and on (ii)
generating new training utterances using the cycle-consistent GANs, assigning
opposite labels to each translated utterance. Original and translated
utterances are converted into spectrograms which are provided as input to a set
of ResNet neural networks with various depths. The networks are combined into
an ensemble through a Support Vector Machines (SVM) classifier. With this
system, we participated in the Mask Sub-Challenge (MSC) of the INTERSPEECH 2020
Computational Paralinguistics Challenge, surpassing the baseline proposed by
the organizers by 2.8%. Our data augmentation technique provided a performance
boost of 0.9% on the private test set. Furthermore, we show that our data
augmentation approach yields better results than other baseline and
state-of-the-art augmentation methods.


  The problem of image-to-image translation is one that is intruiging and
challenging at the same time, for the impact potential it can have on a wide
variety of other computer vision applications like colorization, inpainting,
segmentation and others. Given the high-level of sophistication needed to
extract patterns from one domain and successfully applying them to another,
especially, in a completely unsupervised (unpaired) manner, this problem has
gained much attention as of the last few years. It is one of the first problems
where successful applications to deep generative models, and especially
Generative Adversarial Networks achieved astounding results that are actually
of realworld impact, rather than just a show of theoretical prowess; the such
that has been dominating the GAN world. In this work, we study some of the
failure cases of a seminal work in the field, CycleGAN [1] and hypothesize that
they are GAN-stability related, and propose two general models to try to
alleviate these problems. We also reach the same conclusion of the problem
being ill-posed that has been also circulating in the literature lately.


  We show that each integral Borel cohomology class of a connected Lie group G
can be represented by a Borel bounded cocycle if and only if the radical of G
is linear. This leads to a generalization of Gromov's boundedness theorem on
characteristic classes of flat bundles.


  We study gauge theories where quasi-hidden sectors are added to the MSSM for
the sake of string consistency conditions which would otherwise not be
satisfied. We focus on quiver gauge theories motivated by weakly coupled type
II orientifold compactifications. Model independent features in this class
include an anomalous U(1)_V symmetry which protects messenger masses and has
strong consequences for superpotential couplings, a rich phenomenology of heavy
and light Z' bosons, and axionic couplings required for anomaly cancellation
via the Green-Schwarz mechanism. We discuss possibilities for dark matter and
supersymmetry breaking in light of these generic features. Dark matter is
necessarily non-baryonic, though many dark matter candidates have weak
interactions. Most models have a U(1)_V Y Y anomaly whose cancellation requires
couplings which allow for dark matter annihilation into photons through
intermediate axions or anomalous Z' bosons, as in two recently proposed
scenarios. There is often an additional non-anomalous U(1) symmetry which can
give rise to a Fayet-like model of metastable supersymmetry breaking. Breaking
of supersymmetry via SQCD can also be realized and flavor masses are often
protected. Natural possibilities for mediation include gauge mediation, Z'
mediation, and D-instanton mediation, though it is not possible to realize
minimal gauge mediation with messengers added for string consistency.


  In this book I treat the structure of D-module which has countable basis. If
we do not care for topology of D-module, then we consider Hamel basis. If norm
is defined in D-module, then we consider Schauder basis. In case of Schauder
basis, we consider vectors whose expansion in the basis converges normally.


  We obtain the hole propagator of the Sutherland model with SU(2) internal
symmetry for coupling parameter $\beta=1$, which is the simplest nontrivial
case. One created hole with spin down breaks into two quasiholes with spin down
and one quasihole with spin up. While these elementary excitations are
energetically free, the form factor reflects their anyonic character. The
expression for arbitrary integer $\beta$ is conjectured.


  Membranes act as selective barriers and play an important role in processes
such as cellular compartmentalization and industrial-scale chemical and gas
purification. The ideal membrane should be as thin as possible to maximize
flux, mechanically robust to prevent fracture, and have well-defined pore sizes
to increase selectivity. Graphene is an excellent starting point for developing
size selective membranes because of its atomic thickness, high mechanical
strength, relative inertness, and impermeability to all standard gases.
However, pores that can exclude larger molecules, but allow smaller molecules
to pass through have to be introduced into the material. Here we show
UV-induced oxidative etching can create pores in micrometre-sized graphene
membranes and the resulting membranes used as molecular sieves. A pressurized
blister test and mechanical resonance is used to measure the transport of a
variety of gases (H2, CO2, Ar, N2, CH4, and SF6) through the pores. The
experimentally measured leak rates, separation factors, and Raman spectrum
agree well with models based on effusion through a small number of
angstrom-sized pores.


  We examine e+e- --> Ds- Ds*+ and Ds*- Ds+ interactions at 4170 MeV using the
CLEO-c detector in order to measure the decay constant fDs+. We use the Ds+ -->
l+ nu channel, where the l+ designates either a mu+ or a tau+, when the tau+
--> pi+ nu. Analyzing both modes independently, we determine B(Ds+ --> mu+ nu)
= (0.594 +- 0.066 +- 0.031)%, and B(Ds+ --> tau+ nu) = (8.0 +- 1.3 +- 0.4)%. We
also analyze them simultaneously to find an effective value of B{eff}(Ds+ -->
mu+ nu) = (0.638 +- 0.059 +- 0.033)% and extract fDs = (274 +- 13 +- 7) MeV.
Combining with our previous determination of B(D+ -> mu+ nu), we also find the
ratio fDs/fD+ = 1.23 +- 0.11 +- 0.04. We compare to current theoretical
estimates. Finally, we find B(Ds+ --> e+ nu) < 1.3 x10^{-4} at 90% confidence
level.


  The conferences on "Strongly Coupled Coulomb Systems" (SCCS) arose from the
"Strongly Coupled Plasmas" meetings, inaugurated in 1977. The progress in SCCS
theory is reviewed in an `author-centered' frame to limit its scope. Our
efforts, i.e., with Fran\c{c}ois Perrot, sought to apply density functional
theory (DFT) to SCCS calculations. DFT was then poised to become the major
computational scheme for condensed matter physics. The ion-sphere models of
Salpeter and others evolved into useful average-atom models for finite-$T$
Coulomb systems, as in Lieberman's Inferno code. We replaced these by
correlation-sphere models that exploit the description of matter via density
functionals linked to pair-distributions. These methods provided practical
computational means for studying strongly interacting electron-ion Coulomb
systems like warm-dense matter (WDM). The staples of SCCS are wide-ranged,
viz., equation of state, plasma spectroscopy, opacity (absorption, emission),
scattering, level shifts, transport properties, e.g., electrical and heat
conductivity, laser- and shock- created plasmas, their energy relaxation and
transient properties etc. These calculations need pseudopotentials and
exchange-correlation functionals applicable to finite-$T$ Coulomb systems that
may be used in ab initio codes, molecular dynamics, etc. The search for simpler
computational schemes has proceeded via proposals for orbital-free DFT,
statistical potentials, classical maps of quantum systems using classical
schemes like HNC to include strong coupling effects (CHNC). Laughlin's
classical plasma map for the fractional quantum Hall effect (FQHE) is a seminal
example where we report new results for graphene.


