  The electrolysis of CO$_2$ in molten carbonate has been introduced as an
alternative mechanism to synthesize carbon nanomaterials inexpensively at high
yield. Until recently, CO$_2$ was thought to be unreactive, making its removal
a challenge. CO$_2$ is the main cause of anthropogenic global warming and its
utilization and transformation into a stable, valuable material provides an
incentivized pathway to mitigate climate change. This study focuses on
controlled electrochemical conditions in molten lithium carbonate to split
CO$_2$ absorbed from the atmosphere into into carbon nanotubes, and into
various macroscopic assemblies of CNTs,, which may be useful for
nano-filtration. Different CNTs, morphologies were prepared electrochemically
by variation of the anode and cathode composition and architecture, electrolyte
composition pre-electrolysis processing, and the variation of current
application and current density. Individual CNT morphologies structures and the
CNT molten carbonate growth mechanism are explored by SEM, TEM, HAADF EDX, XRD
and Raman. The principle commercial technology for CNT production had been
chemical vapor deposition, which is an order of magnitude more expensive,
generally requires metallo-organics, rather than CO$_2$ as reactants, and can
be highly energy and CO$_2$ emission intensive (carries a high carbon positive,
rather than negative, footprint).


  We use general arguments to show that a continuously powered radiative blast
wave can behave self similarly if the energy injection and radiation mechanisms
are self similar. In that case, the power-law indices of the blast wave
evolution are set by only one of the two constituent physical mechanisms. If
the luminosity of the energy source drops fast enough, the radiation mechanisms
set the power-law indices, otherwise, they are set by the behavior of the
energy source itself. We obtain self similar solutions for the Newtonian and
the ultra-relativistic limits. Both limits behave self similarly if we assume
that the central source supplies energy in the form of a hot wind, and that the
radiative mechanism is the semi-radiative mechanism of Cohen, Piran & Sari
(1998). We calculate the instantaneous radiative efficiencies for both limits
and find that a relativistic blast wave has a higher efficiency than a
Newtonian one. The instantaneous radiative efficiency depends strongly on the
hydrodynamics and cannot be approximated by an estimate of local microscopic
radiative efficiencies, since a fraction of the injected energy is deposited in
shocked matter. These solutions can be used to calculate Gamma Ray Bursts
afterglows, for cases in which the energy is not supplied instantaneously.


  Feynman famously recommended accepting the basic principles of quantum
mechanics without trying to guess the machinery behind the law. One of the
corollaries of the Uncertainty Principle is that the knowledge of probability
amplitudes does not allow one to make meaningful statements about the past of
an unobserved quantum system. A particular type of reasoning, based on weak
values, appears to do just that. Has Feynman been proven wrong by the more
recent developments? Most likely not.


  We study Riemannian metrics on compact, torsionless, non-geometric
$3$-manifolds, i.e. whose interior does not support any of the eight model
geometries. We prove a lower bound "\`a la Margulis" for the systole and a
volume estimate for these manifolds, only in terms of an upper bound of entropy
and diameter. We then deduce corresponding local topological rigidy results in
the class $\mathscr{M}_{ngt}^\partial (E,D) $ of compact non-geometric
3-manifolds with torsionless fundamental group (with possibly empty,
non-spherical boundary) whose entropy and diameter are bounded respectively by
$E, D$. For instance, this class locally contains only finitely many
topological types; and closed, irreducible manifolds in this class which are
close enough (with respect to $E,D$) are diffeomorphic. Several examples and
counter-examples are produced to stress the differences with the geometric
case.


  We apply the method of QCD sum rules to study the doubly heavy tetraquark
states $QQ\bar{q}\bar{n}$ with spin-parity $J^{P}=1^{+}$ and strangeness $S=0,
-1$ using careful estimates of the Borel and threshold parameters involved.
Masses of the doubly bottom and charmed tetraquarks with isospin $I=0,1/2, 1$
are computed precisely via taking into account multifarious condensates up to
dimension $10$. Comparing with the two-heavy meson thresholds, we find that all
nonstrange doubly-bottom tetraquarks and a doubly-charmed tetraquarks associted
with $J_{3}$ with $J^{P}=1^{+}$ are stable against strong decay into two bottom
mesons while a doubly-charmed tetraquarks associated with current $J_{2}$ is
unstable against strong decay. By the way, weak decay widths of the doubly
bottom tetraquarks are also given.


  We introduce a system of phenomenological equations for Bose-Einstein
condensates of magnons in the one-dimensional setting. The nonlinearly coupled
equations, written for amplitudes of the right-and left-traveling waves,
combine basic features of the Gross-Pitaevskii and complex Ginzburg-Landau
models. They include localized source terms, to represent the microwave
magnon-pumping field. With the source represented by the $\delta $-functions,
we find analytical solutions for symmetric localized states of the magnon
condensates. We also predict the existence of asymmetric states with unequal
amplitudes of the two components. Numerical simulations demonstrate that all
analytically found solutions are stable. With the $\delta $-function terms
replaced by broader sources, the simulations reveal a transition from the
single-peak stationary symmetric states to multi-peak ones, generated by the
modulational instability of extended nonlinear-wave patterns. In the
simulations, symmetric initial conditions always converge to symmetric
stationary patterns. On the other hand, asymmetric inputs may generate
nonstationary asymmetric localized solutions, in the form of traveling or
standing waves. Comparison with experimental results demonstrates that the
phenomenological equations provide for a reasonably good model for the
description of the spatiotemporal dynamics of magnon condensates.


  The Dynamic Time Warping (DTW) distance is a popular similarity measure for
polygonal curves (i.e., sequences of points). It finds many theoretical and
practical applications, especially for temporal data, and is known to be a
robust, outlier-insensitive alternative to the \frechet distance. For static
curves of at most $n$ points, the DTW distance can be computed in $O(n^2)$ time
in constant dimension. This tightly matches a SETH-based lower bound, even for
curves in $\mathbb{R}^1$.
  In this work, we study \emph{dynamic} algorithms for the DTW distance. Here,
the goal is to design a data structure that can be efficiently updated to
accommodate local changes to one or both curves, such as inserting or deleting
vertices and, after each operation, reports the updated DTW distance. We give
such a data structure with update and query time $O(n^{1.5} \log n)$, where $n$
is the maximum length of the curves.
  As our main result, we prove that our data structure is conditionally
\emph{optimal}, up to subpolynomial factors. More precisely, we prove that,
already for curves in $\mathbb{R}^1$, there is no dynamic algorithm to maintain
the DTW distance with update and query time~\makebox{$O(n^{1.5 - \delta})$} for
any constant $\delta > 0$, unless the Negative-$k$-Clique Hypothesis fails. In
fact, we give matching upper and lower bounds for various trade-offs between
update and query time, even in cases where the lengths of the curves differ.


  In this paper, we will develop a family of braid representations of Artin
groups of type B from braided vector spaces, and identify the homology of these
groups with these coefficients with the cohomology of a specific bimodule over
a quantum shuffle algebra. As an application, we give a complete
characterization of the homology of type-B Artin groups with coefficients in
one-dimensional braid representations over a field of characteristic 0. We will
also discuss two different approaches to this computation: the first method
extends a computation of the homology of braid groups due to
Ellenberg-Tran-Westerland by means of induced representation, while the second
method involves constructing a cellular stratification for configuration spaces
of the punctured complex plane.


  We derive the equations governing the protocols minimizing the heat released
by a continuous-time Markov jump process on a one-dimensional countable state
space during a transition between assigned initial and final probability
distributions in a finite time horizon. In particular, we identify the
hypotheses on the transition rates under which the optimal control strategy and
the probability distribution of the Markov jump problem obey a system of
differential equations of Hamilton-Bellman-Jacobi-type. As the state-space mesh
tends to zero, these equations converge to those satisfied by the diffusion
process minimizing the heat released in the Langevin formulation of the same
problem. We also show that in full analogy with the continuum case, heat
minimization is equivalent to entropy production minimization. Thus, our
results may be interpreted as a refined version of the second law of
thermodynamics.


  The physics of electronic energy level alignment at interfaces formed between
molecules and metals can in general be accurately captured by the \emph{ab
initio} $GW$ approach. However, the computational cost of such $GW$
calculations for typical interfaces is significant, given their large system
size and chemical complexity. In the past, approximate self-energy corrections,
such as those constructed from image-charge models together with gas-phase
molecular level corrections, have been used to compute level alignment with
good accuracy. However, these approaches often neglect dynamical effects of the
polarizability and require the definition of an image plane. In this work, we
propose a new approximation to enable more efficient $GW$-quality calculations
of interfaces, where we greatly simplify the calculation of the non-interacting
polarizability, a primary bottleneck for large heterogeneous systems. This is
achieved by first computing the non-interacting polarizability of each
individual component of the interface, e.g., the molecule and the metal,
without the use of large supercells; and then using folding and spatial
truncation techniques to efficiently combine these quantities. Overall this
approach significantly reduces the computational cost for conventional $GW$
calculations of level alignment without sacrificing the accuracy. Moreover,
this approach captures both dynamical and nonlocal polarization effects without
the need to invoke a classical image-charge expression or to define an image
plane. We demonstrate our approach by considering a model system of benzene at
relatively low coverage on aluminum (111) surface. Although developed for such
interfaces, the method can be readily extended to other heterogeneous
interfaces.


  Binary Convolutional Neural Networks (CNNs) can significantly reduce the
number of arithmetic operations and the size of memory storage, which makes the
deployment of CNNs on mobile or embedded systems more promising. However, the
accuracy degradation of single and multiple binary CNNs is unacceptable for
modern architectures and large scale datasets like ImageNet. In this paper, we
proposed a Piecewise Approximation (PA) scheme for multiple binary CNNs which
lessens accuracy loss by approximating full precision weights and activations
efficiently and maintains parallelism of bitwise operations to guarantee
efficiency. Unlike previous approaches, the proposed PA scheme segments
piece-wisely the full precision weights and activations, and approximates each
piece with a scaling coefficient. Our implementation on ResNet with different
depths on ImageNet can reduce both Top-1 and Top-5 classification accuracy gap
compared with full precision to approximately 1.0%. Benefited from the
binarization of the downsampling layer, our proposed PA-ResNet50 requires less
memory usage and two times Flops than single binary CNNs with 4 weights and 5
activations bases. The PA scheme can also generalize to other architectures
like DenseNet and MobileNet with similar approximation power as ResNet which is
promising for other tasks using binary convolutions. The code and pretrained
models will be publicly available.


