  The double electron E1 transition energies, probabilities, and oscillator
strengths between the $2s2p^{n}$ and $1s^{2}2p^{n-1}$($1\!\leq\!n\leq\!6$)
configurations of Xe$^{q+}$($47\!\leq\!q\leq\!52$) ions with different
spectator electrons have been calculated based on the multi-configuration
Dirac-Hartree-Fock method. A reasonable electron correlation model is
constructed with the aid of the active space method. The finite mass of
nuclear, Breit interaction and QED effects have also been included. The
calculated results are in good agreement with the available data. The
theoretical spectra of different spectator electrons of the double K hole state
have been predicted. The spectator electron effects on the transition spectra
have been analyzed in detail. The present results will be helpful for analyzing
the high energy X-ray spectrum observed from the interaction between high
energy highly charged ions and the surface.


  We study the virtual effects of unparticle physics in the lepton flavor
violating processes $M^0\to l^+l'^-$ and $e^+e^-\to l^+l'^-$ scattering, where
$M^0$ denotes the pseudoscalar mesons: $\pi^0,K_L, D_0,B_0,B_s^0$ and $l,l'$
denote two different lepton flavors. For the decay of $B^0\to l^+l'^-$, there
is no constraint from the current experimental upper bounds on the vector
unparticle coupling with leptons. The constraint on the coupling constant
between scalar unparticle field and leptons is sensitive to the scaling
dimension of the unparticle $d_{\cal U}$. For the scattering process $e^-e^+\to
l^-l'^+$, there is only constraint from experiments on the vector unparticle
couplings with leptons but no constraint on the scalar unparticle. We study the
$\sqrt s$ dependence of the cross section $ \frac{1}{\sigma}
\frac{d\sigma}{d\sqrt s}$ of $e^+e^-\to l^-l'^+$ with different values of
$d_{\cal U}$. If $d_{\cal U}=1.5$, the cross section is independent on the
center mass energy. For $d_{\cal U}>1.5$, the cross section increases with
$\sqrt s$.


  Physics-informed neural networks (PINNs) as a means of solving partial
differential equations (PDE) have garnered much attention in the Computational
Science and Engineering (CS&E) world. However, a recent topic of interest is
exploring various training (i.e., optimization) challenges - in particular,
arriving at poor local minima in the optimization landscape results in a PINN
approximation giving an inferior, and sometimes trivial, solution when solving
forward time-dependent PDEs with no data. This problem is also found in, and in
some sense more difficult, with domain decomposition strategies such as
temporal decomposition using XPINNs. We furnish examples and explanations for
different training challenges, their cause, and how they relate to information
propagation and temporal decomposition. We then propose a new
stacked-decomposition method that bridges the gap between time-marching PINNs
and XPINNs. We also introduce significant computational speed-ups by using
transfer learning concepts to initialize subnetworks in the domain and loss
tolerance-based propagation for the subdomains. Finally, we formulate a new
time-sweeping collocation point algorithm inspired by the previous PINNs
causality literature, which our framework can still describe, and provides a
significant computational speed-up via reduced-cost collocation point
segmentation. The proposed methods form our unified framework, which overcomes
training challenges in PINNs and XPINNs for time-dependent PDEs by respecting
the causality in multiple forms and improving scalability by limiting the
computation required per optimization iteration. Finally, we provide numerical
results for these methods on baseline PDE problems for which unmodified PINNs
and XPINNs struggle to train.


  We summarize recent progress in applying the worldline formalism to the
analytic calculation of one-loop N-point amplitudes. This string-inspired
approach is well-adapted to avoiding some of the calculational inefficiencies
of the standard Feynman diagram approach, most notably by providing master
formulas that sum over diagrams differing only by the position of external legs
and/or internal propagators. We illustrate the mathematical challenge involved
with the low-energy limit of the N-photon amplitudes in scalar and spinor QED,
and then present an algorithm that, in principle, solves this problem for the
much more difficult case of the N-point amplitudes at full momentum in phi^3
theory. The method is based on the algebra of inverse derivatives in the
Hilbert space of periodic functions orthogonal to the constant ones, in which
the Bernoulli numbers and polynomials play a central role.