  The exoplanets known as hot Jupiters---Jupiter-sized planets with periods
less than 10 days---likely are relics of dynamical processes that shape all
planetary system architectures. Socrates et al. (2012) argued that high
eccentricity migration (HEM) mechanisms proposed for situating these close-in
planets should produce an observable population of highly eccentric proto-hot
Jupiters that have not yet tidally circularized. HEM should also create
failed-hot Jupiters, with periapses just beyond the influence of fast
circularization. Using the technique we previously presented for measuring
eccentricities from photometry (the "photoeccentric effect"), we are distilling
a collection of eccentric proto- and failed-hot Jupiters from the Kepler
Objects of Interest (KOI). Here we present the first, KOI-1474.01, which has a
long orbital period (69.7340 days) and a large eccentricity e =
0.81+0.10/-0.07, skirting the proto-hot Jupiter boundary. Combining Kepler
photometry, ground-based spectroscopy, and stellar evolution models, we
characterize host KOI-1474 as a rapidly-rotating F-star. Statistical arguments
reveal that the transiting candidate has a low false-positive probability of
3.1%. KOI-1474.01 also exhibits transit timing variations of order an hour. We
explore characteristics of the third-body perturber, which is possibly the
"smoking-gun" cause of KOI-1474.01's large eccentricity. Using the host-star's
rotation period, radius, and projected rotational velocity, we find
KOI-1474.01's orbit is marginally consistent with aligned with the stellar spin
axis, although a reanalysis is warranted with future additional data. Finally,
we discuss how the number and existence of proto-hot Jupiters will not only
demonstrate that hot Jupiters migrate via HEM, but also shed light on the
typical timescale for the mechanism.


  Many biological electron transfer (ET) reactions are mediated by metal
centres in proteins. NADH:ubiquinone oxidoreductase (complex I) contains an
intramolecular chain of seven iron-sulphur (FeS) clusters, one of the longest
chains of metal centres in biology and a test case for physical models of
intramolecular ET. In biology, intramolecular ET is commonly described as a
diffusive hopping process, according to the semi-classical theories of Marcus
and Hopfield. However, recent studies have raised the possibility that
non-trivial quantum mechanical effects play a functioning role in certain
biomolecular processes. Here, we extend the semi-classical model for biological
ET to incorporate both semi-classical and coherent quantum phenomena using a
quantum master equation based on the Holstein Hamiltonian. We test our model on
the structurally-defined chain of FeS clusters in complex I. By exploring a
wide range of realistic parameters we find that, when the energy profile for ET
along the chain is relatively flat, just a small coherent contribution can
provide a robust and significant increase in ET rate (above the semi-classical
diffusive-hopping rate), even at physiologically-relevant temperatures.
Conversely, when the on-site energies vary significantly along the chain the
coherent contribution is negligible. For complex I, a crucial respiratory
enzyme that is linked to many neuromuscular and degenerative diseases, our
results suggest a new contribution towards ensuring that intramolecular ET does
not limit the rate of catalysis. For the emerging field of quantum biology, our
model is intended as a basis for elucidating the general role of coherent ET in
biological ET reactions.


  A recently proposed approximate large-n ground state solution of the
U_L(n)xU_R(n) symmetric linear sigma model is investigated at finite
temperature. We study the coupled evaporation of two condensates corresponding
to the symmetry breaking pattern U_L(3)xU_R(3) -> U_V(2), realized by the
ground state in certain parts of the coupling space. The region of the
fluctuation induced first order transitions and its second order boundary is
mapped out. The existence of a tricritical point is conjectured.


  Using quantum Heisenberg model calculations with Green's function technique
generalized for arbitrary spins, we found that for a system of small spins the
quantum spin effects significantly contribute to the magnetic short-range order
and strongly affect physical properties of magnets. The spin dynamics
investigation confirms that these quantum spin effects favor the persistence of
propagating spin-wave excitations above the Curie temperature. Our
investigation suggests a reconsideration of prevailing point of view on finite
temperature magnetism to include quantum effects and the magnetic short-range
order.


  This work presents our solutions to the Algonauts Project 2023 Challenge. The
primary objective of the challenge revolves around employing computational
models to anticipate brain responses captured during participants' observation
of intricate natural visual scenes. The goal is to predict brain responses
across the entire visual brain, as it is the region where the most reliable
responses to images have been observed. We constructed an image-based brain
encoder through a two-step training process to tackle this challenge.
Initially, we created a pretrained encoder using data from all subjects. Next,
we proceeded to fine-tune individual subjects. Each step employed different
training strategies, such as different loss functions and objectives, to
introduce diversity. Ultimately, our solution constitutes an ensemble of
multiple unique encoders. The code is available at
https://github.com/uark-cviu/Algonauts2023


  In this paper we study a non strictly system of conservation law when
viscosity is present and viscosity is zero, which is studied in [10]. We show
the existence and uniqueness of the solution in the space of generalized
functions of Colombeau for the viscous problem and construct a solution to the
inviscid system in the sense of association. Also we construct a solution using
shadow wave approach [5] and Volpert product which was partly determined as
vanishing viscosity limit in [10].


  A Fermion to Boson transformation is accomplished by attaching to each
Fermion a single flux quantum oriented opposite to the applied magnetic field.
When the mean field approximation is made in the Haldane spherical geometry,
the Fermion angular momentum $l_F$ is replaced by $l_B= l_F-{1\over2}(N-1)$.
The set of allowed total angular momentum multiplets is identical in the two
different pictures. The Fermion and Boson energy spectra in the presence of
many body interactions are identical if and only if the pseudopotential is
``harmonic'' in form. However, similar low energy bands of states with Laughlin
correlations occur in the two spectra if the interaction has short range. The
transformation is used to clarify the relation between Boson and Fermion
descriptions of the hierarchy of condensed fractional quantum Hall states.


  We drop a circular disk magnet through a thin coil of wire, record the
induced voltage, and compare the results to an analytic model based on the
dipole approximation and Faraday's law, which predicts that the difference
between the voltage peak magnitudes corresponding to the entry and exit of the
magnet should be in proportion to $z_0^{-1/2}$, where $z_0$ is the initial
height of the magnet above the center of the coil. Agreement between the model
and experimental data are excellent. This easily-reproduced experiment provides
an opportunity for students at a range of levels to quantitatively explore the
effects of magnetic induction.


  Directly imaging extrasolar terrestrial planets necessarily means contending
with the astrophysical noise of exozodiacal dust and the resonant structures
created by these planets in exozodiacal clouds. Using a custom tailored hybrid
symplectic integrator we have constructed 120 models of resonant structures
created by exo-Earths and super-Earths on circular orbits interacting with
collisionless steady-state dust clouds around a Sun-like star. Our models
include enough particles to overcome the limitations of previous simulations
that were often dominated by a handful of long-lived particles, allowing us to
quantitatively study the contrast of the resulting ring structures. We found
that in the case of a planet on a circular orbit, for a given star and dust
source distribution, the morphology and contrast of the resonant structures
depend on only two parameters: planet mass and $\sqrt{a_{\rm p}}/\beta$, where
$a_{\rm p}$ is the planet's semi-major axis and $\beta$ is the ratio of
radiation pressure force to gravitational force on a grain. We constructed
multiple-grain-size models of 25,000 particles each and showed that in a
collisionless cloud, a Dohnanyi crushing law yields a resonant ring whose
optical depth is dominated by the largest grains in the distribution, not the
smallest. We used these models to estimate the mass of the lowest-mass planet
that can be detected through observations of a resonant ring for a variety of
assumptions about the dust cloud and the planet's orbit. Our simulations
suggest that planets with mass as small as a few times Mar's mass may produce
detectable signatures in debris disks for semi-major axes greater than 10 AU.


