  Algebraic logic studies algebraic theories related to proposition and
first-order logic. A new algebraic approach to first-order logic is sketched in
this paper. We introduce the notion of a quantifier theory, which is a functor
from the category of a monad of sets to the category of Boolean algebras,
together with a uniquely determined system of quantifiers. A striking feature
of this approach is that Cayley's Completeness Theorem and Godel's Completeness
Theorem can be stated and proved in a much simpler fashion for quantifier
theories. Both theorems are due to Halmos for polyadic algebras. We also
present a simple transparent treatment of ultraproducts of models of a
quantifier theory.


  This is a preliminary report on the application of Difference Image Analysis
(DIA) to galactic bulge images. The aim of this analysis is to increase the
sensitivity to the detection of gravitational microlensing. We discuss how the
DIA technique simplifies the process of discovering microlensing events by
detecting only objects which have variable flux. We illustrate how the DIA
technique is not limited to detection of so called ``pixel lensing'' events,
but can also be used to improve photometry for classical microlensing events by
removing the effects of blending. We will present a method whereby DIA can be
used to reveal the true unblended colours, positions and light curves of
microlensing events. We discuss the need for a technique to obtain the accurate
microlensing time scales from blended sources, and present a possible solution
to this problem using the existing HST colour magnitude diagrams of the
galactic bulge and LMC. The use of such a solution with both classical and
pixel microlensing searches is discussed. We show that one of the major causes
of systematic noise in DIA is differential refraction. A technique for removing
this systematic by effectively registering images to a common airmass is
presented. Improvements to commonly used image differencing techniques are
discussed.


  Recommender system has been more and more popular and widely used in many
applications recently. The increasing information available, not only in
quantities but also in types, leads to a big challenge for recommender system
that how to leverage these rich information to get a better performance. Most
traditional approaches try to design a specific model for each scenario, which
demands great efforts in developing and modifying models. In this technical
report, we describe our implementation of feature-based matrix factorization.
This model is an abstract of many variants of matrix factorization models, and
new types of information can be utilized by simply defining new features,
without modifying any lines of code. Using the toolkit, we built the best
single model reported on track 1 of KDDCup'11.


  The calibration and analysis of polarization observations in Very Long
Baseline Interferometry (VLBI) requires the use of specific algorithms that
suffer from several limitations, closely related to assumptions in the data
properties that may not hold in observations taken with new-generation VLBI
equipment. Nowadays, the instantaneous bandwidth achievable with VLBI backends
can be as high as several GHz, covering several radio bands simultaneously. In
addition, the sensitivity of VLBI observations with state-of-the-art equipment
may reach dynamic ranges of tens of thousands, both in total intensity and in
polarization. In this paper, we discuss the impact of the limitations of common
VLBI polarimetry algorithms on narrow-field observations taken with modern VLBI
arrays (from the VLBI Global Observing System, VGOS, to the Event Horizon
Telescope, EHT) and present new software that overcomes these limitations. In
particular, our software is able to perform a simultaneous fit of multiple
calibrator sources, include non-linear terms in the model of the instrumental
polarization and use a self-calibration approach for the estimate of the
polarization leakage in the antenna receivers.


  We report on our observations of the 79 and 119um doublet transitions of OH
for 24 local (z<0.262) ULIRGs observed with Herschel-PACS as part of the
Herschel ULIRG Survey (HERUS). Some OH119 profiles display a clear P-Cygni
shape and therefore imply outflowing OH gas, other profiles are predominantly
in absorption or are completely in emission. We find that the relative strength
of the OH emission component decreases as the silicate absorption increases.
This locates the OH outflows inside the obscured nuclei. The maximum outflow
velocities for our sources range from less than 100 to 2000 km/s, with 15/24
(10/24) sources showing OH absorption at velocities exceeding 700 km/s (1000
km/s). Three sources show maximum OH outflow velocities exceeding that of
Mrk231. Since outflow velocities above 500-700 km/s are thought to require an
active galactic nucleus (AGN) to drive them, about 2/3 of our ULIRG sample may
host AGN-driven molecular outflows. This finding is supported by the
correlation we find between the maximum OH outflow velocity and the IR-derived
bolometric AGN luminosity. No such correlation is found with the IR-derived
star formation rate. The highest outflow velocities are found among sources
which are still deeply embedded. We speculate that the molecular outflows in
these sources may be in an early phase of disrupting the nuclear dust veil
before these sources evolve into less obscured AGN. Four of our sources show
high-velocity wings in their [C II] fine-structure line profiles implying
neutral gas outflow masses of at least 2-4.5 x 10^8 Msun.


  We study the exploration problem with approximate linear action-value
functions in episodic reinforcement learning under the notion of low inherent
Bellman error, a condition normally employed to show convergence of approximate
value iteration. First we relate this condition to other common frameworks and
show that it is strictly more general than the low rank (or linear) MDP
assumption of prior work. Second we provide an algorithm with a high
probability regret bound $\widetilde O(\sum_{t=1}^H d_t \sqrt{K} + \sum_{t=1}^H
\sqrt{d_t} \IBE K)$ where $H$ is the horizon, $K$ is the number of episodes,
$\IBE$ is the value if the inherent Bellman error and $d_t$ is the feature
dimension at timestep $t$. In addition, we show that the result is unimprovable
beyond constants and logs by showing a matching lower bound. This has two
important consequences: 1) it shows that exploration is possible using only
\emph{batch assumptions} with an algorithm that achieves the optimal
statistical rate for the setting we consider, which is more general than prior
work on low-rank MDPs 2) the lack of closedness (measured by the inherent
Bellman error) is only amplified by $\sqrt{d_t}$ despite working in the online
setting. Finally, the algorithm reduces to the celebrated \textsc{LinUCB} when
$H=1$ but with a different choice of the exploration parameter that allows
handling misspecified contextual linear bandits. While computational
tractability questions remain open for the MDP setting, this enriches the class
of MDPs with a linear representation for the action-value function where
statistically efficient reinforcement learning is possible.


  Image denoising is an important pre-processing step in medical image
analysis. Different algorithms have been proposed in past three decades with
varying denoising performances. More recently, having outperformed all
conventional methods, deep learning based models have shown a great promise.
These methods are however limited for requirement of large training sample size
and high computational costs. In this paper we show that using small sample
size, denoising autoencoders constructed using convolutional layers can be used
for efficient denoising of medical images. Heterogeneous images can be combined
to boost sample size for increased denoising performance. Simplest of networks
can reconstruct images with corruption levels so high that noise and signal are
not differentiable to human eye.


  In this manuscript we discuss the results of our recent study on $\Xi$
resonances. We have studied meson-baryon interaction with strangeness $-2$ by
solving scattering equations in a coupled channel approach and found that the
dynamics gives rise to the development of two poles in the complex plane close
to the real axis. The corresponding narrow states have isospin half and spin
half in one case and spin 3/2 in the other case. We find that the properties of
the isospin and spin 1/2 state are strikingly similar to $\Xi(1690)$, while the
state with spin 3/2 can be related to $\Xi(2120)$. We find that our results on
$\Xi(1690)$ are in good agreement with the data available from the BELLE and
BABAR Collaborations. Our formalism consists of treating pseudoscalar-baryon
and vector-baryon channels on an equal footing. Since the thresholds of such
channels are distributed over a relatively larger energy range, we obtain all
interaction kernels needed to solve the Bethe-Salpeter equation without
resorting to any nonrelativistic approximation even though the amplitudes are
calculated at low energies.


  There has been recent and growing interest in the development and deployment
of autonomous vehicles, encouraged by the empirical successes of powerful
artificial intelligence techniques (AI), especially in the applications of deep
learning and reinforcement learning. However, as demonstrated by recent traffic
accidents, autonomous driving technology is not fully reliable for safe
deployment. As AI is the main technology behind the intelligent navigation
systems of self-driving vehicles, both the stakeholders and transportation
regulators require their AI-driven software architecture to be safe,
explainable, and regulatory compliant. In this paper, we propose a design
framework that integrates autonomous control, explainable AI (XAI), and
regulatory compliance to address this issue, and then provide an initial
validation of the framework with a critical analysis in a case study. Moreover,
we describe relevant XAI approaches that can help achieve the goals of the
framework.


  A three-dimensional layered Ising-Antiferromagnet with a ferromagnetic
intra-layer coupling to z neighbors, zJ > 0, and an antiferromagnetic
interlayer coupling to z' neighbors, z'J' < 0, is investigated by Monte Carlo
simulations on a hexagonal lattice. The physical nature of the anomalous
temperature bahavior of the sublattice magnetizations, which is found for
certain values of r=zJ/z'J' and z' in magnetic fields is explained in terms of
successive phase transitions. They take place on the ferromagnetic
2-dimensional spin-down sublattice at T = T_c^{2d}, smeared by a finite
stabilizing molecular field, and on both antiferromagnetically coupled
sublattices at T_c^{3d} > T_c^{2d}.


  We present an ab initio study of the ground state of an ideal coupled
two-component gas of ultracold atoms in a one dimensional optical lattice,
either bosons or fermions. Due to the internal two-level structure of the
atoms, the Brillouin zone is twice as large as imposed by the periodicity of
the lattice potential. This is reflected in the Bloch dispersion curves, where
the energy bands regularly possess several local minima. As a consequence, when
the system parameters are tuned across a resonance condition, a non-zero
temperature phase transition occurs which arises from an interplay between
internal and kinetic atomic energies. For fermions, this phase transition is of
topological character since the structure of the Fermi surface is changed
across the critical value. It is shown that these phenomena are also expected
to occur for two and three dimensional optical lattices.


  The hydroperoxyalkyl radicals (.QOOH) are known to play a significant role in
combustion and tropospheric processes, yet their direct spectroscopic detection
remains challenging. In this study, we investigate molecular stereo-electronic
effects influencing the kinetic and thermodynamic stability of a .QOOH along
its formation path from the precursor, alkylperoxyl radical (ROO.), and the
depletion path resulting in the formation of cyclic ether + .OH. We focus on
reactive intermediates encountered in the oxidation of acyclic hydrocarbon
radicals: ethyl, isopropyl, isobutyl, tert-butyl, neopentyl, and their
alicyclic counterparts: cyclohexyl, cyclohexenyl, and cyclohexadienyl. We
report reaction energies and barriers calculated with the highly accurate
method Weizmann-1 (W1) for the channels: ROO. <=> .QOOH, ROO. <=> alkene +
.OOH, .QOOH <=> alkene + .OOH, and .QOOH <=> cyclic ether + .OH. Using W1
results as a reference, we have systematically benchmarked the accuracy of
popular density functional theory (DFT), composite thermochemistry methods, and
an explicitly correlated coupled-cluster method. We ascertain inductive,
resonance, and steric effects on the overall stability of .QOOH and
computationally investigate the possibility of forming more stable species.
With new reactions as test cases, we probe the capacity of various ab initio
methods to yield quantitative insights on the elementary steps of combustion.