  We show how the non-linearity of general relativity generates a
characteristic non-Gaussian signal in cosmological large-scale structure that
we calculate at all perturbative orders in a large scale limit. Newtonian
gravity and general relativity provide complementary theoretical frameworks for
modelling large-scale structure in $\Lambda$CDM cosmology; a relativistic
approach is essential to determine initial conditions which can then be used in
Newtonian simulations studying the non-linear evolution of the matter density.
Most inflationary models in the very early universe predict an almost Gaussian
distribution for the primordial metric perturbation, $\zeta$. However, we argue
that it is the Ricci curvature of comoving-orthogonal spatial hypersurfaces,
$R$, that drives structure formation at large scales. We show how the
non-linear relation between the spatial curvature, $R$, and the metric
perturbation, $\zeta$, translates into a specific non-Gaussian contribution to
the initial comoving matter density that we calculate for the simple case of an
initially Gaussian $\zeta$. Our analysis shows the non-linear signature of
Einstein's gravity in large-scale structure.


  This paper is intended to help the readers to understand the article: Y.
Hirashita, Least-Squares Prices of Games, Preprint (arXiv:math.OC/0703079).


  We investigate the behaviour of the pion decay constant and the pion mass in
two-flavour lattice QCD, with the physical and chiral points as ultimate goal.
Measurements come from the ensembles generated by the CLS initiative using the
O(a)-improved Wilson formulation, with lattice spacing down to about 0.05 fermi
and pion masses as low as 190 MeV. The applicability of SU(2) chiral
perturbation theory is investigated, and various functional forms, and their
range of validity, are compared. The physical scale is set through the kaon
decay constant, whose measurement is enabled by inserting a third, heavier
valence strange quark.


  An unexpected enhancement in the $\gamma$-ray strength function, as compared
to the low energy tail of the Giant Dipole Resonance (GDR), has been observed
for Sc, Ti, V, Fe and Mo isotopes for $E_\gamma<4$ MeV. This enhancement was
not observed in subsequent analyses on Sn isotopes, but a Pygmy Dipole
Resonance (PDR) centered at $E_\gamma\approx8$ MeV was however detected. The
$\gamma$-ray strength functions measured for Cd isotopes exhibit both features
over the range of isotopes, with the low-energy enhancement decreasing- and PDR
strength increasing as a function of neutron number. This suggests a
transitional region for the onset of low-energy enhancement, and also that the
PDR strength depends on the number of neutrons. The $\gamma$-ray strength
functions of $^{105-108}$Pd have been measured in order to further explore the
proposed transitional region. Experimental data were obtained at the Oslo
Cyclotron Laboratory by using the charged particle reactions ($^{3}$He,
$^{3}$He$^{\prime}\gamma$) and ($^{3}$He, $\alpha$$\gamma$) on $^{106,108}$Pd
target foils. Particle$-\gamma$ coincidence measurements provided information
on initial excitation energies and the corresponding $\gamma$-ray spectra,
which were used to extract the level densities and $\gamma$-ray strength
functions according to the Oslo method. The $\gamma$-ray strength functions
indicate a sudden increase in magnitude for $E_{\gamma}>4$ MeV, which is
interpreted as a PDR centered at $E_{\gamma}\approx8$ MeV. An enhanced
$\gamma$-ray strength at low energies is also observed for $^{105}$Pd, which is
the lightest isotope measured in this work. Further, the results correspond and
agree very well with the observations from the Cd isotopes, and support the
suggested transitional region for the onset of low-energy enhancement with
decreasing mass number. The neutron number dependency of the PDR strength is
also evident.


  This chapter aims to provide a review of the basics of 21 cm interferometric
observations and its methodologies. A summary of the main concepts of radio
interferometry and their connection with the 21 cm observables - power spectra
and images - is presented. I then provide a review of interferometric
calibration and its interplay with foreground separation, including the current
open challenges in calibration of 21 cm observations. Finally, a review of 21
cm instrument designs in the light of calibration choices and observing
strategies follows.


  In the present study, we addressed the question of how the growth rate of the
magnetorotational instability is modified when the radial component of the
stellar dipole magnetic field is taken into account in addition to the vertical
component. Considering a fiducial radius in the disc where diamagnetic currents
are pronounced, we carried out a linear stability analysis to obtain the growth
rates of the magnetorotational instability for various parameters such as the
ratio of the radial-to-vertical component and the gradient of the magnetic
field, the Alfvenic Mach number and the diamagnetization parameter. Our results
show that the interaction between the diamagnetic current and the radial
component of the magnetic field increases the growth rate of the
magnetorotational instability and generates a force perpendicular to the disc
plane which may induce a torque. It is also shown that considering the radial
component of the magnetic field and taking into account a radial gradient in
the vertical component of the magnetic field causes an increase in the
magnitudes of the growth rates of both the axisymmetric ($m=0$) and the
non-axisymmetric ($m=1$) modes.


  3D reconstruction from single view images is an ill-posed problem. Inferring
the hidden regions from self-occluded images is both challenging and ambiguous.
We propose a two-pronged approach to address these issues. To better
incorporate the data prior and generate meaningful reconstructions, we propose
3D-LMNet, a latent embedding matching approach for 3D reconstruction. We first
train a 3D point cloud auto-encoder and then learn a mapping from the 2D image
to the corresponding learnt embedding. To tackle the issue of uncertainty in
the reconstruction, we predict multiple reconstructions that are consistent
with the input view. This is achieved by learning a probablistic latent space
with a novel view-specific diversity loss. Thorough quantitative and
qualitative analysis is performed to highlight the significance of the proposed
approach. We outperform state-of-the-art approaches on the task of single-view
3D reconstruction on both real and synthetic datasets while generating multiple
plausible reconstructions, demonstrating the generalizability and utility of
our approach.


  Let G be a group and H be a Hartley set of G. In this paper, we prove the
existence and conjugacy of H-injectors of G and describe the structure of the
injectors. As application, some known results are directly followed.


  Realistic generative face video synthesis has long been a pursuit in both
computer vision and graphics community. However, existing face video generation
methods tend to produce low-quality frames with drifted facial identities and
unnatural movements. To tackle these challenges, we propose a principled
framework named StyleFaceV, which produces high-fidelity identity-preserving
face videos with vivid movements. Our core insight is to decompose appearance
and pose information and recompose them in the latent space of StyleGAN3 to
produce stable and dynamic results. Specifically, StyleGAN3 provides strong
priors for high-fidelity facial image generation, but the latent space is
intrinsically entangled. By carefully examining its latent properties, we
propose our decomposition and recomposition designs which allow for the
disentangled combination of facial appearance and movements. Moreover, a
temporal-dependent model is built upon the decomposed latent features, and
samples reasonable sequences of motions that are capable of generating
realistic and temporally coherent face videos. Particularly, our pipeline is
trained with a joint training strategy on both static images and high-quality
video data, which is of higher data efficiency. Extensive experiments
demonstrate that our framework achieves state-of-the-art face video generation
results both qualitatively and quantitatively. Notably, StyleFaceV is capable
of generating realistic $1024\times1024$ face videos even without
high-resolution training videos.


  Recently, Sharpness-Aware Minimization (SAM) has shown state-of-the-art
performance by seeking flat minima. To minimize the maximum loss within a
neighborhood in the parameter space, SAM uses an ascent step, which perturbs
the weights along the direction of gradient ascent with a given radius. While
single-step or multi-step can be taken during ascent steps, previous studies
have shown that multi-step ascent SAM rarely improves generalization
performance. However, this phenomenon is particularly interesting because the
multi-step ascent is expected to provide a better approximation of the maximum
neighborhood loss. Therefore, in this paper, we analyze the effect of the
number of ascent steps and investigate the difference between both single-step
ascent SAM and multi-step ascent SAM. We identify the effect of the number of
ascent on SAM optimization and reveal that single-step ascent SAM and
multi-step ascent SAM exhibit distinct loss landscapes. Based on these
observations, we finally suggest a simple modification that can mitigate the
inefficiency of multi-step ascent SAM.


  We propose a spin-mechanical device to control and detect spin currents by
mechanical torque. Our hybrid nano-electro-mechanical device, which contains a
nanowire with a ferromagnetic-nonmagnetic interface, is designed to measure or
induce spin polarized currents. Since spin carries angular momentum, a spin
flip or spin transfer process involves a change in angular momentum--and hence,
a torque--which enables mechanical measurement of spin flips. Conversely, an
applied torque can result in spin polarization and spin current.


  We report a numerical design procedure for pursuing a near-unity coupling
efficiency in quantum dot-cavity ridge waveguide single-photon sources by
performing simulations with the finite element method. Our optimum design which
is based on a 1D nanobeam cavity, achieves a high source efficiency
$\epsilon_{xy}$ of 97.7$\%$ for an isotropic in-plane dipole, together with a
remarkable Purcell factor of 38.6. Such a good performance is mainly attributed
to the high index contrast of GaAs/SiO$_2$ and a careful cavity design
achieving constructive interference and low scattering losses. Furthermore, we
analyze the bottleneck of the proposed platform, which is the mode mismatch
between the cavity mode and the Bloch mode in the nanobeam. Accordingly, we
present the optimization recipe of an arbitrarily high-efficiency on-chip
single-photon source by implementing a taper section, whose high smoothness is
beneficial to gradually overcoming the mode mismatch, and therefore leading to
a higher Purcell factor and source efficiency. Finally, we see good robustness
of the source properties in the taper-nanobeam system under the consideration
of realistic fabrication imperfections on the hole variation.


  It is well-known that the convergence of a family of smooth functions does
not imply the convergence of its gradients. In this work, we show that if the
family is definable in an o-minimal structure (for instance semialgebraic,
subanalytic, or any composition of the previous with exp, log), then the
gradient's limit is a conservative set-valued field in the sense introduced by
Bolte and Pauwels. Immediate implications of this result on convergence
guarantees of smoothing methods are discussed. Finally, a more general result
is established, where the functions in the original family might be merely
Lipschitz continuous, vector-valued and the gradients are replaced by their
Clarke's Jacobians or an arbitrary definable conservative mapping.