  We measured the static uniform spin susceptibility of
Ba(Fe$_{1-x}$Rh$_x$)$_2$As$_2$ iron-based superconductors, over a broad range
of doping ($0.041\leq x\leq 0.094$) and magnetic fields. At small fields ($H
\le$ 1 kOe) we observed, above the transition temperature $T_c$, the occurrence
of precursor diamagnetism, which is not ascribable to the Ginzburg-Landau
theory. On the contrary, our data fit a phase fluctuation model, which has been
used to interpret a similar phenomenology occurring in the high-$T_c$ cuprate
superconductors. On the other hand, in presence of strong fields the
unconventional fluctuating diamagnetism is suppressed, whereas 3D fluctuations
are found, in agreement with literature.


  We find generators for the algebra of rational differential invariants for
general and degenerate Kundt spacetimes and relate this to other approaches to
the equivalence problem for Lorentzian metrics. Special attention is given to
dimensions three and four.


  The prediction of cross sections for nuclei far off stability is crucial in
the field of nuclear astrophysics. For spherical nuclei close to the dripline
the statistical model (Hauser-Feshbach) approach is not applicable and direct
contributions may dominate the cross sections. For neutron-rich, even-even Sn
targets, we compare the resulting neutron capture cross sections when
consistently taking the input for the direct capture calculations from three
different microscopic models. The results underline the sensitivity of cross
sections calculated in the direct model to nuclear structure models which can
lead to high uncertainties when lacking experimental information.


  We present a python-based tool to detect the occultation of background
sources by foreground Solar coronal mass ejections. The tool takes as input
standard celestial coordinates of the source and translates those to the
Helioprojective plane, and is thus well suited for use with a wide variety of
background astronomical sources. This tool provides an easy means to search
through a large archival dataset for such crossings and relies on the
well-tested Astropy and Sunpy modules.


  In this work, we propose an open-vocabulary object detection method that,
based on image-caption pairs, learns to detect novel object classes along with
a given set of known classes. It is a two-stage training approach that first
uses a location-guided image-caption matching technique to learn class labels
for both novel and known classes in a weakly-supervised manner and second
specializes the model for the object detection task using known class
annotations. We show that a simple language model fits better than a large
contextualized language model for detecting novel objects. Moreover, we
introduce a consistency-regularization technique to better exploit
image-caption pair information. Our method compares favorably to existing
open-vocabulary detection approaches while being data-efficient. Source code is
available at https://github.com/lmb-freiburg/locov .


  Black hole mass measurements outside the local universe are critically
important to derive the growth of supermassive black holes over cosmic time,
and to study the interplay between black hole growth and galaxy evolution. In
this paper we present two measurements of supermassive black hole masses from
reverberation mapping (RM) of the broad CIV emission line. These measurements
are based on multi-year photometry and spectroscopy from the Dark Energy Survey
Supernova Program (DES-SN) and the Australian Dark Energy Survey (OzDES), which
together constitute the OzDES RM Program. The observed reverberation lag
between the DES continuum photometry and the OzDES emission-line fluxes is
measured to be $358^{+126}_{-123}$ and $343^{+58}_{-84}$ days for two quasars
at redshifts of $1.905$ and $2.593$ respectively. The corresponding masses of
the two supermassive black holes are $4.4 \times 10^{9}$ and $3.3 \times
10^{9}$ M$_\odot$, which are among the highest-redshift and highest-mass black
holes measured to date with RM studies. We use these new measurements to better
determine the CIV radius$-$luminosity relationship for high-luminosity quasars,
which is fundamental to many quasar black hole mass estimates and demographic
studies.


  We apply Bayesian Linear Regression to estimate the response rate of drivers
to variable message signs at Seattle-Tacoma International Airport, or SeaTac.
Our approach uses vehicle speed and flow data measured at the entrances of the
arrival and departure-ways of the airport terminal, and sign message data.
Depending on the time of day, we estimate that between 5.5 and 9.1% of drivers
divert from departures to arrivals when the sign reads departures full, use
arrivals, and conversely, between 1.9 and 4.2% of drivers divert from arrivals
to departures. Though we lack counterfactual data (i.e., what would have
happened had the diversionary treatment not been active), adopting a causal
model that encodes time dependency with prior distributions rate can yield a
measurable effect.


  Motivated by black hole physics in N=2, D=4 supergravity, we study the
geometry of quaternionic-Kahler manifolds M obtained by the c-map construction
from projective special Kahler manifolds M_s. Improving on earlier treatments,
we compute the Kahler potentials on the twistor space Z and Swann space S in
the complex coordinates adapted to the Heisenberg symmetries. The results bear
a simple relation to the Hesse potential \Sigma of the special Kahler manifold
M_s, and hence to the Bekenstein-Hawking entropy for BPS black holes. We
explicitly construct the ``covariant c-map'' and the ``twistor map'', which
relate real coordinates on M x CP^1 (resp. M x R^4/Z_2) to complex coordinates
on Z (resp. S). As applications, we solve for the general BPS geodesic motion
on M, and provide explicit integral formulae for the quaternionic Penrose
transform relating elements of H^1(Z,O(-k)) to massless fields on M annihilated
by first or second order differential operators. Finally, we compute the exact
radial wave function (in the supergravity approximation) for BPS black holes
with fixed electric and magnetic charges.


  Medical systematic reviews play a vital role in healthcare decision making
and policy. However, their production is time-consuming, limiting the
availability of high-quality and up-to-date evidence summaries. Recent
advancements in large language models (LLMs) offer the potential to
automatically generate literature reviews on demand, addressing this issue.
However, LLMs sometimes generate inaccurate (and potentially misleading) texts
by hallucination or omission. In healthcare, this can make LLMs unusable at
best and dangerous at worst. We conducted 16 interviews with international
systematic review experts to characterize the perceived utility and risks of
LLMs in the specific context of medical evidence reviews. Experts indicated
that LLMs can assist in the writing process by drafting summaries, generating
templates, distilling information, and crosschecking information. They also
raised concerns regarding confidently composed but inaccurate LLM outputs and
other potential downstream harms, including decreased accountability and
proliferation of low-quality reviews. Informed by this qualitative analysis, we
identify criteria for rigorous evaluation of biomedical LLMs aligned with
domain expert views.