  Ultra-pure NaI(Tl) crystals are the key element for a model-independent
verification of the long standing DAMA result and a powerful means to search
for the annual modulation signature of dark matter interactions. The SABRE
collaboration has been developing cutting-edge techniques for the reduction of
intrinsic backgrounds over several years. In this paper we report the first
characterization of a 3.4 kg crystal, named NaI-33, performed in an underground
passive shielding setup at LNGS. NaI-33 has a record low $^{39}$K contamination
of 4.3$\pm$0.2 ppb as determined by mass spectrometry. We measured a light
yield of 11.1$\pm$0.2 photoelectrons/keV and an energy resolution of 13.2%
(FWHM/E) at 59.5 keV. We evaluated the activities of $^{226}$Ra and $^{228}$Th
inside the crystal to be $5.9\pm0.6 \mu$Bq/kg and $1.6\pm0.3 \mu$Bq/kg,
respectively, which would indicate a contamination from $^{238}$U and
$^{232}$Th at part-per-trillion level. We measured an activity of 0.51$\pm$0.02
mBq/kg due to $^{210}$Pb out of equilibrium and a $\alpha$ quenching factor of
0.63$\pm$0.01 at 5304 keV. We illustrate the analyses techniques developed to
reject electronic noise in the lower part of the energy spectrum. A cut-based
strategy and a multivariate approach indicated a rate, attributed to the
intrinsic radioactivity of the crystal, of $\sim$1 count/day/kg/keV in the
[5-20] keV region.


  The structural origin of the size of the 11 nm nucleosomal disc is addressed.
On the nanometer length-scale the organization of DNA as chromatin in the
chromosomes involves a coiling of DNA around the histone core of the
nucleosome. We suggest that the size of the nucleosome core particle is
dictated by the fulfillment of two criteria: One is optimizing the volume
fraction of the DNA double helix; this requirement for close-packing has its
root in optimizing atomic and molecular interactions. The other criterion being
that of having a zero strain-twist coupling; being a zero-twist structure is a
necessity when allowing for transient tensile stresses during the
reorganization of DNA, e.g., during the reposition, or sliding, of a nucleosome
along the DNA double helix. The mathematical model we apply is based on a
tubular description of double helices assuming hard walls. When the base-pairs
of the linker-DNA is included the estimate of the size of an ideal nucleosome
is in close agreement with the experimental numbers. Interestingly, the size of
the nucleosome is shown to be a consequence of intrinsic properties of the DNA
double helix.


  We introduce a new variant of tight closure and give an interpretation of
adjoint ideals via this tight closure. As a corollary, we prove that a log pair
$(X,\Delta)$ is plt if and only if the modulo $p$ reduction of $(X,\Delta)$ is
divisorially F-regular for all large $p \gg 0$. Here, divisorially F-regular
pairs are a class of singularities in positive characteristic introduced by
Hara and Watanabe in terms of Frobenius splitting.


  This paper considers an example of Object-Oriented Programming (OOP) leading
to subtle errors that break separation of interface and implementations. A
comprehensive principle that guards against such errors is undecidable. The
paper introduces a set of mechanically verifiable rules that prevent these
insidious problems. Although the rules seem restrictive, they are powerful and
expressive, as we show on several familiar examples. The rules contradict both
the spirit and the letter of the OOP. The present examples as well as available
theoretical and experimental results pose a question if OOP is conducive to
software development at all.


  We present a switching control strategy based on Lyapunov control for
arbitrary state transitions in open qubit systems. With coherent vector
representation, we propose a switching control strategy, which can prevent the
state of the qubit from entering invariant sets and singular value sets,
effectively driving the system ultimately to a sufficiently small neighborhood
of target states. In comparison to existing works, this control strategy
relaxes the strict constraints on system models imposed by special target
states. Furthermore, we identify conditions under which the open qubit system
achieves finite-time stability (FTS) and finite-time contractive stability
(FTCS), respectively. This represents a critical improvement in quantum state
transitions, especially considering the asymptotic stability of arbitrary
target states is unattainable in open quantum systems. The effectiveness of our
proposed method is convincingly demonstrated through its application in a qubit
system affected by various types of decoherence, including amplitude, dephasing
and polarization decoherence.


  We analyze the compatibility between the geometrodynamics and thermodynamics
of a binary mixture of perfect fluids which describe inhomogeneous cosmological
models. We generalize the thermodynamic scheme of general relativity to include
the chemical potential of the fluid mixture with non-vanishing entropy
production. This formalism is then applied to the case of Szekeres and Stephani
families of cosmological models. The compatibility conditions turn out to
impose symmetry conditions on the cosmological models in such a way that only
the limiting case of the Friedmann-Robertson-Walker model remains compatible.
This result is an additional indication of the incompatibility between
thermodynamics and relativity.


  In this paper we present a chemical and kinematic analysis of two ultra-faint
dwarf galaxies (UFDs), Aquarius II (Aqu~II) and \text{Bo\"{o}tes II} (Boo~II),
using Magellan/IMACS spectroscopy. We present the largest sample of member
stars for Boo~II (12), and the largest sample of red-giant-branch members with
metallicity measurements for Aqu~II (8). In both UFDs, over 80\% of targets
selected based on $Gaia$ proper motions turned out to be spectroscopic members.
In order to maximize the accuracy of stellar kinematic measurements, we remove
the identified binary stars and RR Lyrae variables. For Aqu~II we measure a
systemic velocity of $-65.3 \pm 1.8$ km s$^{-1}$ and a metallicity of [Fe/H] =
$-2.57^{+0.17}_{-0.17}$. When compared with previous measurements, these values
display a $\sim 6$ km s$^{-1}$ difference in radial velocity and a decrease of
0.27 dex in metallicity. Similarly for Boo~II, we measure a systemic velocity
of $-130.4^{+1.4}_{-1.1}$ km s$^{-1}$, more than 10 km s$^{-1}$ different from
the literature, a metallicity almost 1 dex smaller at [Fe/H] =
$-2.71^{+0.11}_{-0.10}$, and a velocity dispersion 3 times smaller at
$\sigma_{v_{\rm hel}} = 2.9^{+1.6}_{-1.2}$ km s$^{-1}$. Additionally, we derive
systemic proper motion parameters and model the orbits of both UFDs. Finally,
we highlight the extremely dark matter dominated nature of Aqu~II and compute
the J-factor for both galaxies to aid searches of dark matter annihilation.
Despite the small size and close proximity of Boo~II, it is an intermediate
target for the indirect detection of dark matter annihilation due to its low
velocity dispersion and corresponding low dark matter density.


  Using phase resolved spectroscopic observations obtained with the Ultraviolet
and Visual Echelle Spectrograph on ESO's Kueyen Very Large Telescope
supplemented by spectroscopic observations obtained with the Boller and Chivens
Spectrograph on the Walter Baade Magellan telescope, we found sinusoidal
radial-velocity variations with a semi-amplitude 327+-17 km/s. From previous
observations and from the fact that the epoch of minimum velocity arrived early
with respect to the epoch calculated from pulse timing we know that the
companion star is suffering from irradiation. Since we most likely observed
primarily the side of the companion star facing the observer at phase ~0.75 the
velocity quoted above is not the true radial velocity semi-amplitude of the
companion star. Assuming a uniform contribution to the line profile from this
hemisphere yields a radial velocity semi-amplitude of 280+-26 km/s for a
systemic velocity of 54+-24 km/s; if the contribution is instead weighted
somewhat more towards the side of the companion facing the X-ray source then
the true semi-amplitude is larger than this value. Together with the well
constrained inclination (81<i<84 degrees) and the mass-function determined from
pulse-timing analysis (2.03+-0.03 x 10^-2 Msun), we derive a lower limit to the
mass of the neutron star and to that of the companion star of 0.97+-0.24 Msun
and 0.33+-0.05 Msun, respectively (1 sigma; including uncertainties in the
inclination). We briefly discuss other aspects of the spectrum and the
implications of our findings.


  We survey the reasons for the ongoing boycott of the publisher Elsevier. We
examine Elsevier's pricing and bundling policies, restrictions on dissemination
by authors, and lapses in ethics and peer review, and we conclude with thoughts
about the future of mathematical publishing.


  Motivated by a problem arising from pharmaceutical science [B. Baeumer et
al., Discr. Contin. Dyn. Sys. B 12], we study random walks on the contact graph
of a bidisperse random sphere packing. For a random walk on the unweighted
graph that terminates in a specified target set, we compare the number of steps
and the total euclidean length of the walk. We find a linear relationship
between the two metrics with a proportionality constant that can be calculated
from the edge length probabilities of the contact graph.


  Sharpness-Aware Minimization (SAM) is a recent optimization framework aiming
to improve the deep neural network generalization, through obtaining flatter
(i.e. less sharp) solutions. As SAM has been numerically successful, recent
papers have studied the theoretical aspects of the framework and have shown SAM
solutions are indeed flat. However, there has been limited theoretical
exploration regarding statistical properties of SAM. In this work, we directly
study the statistical performance of SAM, and present a new theoretical
explanation of why SAM generalizes well. To this end, we study two statistical
problems, neural networks with a hidden layer and kernel regression, and prove
under certain conditions, SAM has smaller prediction error over Gradient
Descent (GD). Our results concern both convex and non-convex settings, and show
that SAM is particularly well-suited for non-convex problems. Additionally, we
prove that in our setup, SAM solutions are less sharp as well, showing our
results are in agreement with the previous work. Our theoretical findings are
validated using numerical experiments on numerous scenarios, including deep
neural networks.