  We discuss the mean-field dynamo action in protoneutron stars that are
subject to instabilities during the early evolutionary phase. The mean field is
generated in the neutron-finger unstable region where the Rossby number is
$\sim 1$ and mean-field dynamo is efficient. Depending on the rotation rate,
the mean-field dynamo can lead to the formation of three different types of
pulsars. If the initial period of the protoneutron star is short, then the
generated large-scale field is very strong ($> 3 \times 10^{13}$G) and exceeds
the small-scale field at the neutron star surface. If rotation is moderate,
then the pulsars are formed with more or less standard dipole fields ($< 3
\times 10^{13}$G) but with surface small-scale magnetic fields stronger than
the dipole field. If rotation is very slow, then the mean-field dynamo does not
operate, and the neutron star has no global field. Nevertheless, strong
small-scale fields are generated in such pulsars, and they can manifest
themselves as objects with very low spin-down rate but with a strong magnetic
field inferred from the spectral features.


  The non-perturbative functional renormalisation group (FRG) approach is
employed to study the Bose polaron problem at finite temperatures in the regime
of strong attractive bath-impurity interactions. Both two- and
three-dimensional configurations are considered. The appearance of two polaron
quasiparticle branches at finite temperatures is revealed, consistent with
recent findings by other analytical techniques. Then, ground-state polaron
energies are reported for selected interactions and temperatures within the gas
superfluid phase.


  Several hadronic observables have been studied in central 158 A GeV Pb+Pb
collisions using data measured by the WA98 experiment at CERN: single negative
pion and kaon production, as well as two- and three-pion interferometry. The
Wiedemann-Heinz hydrodynamical model has been fitted to the pion spectrum,
giving an estimate of the temperature and transverse flow velocity.
Bose-Einstein correlations between two identified negative pions have been
analysed as a function of kT, using two different parameterizations. The
results indicate that the source does not have a strictly boost invariant
expansion or spend time in a long-lived intermediate phase. A comparison
between data and a hydrodynamical based simulation shows very good agreement
for the radii parameters as a function of kT. The pion phase-space density at
freeze-out has been measured and agrees well with the Tomasik-Heinz model. A
large pion chemical potential close to the condensation limit of the pion mass
seems to be excluded. The three-pion Bose-Einstein interferometry shows a
substantial contribution of the genuine three-pion correlation, but not quite
as large as expected for a fully chaotic and symmetric source.


  Querying very large RDF data sets in an efficient manner requires a
sophisticated distribution strategy. Several innovative solutions have recently
been proposed for optimizing data distribution with predefined query workloads.
This paper presents an in-depth analysis and experimental comparison of five
representative and complementary distribution approaches. For achieving fair
experimental results, we are using Apache Spark as a common parallel computing
framework by rewriting the concerned algorithms using the Spark API. Spark
provides guarantees in terms of fault tolerance, high availability and
scalability which are essential in such systems. Our different implementations
aim to highlight the fundamental implementation-independent characteristics of
each approach in terms of data preparation, load balancing, data replication
and to some extent to query answering cost and performance. The presented
measures are obtained by testing each system on one synthetic and one
real-world data set over query workloads with differing characteristics and
different partitioning constraints.


  The s-wave scattering of $\Sigma_c \bar{D}$ and $\Sigma_c \bar{D}^*$ in the
$I(J^P) = \frac{1}{2}(\frac{1}{2}^-)$ channel is calculated in lattice QCD
using two ensembles with different volumes but the same lattice spacing $a\sim
0.08\mathrm{fm}$ and pion mass $M_\pi \sim 294\mathrm{MeV}$. The scattering
amplitudes near threshold are obtained by L\"uscher's finite volume method. We
find bound state poles in both $\Sigma_c \bar{D}$ and $\Sigma_c \bar{D}^*$
channels, which are possibly related to the $P_c(4312)$ and $P_c(4440) /
P_c(4457)$ pentaquarks observed in experiments. The binding energy is
$6(2)(2)$MeV for $\Sigma_c \bar{D}$ and $7(3)(1)$MeV for $\Sigma_c \bar{D}^*$,
where the first error is the statistical error and the second is the systematic
error due to the lattice artifacts.