  We develop a formalism suitable for studying Maxwell's equations in the
presence of a medium that is axially symmetric, in particular with respect to
Casimir-Polder interaction energies. As an application, we derive the
Casimir-Polder interaction energy between an electric $\delta$-function plate
and an anisotropically polarizable molecule for arbitrary orientations of the
principal axes of polarizabilities of the molecule. We show that in the perfect
conductor limit for the plate the interaction is insensitive to the orientation
of the polarizabilities of the molecule. We obtain the Casimir-Polder energy
between an electric $\delta$-function sphere and an anisotropically polarizable
molecule, again for arbitrary orientations of the principal axes of
polarizabilities of the molecule. We derive results when the polarizable
molecule is either outside the sphere, or inside the sphere. We present the
perfectly conducting limit for the $\delta$-function sphere, and also the
interaction energy for the special case when the molecule is at the center of
the sphere. Our general proposition is that the Casimir-Polder energy between a
dielectric body with axial symmetry and an unidirectionally polarizable
molecule placed on the axis with its polarizability parallel to the axis gets
non-zero contribution only from the $m=0$ azimuth mode. This feature in
conjunction with the property that the $m=0$ mode separates into transverse
electric and transverse magnetic modes allows the evaluation of Casimir-Polder
energies for axially symmetric systems in a relatively easy manner.


  In this work, we propose a robust optimization approach to mitigate the
impact of uncertainties in particle precipitation. Our model incorporates
partial differential equations, more particular nonlinear and nonlocal
population balance equations to describe particle synthesis. The goal of the
optimization problem is to design products with desired size distributions.
Recognizing the impact of uncertainties, we extend the model to hedge against
them. We emphasize the importance of robust protection to ensure the production
of high-quality particles. To solve the resulting robust problem, we enhance a
novel adaptive bundle framework for nonlinear robust optimization that
integrates the exact method of moments approach for solving the population
balance equations. Computational experiments performed with the integrated
algorithm focus on uncertainties in the total mass of the system as it greatly
influence the quality of the resulting product. Using realistic parameter
values for quantum dot synthesis, we demonstrate the efficiency of our
integrated algorithm. Furthermore, we find that the unprotected process fails
to achieve the desired particle characteristics, even for small uncertainties,
which highlights the necessity of the robust process. The latter consistently
outperforms the unprotected process in quality of the obtained product, in
particular in perturbed scenarios.


  With SNO data on electron-neutrino flux from the sun, it is possible to
derive the $\nu_e$ survival probability $P_{ee}(E)$ from existing experimental
data of Super-Kamiokande, gallium experiments and Homestake. The combined data
of SNO and Super-Kamiokande provide boron $\nu_e$ flux and the total flux of
all active boron neutrinos, giving thus $P_{ee}(E)$ for boron neutrinos. The
Homestake detector, after subtraction of the signal from boron neutrinos, gives
the flux of Be+CNO neutrinos, and $P_{ee}$ for the corresponding energy
interval, if the produced flux is taken from the Standard Solar Model (SSM).
Gallium detectors, GALLEX, SAGE and GNO, detect additionally pp-neutrinos. The
pp-flux can be calculated subtracting from the gallium signal the rate due to
boron, beryllium and CNO neutrinos. The ratio of the measured $pp$-neutrino
flux to that predicted by the SSM gives the survival probability for
$pp$-neutrinos. Comparison with theoretical survival probabilities shows that
the best (among known models) fit is given by LMA and LOW solutions.


  In this study, the spin-momentum correlation of one massive spin-1/2 and
spin-1 particle states, which are made based on projection of a relativistic
spin operator into timelike direction is investigated. It is shown that by
using Non-Linear entanglement witnesses (NLEWs), the effect of Lorentz
transformation would decrease both the amount and the region of entanglement.


  Over the past few years, deep neural networks have shown excellent results in
multiple tasks, however, there is still an increasing need to address the
problem of interpretability to improve model transparency, performance, and
safety. Achieving eXplainable Artificial Intelligence (XAI) by combining neural
networks with continuous logic and multi-criteria decision-making tools is one
of the most promising ways to approach this problem: by this combination, the
black-box nature of neural models can be reduced. The continuous logic-based
neural model uses so-called Squashing activation functions, a parametric family
of functions that satisfy natural invariance requirements and contain rectified
linear units as a particular case. This work demonstrates the first benchmark
tests that measure the performance of Squashing functions in neural networks.
Three experiments were carried out to examine their usability and a comparison
with the most popular activation functions was made for five different network
types. The performance was determined by measuring the accuracy, loss, and time
per epoch. These experiments and the conducted benchmarks have proven that the
use of Squashing functions is possible and similar in performance to
conventional activation functions. Moreover, a further experiment was conducted
by implementing nilpotent logical gates to demonstrate how simple
classification tasks can be solved successfully and with high performance. The
results indicate that due to the embedded nilpotent logical operators and the
differentiability of the Squashing function, it is possible to solve
classification problems, where other commonly used activation functions fail.


  In this study, we present a method to measure changes over time of fractal
dimension. We confirmed that our method can calculate the fractal dimension
with the same precision as conventional methods, and tracking performance of
our method is higher than that of the conventional methods.


  By functional calculus methods, we obtain optimal convergence rates in
Euler's approximation formula for C_0-semigroups restricted to ranges of
generalized Stieltjes functions. Our results include a number of partial cases
studied in the literature and cannot essentially be improved.


  We propose an end-to-end speech enhancement method with trainable
time-frequency~(T-F) transform based on invertible deep neural network~(DNN).
The resent development of speech enhancement is brought by using DNN. The
ordinary DNN-based speech enhancement employs T-F transform, typically the
short-time Fourier transform~(STFT), and estimates a T-F mask using DNN. On the
other hand, some methods have considered end-to-end networks which directly
estimate the enhanced signals without T-F transform. While end-to-end methods
have shown promising results, they are black boxes and hard to understand.
Therefore, some end-to-end methods used a DNN to learn the linear T-F transform
which is much easier to understand. However, the learned transform may not have
a property important for ordinary signal processing. In this paper, as the
important property of the T-F transform, perfect reconstruction is considered.
An invertible nonlinear T-F transform is constructed by DNNs and learned from
data so that the obtained transform is perfectly reconstructing filterbank.


  According to a folklore characterization of supercompact spaces, a compact
Hausdorff space is supercompact if and only if it has a binary closed
$k$-network. This characterization suggests to call a topological space $super$
if it has a binary closed $k$-network $\mathcal N$. The binarity of $\mathcal
N$ means that every linked subfamily of $\mathcal N$ is centered. Therefore, a
Hausdorff space is supercompact if and only if it is super and compact. In this
paper we prove that the class of super spaces contains all GO-spaces, all
supercompact spaces, all metrizable spaces, and all collectionwise normal
$\aleph$-spaces. Moreover, the class of super spaces is closed under taking
Tychonoff products and discretely dense sets in Tychonoff products. The
superness of metrizable spaces implies that each compact metrizable space is
supercompact, which was first proved by Strok and Szyma\'nski (1975) and then
reproved by Mills (1979), van Douwen (1981), and D{\c e}bski (1984).