  In this work we show that the critical exponents of the order parameter
(CEOPs) of diffuse ferroelectric phase transitions (DFEPTs) occurring in lead
germanate-based crystals can be determined using experimental temperature
dependences of their optical rotation. We also describe the approach that
suggests dividing a crystal sample into many homogeneous unit cells, each of
which is characterized by a non-diffuse phase transition with a specific local
Curie temperature. Using this approach, the CEOPs have been determined for the
pure Pb$_{5}$Ge$_{3}$O$_{11}$ crystals, the solid solutions
Pb$_{5}$(Ge$_{1-x}$Si$_{x}$)$_{3}$O$_{11}$ ($x = $0.03, 0.05, 0.10, 0.20, 0.40)
and (Pb$_{1-x}$Ba$_{x}$)$_{5}$Ge$_{3}$O$_{11}$ ($x =$ 0.02, 0.05), and the
doped crystals Pb$_{5}$Ge$_{3}$O$_{11}$:Li$^{3+}$ (0.005 wt. %),
Pb$_{5}$Ge$_{3}$O$_{11}$:La$^{3+}$ (0.02 wt. %),
Pb$_{5}$Ge$_{3}$O$_{11}$:Eu$^{3+}$ (0.021 wt. %),
Pb$_{5}$Ge$_{3}$O$_{11}$:Li$^{3+}$, Bi$^{3+}$ (0.152 wt.~\%) and
Pb$_{5}$Ge$_{3}$O$_{11}$:Cu$^{2+}$ (0.14 wt. %). Comparison of our approach
with the other techniques used for determining the Curie temperatures and the
CEOPs of DFEPTs testifies to its essential advantages.


  We show sharp bounds for probabilities of large deviations for sums of
independent random variables satisfying Bernstein's condition. One such bound
is very close to the tail of the standard Gaussian law in certain case; other
bounds improve the inequalities of Bennett and Hoeffding by adding missing
factors in the spirit of Talagrand (1995). We also complete Talagrand's
inequality by giving a lower bound of the same form, leading to an equality. As
a consequence, we obtain large deviation expansions similar to those of
Cram\'{e}r (1938), Bahadur-Rao (1960) and Sakhanenko (1991). We also show that
our bound can be used to improve a recent inequality of Pinelis (2014).


  We present and discuss an asynchronous coordinate system covering de Sitter
spacetime, notably in a complete way in 1+1 dimensions. The new coordinates
have several interesting cosmological properties: the worldlines of comoving
($x^i=const$) observers are geodesics, cosmic time is finite in the past, and
the coordinates asymptotically tend to that of a flat Robertson & Walker model
at large times. This analysis also provides an argument in favor of the natural
emergence of an equation of state of the type $p=-\rho$ in the context of the
standard cosmological model.


  This note studies local integral gradient bounds for distributional solutions
of a large class of partial differential inequalities with diffusion in
divergence form and power-like first-order terms. The applications of these
estimates are two-fold. First, we show the (sharp) global H\"older regularity
of distributional semi-solutions to this class of diffusive PDEs with
first-order terms having supernatural growth and right-hand side in a suitable
Morrey class posed on a bounded and regular open set $\Omega$. Second, we
provide a new proof of entire Liouville properties for inequalities with
superlinear first-order terms without assuming any one-side bound on the
solution for the corresponding homogeneous partial differential inequalities.
We also discuss some extensions of the previous properties to problems arising
in sub-Riemannian geometry and also to partial differential inequalities posed
on noncompact complete Riemannian manifolds under appropriate area-growth
conditions of the geodesic spheres, providing new results in both these
directions. The methods rely on integral arguments and do not exploit maximum
and comparison principles.


  Although machine learning models typically experience a drop in performance
on out-of-distribution data, accuracies on in- versus out-of-distribution data
are widely observed to follow a single linear trend when evaluated across a
testbed of models. Models that are more accurate on the out-of-distribution
data relative to this baseline exhibit "effective robustness" and are
exceedingly rare. Identifying such models, and understanding their properties,
is key to improving out-of-distribution performance. We conduct a thorough
empirical investigation of effective robustness during fine-tuning and
surprisingly find that models pre-trained on larger datasets exhibit effective
robustness during training that vanishes at convergence. We study how
properties of the data influence effective robustness, and we show that it
increases with the larger size, more diversity, and higher example difficulty
of the dataset. We also find that models that display effective robustness are
able to correctly classify 10% of the examples that no other current testbed
model gets correct. Finally, we discuss several strategies for scaling
effective robustness to the high-accuracy regime to improve the
out-of-distribution accuracy of state-of-the-art models.


  This paper investigated the distributed leader follower formation control
problem for multiple differentially driven mobile robots. A distributed
estimator is first introduced and it only requires the state information from
each follower itself and its neighbors. Then, we propose a bioinspired neural
dynamic based backstepping and sliding mode control hybrid formation control
method with proof of its stability. The proposed control strategy resolves the
impractical speed jump issue that exists in the conventional backstepping
design. Additionally, considering the system and measurement noises, the
proposed control strategy not only removes the chattering issue existing in the
conventional sliding mode control but also provides smooth control input with
extra robustness. After that, an adaptive sliding innovation filter is
integrated with the proposed control to provide accurate state estimates that
are robust to modeling uncertainties. Finally, we performed multiple
simulations to demonstrate the efficiency and effectiveness of the proposed
formation control strategy.


  Efficient deep learning-based approaches have achieved remarkable performance
in single image super-resolution. However, recent studies on efficient
super-resolution have mainly focused on reducing the number of parameters and
floating-point operations through various network designs. Although these
methods can decrease the number of parameters and floating-point operations,
they may not necessarily reduce actual running time. To address this issue, we
propose a novel multi-stage lightweight network boosting method, which can
enable lightweight networks to achieve outstanding performance. Specifically,
we leverage enhanced high-resolution output as additional supervision to
improve the learning ability of lightweight student networks. Upon convergence
of the student network, we further simplify our network structure to a more
lightweight level using reparameterization techniques and iterative network
pruning. Meanwhile, we adopt an effective lightweight network training strategy
that combines multi-anchor distillation and progressive learning, enabling the
lightweight network to achieve outstanding performance. Ultimately, our
proposed method achieves the fastest inference time among all participants in
the NTIRE 2023 efficient super-resolution challenge while maintaining
competitive super-resolution performance. Additionally, extensive experiments
are conducted to demonstrate the effectiveness of the proposed components. The
results show that our approach achieves comparable performance in
representative dataset DIV2K, both qualitatively and quantitatively, with
faster inference and fewer number of network parameters.


  Phase-field-based models have become common in material science, mechanics,
physics, biology, chemistry, and engineering for the simulation of
microstructure evolution. Yet, they suffer from the drawback of being
computationally very costly when applied to large, complex systems. To reduce
such computational costs, a Unet-based artificial neural network is developed
as a surrogate model in the current work. Training input for this network is
obtained from the results of the numerical solution of initial-boundary-value
problems (IBVPs) based on the Fan-Chen model for grain microstructure
evolution. In particular, about 250 different simulations with varying initial
order parameters are carried out and 200 frames of the time evolution of the
phase fields are stored for each simulation. The network is trained with 90% of
this data, taking the $i$-th frame of a simulation, i.e. order parameter field,
as input, and producing the $(i+1)$-th frame as the output. Evaluation of the
network is carried out with a test dataset consisting of 2200 microstructures
based on different configurations than originally used for training. The
trained network is applied recursively on initial order parameters to calculate
the time evolution of the phase fields. The results are compared to the ones
obtained from the conventional numerical solution in terms of the errors in
order parameters and the system's free energy. The resulting order parameter
error averaged over all points and all simulation cases is 0.005 and the
relative error in the total free energy in all simulation boxes does not exceed
1%.


  The promise of gyrochronology is that given a star's rotation period and
mass, its age can be inferred. The reality of gyrochronology is complicated by
effects other than ordinary magnetized braking that alter stellar rotation
periods. In this work, we present an interpolation-based gyrochronology
framework that reproduces the time- and mass-dependent spin-down rates implied
by the latest open cluster data, while also matching the rate at which the
dispersion in initial stellar rotation periods decreases as stars age. We
validate our technique for stars with temperatures of 3800-6200 K and ages of
0.08-2.6 gigayears (Gyr), and use it to reexamine the empirical limits of
gyrochronology. In line with previous work, we find that the uncertainty floor
varies strongly with both stellar mass and age. For Sun-like stars (5800 K),
the statistical age uncertainties improve monotonically from $\pm$38% at 0.2
Gyr to $\pm12$% at 2 Gyr, and are caused by the empirical scatter of the
cluster rotation sequences combined with the rate of stellar spin-down. For
low-mass K-dwarfs (4200 K), the posteriors are highly asymmetric due to stalled
spin-down, and $\pm$1$\sigma$ age uncertainties vary non-monotonically between
10% and 50% over the first few gigayears. High-mass K-dwarfs (5000 K) older
than 1.5 Gyr yield the most precise ages, with limiting uncertainties currently
set by possible changes in the spin-down rate (12% systematic), the calibration
of the absolute age scale (8% systematic), and the width of the slow sequence
(4% statistical). An open-source implementation, called gyro-interp, is
available online at https://github.com/lgbouma/gyro-interp


  In this paper, we provide a theoretical framework to analyze an agent who
misinterprets or misperceives the true decision problem she faces. We show that
a wide range of behavior observed in experimental settings manifest as failures
to perceive implications, in other words, to properly account for the logical
relationships between various payoff relevant contingencies. We present a
behavioral definition of perceived implication, thereby providing an
elicitation technique, and show that an agent's account of implication
identifies a subjective state-space that underlies her behavior. By analyzing
this state-space, we characterize distinct benchmarks of logical sophistication
that drive empirical phenomena. We disentangle static and dynamic rationality.
Thus, our framework delivers both a methodology for assessing an agent's level
of contingent thinking and a strategy for identifying her beliefs in the
absence full rationality.


  Topological phases in electronic structures contain a new type of topology,
called fragile, which can arise, for example, when an Elementary Band
Representation (Atomic Limit Band) splits into a particular set of bands. We
obtain, for the first time, a complete classification of the fragile
topological phases which can be diagnosed by symmetry eigenvalues, to find an
incredibly rich structure which far surpasses that of stable/strong topological
states. We find and enumerate all hundreds of thousands of different fragile
topological phases diagnosed by symmetry eigenvalues (available at
http://www.cryst.ehu.es/html/doc/FragileRoots.pdf), and link the mathematical
structure of these phases to that of Affine Monoids in mathematics.
Furthermore, we predict and calculate, for the first time, (hundred of
realistic) materials where fragile topological bands appear, and show-case the
very best ones.


  We present a methodology based on point-like Lambertian sources that enables
one to perform a reliable and comprehensive estimate of the overall thermally
induced acceleration of the Pioneer 10 and 11 spacecraft. We show, by
developing a sensitivity analysis of the several parameters of the model, that
one may achieve a valuable insight on the possible thermal origin of the
so-called Pioneer anomaly.