  We report the discovery of a 70-degree long stellar stream in the Milky Way
halo, which criss-crosses the well known "GD-1" stream. We show that this new
stellar structure ("Kshir") and GD-1 lie at similar distance, and are
remarkably correlated in kinematics. We propose several explanations for the
nature of this new structure and its possible association with GD-1. However, a
scenario in which these two streams were accreted onto the Milky Way within the
same dark matter sub-halo seems to provide a natural explanation for their
phase-space entanglement, and other complexities of this coupled-system.


  This paper continues math.DG/9903140. Here we construct a linking form on the
torsion part of middle dimensional extended L^2 homology and cohomology of
odd-dimensional manifolds. We give a geometric necessary condition when this
linking form is hyperbolic. We compute this linking form in case when the
manifold bounds. We introduce and study new numerical invariants of the linking
form: the Novikov - Shubin signature and the torsion signature. We compute
these invariants explicitly for manifolds with $\pi_1 = Z$ in terms of the
Blanchfield form. We develop a notion of excess for extensions of torsion
modules and show how this concept can be used to guarantee vanishing of the
torsion signature.


  Progenitor scenarios for short gamma-ray bursts (short GRBs) include
coalescenses of two neutron stars or a neutron star and black hole, which would
necessarily be accompanied by the emission of strong gravitational waves. We
present a search for these known gravitational-wave signatures in temporal and
directional coincidence with 22 GRBs that had sufficient gravitational-wave
data available in multiple instruments during LIGO's fifth science run, S5, and
Virgo's first science run, VSR1. We find no statistically significant
gravitational-wave candidates within a [-5, +1) s window around the trigger
time of any GRB. Using the Wilcoxon-Mann-Whitney U test, we find no evidence
for an excess of weak gravitational-wave signals in our sample of GRBs. We
exclude neutron star-black hole progenitors to a median 90% CL exclusion
distance of 6.7 Mpc.


  Federated Learning is a new learning scheme for collaborative training a
shared prediction model while keeping data locally on participating devices. In
this paper, we study a new model of multiple federated learning services at the
multi-access edge computing server. Accordingly, the sharing of CPU resources
among learning services at each mobile device for the local training process
and allocating communication resources among mobile devices for exchanging
learning information must be considered. Furthermore, the convergence
performance of different learning services depends on the hyper-learning rate
parameter that needs to be precisely decided. Towards this end, we propose a
joint resource optimization and hyper-learning rate control problem, namely
MS-FEDL, regarding the energy consumption of mobile devices and overall
learning time. We design a centralized algorithm based on the block coordinate
descent method and a decentralized JP-miADMM algorithm for solving the MS-FEDL
problem. Different from the centralized approach, the decentralized approach
requires many iterations to obtain but it allows each learning service to
independently manage the local resource and learning process without revealing
the learning service information. Our simulation results demonstrate the
convergence performance of our proposed algorithms and the superior performance
of our proposed algorithms compared to the heuristic strategy.


  The equations describing nonradial adiabatic oscillations of differentially
rotating relativistic stars are derived in relativistic slow rotation
approximation. The differentially rotating configuration is described by a
perturbative version of the relativistic j-constant rotation law. Focusing on
the oscillation properties of the stellar fluid, the adiabatic nonradial
perturbations are studied in the Cowling approximation with a system of five
partial differential equations. In these equations, differential rotation
introduces new coupling terms between the perturbative quantites with respect
to the uniformly rotating stars. In particular, we investigate the axisymmetric
and barotropic oscillations and compare their spectral properties with those
obtained in nonlinear hydrodynamical studies. The perturbative description of
the differentially rotating background and the oscillation spectrum agree
within a few percent with those of the nonlinear studies.


  We study surfaces of constant positive Gauss curvature in Euclidean 3-space
via the harmonicity of the Gauss map. Using the loop group representation, we
solve the regular and the singular geometric Cauchy problems for these
surfaces, and use these solutions to compute several new examples. We give the
criteria on the geometric Cauchy data for the generic singularities, as well as
for the cuspidal beaks and cuspidal butterfly singularities. We consider the
bifurcations of generic one parameter families of spherical fronts and provide
evidence that suggests that these are the cuspidal beaks, cuspidal butterfly
and one other singularity. We also give the loop group potentials for spherical
surfaces with finite order rotational symmetries and for surfaces with embedded
isolated singularities.


  In hot plasmas, a temperature of a few tens of eV is sufficient for producing
highly stripped ions where multipole transitions become important. At low
density, the transitions from tightly bound inner shells lead to
electric-quadrupole (E2) lines which are comparable in strength with
electric-dipole ones. In this work, we propose analytical formulas for the
estimation of the number of E2 lines in a transition array. Such expressions
rely on statistical descriptions of electron states and J-levels. A generalized
'J-file' sum rule for E2 lines and the strength-weighted shift and variance of
the line energies of a transition array nl^N+1 \rightarrow nl^Nn'l' of
inter-configuration E2 lines are also presented.


  Explainable AI (XAI) methods are frequently applied to obtain qualitative
insights about deep models' predictions. However, such insights need to be
interpreted by a human observer to be useful. In this paper, we aim to use
explanations directly to make decisions without human observers. We adopt two
gradient-based explanation methods, Integrated Gradients (IG) and backprop, for
the task of 3D object detection. Then, we propose a set of quantitative
measures, named Explanation Concentration (XC) scores, that can be used for
downstream tasks. These scores quantify the concentration of attributions
within the boundaries of detected objects. We evaluate the effectiveness of XC
scores via the task of distinguishing true positive (TP) and false positive
(FP) detected objects in the KITTI and Waymo datasets. The results demonstrate
an improvement of more than 100\% on both datasets compared to other heuristics
such as random guesses and the number of LiDAR points in the bounding box,
raising confidence in XC's potential for application in more use cases. Our
results also indicate that computationally expensive XAI methods like IG may
not be more valuable when used quantitatively compare to simpler methods.


  We realize a strongly coupled double quantum dot in a single all-organic
molecule by introducing a non-conjugated bridge in between two identical
conjugated moieties. Spin-1/2 Kondo and Kondo enhanced low-energy excitations
for respectively the odd and even electron occupation are observed in
off-resonant transport. The ground state in the even occupation can be the
singlet or the triplet state varying between samples. This observation suggests
that both anti-ferromagnetic and ferromagnetic interactions between spins are
of the same order of magnitude.


  In this article, we exploit the theory of graded module category with
semi-infinite character developed by Soergel in \cite{Soe} to study
representations of the infinite dimensional Lie algebras of vector fields
$W(n), S(n)$ and $H(n)$ $(n\geq 2)$, and obtain the description of
indecomposable tilting modules. The character formulas for those tilting
modules are determined.


  Eight production quality PbWO4 crystals of CMS have been irradiated in a 20
GeV/c proton beam up to fluences of 5.4E13cm-2. The damage recovery in these
crystals has been followed for over a year. Comparative irradiations with 60Co
photons have been performed on seven other crystals using a dose rate of 1
kGy/h. In proton irradiated crystals the light transmission band-edge shifts
and the induced absorption length is proportional to the inverse of the 4th
power of the wavelength. In gamma-irradiated crystals the band-edge does not
shift but formation of absorption bands is seen clearly. The absorption length
induced by gamma-radiation in crystals verified to have excellent radiation
hardness, saturates at a level below 0.5 m-1. In the case of protons, we
observe no correlation with the pre-characterised radiation hardness of the
crystals and the induced absorption increases linearly with fluence. After a
fluence of 5E13 cm-2, an induced absorption length of approx. 15m-1 is seen
with no sign of saturation. These observations provide strong evidence that
high-energy protons create damage that cannot be reproduced with
gamma-irradiation. However, these hadronic effects manifest themselves only at
integral fluences well beyond 1E12cm-2 and most likely would escape undetected
at lower fluences. A large fraction of the damage, both in proton- and
gamma-irradiated crystals, is either stable or recovers very slowly.


  Aperture synthesis and single-dish (sub) millimeter molecular lines and
continuum observations reveal in great detail the envelope structure of deeply
embedded young stellar objects (SMM1, SMM2, SMM3, SMM4) in the densely
star-forming Serpens Molecular Cloud. Resolved millimeter continuum emission
constrains the density structure to a radial power law with index -2.0 +/- 0.5,
and envelope masses of 8.7, 3.0, and 5.3 M_sol for SMM1, SMM3, and SMM4. The
core SMM2 does not seem to have a central condensation and may not have formed
a star yet. The molecular line observations can be described by the same
envelope model, if an additional, small amount of warm (100 K) material is
included. This probably corresponds to the inner few hundred AU of the envelope
were the temperature is high. In the interferometer beam, the molecular lines
reveal the inner regions of the envelopes, as well as interaction of the
outflow with the surrounding envelope. Bright HCO+ and HCN emission outlines
the cavities, while SiO and SO trace the direct impact of the outflow on
ambient gas. Taken together, these observations provide a first comprehensive
view of the physical and chemical structure of the envelopes of deeply embedded
young stellar objects in a clustered environment on scales between 1000 and
10,000 AU.


  Knapsack problems (KPs) are common in industry, but solving KPs is known to
be NP-hard and has been tractable only at a relatively small scale. This paper
examines KPs in a slightly generalized form and shows that they can be solved
nearly optimally at scale via distributed algorithms. The proposed approach can
be implemented fairly easily with off-the-shelf distributed computing
frameworks (e.g. MPI, Hadoop, Spark). As an example, our implementation leads
to one of the most efficient KP solvers known to date -- capable to solve KPs
at an unprecedented scale (e.g., KPs with 1 billion decision variables and 1
billion constraints can be solved within 1 hour). The system has been deployed
to production and called on a daily basis, yielding significant business
impacts at Ant Financial.


  We develop a microscopic description of an electron-doped two-dimensional
semiconductor embedded in a microcavity. Specifically, we investigate the
interactions between exciton-polaritons and electrons for the case where the
interactions between charges are strongly screened and the system is spin
polarized. As a starting point, we obtain an analytic expression for the
exciton-polariton wave function, and we relate the microscopic parameters of
the light-matter system to experimentally measurable quantities, such as the
Rabi coupling and the cavity photon frequency. We then derive the
polariton-electron interaction within the standard Born approximation and
compare it with the exact polariton-electron scattering $T$ matrix that we
obtain from a diagrammatic approach that has proven highly successful in the
context of nuclear physics and ultracold atomic gases. In particular, we show
that the Born approximation provides an upper bound on the polariton-electron
coupling strength at vanishing momentum. Using our exact microscopic
calculation, we demonstrate that polariton-electron scattering can be strongly
enhanced compared to the exciton-electron case, which is the opposite of that
expected from the Born approximation. We furthermore expose a resonance-like
peak at scattering momenta near the polariton inflection point, whose size is
set by the strength of the light-matter coupling. Our results arise from the
non-Galilean nature of the polariton system and should thus be applicable to a
range of semiconductor microcavities such as GaAs quantum wells and atomically
thin materials.