  Understanding the evolution of scaling relations between the observable
properties of clusters and their total mass is key to realizing their potential
as cosmological probes. In this study, we investigate whether the evolution of
cluster scaling relations is affected by the spurious evolution of mass caused
by the evolving reference density with respect to which halo masses are defined
(pseudo-evolution). We use the relation between mass, M, and velocity
dispersion, sigma, as a test case, and show that the deviation from the M-sigma
relation of cluster-sized halos caused by pseudo-evolution is smaller than 10%
for a wide range of mass definitions. The reason for this small impact is a
tight relation between the velocity dispersion and mass profiles, sigma(<r) =
const * (GM(<r) / r)^1/2, which holds across a wide range of radii. We show
that such a relation is generically expected for a variety of density profiles,
as long as halos are in approximate Jeans equilibrium. Thus, as the outer
"virial" radius used to define the halo mass, R, increases due to
pseudo-evolution, halos approximately preserve their M-sigma relation. This
result highlights the fact that tight scaling relations are the result of tight
equilibrium relations between radial profiles of physical quantities. We find
exceptions at very small and very large radii, where the profiles deviate from
the relations they exhibit at intermediate radii. We discuss the implications
of these results for other cluster scaling relations, and argue that
pseudo-evolution should have a small effect on most scaling relations, except
for those that involve the stellar masses of galaxies. In particular, we show
that the relation between stellar-mass fraction and total mass is affected by
pseudo-evolution and is largely shaped by it for halo masses of less than 10^14
solar masses.


  Modern computer architectures rely on caches to reduce the latency gap
between the CPU and main memory. While indispensable for performance, caches
pose a serious threat to security because they leak information about memory
access patterns of programs via execution time.
  In this paper, we present a novel approach for reasoning about the security
of cache algorithms with respect to timing leaks. The basis of our approach is
the notion of leak competitiveness, which compares the leakage of two cache
algorithms on every possible program. Based on this notion, we prove the
following two results:
  First, we show that leak competitiveness is symmetric in the cache
algorithms. This implies that no cache algorithm dominates another in terms of
leakage via a program's total execution time. This is in contrast to
performance, where it is known that such dominance relationships exist.
  Second, when restricted to caches with finite control, the
leak-competitiveness relationship between two cache algorithms is either
asymptotically linear or constant. No other shapes are possible.


  Using ALMA, we observed the stellar wind of two oxygen-rich Asymptotic Giant
Branch (AGB) stars, IK Tau and R Dor, between 335 and 362 GHz. One aim was to
detect metal oxides and metal hydroxides (AlO, AlOH, FeO, MgO, MgOH), some of
which are thought to be direct precursors of dust nucleation and growth. We
report on the potential first detection of FeO (v=0, Omega=4, J=11-10) in RDor
(mass-loss rate, Mdot, ~1e-7 Msun/yr). The presence of FeO in IK Tau (Mdot~5e-6
Msun/yr) cannot be confirmed due to a blend with 29SiS, a molecule that is
absent in R Dor. The detection of AlO in R Dor and of AlOH in IK Tau was
reported earlier by Decin et al. (2017). All other metal oxides and hydroxides,
as well as MgS, remain undetected. We derive a column density N(FeO) of
1.1+/-0.9e15 cm^{-2} in R Dor, or a fractional abundance [FeO/H]~1.5e-8
accounting for non-LTE effects. The derived fractional abundance [FeO/H] is a
factor ~20 larger than conventional gas-phase chemical kinetic predictions.
This discrepancy may be partly accounted for by the role of vibrationally
excited OH in oxidizing Fe, or may be evidence for other currently unrecognised
chemical pathways producing FeO. Assuming a constant fractional abundance
w.r.t. H_2, the upper limits for the other metals are [MgO/H_2] <5.5e-10 (R
Dor) and <7e-11 (IK Tau), [MgOH/H_2] <9e-9 (R Dor) and <1e-9 (IK Tau),
[CaO/H_2] <2.5e-9 (R Dor) and <1e-10 (IK Tau), [CaOH/H_2] <6.5e-9 (R Dor) and
<9e-10 (IK Tau), and [MgS/H_$] <4.5e-10 (R Dor) and <6e-11 (IK Tau). The
retrieved upper limit abundances for these latter molecules are in accord with
the chemical model predictions.


  Given a fully extended topological quantum field theory, the 'crossing with
the circle' conditions establish that the dimension, or categorification
thereof, of the quantum invariant assigned to a closed $k$-manifold $\Sigma$ is
equivalent to that assigned to the ($k$+1)-manifold $\Sigma \times \mathbb
S^1$. We compute in this manuscript these conditions for the 4-3-2-1
Dijkgraaf-Witten theory. In the context of the lattice Hamiltonian realisation
of the theory, the quantum invariants assigned to the circle and the torus
encode the defect open string-like and bulk loop-like excitations,
respectively. The corresponding 'crossing with the circle' condition thus
formalises the process by which loop-like excitations are formed out of
string-like ones. Exploiting this result, we revisit the statement that
loop-like excitations define representations of the linear necklace group as
well as the loop braid group.


  Electrostatic actuators provide a promising approach to creating soft robotic
sheets, due to their flexible form factor, modular integration, and fast
response speed. However, their control requires kilo-Volt signals and
understanding of complex dynamics resulting from force interactions by on-board
and environmental effects. In this work, we demonstrate an untethered planar
five-actuator piezoelectric robot powered by batteries and on-board
high-voltage circuitry, and controlled through a wireless link. The scalable
fabrication approach is based on bonding different functional layers on top of
each other (steel foil substrate, actuators, flexible electronics). The robot
exhibits a range of controllable motions, including bidirectional crawling (up
to ~0.6 cm/s), turning, and in-place rotation (at ~1 degree/s). High-speed
videos and control experiments show that the richness of the motion results
from the interaction of an asymmetric mass distribution in the robot and the
associated dependence of the dynamics on the driving frequency of the
piezoelectrics. The robot's speed can reach 6 cm/s with specific payload
distribution.


  Protein function may be modulated by an event occurring far away from the
functional site, a phenomenon termed allostery. While classically allostery
involves conformational changes, we recently observed that charge
redistribution within an antibody can also lead to an allosteric effect,
modulating the kinetics of binding to target antigen. In the present study, we
study the association of a poly-histidine tagged enzyme (phosphoglycerate
kinase, PGK) to surface-immobilized anti-His antibodies, finding a significant
Charge-Reorganization Allostery (CRA) effect. We further observe that the
negatively charged nucleotide substrates of PGK modulate CRA substantially,
even though they bind far away from the His-tag-antibody interaction interface.
In particular, binding of ATP reduces CRA by more than 50%. The results
indicate that CRA may be affected by charged substrates bound to a protein and
provide further insight into the role of charge redistribution in protein
function.


  Reducing the interference noise in a monaural noisy speech signal has been a
challenging task for many years. Compared to traditional unsupervised speech
enhancement methods, e.g., Wiener filtering, supervised approaches, such as
algorithms based on hidden Markov models (HMM), lead to higher-quality enhanced
speech signals. However, the main practical difficulty of these approaches is
that for each noise type a model is required to be trained a priori. In this
paper, we investigate a new class of supervised speech denoising algorithms
using nonnegative matrix factorization (NMF). We propose a novel speech
enhancement method that is based on a Bayesian formulation of NMF (BNMF). To
circumvent the mismatch problem between the training and testing stages, we
propose two solutions. First, we use an HMM in combination with BNMF (BNMF-HMM)
to derive a minimum mean square error (MMSE) estimator for the speech signal
with no information about the underlying noise type. Second, we suggest a
scheme to learn the required noise BNMF model online, which is then used to
develop an unsupervised speech enhancement system. Extensive experiments are
carried out to investigate the performance of the proposed methods under
different conditions. Moreover, we compare the performance of the developed
algorithms with state-of-the-art speech enhancement schemes using various
objective measures. Our simulations show that the proposed BNMF-based methods
outperform the competing algorithms substantially.