  We study the impact of bound state formation on dark matter annihilation
rates in models where dark matter interacts via a light mediator, the dark
photon. We derive the general cross section for radiative capture into all
possible bound states, and point out its non-trivial dependence on the dark
matter velocity and the dark photon mass. For indirect detection, our result
shows that dark matter annihilation inside bound states can play an important
role in enhancing signal rates over the rate for direct dark matter
annihilation with Sommerfeld enhancement. The effects are strongest for large
dark gauge coupling and when the dark photon mass is smaller than the typical
momentum of dark matter in the galaxy. As an example, we show that for thermal
dark matter the Fermi gamma ray constraint is substantially increased once
bound state effects are taken into account. We also find that bound state
effects are not important for dark matter annihilation during the freeze out
and recombination epochs.


  We find sufficient conditions for commutative non-autonomous systems on
certain metric spaces to be topologically stable. In particular, we prove that
(i) Every mean equicontinuous, mean expansive system with strong average
shadowing property is topologically stable. (ii) Every equicontinuous,
recurrently expansive system with almost shadowing property is topologically
stable. (iii) Every equicontinuous, expansive system with shadowing property is
topologically stable.


  We propose an unsupervised machine-learning checkpoint-restart (CR) lossy
algorithm for particle-in-cell (PIC) algorithms using Gaussian mixtures (GM).
The algorithm features a particle compression stage and a particle
reconstruction stage, where a continuum particle distribution function is
constructed and resampled, respectively. To guarantee fidelity of the CR
process, we ensure the exact preservation of charge, momentum, and energy for
both compression and reconstruction stages, everywhere on the mesh. We also
ensure the preservation of Gauss' law after particle reconstruction. As a
result, the GM CR algorithm is shown to provide a clean, conservative restart
capability while potentially affording orders of magnitude savings in
input/output requirements. We demonstrate the algorithm using a recently
developed exactly energy- and charge-conserving PIC algorithm on physical
problems of interest, with compression factors $\gtrsim75$ with no appreciable
impact on the quality of the restarted dynamics.


  Podcasts are traditionally shared through RSS feeds. As well as pointing to
the audio files, RSS gives a creator a way of providing metadata about the
podcast shows and episodes. We investigate how certain metadata fields
associated with podcasts are currently being used and comment on their
applicability to recommendations. Specifically, we find that many creators are
not using the itunes:type field in the expected fashion, and that using this
field for recommendations might not lead to an optimal user experience. We
perform similar explorations for the season number and the category associated
with a podcast, and also find that the fields aren't being used in the expected
fashion. Finally, we examine the notion that a single podcast show is the same
as a single RSS feed. This also turns out to not be strictly true in all cases.
In short, the metadata associated with many podcasts isn't always reflective of
the show and should be used with caution.


  We present a self-contained review of the Plane-wave/super-Yang-Mills
duality, which states that strings on a plane-wave background are dual to a
particular large R-charge sector of N=4, D=4 superconformal U(N) gauge theory.
This duality is a specification of the usual AdS/CFT correspondence in the
"Penrose limit''. The Penrose limit of AdS_5 S^5 leads to the maximally
supersymmetric ten dimensional plane-wave (henceforth "the'' plane-wave) and
corresponds to restricting to the large R-charge sector, the BMN sector, of the
dual superconformal field theory. After assembling the necessary background
knowledge, we state the duality and review some of its supporting evidence. We
review the suggestion by 't Hooft that Yang-Mills theories with gauge groups of
large rank might be dual to string theories and the realization of this
conjecture in the form of the AdS/CFT duality. We discuss plane-waves as exact
solutions of supergravity and their appearance as Penrose limits of other
backgrounds, then present an overview of string theory on the plane-wave
background, discussing the symmetries and spectrum. We then make precise the
statement of the proposed duality, classify the BMN operators, and mention some
extensions of the proposal. We move on to study the gauge theory side of the
duality, studying both quantum and non-planar corrections to correlation
functions of BMN operators, and their operator product expansion. The important
issue of operator mixing and the resultant need for re-diagonalization is
stressed. Finally, we study strings on the plane-wave via light-cone string
field theory, and demonstrate agreement on the one-loop correction to the
string mass spectrum and the corresponding quantity in the gauge theory. A new
presentation of the relevant superalgebra is given.


  We aim to create the highest possible quality of treatment-control matches
for categorical data in the potential outcomes framework. Matching methods are
heavily used in the social sciences due to their interpretability, but most
matching methods do not pass basic sanity checks: they fail when irrelevant
variables are introduced, and tend to be either computationally slow or produce
low-quality matches. The method proposed in this work aims to match units on a
weighted Hamming distance, taking into account the relative importance of the
covariates; the algorithm aims to match units on as many relevant variables as
possible. To do this, the algorithm creates a hierarchy of covariate
combinations on which to match (similar to downward closure), in the process
solving an optimization problem for each unit in order to construct the optimal
matches. The algorithm uses a single dynamic program to solve all of the
optimization problems simultaneously. Notable advantages of our method over
existing matching procedures are its high-quality matches, versatility in
handling different data distributions that may have irrelevant variables, and
ability to handle missing data by matching on as many available covariates as
possible.


  Let $M$ be a finite von Neumann algebra with the Haagerup property, and let
$G$ be a compact group that acts continuously on $M$ and that preserves some
finite trace $\tau$. We prove that if $\Gamma$ is a countable subgroup of $G$
which has the Haagerup property, then the crossed product algebra
$M\rtimes\Gamma$ has also the Haagerup property. In particular, we study some
ergodic, non-weakly mixing actions of groups with the Haagerup property on
finite, injective von Neumann algebras, and we prove that the associated
crossed products von Neumann algebras are $\textrm{II}_1$-factors with the
Haagerup property. If moreover the actions have Property $(\tau)$, then the
latter factors are full.


  We analyse a nonlinear Schr\"odinger equation for the time-evolution of the
wave function of an electron beam, interacting selfconsistently through a
Hartree-Fock nonlinearity and through the repulsive Coulomb interaction of an
atomic nucleus. The electrons are supposed to move under the action of a time
dependent, rapidly periodically oscillating electromagnetic potential. This can
be considered a simplified effective single particle model for an X-ray Free
Electron Laser (XFEL). We prove the existence and uniqueness for the Cauchy
problem and the convergence of wave-functions to corresponding solutions of a
Schr\"odinger equation with a time-averaged Coulomb potential in the high
frequency limit for the oscillations of the electromagnetic potential.


  We analyse a recent generalised free-energy for liquid crystals posited by
Virga and falling in the class of quartic functionals in the spatial gradients
of the nematic director. We review some known interesting solutions, i. e.,
uniform heliconical structures, and we find new liquid crystal configurations,
which closely resemble some novel, experimentally detected, structures called
Skyrmion tubes. These new configurations are characterised by a localised
pattern given by the variation of the conical angle. We study the equilibrium
differential equations and find numerical solutions and analytical
approximations.


  We establish a lower bound for the real eigenvalues of a Laplace-Beltrami
operator with an $L^\infty$-drift term. We make no assumptions that the
operator is self-adjoint or that the drift has any additional regularity. In
the case where the operator is self-adjoint, this establishes a lower bound on
the spectrum without assuming a lower bound for the Bakry-Emery Ricci tensor.
Put colloquially, this result states that no matter which way the wind blows,
heat will diffuse at a definite rate depending only on the geometry of the
underlying space and the maximal wind speed.


  Accurate disease identification and its severity estimation is an important
consideration for disease management. Deep learning-based solutions for disease
management using imagery datasets are being increasingly explored by the
research community. However, most reported studies have relied on imagery
datasets that were acquired under controlled lab conditions. As a result, such
models lacked the ability to identify diseases in the field. Therefore, to
train a robust deep learning model for field use, an imagery dataset was
created using raw images acquired under field conditions using a handheld
sensor and augmented images with varying backgrounds. The Corn Disease and
Severity (CD&S) dataset consisted of 511, 524, and 562, field acquired raw
images, corresponding to three common foliar corn diseases, namely Northern
Leaf Blight (NLB), Gray Leaf Spot (GLS), and Northern Leaf Spot (NLS),
respectively. For training disease identification models, half of the imagery
data for each disease was annotated using bounding boxes and also used to
generate 2343 additional images through augmentation using three different
backgrounds. For severity estimation, an additional 515 raw images for NLS were
acquired and categorized into severity classes ranging from 1 (resistant) to 5
(susceptible). Overall, the CD&S dataset consisted of 4455 total images
comprising of 2112 field images and 2343 augmented images.


  In this paper, we study analytic self-maps of the unit disk which distort
hyperbolic area of large hyperbolic disks by a bounded amount. We give a number
of characterizations involving angular derivatives, Lipschitz extensions,
M\"obius distortion, the distribution of critical points and Aleksandrov-Clark
measures. We also study Lyapunov exponents of their Aleksandrov-Clark measures.


  In previous work, we introduced the notion of functional strategies:
first-class generic functions that can traverse terms of any type while mixing
uniform and type-specific behaviour. Functional strategies transpose the notion
of term rewriting strategies (with coverage of traversal) to the functional
programming paradigm. Meanwhile, a number of Haskell-based models and
combinator suites were proposed to support generic programming with functional
strategies.
  In the present paper, we provide a compact and matured reconstruction of
functional strategies. We capture strategic polymorphism by just two primitive
combinators. This is done without commitment to a specific functional language.
We analyse the design space for implementational models of functional
strategies. For completeness, we also provide an operational reference model
for implementing functional strategies (in Haskell). We demonstrate the
generality of our approach by reconstructing representative fragments of the
Strafunski library for functional strategies.


  The X-ray pulsar SAX J0635+0533 was repeatedly observed with the XMM-Newton
satellite in 2003-2004. The precise localization provided by these observations
confirms the association of SAX J0635+0533 with a Be star. The source was
found, for the first time, in a low intensity state, a factor ~30 lower than
that seen in all previous observations. The spectrum, well fitted by an
absorbed power law with photon index ~1.7 and N_H = 1.2x10^22 cm^-2, was
compatible with that of the high state. The low flux did not allow the
detection of the pulsations at 33.8 ms seen BeppoSAX and RXTE data. In view of
the small luminosity observed in 2003-2004, we reconsider the peculiarities of
this source in both the accretion and rotation powered scenarios.