  The one-point probability distribution function (PDF) of the matter density
field in the universe is a fundamental property that plays an essential role in
cosmology for estimates such as gravitational weak lensing, non-linear
clustering, massive production of mock galaxy catalogs, and testing predictions
of cosmological models. Here we make a comprehensive analysis of the dark
matter PDF using a suite of 7000 N-body simulations that covers a wide range of
numerical and cosmological parameters. We find that the PDF has a simple shape:
it declines with density as a power-law P~rho**(-2), which is exponentially
suppressed on both small and large densities. The proposed double-exponential
approximation provides an accurate fit to all our N-body results for small
filtering scales R< 5Mpc/h with rms density fluctuations sigma>1. In
combination with the spherical infall model that works well for small
fluctuations sigma<1, the PDF is now approximated with just few percent errors
over the range of twelve orders of magnitude -- a remarkable example of
precision cosmology. We find that at 5-10% level the PDF explicitly depends on
redshift (at fixed sigma) and on cosmological density parameter Omega_m. We
test different existing analytical approximations and find that the often used
log-normal approximation is always 3-5 times less accurate than either the
double-exponential approximation or the spherical infall model.


  We study the local moment formation and the Kondo effect at single-atom
vacancies in Graphene. We develop a model accounting for the vacancy
reconstruction as well as non-planarity effects induced by strain and/or
temperature. Thus, we find that the dangling $\sigma$ orbital localized at the
vacancy is allowed to strongly hybridize with the $\pi$-band since the
scattering with the vacancy turns the hybridization into singular function of
the energy ($\sim [|\epsilon| \ln^2 \epsilon/D]^{-1}$, $D\sim$ the bandwidth).
This leads to several new types of impurity phases, which control the magnitude
of the vacancy magnetic moment and the possibility of Kondo effect depending on
the strength of the local Coulomb interactions, the Hund's rule coupling, the
doping level, and the degree of particle-symmetry breaking.


  Single crystal synthesis, structure, electric polarization and heat capacity
measurements on hexagonal InMnO3 show that this small R ion in the RMnO3 series
is ferroelectric (space group P63cm). Structural analysis of this system
reveals a high degree of order within the MnO5 polyhedra but significant
distortions in the R-O bond distributions compared to the previously studied
materials. Point-charge estimates of the electric polarization yield an
electrical polarization of approximately 7.8 micro C/cm^2, 26% larger than the
well-studied YMnO3 system. This system with enhanced room temperature
polarization values may serve as a possible replacement for YMnO3 in device
application.


  Quantum field theories on noncommutative spacetime have many different
properties from those on commutative spacetime. In this paper, we study the
microcausality of free scalar field on noncommutative spacetime. We expand the
scalar field in the form of usual Lorentz invariant measure in noncommutative
spacetime. Then we calculate the expectation values of the Moyal commutators
for the quadratic operators, such as $\phi(x)\star\phi(x)$, $\pi({\bf
x},t)\star\pi({\bf x},t)$, $\partial_{i}\phi({\bf
x},t)\star\partial_{i}\phi({\bf x},t)$, and $\partial_{i}\phi({\bf
x},t)\star\pi({\bf x},t)$. We obtain that for space-space noncommutativity,
i.e., $\theta^{0i}=0$ in $\theta^{\mu\nu}$, microcausality of free scalar field
on noncommutative spacetime is satisfied. For time-space noncommutativity,
i.e., $\theta^{0i}\neq0$ in $\theta^{\mu\nu}$, microcausality of free scalar
field on noncommutative spacetime is violated.


  Coarsening of bicontinuous microstructures is observed in a variety of
systems, such as nanoporous metals and mixtures that have undergone spinodal
decomposition. To better understand the morphological evolution of these
structures during coarsening, we compare the morphologies resulting from two
different coarsening mechanisms, surface and bulk diffusion. We perform
phase-field simulations of coarsening via each mechanism in a two-phase mixture
at nominal volume fractions of 50%-50% and 36%-64%, and the simulated
structures are characterized in terms of topology (genus density), the
interfacial shape distribution, structure factor, and autocorrelations of phase
and mean curvature. We observe self-similar evolution of morphology and
topology and agreement with the expected power laws for dynamic scaling, in
which the characteristic length scale increases over time proportionally to
$t^{1/4}$ for surface diffusion and $t^{1/3}$ for bulk diffusion. While we
observe the expected difference in the coarsening kinetics, we find that
differences in self-similar morphology due to coarsening mechanism are
relatively small, although typically they are larger at 36% volume fraction
than at 50% volume fraction. In particular, we find that bicontinuous
structures coarsened via surface diffusion have lower scaled genus densities
than structures coarsened via bulk diffusion. We also compare the self-similar
morphologies to those in literature and to two model bicontinuous structures,
namely, constant-mean-curvature surfaces based on the Schoen G minimal surface
and random leveled-wave structures. The average scaled mean curvatures of these
model structures agree reasonably with those of the coarsened structures at
both 36% and 50%, but we find substantial disagreements in the scaled genus
densities and the standard deviations of mean curvature.


  The task of Dense Video Captioning (DVC) aims to generate captions with
timestamps for multiple events in one video. Semantic information plays an
important role for both localization and description of DVC. We present a
semantic-assisted dense video captioning model based on the encoding-decoding
framework. In the encoding stage, we design a concept detector to extract
semantic information, which is then fused with multi-modal visual features to
sufficiently represent the input video. In the decoding stage, we design a
classification head, paralleled with the localization and captioning heads, to
provide semantic supervision. Our method achieves significant improvements on
the YouMakeup dataset under DVC evaluation metrics and achieves high
performance in the Makeup Dense Video Captioning (MDVC) task of PIC 4th
Challenge.


  We discuss if experimental tests of Bell inequalities performed with
pseudoscalar mesons (K or B) can be definitive. Our conclusion is that this is
not the case, for the efficiency loophole cannot be eliminated.


  When data is transmitted by encoding it in the amplitude of the transmitted
signal, such as in Amplitude Shift Keying, the receiver makes a decision on the
transmitted data by observing the amplitude of the received signal. Depending
on the level of the received signal, the receiver has to decode the received
data, with minimum probability of error. For binary transmission, this is
achieved by choosing a decision threshold. A threshold detection mechanism is
evaluated in this paper, which uses parametric probability distribution fitting
to the received signal. Based on our earlier work on visible light
communication, the idea is extended to a fiber optic channel and it is found
that in a fiber optic channel, the threshold value obtained by fitting a
Rayleigh distribution to the received data results in error probability
approaching zero.


  We construct an index for BPS operators supported on a ray in five
dimensional superconformal field theories with exceptional global symmetries.
We compute the $E_n$ representations (for $n=2,\dots,7$) of operators of low
spin, thus verifying that while the expression for the index is only
SO$(2n-2)\times$U(1) invariant, the index itself exhibits the full $E_n$
symmetry (at least up to the order we expanded). The ray operators we studied
in 5d can be viewed as generalizations of operators constructed in a Yang-Mills
theory with fundamental matter by attaching an open Wilson line to a quark. For
$n\le 7$, in contrast to local operators, they carry nontrivial charge under
the $\mathbb{Z}_{9-n}\subset E_n$ center of the global symmetry. The
representations that appear in the ray operator index are therefore different,
for $n\le 7$, from those appearing in the previously computed superconformal
index. For $3\le n\le 7$, we find that the leading term in the index is a
character of a minuscule representation of $E_n$. We also discuss the case
$n=8$, which presents a unique technical challenge, and remains an open
problem.


  In 1957 M.\ Krasner described a complete valued field $(K,v)$ via the
projective limit of a system of certain structures, called hyperfields,
associated to $(K,v)$. We put this result in purely category-theoretic terms by
translating into a limit construction in certain slice categories of the
category of valued hyperfields and their homomorphisms.


  In this paper we are concerned with the existence of ground states solutions
for the following fractional Hamiltonian systems $$ \left\{ \begin{array}{ll}
-_tD^\alpha_\infty(_{-\infty}D^\alpha_t u(t)) - \lambda L(t)u(t)+\nabla
W(t,u(t))=0,\\[0.1cm] u \in H^\alpha (\mathbb{R},\mathbb{R}^n), \end{array}
\right.\qquad(\hbox{FHS})_\lambda$$ where $\alpha\in (1/2,1)$, $t\in
\mathbb{R}$, $u\in \mathbb{R}^n$, $\lambda>0$ is a parameter, $L\in
C(\mathbb{R},\mathbb{R}^{n^2})$ is a symmetric matrix for all $t\in
\mathbb{R}$, $W\in C^1(\mathbb{R} \times \mathbb{R}^n,\mathbb{R})$ and $\nabla
W(t,u)$ is the gradient of $W(t,u)$ at $u$. Assuming that $L(t)$ is a positive
semi-definite symmetric matrix for all $t\in \mathbb{R}$, that is, $L(t)\equiv
0$ is allowed to occur in some finite interval $T$ of $\mathbb{R}$, $W(t,u)$
satisfies Ambrosetti-Rabinowitz condition and some other reasonable hypotheses,
we show that (FHS)$_\lambda$ has a ground sate solution which vanishes on
$\mathbb{R}\setminus T$ as $\lambda \to \infty$, and converges to $u\in
H^\alpha(\mathbb{R}, \mathbb{R}^n)$, where $u\in E_{0}^{\alpha}$ is a ground
state solution of the Dirichlet BVP for fractional systems on the finite
interval $T$. Recent results are generalized and significantly improved.


  A simple, yet accurate solution of the electron-phonon coupling problem in
C_{60} is presented. The basic idea behind it is to be found in the
parametrization of the ground state electronic density of the system calculated
making use of ab-initio methods, in term of sp$^{2+x}$ hybridized orbitals.
This parametrization allows for an economic determination of the deformation
potential associated with the fullerene's normal modes. The resulting
electron-phonon coupling constants are used to calculate Jahn-Teller effects in
C_{60}^-, and multiple satellite peaks in the corresponding photoemission
reaction. Theory provides an accurate account of the experimental findings.