  In this survey, we report on progress concerning families of projective
curves with fixed number and fixed (topological or analytic) types of
singularities. We are, in particular, interested in numerical, universal and
asymptotically proper sufficient conditions to guarantee the nonemptyness,
T-smoothness and irreducibility of the variety of all projective curves with
prescribed singularities in a fixed linear system. We also discuss the
analogous problem for hypersurfaces of arbitrary dimension with isolated
singularities, and we close with a section on open problems and conjectures.


  We present the Red-sequence Cluster Lensing Survey (RCSLenS), an application
of the methods developed for the Canada France Hawaii Telescope Lensing Survey
(CFHTLenS) to the ~785deg$^2$, multi-band imaging data of the Red-sequence
Cluster Survey 2 (RCS2). This project represents the largest public,
sub-arcsecond seeing, multi-band survey to date that is suited for weak
gravitational lensing measurements. With a careful assessment of systematic
errors in shape measurements and photometric redshifts we extend the use of
this data set to allow cross-correlation analyses between weak lensing
observables and other data sets. We describe the imaging data, the data
reduction, masking, multi-colour photometry, photometric redshifts, shape
measurements, tests for systematic errors, and a blinding scheme to allow for
more objective measurements. In total we analyse 761 pointings with r-band
coverage, which constitutes our lensing sample. Residual large-scale B-mode
systematics prevent the use of this shear catalogue for cosmic shear science.
The effective number density of lensing sources over an unmasked area of
571.7deg$^2$ and down to a magnitude limit of r~24.5 is 8.1 galaxies per
arcmin$^2$ (weighted: 5.5 arcmin$^{-2}$) distributed over 14 patches on the
sky. Photometric redshifts based on 4-band griz data are available for 513
pointings covering an unmasked area of 383.5 deg$^2$ We present weak lensing
mass reconstructions of some example clusters as well as the full survey
representing the largest areas that have been mapped in this way. All our data
products are publicly available through CADC at
  http://www.cadc-ccda.hia-iha.nrc-cnrc.gc.ca/en/community/rcslens/query.html
  in a format very similar to the CFHTLenS data release.


  In 1936 H. Lewy showed that the Jacobian determinant of a harmonic
homeomorphism between planar domains does not vanish and thus the map is a
diffeomorphism. This built on the earlier existence results of Rad\'o and
Kneser. R. Shoen and S.T. Yau generalised this result to degree 1 harmonic
mappings between closed Riemann surfaces. Here we give a new approach that
establishes all these results in complete generality.


  We develop a systematic study of Jahn-Teller (JT) models with continuous
symmetries by explor- ing their algebraic properties. The compact symmetric
spaces corresponding to JT models carrying a Lie group symmetry are identified,
and their invariants used to reduce their adiabatic potential energy surfaces
into orbit spaces. Each orbit consists of a set of JT distorted molecular
structures with equal adiabatic electronic spectrum. Molecular motion may be
decomposed into pseudorota- tional and radial. The former preserves the orbit,
while the latter maps an orbit into another. The dimensionality and topology of
the internal space of each orbit depends on the number of degener- ate states
in its adiabatic electronic spectra. Furthermore, qualitatively different
pseudorotational modes occur in orbits of different types. We also provide a
simple proof that the electronic spectrum for the space of JT minimum-energy
structures (trough) displays a universality predicted by the epikernel
principle. This result is in turn used to prove the topological equivalence
between bosonic (fermionic) JT troughs and real (quaternionic) projective
spaces, a conclusion which has outstanding physical consequences, as explained
in our work. The relevance of our study for the more common case of JT systems
with only discrete point group symmetry, and for generic asymmetric molecular
systems with conical intersections involving more than two states is likewise
discussed. In particular, we show that JT models with continuous symmetries
present the simplest models of conical intersections among an arbitrary number
of electronic state crossings.


  Here we give two bijections, one to show that the number of UUU-free Dyck
n-paths is the Motzkin number M_n, the other to obtain the (known)
distributions of the parameters "number of UDUs" and "number of DDUs" on Dyck
n-paths. The first bijection is straightforward, the second not quite so
obvious.


  This paper is concerned with the invisibility cloaking in acoustic wave
scattering from a new perspective. We are especially interested in achieving
the invisibility cloaking by completely regular and isotropic mediums. It is
shown that an interior transmission eigenvalue problem arises in our study,
which is the one considered theoretically in \cite{CCH}. Based on such an
observation, we propose a cloaking scheme that takes a three-layer structure
including a cloaked region, a lossy layer and a cloaking shell. The target
medium in the cloaked region can be arbitrary but regular, whereas the mediums
in the lossy layer and the cloaking shell are both regular and isotropic. We
establish that if a certain non-transparency condition is satisfied, then there
exists an infinite set of incident waves such that the cloaking device is
nearly-invisible under the corresponding wave interrogation. The set of waves
is generated from the Herglotz-approximation of the associated interior
transmission eigenfunctions. We provide both theoretical and numerical
justifications.


  The negative parity states in 116Sn have been investigated in terms of
octupole correlation. The same is probed by using the Indian National Gamma
Array (INGA) facility at Variable Energy Cyclotron Centre, Kolkata using the
reaction, 114Cd({\alpha},2n) 116Sn at 34 MeV energy. Three new
{\gamma}-transitions relevant to the present investigation are reported and the
spin-parities of the associated levels are assigned based on the DCO-ratios and
polarisation measurements. The interband transitions between the positive
parity ground band and the negative parity band are newly observed and the
corresponding extracted ratio of transition probability, B(E1)/B(E2) indicated
the existence of octupole correlation in these nuclei. The enhanced transition
rates for E1 and E3 transitions between these opposite parity bands and
corroboration of soft octupole deformation ultimately aid the onset of octupole
excitation in this isotope.


  The Rapid Serial Visual Presentation (RSVP)-based Brain-Computer Interface
(BCI) is an efficient technology for target retrieval using
electroencephalography (EEG) signals. The performance improvement of
traditional decoding methods relies on a substantial amount of training data
from new test subjects, which increases preparation time for BCI systems.
Several studies introduce data from existing subjects to reduce the dependence
of performance improvement on data from new subjects, but their optimization
strategy based on adversarial learning with extensive data increases training
time during the preparation procedure. Moreover, most previous methods only
focus on the single-view information of EEG signals, but ignore the information
from other views which may further improve performance. To enhance decoding
performance while reducing preparation time, we propose a Temporal-Spectral
fusion transformer with Subject-specific Adapter (TSformer-SA). Specifically, a
cross-view interaction module is proposed to facilitate information transfer
and extract common representations across two-view features extracted from EEG
temporal signals and spectrogram images. Then, an attention-based fusion module
fuses the features of two views to obtain comprehensive discriminative features
for classification. Furthermore, a multi-view consistency loss is proposed to
maximize the feature similarity between two views of the same EEG signal.
Finally, we propose a subject-specific adapter to rapidly transfer the
knowledge of the model trained on data from existing subjects to decode data
from new subjects. Experimental results show that TSformer-SA significantly
outperforms comparison methods and achieves outstanding performance with
limited training data from new subjects. This facilitates efficient decoding
and rapid deployment of BCI systems in practical use.