  Handwritten mathematical expression recognition (HMER) is challenging in
image-to-text tasks due to the complex layouts of mathematical expressions and
suffers from problems including over-parsing and under-parsing. To solve these,
previous HMER methods improve the attention mechanism by utilizing historical
alignment information. However, this approach has limitations in addressing
under-parsing since it cannot correct the erroneous attention on image areas
that should be parsed at subsequent decoding steps. This faulty attention
causes the attention module to incorporate future context into the current
decoding step, thereby confusing the alignment process. To address this issue,
we propose an attention guidance mechanism to explicitly suppress attention
weights in irrelevant areas and enhance the appropriate ones, thereby
inhibiting access to information outside the intended context. Depending on the
type of attention guidance, we devise two complementary approaches to refine
attention weights: self-guidance that coordinates attention of multiple heads
and neighbor-guidance that integrates attention from adjacent time steps.
Experiments show that our method outperforms existing state-of-the-art methods,
achieving expression recognition rates of 60.75% / 61.81% / 63.30% on the
CROHME 2014/ 2016/ 2019 datasets.


  In this paper, we produce a cellular motivic spectrum of motivic modular
forms over $\R$ and $\C$, answering positively to a conjecture of Dan Isaksen.
This spectrum is constructed to have the appropriate cohomology, as a module
over the relevant motivic Steenrod algebra. We first produce a $\G$-equivariant
version of this spectrum, and then use a machinery to construct a motivic
spectrum from an equivariant one. We believe that this machinery will be of
independent interest.


  The abstract notion of a Universal Turing machine cannot exist as a physical
subsystem without the introduction of noise from an external energy source.
Like all other physical systems, physical Turing machines must convert energy
sourced from an external environment into useful work, thus subjecting them to
the laws of thermodynamics. Consequently, asymptotic mathematical theorems
including those derived by Godel and Turing do not bear any consequence on
physical world because they can never be truly realised in physical systems.
Rather these theorems highlight the seemingly unbridgeable chasm between
Platonic forms (mathematics) and objects (physics).


  Background: Adaptation technique is a crucial task for analogy based
estimation. Current adaptation techniques often use linear size or linear
similarity adjustment mechanisms which are often not suitable for datasets that
have complex structure with many categorical attributes. Furthermore, the use
of nonlinear adaptation technique such as neural network and genetic algorithms
needs many user interactions and parameters optimization for configuring them
(such as network model, number of neurons, activation functions, training
functions, mutation, selection, crossover, ... etc.). Aims: In response to the
abovementioned challenges, the present paper proposes a new adaptation strategy
using Model Tree based attribute distance to adjust estimation by analogy and
derive new estimates. Using Model Tree has an advantage to deal with
categorical attributes, minimize user interaction and improve efficiency of
model learning through classification. Method: Seven well known datasets have
been used with 3-Fold cross validation to empirically validate the proposed
approach. The proposed method has been investigated using various K analogies
from 1 to 3. Results: Experimental results showed that the proposed approach
produced better results when compared with those obtained by using estimation
by analogy based linear size adaptation, linear similarity adaptation,
'regression towards the mean' and null adaptation. Conclusions: Model Tree
could form a useful extension for estimation by analogy especially for complex
data sets with large number of categorical attributes.


  We find upper bounds on the essential dimension of the moduli stack of
parabolic vector bundles over a curve. When there is no parabolic structure, we
improve the known upper bound on the essential dimension of the usual moduli
stack. Our calculations also give lower bounds on the essential dimension of
the semistable locus inside the moduli stack of vector bundles of rank $r$ and
degree $d$ without parabolic structure.


  We classify all groups of order $p^5$ with non-trivial unramified Brauer
groups. We show that if $p>3$, then there are precisely $\gcd (p-1,4)+\gcd
(p-1,3)+1$ such groups.


  The sensitivity of the Advanced LIGO detectors to gravitational waves can be
affected by environmental disturbances external to the detectors themselves.
Since the transition from the former initial LIGO phase, many improvements have
been made to the equipment and techniques used to investigate these
environmental effects. These methods have aided in tracking down and mitigating
noise sources throughout the first three observing runs of the advanced
detector era, keeping the ambient contribution of environmental noise below the
background noise levels of the detectors. In this paper we describe the methods
used and how they have led to the mitigation of noise sources, the role that
environmental monitoring has played in the validation of gravitational wave
events, and plans for future observing runs.


  We report precision ground-based broadband optical intensity and
linear-polarisation light-curves for the sky's brightest WN8 star, WR40. WN8
stars are notorious for their high level of variability, stemming from
stochastic clumps in their strong winds that are slower and less hot than the
winds of most other Wolf-Rayet (WR) stars. We confirm previous results that
many WR stars display an amplitude of variability that is an order-of-magnitude
higher in photometry than in polarimetry. For the first time, the unique nature
of near simultaneity of our photometric and polarimetric observations of WR40
allows us to check whether the two types of variability show correlated
behaviour, of which we find none. Assuming simple temporal functions for the
brightness and polarisation of individual clumps, a model for simulated light
curves is found to reproduce the properties of the observations, specifically
the absence of correlation between photometric and polarimetric variations, the
ratio of standard deviations for photometric and polarimetric variability, and
the ratio of the average intrinsic polarisation relative to its standard
deviation. Mapping the solution for time variability to a spatial coordinate
suggests that the wind clumps of WR40 are free-free emitting in addition to
light scattering.


  The objective behind the Twin Sort technique is to sort the list of unordered
data elements efficiently and to allow efficient and simple arrangement of data
elements within the data structure with optimization of comparisons and
iterations in the sorting method. This sorting technique effectively terminates
the iterations when there is no need of comparison if the elements are all
sorted in between the iterations. Unlike Quick sort, Merge sorting technique,
this new sorting technique is based on the iterative method of sorting elements
within the data structure. So it will be advantageous for optimization of
iterations when there is no need for sorting elements. Finally, the Twin Sort
technique is more efficient and simple method of arranging elements within a
data structure and it is easy to implement when comparing to the other sorting
technique. By the introduction of optimization of comparison and iterations, it
will never allow the arranging task on the ordered elements.


  We propose a left-right model of quarks and leptons based on the gauge group
$SU(3)_C \times SU(2)_L \times SU(2)_R \times U(1)_{B-L}$, where the scalar
sector consists of only two doublets: (1,2,1,1) and (1,1,2,1). As a result, any
fermion mass, whether it be Majorana or Dirac, must come from dimension-five
operators. This allows us to have a common view of quark and lepton masses,
including the smallness of Majorana neutrino masses as the consequence of a
double seesaw mechanism.


  It is shown that the CKMT model for the nucleon structure function F2, taken
as the initial condition for the NLO evolution equations in perturbative QCD,
provides a good description of the HERA data when presented in the form of the
logarithmic slopes of F2 vs x and Q2 (Caldwell-plot), in the whole available
kinematic ranges. Also the results obtained for the behavior of the gluon
component of a nucleon are presented.


  This paper aims to provide an overview of the ethical concerns in artificial
intelligence (AI) and the framework that is needed to mitigate those risks, and
to suggest a practical path to ensure the development and use of AI at the
United Nations (UN) aligns with our ethical values. The overview discusses how
AI is an increasingly powerful tool with potential for good, albeit one with a
high risk of negative side-effects that go against fundamental human rights and
UN values. It explains the need for ethical principles for AI aligned with
principles for data governance, as data and AI are tightly interwoven. It
explores different ethical frameworks that exist and tools such as assessment
lists. It recommends that the UN develop a framework consisting of ethical
principles, architectural standards, assessment methods, tools and
methodologies, and a policy to govern the implementation and adherence to this
framework, accompanied by an education program for staff.


  In this paper, we provide necessary and sufficient conditions under which two
sequence variable Lebesgue spaces $\ell_{p_n}$ and $\ell_{q_n}$ are equivalent
and also describe conditions under which the natural embeddings $id:\ell_{p_n}
\to \ell_{q_n}$ are strictly or finitely strictly singular.
  We also provide estimates for the Bernstein numbers of the natural embedding
$id$ and show how they depend on the exponents $p_n$ and $q_n$.


  We consider a coupling of conformal gravity to the classically
scale-invariant B-L extended standard model which has been recently proposed as
a phenomenologically viable model realizing the Coleman-Weinberg mechanism of
breakdown of the electro-weak symmetry. As in a globally scale-invariant
dilaton gravity, it is also shown in a locally scale-invariant conformal
gravity that without recourse to the Coleman-Weinberg mechanism, the B-L gauge
symmetry is broken in the process of spontaneous symmetry breakdown of the
local scale invariance (Weyl invariance) at the tree level and as a result the
B-L gauge field becomes massive via the Higgs mechanism. As a bonus of
conformal gravity, the massless dilaton field does not appear and the
parameters in front of the non-minimal coupling of gravity are completely fixed
in the present model. This observation clearly shows that the conformal gravity
has a practical application even if the scalar field does not possess any
dynamical degree of freedom owing to the local scale symmetry.


  The horizon-scale images of black holes obtained with the Event Horizon
Telescope have provided new probes of their metrics and tests of General
Relativity. The images are characterized by a bright, near circular ring from
the gravitationally lensed emission from the hot plasma and a deep central
depression cast by the black hole. The metric tests rely on fact that the
bright ring closely traces the boundary of the black hole shadow with a small
displacement that has been quantified using simulations. In this paper we
develop a self-consistent covariant analytic model of the accretion flow that
spans a broad range of plasma conditions and black-hole properties to explore
the general validity of this result. We show that, for any physical model of
the accretion flow, the ring always encompasses the outline of the shadow and
is not displaced by it by more than half the ring width. This result is a
consequence of conservation laws and basic thermodynamic considerations and
does not depend on the microphysics of the plasma or the details of the
numerical simulations. We also present a quantitative measurement of the bias
between the bright ring and the shadow radius based on the analytical models.