  Let $p$ and $q$ be two imprecise points, given as probability density
functions on $\mathbb R^2$, and let $\cal R$ be a set of $n$ line segments
(obstacles) in $\mathbb R^2$. We study the problem of approximating the
probability that $p$ and $q$ can see each other; that is, that the segment
connecting $p$ and $q$ does not cross any segment of $\cal R$. To solve this
problem, we approximate each density function by a weighted set of polygons; a
novel approach to dealing with probability density functions in computational
geometry.


  Compression techniques for deep neural networks are important for
implementing them on small embedded devices. In particular, channel-pruning is
a useful technique for realizing compact networks. However, many conventional
methods require manual setting of compression ratios in each layer. It is
difficult to analyze the relationships between all layers, especially for
deeper models. To address these issues, we propose a simple channel-pruning
technique based on attention statistics that enables to evaluate the importance
of channels. We improved the method by means of a criterion for automatic
channel selection, using a single compression ratio for the entire model in
place of per-layer model analysis. The proposed approach achieved superior
performance over conventional methods with respect to accuracy and the
computational costs for various models and datasets. We provide analysis
results for behavior of the proposed criterion on different datasets to
demonstrate its favorable properties for channel pruning.


  We investigate the dripping of liquids around solid surfaces in the regime of
inertial flows, a situation commonly encountered with the so-called "teapot
effect". We demonstrate that surface wettability is an unexpected key factor in
controlling flow separation and dripping, the latter being completely
suppressed in the limit of superhydrophobic substrates. This unforeseen
coupling is rationalized in terms of a novel hydro-capillary adhesion
framework, which couples inertial flows to surface wettability effects. This
description of flow separation successfully captures the observed dependence on
the various experimental parameters - wettability, flow velocity, solid surface
edge curvature-. As a further illustration of this coupling, a real-time
control of dripping is demonstrated using electro-wetting for contact angle
actuation.


  The synthesis of stoichiometric Sr$_2$RuO$_4$ thin films has been a challenge
because of the high volatility of ruthenium oxide precursors, which gives rise
to ruthenium vacancies in the films. Ru vacancies greatly affect the transport
properties and electronic phase behavior of Sr$_2$RuO$_4$, but their direct
detection is difficult due to their atomic dimensions and low concentration. We
applied polarized X-ray absorption spectroscopy at the oxygen K-edge and
confocal Raman spectroscopy to Sr$_2$RuO$_4$ thin films synthesized under
different conditions. The results show that these methods can serve as
sensitive probes of the electronic and vibrational properties of Ru vacancies,
respectively. The intensities of the vacancy-related spectroscopic features
extracted from these measurements are well correlated with the transport
properties of the films. The methodology introduced here can thus help to
understand and control the stoichiometry and transport properties in films of
Sr$_2$RuO$_4$ and other ruthenates.


  Reed-Solomon (RS) codes have been increasingly adopted by distributed storage
systems in place of replication,because they provide the same level of
availability with much lower storage overhead. However, a key drawback of those
RS-coded distributed storage systems is the poor latency of degraded reads,
which can be incurred by data failures or hot spots,and are not rare in
production environments. To address this issue, we propose a novel parallel
reconstruction solution called APLS. APLS leverages all surviving source nodes
to send the data needed by degraded reads and chooses light-loaded starter
nodes to receive the reconstructed data of those degraded reads. Hence, the
latency of the degraded reads can be improved.Prototyping-based experiments are
conducted to compare APLS with ECPipe, the state-of-the-art solution of
improving the latency of degraded reads. The experimental results demonstrate
that APLS effectively reduces the latency, particularly under heavy or medium
workloads.


  The AdS/QCD holographic wave function of basis light-front quantization
(BLFQ) for vector meson $J/\psi$ is applied in this manuscript. The exclusive
production of $J/\psi$ in diffractive process is computed in dipole model with
AdS/QCD holographic wave function. We use IP-Sat and IIM model in the
calculation of the differential cross section of the dipole scattering off the
proton. The prediction of AdS/QCD holographic wave function in BLFQ gives a
good agreement to the experimental data.


  Product graphs have been gainfully used in literature to generate
mathematical models of complex networks which inherit properties of real
networks. Realizing the duplication phenomena imbibed in the definition of
corona product of two graphs, we define Corona graphs. Given a small simple
connected graph which we call seed graph, Corona graphs are defined by taking
corona product of a seed graph iteratively. We show that the cumulative degree
distribution of Corona graphs decay exponentially when the seed graph is
regular and cumulative betweenness distribution follows power law when seed
graph is a clique. We determine explicit formulae of eigenvalues, Laplacian
eigenvalues and signless Laplacian eigenvalues of Corona graphs when the seed
graph is regular. Computable expressions of eigenvalues and signless Laplacian
eigenvalues of Corona graphs are also obtained when the seed graph is a star
graph.


  Let $G$ be a graph of order $n$. The path decomposition of $G$ is a set of
disjoint paths, say $\mathcal{P}$, which cover all vertices of $G$. If all
paths are induced paths in $G$, then we say $\mathcal{P}$ is an induced path
decomposition of $G$. Moreover, if every path is of order at least 2, then we
say $G$ has an IPD. In this paper, we prove that every connected $r$-regular
graph which is not complete graph of odd order admits an IPD. Also we show that
every connected bipartite cubic graph of order $n$ admits an IPD of size at
most $\frac{n}{3}$. We classify all connected claw-free graphs which admit an
IPD.


  In this work, we demonstrate yet another approach to tackle the amodal
segmentation problem. Specifically, we first introduce a new representation,
namely a semantics-aware distance map (sem-dist map), to serve as our target
for amodal segmentation instead of the commonly used masks and heatmaps. The
sem-dist map is a kind of level-set representation, of which the different
regions of an object are placed into different levels on the map according to
their visibility. It is a natural extension of masks and heatmaps, where modal,
amodal segmentation, as well as depth order information, are all
well-described. Then we also introduce a novel convolutional neural network
(CNN) architecture, which we refer to as semantic layering network, to estimate
sem-dist maps layer by layer, from the global-level to the instance-level, for
all objects in an image. Extensive experiments on the COCOA and D2SA datasets
have demonstrated that our framework can predict amodal segmentation, occlusion
and depth order with state-of-the-art performance.


  The beta equilibrated dense matter with kaon condensate is analyzed with
respect to extended stability conditions including charge fluctuations. This
kind of the diffusive instability, appeared to be common property in the kaon
condensation case. Results for three different nuclear models are presented.


  We present detailed experimental and numerical studies of random lasing in
weakly scattering systems. The interference of scattered light, which is weak
in the passive systems, is greatly enhanced in the presence of high gain,
providing coherent and resonant feedback for lasing. The lasing modes are
confined in the vicinity of the pumped volume due to absorption of emitted
light outside it. In the ballistic regime where the size of gain volume is less
than the scattering mean free path, lasing oscillation occurs along the
direction in which the gain volume is most extended, producing directional
laser output. The feedback for lasing originates mainly from backscattering of
particles near the boundaries of pumped region. It results in nearly constant
frequency spacing of lasing modes, which scales inversely with the maximum
dimension of the gain volume.


  We have carried out first-principles calculations of Be(0001) thin films to
study the oscillatory quantum size effects exhibited in the surface energy,
work function, and binding energy of the atomic hydrogen monolayer adsorption.
The prominent enhancement of the surface density of states at the Fermi level
makes Be(0001) thin films more metallic compared to the crystalline Be. As a
result, the calculated energetics of Be films and the properties of atomic H
adsorption onto Be(0001) surface are featured by a quantum oscillatory
behavior. Furthermore, The prominent change in the Be(0001) surface electronic
structure by the atomic hydrogen adsorption has also been shown.


  We report results from the first search for $\nu_\mu\to\nu_e$ transitions by
the NOvA experiment. In an exposure equivalent to $2.74\times10^{20}$
protons-on-target in the upgraded NuMI beam at Fermilab, we observe 6 events in
the Far Detector, compared to a background expectation of $0.99\pm0.11$ (syst.)
events based on the Near Detector measurement. A secondary analysis observes 11
events with a background of $1.07\pm0.14$ (syst.). The $3.3\sigma$ excess of
events observed in the primary analysis disfavors $0.1\pi < \delta_{CP} <
0.5\pi$ in the inverted mass hierarchy at the 90% C.L.


  Emerging edge computing platforms often contain machine learning (ML)
accelerators that can accelerate inference for a wide range of neural network
(NN) models. These models are designed to fit within the limited area and
energy constraints of the edge computing platforms, each targeting various
applications (e.g., face detection, speech recognition, translation, image
captioning, video analytics). To understand how edge ML accelerators perform,
we characterize the performance of a commercial Google Edge TPU, using 24
Google edge NN models (which span a wide range of NN model types) and analyzing
each NN layer within each model. We find that the Edge TPU suffers from three
major shortcomings: (1) it operates significantly below peak computational
throughput, (2) it operates significantly below its theoretical energy
efficiency, and (3) its memory system is a large energy and performance
bottleneck. Our characterization reveals that the one-size-fits-all, monolithic
design of the Edge TPU ignores the high degree of heterogeneity both across
different NN models and across different NN layers within the same NN model,
leading to the shortcomings we observe.
  We propose a new acceleration framework called Mensa. Mensa incorporates
multiple heterogeneous edge ML accelerators (including both on-chip and
near-data accelerators), each of which caters to the characteristics of a
particular subset of NN models and layers. During NN inference, for each NN
layer, Mensa decides which accelerator to schedule the layer on, taking into
account both the optimality of each accelerator for the layer and
layer-to-layer communication costs. Averaged across all 24 Google edge NN
models, Mensa improves energy efficiency and throughput by 3.0x and 3.1x over
the Edge TPU, and by 2.4x and 4.3x over Eyeriss~v2, a state-of-the-art
accelerator.