  Embodied Question Answering (EQA) is a recently proposed task, where an agent
is placed in a rich 3D environment and must act based solely on its egocentric
input to answer a given question. The desired outcome is that the agent learns
to combine capabilities such as scene understanding, navigation and language
understanding in order to perform complex reasoning in the visual world.
However, initial advancements combining standard vision and language methods
with imitation and reinforcement learning algorithms have shown EQA might be
too complex and challenging for these techniques. In order to investigate the
feasibility of EQA-type tasks, we build the VideoNavQA dataset that contains
pairs of questions and videos generated in the House3D environment. The goal of
this dataset is to assess question-answering performance from nearly-ideal
navigation paths, while considering a much more complete variety of questions
than current instantiations of the EQA task. We investigate several models,
adapted from popular VQA methods, on this new benchmark. This establishes an
initial understanding of how well VQA-style methods can perform within this
novel EQA paradigm.


  Inspired by the analogy between different types of differential forms on
supermanifolds and string fields in superstring theory, we construct new
multilinear non-associative products of forms which yield an
$A_\infty$-algebra.


  Over the last 5 years, UVIT has completed observations of more than 500
proposals with ~ 800 unique pointings. In addition, regular planned monitoring
observations have been made and from their analysis various key parameters
related to in orbit performance of UVIT have been quantified. The sensitivities
of the UV channels have remained steady indicating no effect of potential
molecular contamination confirming the adequacy of all the protocols
implemented for avoiding contamination. The quality of the PSF through the
years confirms adequacy of thermal control measures. The early calibrations
obtained during the Performance Verification (PV) phase have been further
revised for more subtle effects. These include flat fields and detector
distortions with greater precision. The operations of UVIT have also evolved
through in orbit experience, e.g. tweaking of operational sequencing, protocol
for recovery from bright object detection (BOD) shutdowns, parameters for BOD
thresholds, etc. Finally, some effects of charged particle hits on electronics
led to opimised strategy for regular resetting. The Near-UV channel was lost in
one of such operations. All the above in-orbit experiences are presented here.


  We perform a semi-automated search for strong gravitational lensing systems
in the 9,000 deg$^2$ Dark Energy Camera Legacy Survey (DECaLS), part of the
DESI Legacy Imaging Surveys (Dey et al.). The combination of the depth and
breadth of these surveys are unparalleled at this time, making them
particularly suitable for discovering new strong gravitational lensing systems.
We adopt the deep residual neural network architecture (He et al.) developed by
Lanusse et al. for the purpose of finding strong lenses in photometric surveys.
We compile a training set that consists of known lensing systems in the Legacy
Surveys and DES as well as non-lenses in the footprint of DECaLS. In this paper
we show the results of applying our trained neural network to the cutout images
centered on galaxies typed as ellipticals (Lang et al.) in DECaLS. The images
that receive the highest scores (probabilities) are visually inspected and
ranked. Here we present 335 candidate strong lensing systems, identified for
the first time.


  Retrieving facial images from attributes plays a vital role in various
systems such as face recognition and suspect identification. Compared to other
image retrieval tasks, facial image retrieval is more challenging due to the
high subjectivity involved in describing a person's facial features. Existing
methods do so by comparing specific characteristics from the user's mental
image against the suggested images via high-level supervision such as using
natural language. In contrast, we propose a method that uses a relatively
simpler form of binary supervision by utilizing the user's feedback to label
images as either similar or dissimilar to the target image. Such supervision
enables us to exploit the contrastive learning paradigm for encapsulating each
user's personalized notion of similarity. For this, we propose a novel loss
function optimized online via user feedback. We validate the efficacy of our
proposed approach using a carefully designed testbed to simulate user feedback
and a large-scale user study. Our experiments demonstrate that our method
iteratively improves personalization, leading to faster convergence and
enhanced recommendation relevance, thereby, improving user satisfaction. Our
proposed framework is also equipped with a user-friendly web interface with a
real-time experience for facial image retrieval.


  Using the first principles calculations, we show that mechanically tunable
electronic energy gap is realizable in bilayer graphene if different
homogeneous strains are applied to the two layers. It is shown that the size of
energy gap can be simply controlled by adjusting the strength and direction of
these strains. We also show that the effect originates from the occurrence of
strain-induced pseudo-scalar potentials in graphene. When homogeneous strains
with different strengths are applied to each layer of bilayer graphene,
transverse electric fields across the two layers can be generated without any
external electronic sources, thereby opening an energy gap. The results
demonstrate a simple mechanical method of realizing pseudo-electromagnetism in
graphene and suggest a maneuverable approach to fabrication of
electromechanical devices based on bilayer graphene.


  Virtualization, a technique once used to multiplex the resources of
high-priced mainframe hardware, is seeing a resurgence in applicability with
the increasing computing power of commodity computers. By inserting a layer of
software between the machine and traditional operating systems, this technology
allows access to a shared computing medium in a manner that is secure,
resource-controlled, and efficient. These properties are attractive in the
field of on-demand computing, where the fine-grained subdivision of resources
provided by virtualized systems allows potentially higher utilization of
computing resources.
  It this work, we survey a number of virtual machine systems with the goal of
finding an appropriate candidate to serve as the basis for the On-Demand Secure
Cluster Computing project at the National Center for Supercomputing
Applications. Contenders are reviewed on a number of desirable properties
including portability and security. We conclude with a comparison and
justification of our choice.


  Within warped extra dimension models that explain flavor through geometry,
flavor changing neutral current constraints generally force the Kaluza-Klein
scale to be above many TeV. This creates tension with a natural electroweak
scale. On the other hand, a much lower scale compatible with precision
electroweak and flavor changing neutral current constraints is allowed if we
decouple the Kaluza-Klein states of Standard Model gauge bosons from light
fermions $c_{\rm light}\simeq c_b\simeq 0.5$ bulk mass parameters). The main
signature for this approach is four top quark production via the Kaluza-Klein
excitations' strong coupling to top quarks. We study single lepton, like-sign
dilepton, and trilepton observables of four-top events at the Large Hadron
Collider. The like-sign dilepton signature typically has the largest discovery
potential for a strongly coupled right-handed top case ($M_{KK} \sim 2-2.5
\TeV$), while single lepton is the better when the left-handed top couples most
strongly ($M_{KK} \sim 2 \TeV$). We also describe challenging lepton-jet
collimation issues in the like-sign dilepton and trilepton channels. An
alternative single lepton observable is considered which takes advantage of the
many bottom quarks in the final state. Although searches of other particles may
compete, we find that four top production via Kaluza-Klein gluons is most
promising in a large region of this parameter space.