  Extensive use of unmanned aerial vehicles (UAVs) is expected to raise privacy
and security concerns among individuals and communities. In this context, the
detection and localization of UAVs will be critical for maintaining safe and
secure airspace in the future. In this work, Keysight N6854A radio frequency
(RF) sensors are used to detect and locate a UAV by passively monitoring the
signals emitted from the UAV. First, the Keysight sensor detects the UAV by
comparing the received RF signature with various other UAVs' RF signatures in
the Keysight database using an envelope detection algorithm. Afterward, time
difference of arrival (TDoA) based localization is performed by a central
controller using the sensor data, and the drone is localized with some error.
To mitigate the localization error, implementation of an extended Kalman
filter~(EKF) is proposed in this study. The performance of the proposed
approach is evaluated on a realistic experimental dataset. EKF requires basic
assumptions on the type of motion throughout the trajectory, i.e., the movement
of the object is assumed to fit some motion model~(MM) such as constant
velocity (CV), constant acceleration (CA), and constant turn (CT). In the
experiments, an arbitrary trajectory is followed, therefore it is not feasible
to fit the whole trajectory into a single MM. Consequently, the trajectory is
segmented into sub-parts and a different MM is assumed in each segment while
building the EKF model. Simulation results demonstrate an improvement in error
statistics when EKF is used if the MM assumption aligns with the real motion.


  Medical image segmentation of gadolinium enhancement magnetic resonance
imaging (GE MRI) is an important task in clinical applications. However, manual
annotation is time-consuming and requires specialized expertise.
Semi-supervised segmentation methods that leverage both labeled and unlabeled
data have shown promise, with contrastive learning emerging as a particularly
effective approach. In this paper, we propose a contrastive learning strategy
of foreground and background representations for semi-supervised 3D medical
image segmentation (FBA-Net). Specifically, we leverage the contrastive loss to
learn representations of both the foreground and background regions in the
images. By training the network to distinguish between foreground-background
pairs, we aim to learn a representation that can effectively capture the
anatomical structures of interest. Experiments on three medical segmentation
datasets demonstrate state-of-the-art performance. Notably, our method achieves
a Dice score of 91.31% with only 20% labeled data, which is remarkably close to
the 91.62% score of the fully supervised method that uses 100% labeled data on
the left atrium dataset. Our framework has the potential to advance the field
of semi-supervised 3D medical image segmentation and enable more efficient and
accurate analysis of medical images with a limited amount of annotated labels.


  This article deals with transport properties of one dimensional Brownian
diffusion under the influence of a correlated quenched random force,
distributed as a two-level Poisson process. We find in particular that large
time scaling laws of the position of the Brownian particle are analogous to the
uncorrelated case. We discuss also the probability distribution of the
stationary flux going through a sample between two prescribed concentrations,
which differs significantly from the uncorrelated case.


  A characteristic result is that if 2^{aleph_0}< mu < mu^+< lambda =
cf(lambda)< mu^{aleph_0}, then among the separable reduced p-groups of
cardinality lambda which are (< lambda)-stable there is no universal one.


  This is a survey of several approaches to the framework for working with
infinitesimals and infinite numbers, originally developed by Abraham Robinson
in the 1960s, and their constructive engagement with the Cantor-Dedekind
postulate and the Intended Interpretation hypothesis. We highlight some
applications including (1) Loeb's approach to the Lebesgue measure, (2) a
radically elementary approach to the vibrating string, (3) true infinitesimal
differential geometry. We explore the relation of Robinson's and related
frameworks to the multiverse view as developed by Hamkins. Keywords:
axiomatisations, infinitesimal, nonstandard analysis, ultraproducts,
superstructure, set-theoretic foundations, multiverse, naive integers,
intuitionism, soritical properties, ideal elements, protozoa.


  We develop a first order formalism for constructing gravitational duals of
conformal defects in a bottom up approach. Similarly as for the flat domain
walls a single function specifies the solution completely. Using this formalism
we construct several novel families of analytic solutions dual to conformal
interfaces and boundaries. As a sample application we study the boundary OPE
and entanglement entropy for one of the found defects.


  Floquet topological insulators describe independent electrons on a lattice
driven out of equilibrium by a time-periodic Hamiltonian, beyond the usual
adiabatic approximation. In dimension two such systems are characterized by
integer-valued topological indices associated to the unitary propagator,
alternatively in the bulk or at the edge of a sample. In this paper we give new
definitions of the two indices, relying neither on translation invariance nor
on averaging, and show that they are equal. In particular weak disorder and
defects are intrinsically taken into account. Finally indices can be defined
when two driven sample are placed next to one another either in space or in
time, and then shown to be equal. The edge index is interpreted as a quantized
pumping occurring at the interface with an effective vacuum.


  We present the dependences of the properties of type Ia Supernovae (SNe Ia)
on their host galaxies by analyzing the multi-band lightcurves of 118
spectroscopically confirmed SNe Ia observed by the Sloan Digital Sky Survey
(SDSS) Supernova Survey and the spectra of their host galaxies. We derive the
equivalent width of the \rm{H}$\alpha$ emission line, star formation rate, and
gas-phase metallicity from the spectra and compare these with the lightcurve
widths and colors of SNe Ia. In addition, we compare host properties with the
deviation of the observed distance modulus corrected for lightcurve parameters
from the distance modulus determined by the best fit cosmological parameters.
This allows us to investigate uncorrected systematic effects in the magnitude
standardization. We find that SNe Ia in host galaxies with a higher star
formation rate have synthesized on average a larger $^{56}$Ni mass and show
wider lightcurves. The $^{56}$Ni mass dependence on metallicity is consistent
with a prediction of Timmes et al. 2003 based on nucleosynthesis. SNe Ia in
metal-rich galaxies ({$\log_{10}(O/H)+12>8.9$) have become 0.13 $\pm$ 0.06
magnitude brighter after corrections for their lightcurve widths and colors,
which corresponds to up to 6% uncertainty in the luminosity distance. We
investigate whether parameters for standardizing SN Ia maximum magnitude differ
among samples with different host characteristics. The coefficient of the color
term is larger by 0.67 $\pm$ 0.19 for SNe Ia in metal-poor hosts than those in
metal-rich hosts when no color cuts are imposed.


  This paper is an extended version of an earlier submission to WoLLIC 2023. We
discuss two-layered logics formalising reasoning with probabilities and belief
functions that combine the Lukasiewicz $[0,1]$-valued logic with Baaz
$\triangle$ operator and the Belnap--Dunn logic. We consider two probabilistic
logics that present two perspectives on the probabilities in the Belnap--Dunn
logic: $\pm$-probabilities and $\mathbf{4}$-probabilities. In the first case,
every event $\phi$ has independent positive and negative measures that denote
the likelihoods of $\phi$ and $\neg\phi$, respectively. In the second case, the
measures of the events are treated as partitions of the sample into four
exhaustive and mutually exclusive parts corresponding to pure belief, pure
disbelief, conflict and uncertainty of an agent in $\phi$. In addition to that,
we discuss two logics for the paraconsistent reasoning with belief and
plausibility functions. They equip events with two measures (positive and
negative) with their main difference being whether the negative measure of
$\phi$ is defined as the \emph{belief in $\neg\phi$} or treated independently
as \emph{the plausibility of $\neg\phi$}. We provide a sound and complete
Hilbert-style axiomatisation of the logic of $\mathbf{4}$-probabilities and
establish faithful translations between it and the logic of
$\pm$-probabilities. We also show that the satisfiability problem in all the
logics is $\mathsf{NP}$-complete.


  Cyberinsurance is a powerful tool to align market incentives toward improving
Internet security. We trace the evolution of cyberinsurance from traditional
insurance policies to early cyber-risk insurance policies to current
comprehensive cyberinsurance products. We find that increasing Internet
security risk in combination with the need for compliance with recent corporate
legislation has contributed significantly to the demand for cyberinsurance.
Cyberinsurance policies have become more comprehensive as insurers better
understand the risk landscape and specific business needs. More specifically,
cyberinsurers are addressing what used to be considered insurmountable problems
(e.g., adverse selection/asymmetric information, moral hazard, etc.) that could
lead to a failure of this market solution. Although some implementation issues
remain, we suggest the future development of cyberinsurance will resolve these
issues as evidenced by insurance solutions in other risk domains.


  Notes based on lessons given at {\sc Escuela " Fico Gonz\'alez Acu\~na" de
Nudos y 3-variedades}, M\'erida Yucat\'an, M\'exico, 7--10 (2015) and {\sc
Encuentro de nudos, trenzas y \'algebras}, Oaxaca--M\'exico, 3--10 October
(2018).


  In this paper we study the class of power ideals generated by the $k^n$ forms
$(x_0+\xi^{g_1}x_1+\ldots+\xi^{g_n}x_n)^{(k-1)d}$ where $\xi$ is a fixed
primitive $k^{th}$-root of unity and $0\leq g_j\leq k-1$ for all $j$. For
$k=2$, by using a $\mathbb{Z}_k^{n+1}$-grading on $\mathbb{C}[x_0,\ldots,x_n]$,
we compute the Hilbert series of the associated quotient rings via a simple
numerical algorithm. We also conjecture the extension for $k>2$. Via Macaulay
duality, those power ideals are related to schemes of fat points with support
on the $k^n$ points $[1:\xi^{g_1}:\ldots:\xi^{g_n}]$ in $\mathbb{P}^n$. We
compute Hilbert series, Betti numbers and Gr\"obner basis for such
$0$-dimensional schemes. This explicitly determines the Hilbert series of the
power ideal for all $k$: that this agrees with our conjecture for $k>2$ is
supported by several computer experiments.


  We introduce and study a computational version of the principal-agent problem
-- a classic problem in Economics that arises when a principal desires to
contract an agent to carry out some task, but has incomplete information about
the agent or their subsequent actions. The key challenge in this setting is for
the principal to design a contract for the agent such that the agent's
preferences are then aligned with those of the principal. We study this problem
using a variation of Boolean games, where multiple players each choose
valuations for Boolean variables under their control, seeking the satisfaction
of a personal goal, given as a Boolean logic formula. In our setting, the
principal can only observe some subset of these variables, and the principal
chooses a contract which rewards players on the basis of the assignments they
make for the variables that are observable to the principal. The principal's
challenge is to design a contract so that, firstly, the principal's goal is
achieved in some or all Nash equilibrium choices, and secondly, that the
principal is able to verify that their goal is satisfied. In this paper, we
formally define this problem and completely characterise the computational
complexity of the most relevant decision problems associated with it.


  We demonstrate by spin quantum beat spectroscopy that in undoped symmetric
(110)-oriented GaAs/AlGaAs single quantum wells even a symmetric spatial
envelope wavefunction gives rise to an asymmetric in-plane electron
Land\'e-g-factor. The anisotropy is neither a direct consequence of the
asymmetric in-plane Dresselhaus splitting nor of the asymmetric Zeeman
splitting of the hole bands but is a pure higher order effect that exists as
well for diamond type lattices. The measurements for various well widths are
very well described within 14 x 14 band k.p theory and illustrate that the
electron spin is an excellent meter variable to map out the internal -otherwise
hidden- symmetries in two dimensional systems. Fourth order perturbation theory
yields an analytical expression for the strength of the g-factor anisotropy,
providing a qualitative understanding of the observed effects.