  We investigate a parallelization strategy for dense matrix factorization
(DMF) algorithms, using OpenMP, that departs from the legacy (or conventional)
solution, which simply extracts concurrency from a multithreaded version of
BLAS. This approach is also different from the more sophisticated
runtime-assisted implementations, which decompose the operation into tasks and
identify dependencies via directives and runtime support. Instead, our strategy
attains high performance by explicitly embedding a static look-ahead technique
into the DMF code, in order to overcome the performance bottleneck of the panel
factorization, and realizing the trailing update via a cache-aware
multi-threaded implementation of the BLAS. Although the parallel algorithms are
specified with a highlevel of abstraction, the actual implementation can be
easily derived from them, paving the road to deriving a high performance
implementation of a considerable fraction of LAPACK functionality on any
multicore platform with an OpenMP-like runtime.


  Handling missing data is crucial in machine learning, but many datasets
contain gaps due to errors or non-response. Unlike traditional methods such as
listwise deletion, which are simple but inadequate, the literature offers more
sophisticated and effective methods, thereby improving sample size and
accuracy. However, these methods require accessing the whole dataset, which
contradicts the privacy regulations when the data is distributed among multiple
sources. Especially in the medical and healthcare domain, such access reveals
sensitive information about patients. This study addresses privacy-preserving
imputation methods for sensitive data using secure multi-party computation,
enabling secure computations without revealing any party's sensitive
information. In this study, we realized the mean, median, regression, and kNN
imputation methods in a privacy-preserving way. We specifically target the
medical and healthcare domains considering the significance of protection of
the patient data, showcasing our methods on a diabetes dataset. Experiments on
the diabetes dataset validated the correctness of our privacy-preserving
imputation methods, yielding the largest error around $3 \times 10^{-3}$,
closely matching plaintext methods. We also analyzed the scalability of our
methods to varying numbers of samples, showing their applicability to
real-world healthcare problems. Our analysis demonstrated that all our methods
scale linearly with the number of samples. Except for kNN, the runtime of all
our methods indicates that they can be utilized for large datasets.


  Background. In recent years, libraries and archives led important
digitisation campaigns that opened the access to vast collections of historical
documents. While such documents are often available as XML ALTO documents, they
lack information about their logical structure. In this paper, we address the
problem of Logical Layout Analysis applied to historical documents in French.
We propose a rule-based method, that we evaluate and compare with two
Machine-Learning models, namely RIPPER and Gradient Boosting. Our data set
contains French newspapers, periodicals and magazines, published in the first
half of the twentieth century in the Franche-Comt\'e Region. Results. Our
rule-based system outperforms the two other models in nearly all evaluations.
It has especially better Recall results, indicating that our system covers more
types of every logical label than the other two models. When comparing RIPPER
with Gradient Boosting, we can observe that Gradient Boosting has better
Precision scores but RIPPER has better Recall scores. Conclusions. The
evaluation shows that our system outperforms the two Machine Learning models,
and provides significantly higher Recall. It also confirms that our system can
be used to produce annotated data sets that are large enough to envisage
Machine Learning or Deep Learning approaches for the task of Logical Layout
Analysis. Combining rules and Machine Learning models into hybrid systems could
potentially provide even better performances. Furthermore, as the layout in
historical documents evolves rapidly, one possible solution to overcome this
problem would be to apply Rule Learning algorithms to bootstrap rule sets
adapted to different publication periods.


  Let $G$ be a connected reductive group over a non-archimedean local field $F$
and $I$ be an Iwahori subgroup of $G(F)$. Let $I_n$ is the $n$-th Moy-Prasad
filtration subgroup of $I$. The purpose of this paper is two-fold: to give some
nice presentations of the Hecke algebra of connected, reductive groups with
$I_n$-level structure; and to introduce the Tits group of the Iwahori-Weyl
group of groups $G$ that split over an unramified extension of $F$.
  The first main result of this paper is a presentation of the Hecke algebra
$\mathcal H(G(F),I_n)$, generalizing the previous work of Iwahori-Matsumoto on
the affine Hecke algebras. For split $GL_n$, Howe gave a refined presentation
of the Hecke algebra $\mathcal H(G(F),I_n)$. To generalize such a refined
presentation to other groups requires the existence of some nice lifting of the
Iwahori-Weyl group $W$ to $G(F)$. The study of a certain nice lifting of $W$ is
the second main motivation of this paper, which we discuss below.
  In 1966, Tits introduced a certain subgroup of $G(\mathbf k)$, which is an
extension of $W$ by an elementary abelian $2$-group. This group is called the
Tits group and provides a nice lifting of the elements in the finite Weyl
group. The "Tits group" $\mathcal T$ for the Iwahori-Weyl group $W$ is a
certain subgroup of $G(F)$, which is an extension of the Iwahori-Weyl group $W$
by an elementary abelian $2$-group. The second main result of this paper is a
construction of Tits group $\mathcal T$ for $W$ when $G$ splits over an
unramified extension of $F$. As a consequence, we generalize Howe's
presentation to such groups. We also show that when $G$ is ramified over $F$,
such a group $\mathcal T$ of $W$ may not exist.


  Researchers from a broad spectrum of scientific and engineering disciplines
are increasingly using near-field infrared spectroscopic techniques to
characterize materials nondestructively and with nanoscale spatial resolution.
However, sub-optimal understanding of a technique's implementation can
complicate data interpretation and even act as a barrier to enter the field.
Here we outline the key detection and processing steps involved in producing
scattering-type near-field nanoscale Fourier transform infrared spectra
(nano-FTIR). The largely self-contained work (i) explains how normalized
complex-valued nano-FTIR spectra are generated, (ii) rationalizes how the real
and imaginary components of spectra relate to dispersion and absorption
respectively, (iii) derives a new and generally valid equation for spectra
which can be used as a springboard for additional modeling of the scattering
processes, and (iv) provides an algebraic expression that can be used to
extract the sample's local extinction coefficient from nano-FTIR. The algebraic
expression is validated with nano-FTIR and attenuated total reflectance Fourier
transform infrared (ATR-FTIR) spectra on samples of polystyrene and Kapton.


  We provide general sufficient conditions for the efficient classical
simulation of quantum-optics experiments that involve inputting states to a
quantum process and making measurements at the output. The first condition is
based on the negativity of phase-space quasiprobability distributions (PQDs) of
the output state of the process and the output measurements; the second one is
based on the negativity of PQDs of the input states, the output measurements,
and the transition function associated with the process. We show that these
conditions provide useful practical tools for investigating the effects of
imperfections in implementations of boson sampling. In particular, we apply our
formalism to boson-sampling experiments that use single-photon or
spontaneous-parametric-down-conversion sources and on-off photodetectors.
Considering simple models for loss and noise, we show that above some threshold
for the probability of random counts in the photodetectors, these
boson-sampling experiments are classically simulatable. We identify mode
mismatching as the major source of error contributing to random counts and
suggest that this is the chief challenge for implementations of boson sampling
of interesting size.


  Understanding the conditions which favor crystallisation or vitrification of
liquids has been a long-standing scientific problem. Another connected, and not
yet well understood question is the relationship between the glassy and the
various possible crystalline forms a system may adopt. In this context, B2O3 is
a puzzling case of study since i) it is one of the best glass-forming systems
despite an apparent lack of low-pressure polymorphism ii) it vitrifies in a
glassy form abnormally different from the only known crystalline phase at
ambient pressure iii) it never crystallises from the melt unless pressure is
applied, an intriguing behaviour known as the crystallisation anomaly. Here, by
means of ab-initio calculations, we discover the existence of novel B2O3
crystalline polymorphs with structural properties similar to the glass and
formation energies comparable to the known ambient crystal. The resulting
configurational degeneracy drives the system vitrification at ambient pressure.
The degeneracy is lifted under pressure, unveiling the origin of the
crystallisation anomaly. This work reconciles the behaviour of B2O3 with that
from other glassy systems and reaffirms the role played by polymorphism in a
system's ability to vitrify. Some of the predicted crystals are cage-like
materials entirely made of three-fold rings, opening new perspectives for the
synthesis of boron-based nanoporous materials.


  We apply Srednicki's regularization to extract the logarithmic term in the
entanglement entropy produced by tracing out a real, massless, scalar field
inside a three dimensional sphere in 3+1 flat spacetime. We find numerically
that the coefficient of the logarithm is -1/90 to 0.2 percent accuracy, in
agreement with an existing analytical result.


  Bernoulli convolutions are certain measures on the unit interval depending on
a parameter $\beta$ between 1 and 2. In spite of their simple definition, they
are not yet well understood. We study their two-dimensional density which
exists by a theorem of Solomyak. To each Bernoulli convolution, there is an
interval $D$ called the overlap region, and a map which assigns two values to
each point of $D$ and one value to all other points of $[0,1].$ There are two
types of finite orbits of these multivalued maps which correspond to zeros and
potential singularities of the density, respectively.
  Orbits which do not meet $D$ belong to an ordinary map called
$\beta$-transformation and exist for all $\beta>1.6182.$ They were studied by
Erd\"os, J\'oo, Komornik, Sidorov, de Vries and others as points with unique
addresses, and by Jordan, Shmerkin and Solomyak as points with maximal local
dimension. In the two-dimensional view, these orbits form address curves
related to the Milnor-Thurston itineraries in one-dimensional dynamics. The
curves depend smoothly on the parameter and represent quantiles of all
corresponding Bernoulli convolutions.
  Finite orbits which intersect $D$ have a network-like structure and can exist
only at Perron parameters $\beta.$ Their points are intersections of extended
address curves, and can have finite or countable number of addresses, as found
by Sidorov. For an uncountable number of parameters, the central point
$\frac12$ has only two addresses. The intersection of periodic address curves
can lead to singularities of the measures. We give examples which are not Pisot
or Salem parameters.
  It seems that all singularities of Bernoulli convolutions are related to
network-like orbits. The paper is self-contained and includes many
illustrations.


  An Adaptive Cruise Control (ACC) system allows vehicles to maintain a desired
headway distance to a preceding vehicle automatically. It is increasingly
adopted by commercial vehicles. Recent research demonstrates that the effective
use of ACC can improve the traffic flow through the adaptation of the headway
distance in response to the current traffic conditions. In this paper, we
demonstrate that a state-of-the-art intelligent ACC system performs poorly on
highways with ramps due to the limitation of the model-based approaches that do
not take into account appropriately the traffic dynamics on ramps in
determining the optimal headway distance. We then propose a dynamic adaptive
cruise control system (D-ACC) based on deep reinforcement learning that adapts
the headway distance effectively according to dynamically changing traffic
conditions for both the main road and ramp to optimize the traffic flow.
Extensive simulations are performed with a combination of a traffic simulator
(SUMO) and vehicle-to-everything communication (V2X) network simulator (Veins)
under numerous traffic scenarios. We demonstrate that D-ACC improves the
traffic flow by up to 70% compared with a state-of-the-art intelligent ACC
system in a highway segment with a ramp.