  Accessibility assessments typically focus on determining a binary measurement
of task performance success/failure; and often neglect to acknowledge the
nuances of those interactions. Although a large population of blind people find
smartphone interactions possible, many experiences take a significant toll and
can have a lasting negative impact on the individual and their willingness to
step out of technological comfort zones. There is a need to assist and support
individuals with the adoption and learning process of new tasks to mitigate
these negative experiences. We contribute with a human-powered nonvisual task
assistant for smartphones to provide pervasive assistance. We argue, in
addition to success, one must carefully consider promoting and evaluating
factors such as self-efficacy and the belief in one's own abilities to control
and learn to use technology. In this paper, we show effective assistant
positively affects self-efficacy when performing new tasks with smartphones,
affects perceptions of accessibility and enables systemic task-based learning.


  In this letter, we investigate the impact of environment on integrated and
spatially-resolved stellar kinematics of a sample of massive, quiescent
galaxies at intermediate redshift ($0.6<z<1.0$). For this analysis, we combine
photometric and spectroscopic parameters from the UltraVISTA and Large Early
Galaxy Astrophysics Census (LEGA-C) surveys in the COSMOS field and
environmental measurements. We analyze the trends with overdensity (1+$\delta$)
on the rotational support of quiescent galaxies and find no universal trends at
either fixed mass or fixed stellar velocity dispersion. This is consistent with
previous studies of the local Universe; rotational support of massive galaxies
depends primarily on stellar mass. We highlight two populations of massive
galaxies ($\log M_\star/M_\odot\geq11$) that deviate from the average mass
relation. First, the most massive galaxies in the most under-dense regions
($(1+\delta)\leq1$) exhibit elevated rotational support. Similarly, at the
highest masses ($\log M_\star/M_\odot\geq11.25$) the range in rotational
support is significant in all but the densest regions. This corresponds to an
increasing slow-rotator fraction such that only galaxies in the densest
environments ($(1+\delta)\geq3.5$) are primarily (90$\pm$10\%)
slow-rotators.This effect is not seen at fixed velocity dispersion, suggesting
minor merging as the driving mechanism: only in the densest regions have the
most massive galaxies experienced significant minor merging, building stellar
mass and diminishing rotation without significantly affecting the central
stellar velocity dispersion. In the local Universe, most massive galaxies are
slow-rotators, regardless of environment, suggesting minor merging occurs at
later cosmic times $(z\lesssim0.6)$ in all but the most dense environments.


  The word-based account of saccades drawn by a central gravity of the PVL is
supported by two pillars of evidences. The first is the finding of the initial
fixation location on a word resembled a normal distribution (Rayner, 1979). The
other is the finding of a moderate slope coefficient between the launch site
and the landing site (b=0.49, see McConkie, Kerr, Reddix, & Zola, 1988). Four
simulations on different saccade targeting strategies and one eye-movement
experiment of Chinese reading have been conducted to evaluate the two findings.
We demonstrated that the current understanding of the word-based account is not
conclusive by showing an alternative strategy of the word-based account and
identifying the problem with the calculation of the slope coefficient. Although
almost all the computational models of eye-movement control during reading have
built on the two findings, future efforts should be directed to understand the
precise contribution of different saccade targeting strategies, and to know how
their weighting might vary across desperate writing systems.