  Objective: We aimed to determine the relationship between day-to-day sleep
efficiency variability and cognitive function among older adults using
accelerometer data and three cognitive tests.
  Methods: Older adults aged 65+ with 5 days of accelerometer data from the
National Health and Nutrition Examination Survey (NHANES) who completed the
Digit Symbol Substitution Test (DSST), the Consortium to Establish a Registry
for Alzheimers Disease Word-Learning subtest (CERAD WL), and Animal Fluency
Test (AFT) were included in this study. Associations between sleep efficiency
variability and each cognitive test were examined adjusted for age, sex,
education, household income, marital status, depressive symptoms, diabetes,
smoking habits, alcohol consumption, arthritis, heart disease, prior heart
attack, prior stroke, activities of daily living, and instrumental activities
of daily living.
  Results: A total of 1074 older adults were included in this study. Greater
sleep efficiency variability was univariably associated with worse cognitive
function based on the DSST (per 10% increase, Beta -3.34, 95% CI -5.33 to
-1.34), CERAD-WL (per 10% increase, Beta -1.00, 95% CI -1.79 to -0.21), and AFT
(per 10% increase, Beta -1.02, 95% CI -1.68 to -0.36). In adjusted models,
greater sleep efficiency variability remained associated with lower DSST (per
10% increase, Beta -2.01, 95% CI -3.62 to -0.40) and AFT (per 10% increase,
Beta -0.84, 95% CI -1.47 to -0.21) scores but not CERAD WL scores.
  Conclusions: Targeting consistency regarding sleep quality may be useful for
interventions seeking to preserve cognitive function among older adults.


  So-called "dirty" black holes are those surrounded by non-zero stress-energy,
rather than vacuum. The presence of the non-zero stress-energy modifies key
features of the black hole, such as the surface gravity, Regge-Wheeler
equation, linear stability, and greybody factors in a rather nontrivial way.
Working within the inverse-Cowling approximation, (effectively the test-field
limit), we shall present general forms for the Regge-Wheeler equation for
linearized spin 0, spin 1, and axial spin 2 perturbations on an arbitrary
static spherically symmetric background spacetime. Using very general features
of the background spacetime, (in particular the classical energy conditions for
the stress-energy surrounding the black hole), we extract several interesting
and robust bounds on the behaviour of such systems, including rigorous bounds
on the greybody factors for dirty black holes.


  We exhibit a way of "forcing a functional to be an effective operation" for
arbitrary partial combinatory algebras (pcas). This gives a method of defining
new pcas from old ones for some fixed functional, where the new partial
functions can be viewed as computable relative to that functional. It is shown
that this generalizes a notion of computation relative to a functional as
defined by Kleene for the natural numbers. The construction can be used to
study subtoposes of the Effective Topos. We will do this for a particular
functional that forces every arithmetical set to be decidable. In this paper we
also prove the convenient result that the two definitions of a pca that are
common in the literature are essentially the same.


  Eternal inflation predicts our observable universe lies within a bubble (or
pocket universe) embedded in a volume of inflating space. The interior of the
bubble undergoes inflation and standard cosmology, while the bubble walls
expand outward and collide with other neighboring bubbles. The collisions
provide either an opportunity to make a direct observation of the multiverse
or, if they produce unacceptable anisotropy, a threat to inflationary theory.
The probability of an observer in our bubble detecting the effects of
collisions has an absolute upper bound set by the odds of being in the part of
our bubble that lies in the forward light-cone of a collision; in the case of
collisions with bubbles of identical vacua, this bound given by the bubble
nucleation rate times ($H_{\rm{O}}/H_{\rm{I}})^2$, where $H_{\rm{O}}$ is the
Hubble scale outside the bubbles and $H_{\rm{I}}$ is the scale of the second
round of inflation that occurs inside our bubble. Similar results were obtained
by Freigovel \emph{et al.} using a different method for the case of collisions
with bubbles of much larger cosmological constant; here it is shown to hold in
the case of collisions with identical bubbles as well. A significant error in a
previous draft was corrected in order to arrive at this result.


  Open data can increase transparency and accountability of a country
government, leading to free information sharing and stimulation of new
innovations. This paper analyses government open data policy as well as open
data initiatives and trends in Russian Federation. The OCDE analytical
framework for national open government data portals and supporting initiatives
is used as the bases for the study. The key issues of Russian open government
data movement are summarized and aggregated. The paper argues the necessity of
systematic development of the open data ecosystem, the leading role of the
government in data release, a deeper business involvement, and a reduction of
bureaucratic barriers.


  This is a broad-brush review of how string theory addresses several important
questions of gravitational physics. The problem of non-renormalizability is
first reviewed, followed by introduction of string theory as an
ultraviolet-finite theory of gravity. String theory's successes also include
predicting both gauge theory and fermions. The difficulty of extra dimensions
becomes a possible virtue, when one notes that these lead to mechanisms to
explain fermion generations, as well as a means to break the large gauge
symmetries of string theory. Finally, a long standing problem of string theory,
that of fixing the size and shape of the extra dimensions, has recently been
addressed and may shed light on the origin of the cosmological constant, the
ultimate fate of our universe, as well as the question of why gravity_is_ so
weak.


  The Internet of Things has rapidly transformed the 21st century, enhancing
decision-making processes and introducing innovative consumer services such as
pay-as-you-use models. The integration of smart devices and automation
technologies has revolutionized every aspect of our lives, from health services
to the manufacturing industry, and from the agriculture sector to mining.
Alongside the positive aspects, it is also essential to recognize the
significant safety, security, and trust concerns in this technological
landscape. This chapter serves as a comprehensive guide for newcomers
interested in the IoT domain, providing a foundation for making future
contributions. Specifically, it discusses the overview, historical evolution,
key characteristics, advantages, architectures, taxonomy of technologies, and
existing applications in major IoT domains. In addressing prevalent issues and
challenges in designing and deploying IoT applications, the chapter examines
security threats across architectural layers, ethical considerations, user
privacy concerns, and trust-related issues. This discussion equips researchers
with a solid understanding of diverse IoT aspects, providing a comprehensive
understanding of IoT technology along with insights into the extensive
potential and impact of this transformative field.


  Here, we report an evolution of structural, magnetic and transport behavior
in doped SrRu$_{1-x}$Ga$_x$O$_3$ ($x$ $\le$ 0.2). The nonmagnetic dopant
Ga$^{3+}$ (3$d^{10}$) not only acts for magnetic site dilution in SrRuO$_3$ but
also it modifies the Ru charge state and electronic density. Our studies show
that Ga$^{3+}$ substitution does not affect the original
orthorhombic-\textit{Pbnm} structure of SrRuO$_3$ which is due to its matching
ionic radii with Ru$^{4+}$. However, Ga$^{3+}$ has a substantial effect on the
magnetic behavior of SrRuO$_3$ where it decreases both magnetic moment as well
as magnetic transition temperature $T_c$. Further, this dilution induces
Griffiths phase behavior across $T_c$ and cluster-glass behavior at low
temperature with higher concentration of doping. The magnetic critical exponent
$\beta$ increases with $x$ due to this site dilution effect. The Ga$^{3+}$
induces an insulating state in SrRuO$_3$ with $x$ $>$ 0.05. The charge
transport in paramagnetic as well as in insulating state of samples can be well
described with Mott's modified variable-range-hopping model. The metallic
charge transport just below $T_c$ in SrRuO$_3$ obeys Fermi liquid behavior
which, however breaks down at low temperature. We further find a correlation
between field dependent magnetoresistance and magnetization through power-law
behavior over the series.


  We proposed the modified version of quantum-mechanical theory of continuous
measurements for the case of classical open systems. In our approach the
influence of measurement on evolution of distribution function of an open
system is described by the Fokker-Planck equation of a special form. The
diffusion tensor of this equation is uniquely defined by a type of the measured
quantity. On the basis of the approach proposed the stationary states of the
linear dissipative systems, induced by measurements in them, are considered.
Also we demonstrate on the simple example, how in the conservative system,
consisting of noninteracting parts, measurement of the integral of motion
results in relaxation to the quasi-thermodynamic equilibrium between parts of
the system. The "temperature" of such state is determined by energy of the
system and by the mean value of measured integral of motion. PACS numbers:
03.65.Ta, 05.40.-a


  Very recently, first-principle technique of full-potential linearized
augmented plane-wave method, by using for exchange-correlation potential the
generalized gradient approximation (GGA), was employed for the study of the
lead chalcogenide semiconductors' alloys PbS$_{x}$Se$_{1-x}$,
PbS$_{x}$Te$_{1-x}$ and PbSe$_{x}$Te$_{1-x}$. These density functional
calculations led to the determination of structural, electronic and optical
properties, including the values of lattice constants and bulk moduli as a
function of composition. Here, we investigate the latter properties, but by
employing a thermodynamical model which has been suggested for the formation
and migration of defects in solids including several recent applications in
semiconductors. The following crucial difference emerges when comparing the
present results with those deduced by density functional calculations: Among
the alloys studied, GGA calculations identify that PbS$_{x}$Te$_{1-x}$ exhibits
the most evident non-linear variation of the bulk modulus versus the
composition, while according to the thermodynamical model such an evident
non-linear behavior -and maybe somewhat stronger- is also expected for
PbSe$_{x}$Te$_{1-x}$. A tentative origin of this diversity is discussed.


  The deformation theory of a Dirac structure is controlled by a differential
graded Lie algebra which depends on the choice of an auxiliary transversal
Dirac structure; if the transversal is not involutive, one obtains an
$L_\infty$ algebra instead. We develop a simplified method for describing this
$L_\infty$ algebra and use it to prove that the $L_\infty$ algebras
corresponding to different transversals are canonically $L_\infty$-isomorphic.
In some cases, this isomorphism provides a formality map, as we show in several
examples including (quasi)-Poisson geometry, Dirac structures on Lie groups,
and Lie bialgebras. Finally, we apply our result to a classical problem in the
deformation theory of complex manifolds: we provide explicit formulas for the
Kodaira-Spencer deformation complex of a fixed small deformation of a complex
manifold, in terms of the deformation complex of the original manifold.