  The formulation of the on-surface radiation condition (OSRC) is extended to
handle wave scattering problems in the presence of multiple obstacles. The new
multiple-OSRC simultaneously accounts for the outgoing behavior of the wave
fields, as well as, the multiple wave reflections between the obstacles. Like
boundary integral equations (BIE), this method leads to a reduction in
dimensionality (from volume to surface) of the discretization region. However,
as opposed to BIE, the proposed technique leads to boundary integral equations
with smooth kernels. Hence, these Fredholm integral equations can be handled
accurately and robustly with standard numerical approaches without the need to
remove singularities. Moreover, under weak scattering conditions, this approach
renders a convergent iterative method which bypasses the need to solve single
scattering problems at each iteration.
  Inherited from the original OSRC, the proposed multiple-OSRC is generally a
crude approximate method. If accuracy is not satisfactory, this approach may
serve as a good initial guess or as an inexpensive pre-conditioner for Krylov
iterative solutions of BIE.


  The reliability of mobile devices is a challenge for vendors, since the
mobile software stack has significantly grown in complexity. In this paper, we
study how to assess the impact of faults on the quality of user experience in
the Android mobile OS through fault injection. We first address the problem of
identifying a realistic fault model for the Android OS, by providing to
developers a set of lightweight and systematic guidelines for fault modeling.
Then, we present an extensible fault injection tool (AndroFIT) to apply such
fault model on actual, commercial Android devices. Finally, we present a large
fault injection experimentation on three Android products from major vendors,
and point out several reliability issues and opportunities for improving the
Android OS.


  Stock market forecasting is a lucrative field of interest with promising
profits but not without its difficulties and for some people could be even
causes of failure. Financial markets by their nature are complex, non-linear
and chaotic, which implies that accurately predicting the prices of assets that
are part of it becomes very complicated. In this paper we propose a stock
trading system having as main core the feed-forward deep neural networks (DNN)
to predict the price for the next 30 days of open market, of the shares issued
by Abercrombie & Fitch Co. (ANF) in the stock market of the New York Stock
Exchange (NYSE).
  The system we have elaborated calculates the most effective technical
indicator, applying it to the predictions computed by the DNNs, for generating
trades. The results showed an increase in values such as Expectancy Ratio of
2.112% of profitable trades with Sharpe, Sortino, and Calmar Ratios of 2.194,
3.340, and 12.403 respectively. As a verification, we adopted a backtracking
simulation module in our system, which maps trades to actual test data
consisting of the last 30 days of open market on the ANF asset. Overall, the
results were promising bringing a total profit factor of 3.2% in just one month
from a very modest budget of $100. This was possible because the system reduced
the number of trades by choosing the most effective and efficient trades,
saving on commissions and slippage costs.


  Inspired by a similar analysis for the vacuum conformal Einstein field
equations by Paetz [Ann. H. Poincar\'e 16, 2059 (2015)], in this article we
show how to construct a system of quasilinear wave equations for the geometric
fields associated to the conformal Einstein field equations coupled to matter
models whose energy-momentum tensor has vanishing trace. In this case, the
equation of conservation for the energy-momentum tensor is conformally
invariant. Our analysis includes the construction of a subsidiary evolution
system which allows to prove the propagation of the constraints. We discuss how
the underlying structure behind these systems of equations is the integrability
conditions satisfied by the conformal field equations. The main result of our
analysis is that both the evolution and subsidiary equations for the geometric
part of the conformal Einstein-tracefree matter field equations close without
the need of any further assumption on the matter models other than the
vanishing of the trace of the energy-momentum tensor. Our work is supplemented
by an analysis of the evolution and subsidiary equations associated to three
basic tracefree matter models: the conformally invariant scalar field, the
Maxwell field and the Yang-Mills field. As an application we provide a global
existence and stability result for de Sitter-like spacetimes. In particular,
the result for the conformally coupled scalar field is new in the literature.


  This paper aims to show that making use of Newton's view on equations of
motion of a physical system and of the Maxwell stress tensor we come to a
natural nonlinearization of Maxwell equations in vacuum making use only of
nonrelativistic terms. The new equations include all Maxwell solutions plus new
ones, among which one may find time-stable and spatially finite ones with
photon-like properties and behavior.


  In this work, we explore the relationship between free resolution of some
monomial ideals and Generalized Hamming Weights (GHWs) of binary codes. More
precisely, we look for a structure smaller than the set of codewords of minimal
support that provides us some information about the GHWs. We prove that the
first and second generalized Hamming weight of a binary linear code can be
computed (by means of a graded free resolution) from a set of monomials
associated to a binomial ideal related with the code. Moreover, the remaining
weights are bounded by the Betti numbers for that set.


  Coherent control of the spatial properties of light is central to a wide
variety of applications from high bandwidth quantum and classical communication
to high power fiber lasers. Low-loss conversion amongst a complete and
orthogonal set of modes is particularly important for robust mode-multiplexed
communication. Here, we introduce tunable impedance mismatch between coupled
Fabry-P\'erot resonators as a powerful tool for manipulation of the spatial and
temporal properties of optical fields. In the single-mode regime, frequency
dependent impedance matching enables tunable finesse optical resonators, with
potential applications in quantum science and sensing. Introducing the spatial
dependence of the impedance mismatch as an additional ingredient enables
coherent spatial mode conversion of optical photons at near-unity efficiency.
We implement these ideas, experimentally demonstrating a NIR resonator whose
finesse is tunable over a decade, and an optical mode converter with efficiency
$>\!\!75\%$ for the first six Hermite-Gauss modes. We anticipate that this new
perspective on coupled multimode resonators will have exciting applications in
micro- and nano- photonics and computer-aided inverse design. In particular,
combination with in-cavity electro-optics will open new horizons for real-time
control of the spatio-spectral properties of lasers, resonators, and optical
filters.


  For widespread deployment in domains characterized by partial observability,
non-deterministic actions and unforeseen changes, robots need to adapt sensing,
processing and interaction with humans to the tasks at hand. While robots
typically cannot process all sensor inputs or operate without substantial
domain knowledge, it is a challenge to provide accurate domain knowledge and
humans may not have the time and expertise to provide elaborate and accurate
feedback. The architecture described in this paper combines declarative
programming and probabilistic reasoning to address these challenges, enabling
robots to: (a) represent and reason with incomplete domain knowledge, resolving
ambiguities and revising existing knowledge using sensor inputs and minimal
human feedback; and (b) probabilistically model the uncertainty in sensor input
processing and navigation. Specifically, Answer Set Programming (ASP), a
declarative programming paradigm, is combined with hierarchical partially
observable Markov decision processes (POMDPs), using domain knowledge to revise
probabilistic beliefs, and using positive and negative observations for early
termination of tasks that can no longer be pursued. All algorithms are
evaluated in simulation and on mobile robots locating target objects in indoor
domains.


  We study graviton-photon conversion in magnetosphere of a pulsar and explore
the possibility of detecting high frequency gravitational waves with pulsar
observations. It is shown that conversion of one polarization mode of photons
can be enhanced significantly due to strong magnetic fields around a pulsar. We
also constrain stochastic gravitational waves in frequency range of
$10^{8}-10^{9}\,$Hz and $10^{13}-10^{27}\,$Hz by using data of observations of
the Crab pulsar and the Geminga pulsar. Our method widely fills the gap among
existing high frequency gravitational wave experiments and boosts the frequency
frontier in gravitational wave observations.