  Relative and center of mass cordinates are used to generalize mutually
unbiased bases (MUB) and define mutually unbiased bases (MUCB). Maximal
entangled states are given as product staes in the collective varibles


  Continuum robots are promising candidates for interactive tasks in medical
and industrial applications due to their unique shape, compliance, and
miniaturization capability. Accurate and real-time shape sensing is essential
for such tasks yet remains a challenge. Embedded shape sensing has high
hardware complexity and cost, while vision-based methods require stereo setup
and struggle to achieve real-time performance. This paper proposes the first
eye-to-hand monocular approach to continuum robot shape sensing. Utilizing a
deep encoder-decoder network, our method, MoSSNet, eliminates the computation
cost of stereo matching and reduces requirements on sensing hardware. In
particular, MoSSNet comprises an encoder and three parallel decoders to uncover
spatial, length, and contour information from a single RGB image, and then
obtains the 3D shape through curve fitting. A two-segment tendon-driven
continuum robot is used for data collection and testing, demonstrating accurate
(mean shape error of 0.91 mm, or 0.36% of robot length) and real-time (70 fps)
shape sensing on real-world data. Additionally, the method is optimized
end-to-end and does not require fiducial markers, manual segmentation, or
camera calibration. Code and datasets will be made available at
https://github.com/ContinuumRoboticsLab/MoSSNet.


  Let $x \ge 2$, let $N_x$ be an integer chosen uniformly at random from the
set $\mathbb Z \cap [1, x]$, and let $(V_1, V_2, \ldots)$ be a
Poisson--Dirichlet process of parameter $1$. We prove that there exists a
coupling of these two random objects such that $$ \mathbb E \, \sum_{i \ge 1}
|\log P_i- V_i\log x| \ll 1, $$ where the implied constant is absolute and $N_x
= P_1P_2 \cdots$ is the unique factorization of $N_x$ into primes or ones with
the $P_i$'s being non-increasing. This establishes a conjecture of Arratia
(2002) arXiv:1305.0941 who proved that the left-hand side in the above estimate
can be made $\ll \log\!\log x$. We also use this coupling to give a
probabilistic proof of the Dirichlet law for the average distribution of the
integer factorization into $k$ parts proved in 2023 by Leung arXiv:2206.14728
and we improve on its error term.


  The study of star clusters has advanced our understanding of stellar
evolution, Galactic chemical evolution and nucleosynthesis. Here we investigate
the composition of turn-off stars in the intriguing open cluster, NGC 6791,
which is old, but super-metal-rich with high-resolution (46,000) Keck/HIRES
spectra. We find [Fe/H] = +0.30 +/-0.02 from measurements of some 40 unblended,
unsaturated lines of both Fe I and Fe II in eight turn-off stars. Our O
abundances come from the O I triplet near 7774 A and we do a differential
analysis relative to the Sun from our Lunar spectrum also obtained with
Keck/HIRES. The O results are corrected for small nLTE effects. We find
consistent ratios of [O/Fe]n with a mean of $-$0.06 +/-0.02. This continues the
trend of decreasing [O/Fe] with increasing [Fe/H] found in field stars that are
also both old and metal-rich. The small range in our oxygen abundances is
consistent with a single population of stars. Our results for the alpha
elements [Mg/Fe], [Si/Fe], [Ca/Fe], and [Ti/Fe] are near solar and compare well
with those of the old, metal-rich field stars. The two Fe-peak elements, Cr and
Ni, are consistent with Fe. These turn-off-star abundances provide benchmark
abundances to investigate changes in the giants that might arise from
nuclear-burning and dredge-up processes. Determinations of upper limits were
found for Li by spectrum synthesis and these results support the prediction
from standard theory that higher-metallicity stars deplete more Li. Probably no
stars in NGC 6791 have retained their initial Li.


  In the past, several models of consciousness have become popular and have led
to the development of models for machine consciousness with varying degrees of
success and challenges for simulation and implementations. Moreover, affective
computing attributes that involve emotions, behavior and personality have not
been the focus of models of consciousness as they lacked motivation for
deployment in software applications and robots. The affective attributes are
important factors for the future of machine consciousness with the rise of
technologies that can assist humans. Personality and affection hence can give
an additional flavor for the computational model of consciousness in humanoid
robotics. Recent advances in areas of machine learning with a focus on deep
learning can further help in developing aspects of machine consciousness in
areas that can better replicate human sensory perceptions such as speech
recognition and vision. With such advancements, one encounters further
challenges in developing models that can synchronize different aspects of
affective computing. In this paper, we review some existing models of
consciousnesses and present an affective computational model that would enable
the human touch and feel for robotic systems.


  Supernova explosions into predecessor stellar winds can lead to particle
acceleration, which we suggest can explain most of the observed cosmic rays of
the nuclei of Helium and heavier elements, from GeV in particle energies up to
near $3 \, 10^9$ GeV, as well as electrons above about 30 GeV. We go through
the following steps:
  1) Using a postulated underlying principle that leads to transport
coefficients in a turbulent plasma, we derive the properties of energetic
particles accelerated in spherical shocks.
  2) We suggest that a dynamo working in the inner convection zone of an upper
main sequence star can lead to high magnetic field strengths.
  3) Such magnetic fields may put additional momentum into stellar winds from
the pressure gradient of the toroidal field.
  4) We derive a lower limit for the magnetic field strengths.
  5) There appears to be a critical Alfv\'enic Machnumber for electron
injection. With this concept we propose an explanation for the observed
proton/electron ratio in galactic cosmic rays at GeV energies.
  6) We check the model prediction quantitatively on cosmic ray spectrum and
chemical composition against airshower data and further cosmic ray data.
  7) Finally, we summarize various important caveats, and outline important
next steps as well as checks.


  Presentations of categories are a well-known algebraic tool to provide
descriptions of categories by means of generators, for objects and morphisms,
and relations on morphisms. We generalize here this notion, in order to
consider situations where the objects are considered modulo an equivalence
relation, which is described by equational generators. When those form a
convergent (abstract) rewriting system on objects, there are three very natural
constructions that can be used to define the category which is described by the
presentation: one consists in turning equational generators into identities
(i.e. considering a quotient category), one consists in formally adding
inverses to equational generators (i.e. localizing the category), and one
consists in restricting to objects which are normal forms. We show that, under
suitable coherence conditions on the presentation, the three constructions
coincide, thus generalizing celebrated results on presentations of groups, and
we extend those conditions to presentations of monoidal categories.


  Session-based Recommender Systems (SRSs) have been actively developed to
recommend the next item of an anonymous short item sequence (i.e., session).
Unlike sequence-aware recommender systems where the whole interaction sequence
of each user can be used to model both the short-term interest and the general
interest of the user, the absence of user-dependent information in SRSs makes
it difficult to directly derive the user's general interest from data.
Therefore, existing SRSs have focused on how to effectively model the
information about short-term interest within the sessions, but they are
insufficient to capture the general interest of users. To this end, we propose
a novel framework to overcome the limitation of SRSs, named ProxySR, which
imitates the missing information in SRSs (i.e., general interest of users) by
modeling proxies of sessions. ProxySR selects a proxy for the input session in
an unsupervised manner, and combines it with the encoded short-term interest of
the session. As a proxy is jointly learned with the short-term interest and
selected by multiple sessions, a proxy learns to play the role of the general
interest of a user and ProxySR learns how to select a suitable proxy for an
input session. Moreover, we propose another real-world situation of SRSs where
a few users are logged-in and leave their identifiers in sessions, and a
revision of ProxySR for the situation. Our experiments on real-world datasets
show that ProxySR considerably outperforms the state-of-the-art competitors,
and the proxies successfully imitate the general interest of the users without
any user-dependent information.


  Greedy Maximal Scheduling (GMS) is an attractive low-complexity scheme for
scheduling in wireless networks. Recent work has characterized its throughput
for the case when there is no fading/channel variations. This paper aims to
understand the effect of channel variations on the relative throughput
performance of GMS vis-a-vis that of an optimal scheduler facing the same
fading. The effect is not a-priori obvious because, on the one hand, fading
could help by decoupling/precluding global states that lead to poor GMS
performance, while on the other hand fading adds another degree of freedom in
which an event unfavourable to GMS could occur.
  We show that both these situations can occur when fading is adversarial. In
particular, we first define the notion of a {\em Fading Local Pooling factor
(F-LPF)}, and show that it exactly characterizes the throughput of GMS in this
setting. We also derive general upper and lower bounds on F-LPF. Using these
bounds, we provide two example networks - one where the relative performance of
GMS is worse than if there were no fading, and one where it is better.


  Numerical simulations play a key important role in modern cosmology. Examples
are plenty including the cosmic web - large scale structure of the distribution
of galaxies in space - which was first observed in N-body simulations and later
discovered in observations. The cuspy dark matter halo profiles, the
overabundance of satellites, the Too-Big-Too-Fail problem are other examples of
theoretical predictions that have a dramatic impact on recent developments in
cosmology and galaxy formation. Large observational surveys such as e.g. SDSS,
Euclid, and LSST are intimately connected with extensive cosmological
simulations that provide statistical errors and tests for systematics. Accurate
predictions for baryonic acoustic oscillations and redshift space distortions
from high-resolution and large-volume cosmological simulations are required for
interpretation of these large-scale galaxy/qso surveys. However, most of the
results from extensive computer simulations, that would be greatly beneficial
if publicly available, are still in hands of few research groups. Even when the
simulation data is available, sharing vast amounts of data can be overwhelming.
We argue that there is an effective and simple path to expand the data access
and dissemination of numerous results from different cosmological models. Here
we demonstrate that public access can be effectively provided with relatively
modest resources. Among different results, we release for the astronomical
community terabytes of raw data of th popular Bolshoi and MultiDark
simulations. We also provide numerous results that are focused on mimicking
observational data and galaxy surveys for major projects. Skies and Universes
is a community effort: data are produced and shared by many research groups. We
offer to other cosmologists and astronomers to host their data products in the
skiesanduniverses.org space.