  Solving large traveling salesman problem (TSP) in an efficient way is a
challenging area for the researchers of computer science. This paper presents a
modified version of the ant colony system (ACS) algorithm called Red-Black Ant
Colony System (RB-ACS) for the solutions of TSP which is the most prominent
member of the combinatorial optimization problem. RB-ACS uses the concept of
ant colony system together with the parallel search of genetic algorithm for
obtaining the optimal solutions quickly. In this paper, it is shown that the
proposed RB-ACS algorithm yields significantly better performance than the
existing best-known algorithms.


  We explore a natural extension of braid arrangements in the context of
determinantal arrangements. We show that these determinantal arrangements are
free divisors. Additionally, we prove that free determinantal arrangements
defined by the minors of $2\times n$ matrices satisfy nice combinatorial
properties.
  We also study the topology of the complements of these determinantal
arrangements, and prove that their higher homotopy groups are isomorphic to
those of $S^3$. Furthermore, we find that the complements of arrangements
satisfying those same combinatorial properties above have Poincar\'e
polynomials that factor nicely.


  We consider membranes interacting via short, intermediate and long stickers.
The effects of the intermediate stickers on the lateral phase separation of the
membranes are studied via mean-field approximation. The critical potential
depth of the stickers increases in the presence of the intermediate sticker.
The lateral phase separation of the membrane thus suppressed by the
intermediate stickers. Considering membranes interacting with short and long
stickers, the effect of confinement on the phase behavior of the membranes is
also investigated analytically.


  We construct explicit pseudorandom generators that fool $n$-variate
polynomials of degree at most $d$ over a finite field $\mathbb{F}_q$. The seed
length of our generators is $O(d \log n + \log q)$, over fields of size
exponential in $d$ and characteristic at least $d(d-1)+1$. Previous
constructions such as Bogdanov's (STOC 2005) and Derksen and Viola's (FOCS
2022) had either suboptimal seed length or required the field size to depend on
$n$.
  Our approach follows Bogdanov's paradigm while incorporating techniques from
Lecerf's factorization algorithm (J. Symb. Comput. 2007) and insights from the
construction of Derksen and Viola regarding the role of indecomposability of
polynomials.


  We introduce the notion of Hypergraph Weighted Model (HWM) that generically
associates a tensor network to a hypergraph and then computes a value by tensor
contractions directed by its hyperedges. A series r defined on a hypergraph
family is said to be recognizable if there exists a HWM that computes it. This
model generalizes the notion of rational series on strings and trees. We prove
some properties of the model and study at which conditions finite support
series are recognizable.


  Recent experimental breakthroughs, particularly for single-qubit and
two-qubit gates exceeding the error correction threshold, highlight silicon
spin qubits as leading candidates for fault-tolerant quantum computation. In
the existing architecture, intrinsic or synthetic spin-orbit coupling (SOC) is
critical in various aspects, including electrical control, addressability,
scalability, etc. However, the high-fidelity SWAP operation and quantum state
transfer (QST) between spin qubits, crucial for qubit-qubit connectivity,
require the switchable nature of SOC which is rarely considered. Here, we
propose a flexible architecture based on spin valves by electrically changing
its magnetization orientation within sub-nanoseconds to generate ultrafast
switchable SOC. Based on the switchable SOC architecture, both SWAP operation
of neighbor spin qubits and resonant QST between distant spins can be realized
with fidelity exceeding 99% while considering the realistic experimental
parameters. Benefiting from the compatible processes with the modern
semiconductor industry and experimental advances in spin valves and spin
qubits, our results pave the way for future construction of silicon-based
quantum chips.


  The vacuum fluctuations give rise to a number of phenomena; however, the the
Casimir Effect is arguably the most salient manifestation of the quantum
vacuum. In its most basic form it is realized through the interaction of a pair
of neutral parallel conducting plates. The presence of the plates modifies the
quantum vacuum, and this modifcation causes the plates to be pulled toward each
other. The Casimir Effect has also been explored in the context of higher
dimensional theories. The non-trivial boundary conditions imposed by
compactified periodic higher dimensions is know to alter the vacuum in a
quantifiable way, and is a possible solution to the issue of modulus
stabilization, namely - the stabilization of higher dimensions. Typical in
Casimir energy calculations are renormalization techniques which are used to
tame the infinite sums and integrals that arise. These calculations are usally
fairly involved, and explicit pedagogical material is sparse. The purpose of
this paper is to introduce Dimensional Regularization techniques specific to
Casimir energy calculations with an additional compactified spatial dimension.


  Motivated by the increasing interest in applications of graph geodesic
convexity in machine learning and data mining, we present a heuristic for
computing the geodesic convex hull of node sets in networks. It generates a set
of almost maximal outerplanar spanning subgraphs for the input graph, computes
the geodesic closure in each of these graphs, and regards a node as an element
of the convex hull if it belongs to the closed sets for at least a user
specified number of outerplanar graphs. Our heuristic algorithm runs in time
linear in the number of edges of the input graph, i.e., it is faster with one
order of magnitude than the standard algorithm computing the closure exactly.
Its performance is evaluated empirically by approximating convexity based
core-periphery decomposition of networks. Our experimental results with large
real-world networks show that for most networks, the proposed heuristic was
able to produce close approximations significantly faster than the standard
algorithm computing the exact convex hulls. For example, while our algorithm
calculated an approximate core-periphery decomposition in 5 hours or less for
networks with more than 20 million edges, the standard algorithm did not
terminate within 50 days.


  Parton distribution functions give the probability to find partons (quarks
and gluons) in a hadron as a function of the fraction x of the proton's
momentum carried by the parton. They are conventionally defined in terms of
matrix elements of certain operators. They are determined from experimental
results on short distance scattering of the partons. Integrals of these
functions weighted with x^n are calculable using lattice QCD. Some simple
models for their behavior have implications that could also be tested in
lattice QCD.


  Biodegradability is a key feature for the application of polymeric devices in
medicine. This study reports an experimental and theoretical study of the
degradation of poly(thioether-ester) (PTEe) nanoparticles in aqueous media. The
$\alpha$,$\omega$-diene diester derived from vegetable oil, 1,3-propylene
diundeca-10-polenoate (Pd10e) was used as monomer in the solvent-free synthesis
of Pd10e-based nanoparticles (A-PTEe nanoparticles) via thiol-ene miniemulsion
polymerization. The theoretical partition coefficients of A-PTEe and a PTEe
based on dianhydro-D-glucityl diundec-10-enoate (DGU) (B-PTEe nanoparticles)
were calculated using density functional theory (DFT), in order to compare
their degradation behavior. The results showed that A-PTEe is more hydrophilic
than B-PTEe, thus indicating the possible faster degradation of the former. The
experimental degradation studies showed that, in fact, A-PTEe nanoparticles are
faster degraded than B-PTEe, presenting substantial molecular weight decrease,
which confirms the theoretical results. The effects of degradation could be
observed in the chemical composition and thermal properties of the polymer.
Considering its applicability potential as a biomaterial due to its fast
degradation behavior, the cytotoxicity of A-PTEe nanoparticles and its
degradation products were evaluated. In vitro assays confirmed the
biocompatibility of A-PTEe nanoparticles and its degradation products when
exposed on fibroblasts and red blood cells. These results suggest A-PTEe
nanoparticles can be promising candidates as biobased nanocarriers for
biomedical applications.


  Given the fact that the relatively light Higgsino mass $\mu$ favored in
natural supersymmetry usually results in a sizable scattering cross section
between the neutralino dark matter and the nucleon, we study the impact of the
recently updated direct detection bounds from LUX experiment, including both
Spin Independent (SI) and Spin Dependent (SD) measurements, on the parameter
space of natural Next-to-Minimal Supersymmetric Standard Model (nNMSSM).
Different from the common impression that the SI bound is stronger than the SD
one, we find that the SD bound is complementary to the SI bound and in some
cases much more powerful than the latter in limiting the nNMSSM scenarios.
After considering the LUX results, nNMSSM is severely limited, e.g. for the
peculiar scenarios of the NMSSM where the next-to-lightest CP-even Higgs
corresponds to the $125 {\rm GeV}$ Higgs boson discovered at the LHC, the
samples obtained in our random scan are excluded by more than $85\%$. By
contrast, the monojet search at the LHC Run-I can not exclude any sample of
nNMSSM. We also investigate the current status of nNMSSM and conclude that,
although the parameter points with low fine tuning are still attainable, they
are distributed in some isolated parameter islands which are difficult to get.
Future dark matter direct search experiments such as XENON-1T will provide a
better test of nNMSSM.


  Diffraction of electromagnetic plane waves by the gratings made by
periodically corrugating the exposed planar boundaries of homogeneous,
isotropic, linear dielectric--magnetic half--spaces is examined. The phase
velocity vector in the diffracting material can be either co-parallel or
anti-parallel to the time-averaged Poynting vector, thereby allowing for the
material to be classified as of either the positive or the negative negative
phase-velocity (PPV or NPV) type. Three methods used for analyzing dielectric
gratings - the Rayleigh-hypothesis method, a perturbative approach, and the C
formalism - are extended here to encompass NPV gratings by a careful
consideration of field representation inside the refracting half--space.
Corrugations of both symmetric as well as asymmetric shapes are studied, as
also the diversity of grating response to the linear polarization states of the
incident plane wave. The replacement of PPV grating by its NPV analog affects
only nonspecular diffraction efficiencies when the corrugations are shallow,
and the effect on specular diffraction efficiencies intensifies as the
corrugations deepen. Whether the type of the refracting material is NPV or PPV
is shown to affect surface wave propagation as well as resonant excitation of
surface waves.


  Speech fluency/disfluency can be evaluated by analyzing a range of phonetic
and prosodic features. Deep neural networks are commonly trained to map
fluency-related features into the human scores. However, the effectiveness of
deep learning-based models is constrained by the limited amount of labeled
training samples. To address this, we introduce a self-supervised learning
(SSL) approach that takes into account phonetic and prosody awareness for
fluency scoring. Specifically, we first pre-train the model using a
reconstruction loss function, by masking phones and their durations jointly on
a large amount of unlabeled speech and text prompts. We then fine-tune the
pre-trained model using human-annotated scoring data. Our experimental results,
conducted on datasets such as Speechocean762 and our non-native datasets, show
that our proposed method outperforms the baseline systems in terms of Pearson
correlation coefficients (PCC). Moreover, we also conduct an ablation study to
better understand the contribution of phonetic and prosody factors during the
pre-training stage.