  The estimation of 3D human body pose and shape from a single image has been
extensively studied in recent years. However, the texture generation problem
has not been fully discussed. In this paper, we propose an end-to-end learning
strategy to generate textures of human bodies under the supervision of person
re-identification. We render the synthetic images with textures extracted from
the inputs and maximize the similarity between the rendered and input images by
using the re-identification network as the perceptual metrics. Experiment
results on pedestrian images show that our model can generate the texture from
a single image and demonstrate that our textures are of higher quality than
those generated by other available methods. Furthermore, we extend the
application scope to other categories and explore the possible utilization of
our generated textures.


  Pairing plays an essential role in describing nuclear spectra and attempts to
describe it has a long history in nuclear physics. Many theoretical tools were
developed to treat the pairing problem either exactly or at various levels of
approximation. In this contribution to the proceedings of a conference honoring
the career of Taka Otsuka, recent developments in the exact solutions of the
pairing problem are described.


  Using the notion of a Lagrangian covering, W. Graham and D. Vogan proposed a
method of constructing representations from the coadjoint orbits for a complex
semisimple Lie group $G$. When the coadjoint orbit $\calO$ is nilpotent, a
representation of $G$ is attached to each orbital variety of $\calO$ in this
way. In the setting of classical groups, we show that whenever it is possible
to carry out the Graham-Vogan construction for an orbital variety of a
spherical $\mathcal{O}$, its infinitesimal character lies in a set of
characters attached to $\mathcal{O}$ by W. M. McGovern. Furthermore, we show
that it is possible to carry out the Graham-Vogan construction for a sufficient
number of orbital varieties to account for all the infinitesimal characters in
this set.


  Recent work has shown that distributed word representations can encode
abstract information from child-directed speech. In this paper, we use
diachronic distributed word representations to perform temporal modeling and
analysis of lexical development in children. Unlike all previous work, we use
temporally sliced corpus to learn distributed word representations of
child-speech and child-directed speech under a curriculum-learning setting. In
our experiments, we perform a lexical categorization task to plot the semantic
and syntactic knowledge acquisition trajectories in children. Next, we perform
linear mixed-effects modeling over the diachronic representational changes to
study the role of input word frequencies in the rate of word acquisition in
children. We also perform a fine-grained analysis of lexical knowledge transfer
from adults to children using Representational Similarity Analysis. Finally, we
perform a qualitative analysis of the diachronic representations from our
model, which reveals the grounding and word associations in the mental lexicon
of children. Our experiments demonstrate the ease of usage and effectiveness of
diachronic distributed word representations in modeling lexical development.


  Opioid peptides are well-known modulators of the central control of
reproduction. Among them, dynorphin coexpressed in kisspeptin (KP) neurons of
the arcuate nucleus (ARC) has been thoroughly studied for its autocrine effect
on KP release through $\kappa$ opioid receptors. Other studies have suggested a
role for $\beta$-endorphin (BEND), a peptide cleaved from the
proopiomelanocortin (POMC) precursor, on food intake and central control of
reproduction. Similarly to KP, BEND content in the ARC of sheep is modulated by
day length and BEND modulates food intake in a dose-dependent manner. As KP
levels in the ARC vary with photoperiodic and metabolic status, a
photoperiod-driven influence of BEND neurons on neighboring KP neurons is
plausible. The aim of this study was therefore to investigate a possible
modulatory action of BEND on KP neurons located in the ovine ARC. Using
confocal microscopy, numerous KP appositions on BEND neurons were found but
there was no photoperiodic variation in the number of these interactions in
ovariectomized, estradiol-replaced ewes. In contrast, BEND terminals on KP
neurons were twice as numerous under short days (SD), in ewes having an
activated gonadotropic axis, as compared to anestrus ewes under long days (LD).
Injection of 5$\mu$g BEND into the third ventricle of SD ewes induced a
significant and specific increase of activated KP neurons (16% versus 9% in
controls) while the percentage of overall activated (c-Fos positive) neurons,
was similar between both groups. These data suggest a photoperiod-dependent
influence of BEND on KP neurons of the ARC, which may influence GnRH pulsatile
secretion and inform KP neurons on the metabolic status.


  Let $X$ be a non-empty set and $\sP(X)$ be its power set. A set-valuation or
a set-labeling of a given graph $G$ is an injective function $f:V(G) \to
\sP(X)$ such that the induced function $f^{\ast}:E(G) \to \sP(X)$ defined by
$f^{\ast} (uv) = f(u)\ast f(v)$, where $\ast$ is a binary operation on sets. A
set-indexer of a graph $G$ is an injective set-valued function $f:V(G) \to
\sP(X)$ such that the induced function $f^{\ast}:E(G) \to \sP(X)$ is also
injective. In this paper, two types of set-labelings, called conjunctive
set-labeling and disjunctive set-labeling, of graphs are introduced and some
properties and characteristics of these types of set-labelings of graphs are
studied.


  The thermodynamic properties of a non-interacting ideal Hadron Resonance Gas
(HRG) of finite volume have been studied in the presence of an external
magnetic field. The inclusion of background magnetic field in the calculation
of thermodynamic potential is done by the modification of the dispersion
relations of the charged hadrons in terms of Landau quantization. The
generalized Matsubara prescription has been employed to take into account the
finite size effects in which a periodic (anti-periodic) boundary conditions is
considered for the mesons (baryons). We find significant effects of the
magnetic field as well as system size on the temperature dependence of energy
density, longitudinal and transverse pressure especially in low temperature
regions. The HRG is found to exhibit diamagnetism (paramagnetism) in the low
(high) temperature region whereas the finite size effect is seen to strengthen
the diamagnetic behavior of the medium.


  We apply the dynamical systems tools to study the (linear) dynamics of
Friedmann-Robertson-Walker universes that are fuelled by non-linear
electrodynamics. We focus, mainly, in two particular models. In the first model
the cosmic evolution is fuelled by cold dark matter, a cosmological constant
and a non-linear electrodynamics field. In the second case non-singular
cosmology and late-time accelerated expansion are unified in a model where the
Einstein's field equations are sourced only by cold dark matter and a
non-linear electrodynamics field. It is shown that, in contrast to previous
claims, the cosmological effects coming from the non-linear electrodynamics
field are not as generic as though. In fact, critical points in the phase space
that could be associated with non-linear electrodynamic effects are not found.


  The dynamics of dislocations confined to grain boundaries in a striped system
are studied using electroconvection in the nematic liquid crystal N4. In
electroconvection, a striped pattern of convection rolls forms for sufficiently
high driving voltages. We consider the case of a rapid change in the voltage
that takes the system from a uniform state to a state consisting of striped
domains with two different wavevectors. The domains are separated by domain
walls along one axis and a grain boundary of dislocations in the perpendicular
direction. The pattern evolves through dislocation motion parallel to the
domain walls. We report on features of the dislocation dynamics. The kinetics
of the domain motion are quantified using three measures: dislocation density,
average domain wall length, and the total domain wall length per area. All
three quantities exhibit behavior consistent with power law evolution in time,
with the defect density decaying as $t^{-1/3}$, the average domain wall length
growing as $t^{1/3}$, and the total domain wall length decaying as $t^{-1/5}$.
The two different exponents are indicative of the anisotropic growth of domains
in the system.


  Large elliptic flow at RHIC seems to indicate that ideal hydrodynamics
provides a good description of Au-Au collisions, at least at the maximum RHIC
energy. The medium formed has been interpreted as a nearly perfect
(low-viscosity) liquid, and connections have been made to gravitation through
string theory. Recently, claimed observations of large flow fluctuations
comparable to participant eccentricity fluctuations seem to confirm the ideal
hydro scenario. However, determination of the azimuth quadrupole with 2D
angular autocorrelations, which accurately distinguish ``flow'' (quadrupole)
from ``nonflow'' (minijets), contradicts conventional interpretations.
Centrality trends may depend only on the initial parton geometry, and methods
used to isolate flow fluctuations are sensitive instead mainly to minijet
correlations. The results presented in this paper suggest that the azimuth
quadrupole may be a manifestation of gluonic multipole radiation.


  In an ultrahigh mobility 2D electron gas, even a weak nonparabolicity of the
electron dispersion, by violating Kohn's theorem, can have a drastic effect on
dc magnetotransport under ac drive. We study theoretically the manifestation of
this effect in the dc response to the combined action of two driving ac-fields
(bichromatic irradiation). Compared to the case of monochromatic irradiation,
which is currently intensively studied both experimentally and theoretically,
the presence of a second microwave source provides additional insight into the
properties of an ac-driven 2D electron gas. In particular, we find that
nonparabolicity, being the simplest cause for a violation of Kohn's theorem,
gives rise to new qualitative effects specific to bichromatic irradiation.
Namely, when the frequencies $\omega_1$ and $\omega_2$ are well away from the
cyclotron frequency, $\omega_c$, our simple classical considerations
demonstrate that the system becomes parametrically unstable with respect to
fluctuations with frequency $(\omega_1+\omega_2)/2$. As an additional effect of
nonparabolicity, this parametric instability can manifest itself in the dc
properties of the system. This happens when $\omega_1$, $\omega_2$ and
$\omega_c$ are related as 3:1:2, respectively. Even for weak detuning between
$\omega_1$ and $\omega_2$, the effect of the bichromatic irradiation on the dc
response in the presence of nonparabolicity can differ dramatically from the
monochromatic case. In particular, the equations of motion can acquire
multistable solutions. As a result, the diagonal dc-conductivity can assume
several stable negative values at the same magnetic field.


  Power-suppressed corrections to parton evolution may affect the theoretical
accuracy of current determinations of parton distributions. We study the role
of multigluon-exchange terms in the extraction of the gluon distribution for
the Large Hadron Collider (LHC). Working in the high-energy approximation, we
analyze multi-gluon contributions in powers of 1/Q^2. We find a moderate,
negative correction to the structure function's derivative d F_2 / d \ln Q^2,
characterized by a slow fall-off in the region of low to medium Q^2 relevant
for determinations of the gluon at small momentum fractions.


  Techniques to achieve various forms of test coverage, such as branch
coverage, typically do not iterate loops; in other words, they treat a loop as
a conditional, executed zero or one time. Existing work by the author and
collaborators produces test suites guaranteeing full branch coverage. More
recent work has shown that by unrolling loops the approach can find
significantly more bugs. The present discussion provides the theoretical basis
and precise definition for this concept of unrolling.