  This paper delves into a fundamental aspect of quantum statistical mechanics
-- the absence of thermal phase transitions in one-dimensional (1D) systems.
Originating from Ising's analysis of the 1D spin chain, this concept has been
pivotal in understanding 1D quantum phases, especially those with finite-range
interactions as extended by Araki. In this work, we focus on quantum long-range
interactions and successfully derive a clustering theorem applicable to a wide
range of interaction decays at arbitrary temperatures. This theorem applies to
any interaction forms that decay faster than $r^{-2}$ and does not rely on
translation invariance or infinite system size assumptions. Also, we rigorously
established that the temperature dependence of the correlation length is given
by $e^{{\rm const.} \beta}$, which is the same as the classical cases. Our
findings indicate the absence of phase transitions in 1D systems with
super-polynomially decaying interactions, thereby expanding upon previous
theoretical research. To overcome significant technical challenges originating
from the divergence of the imaginary-time Lieb-Robinson bound, we utilize the
quantum belief propagation to refine the cluster expansion method. This
approach allowed us to address divergence issues effectively and contributed to
a deeper understanding of low-temperature behaviors in 1D quantum systems.


  In this Letter we study the connection between the large-scale dynamics of
the turbulence cascade and particle heating on kinetic scales. We find that the
inertial range turbulence amplitude ($\delta B_i$; measured in the range of
0.01-0.1 Hz) is a simple and effective proxy to identify the onset of
significant ion heating and when it is combined with $\beta_{||p}$, it
characterizes the energy partitioning between protons and electrons
($T_p/T_e$), proton temperature anisotropy ($T_{\perp}/T_{||}$) and scalar
proton temperature ($T_p$) in a way that is consistent with previous
predictions. For a fixed $\delta B_i$, the ratio of linear to nonlinear
timescales is strongly correlated with the scalar proton temperature in
agreement with Matthaeus et al., though for solar wind intervals with
$\beta_{||p}>1$ some discrepancies are found. For a fixed $\beta_{||p}$, an
increase of the turbulence amplitude leads to higher $T_p/T_e$ ratios, which is
consistent with the models of Chandran et al. and Wu et al. We discuss the
implications of these findings for our understanding of plasma turbulence.


  We investigate some interesting properties of Bernstein polynomials
associated with boson p-adic integrals on Zp.


  Graphs are arguably one of the most fundamental data-structure used in many
domains such as block-chain, networks etc. Theoretically and practically,
improving Graph performance is one of the most studied and omnipresent research
problems. In this paper, we have implemented a dynamic unbounded concurrent
graph which can perform the add, delete or lookup operations on vertices and
edges concurrently. All these methods are lock-free and linearizable. On top of
this, we have also implemented the wait-free graph snapshot algorithm. To the
best of knowledge this is first wait-free implementation of snapshot on
concurrent graphs. We have used the snapshot of the algorithm to calculate the
diameter and between centrality. We have compared our implementation with its
counterparts and outperformed them by a good margin. This illustrates the
efficiency of our snapshot method which is a generic method and can be used to
perform other useful graph analytics operations.


  Picosecond laser pulses have been used as a surface colouring technique for
noble metals, where the colours result from plasmonic resonances in the
metallic nanoparticles created and redeposited on the surface by ablation and
deposition processes. This technology provides two datasets which we use to
train artificial neural networks, data from the experiment itself (laser
parameters vs. colours) and data from the corresponding numerical simulations
(geometric parameters vs. colours). We apply deep learning to predict the
colour in both cases. We also propose a method for the solution of the inverse
problem -- wherein the geometric parameters and the laser parameters are
predicted from colour -- using an iterative multivariable inverse design
method.


  We develop an $L^p(\mathbb{R}^n)$-functional calculus appropriated for
interpreting "non-classical symbols" of the form $a(-\Delta)$, and for proving
existence in $L^q(\mathbb{R}^n)$, some $q > p$, of solutions to nonlinear
pseudo-differential equations of the form $[1 + a(-\Delta)]^{s/2} (u) =
V(\cdot, u)$. More precisely, we use the theory of Fourier multipliers for
constructing suitable domains on which the formal operator appearing in the
above equation can be rigorously defined, and we prove existence of solutions
belonging to these domains. We also include applications of the theory to
equations of physical interest involving the fractional Laplace operator such
as the Allen-Cahn equation.


This paper has been withdrawn by the author


  The Tur\'{a}n number of a graph $H$, $ex(n,H)$, is the maximum number of
edges in any graph of order $n$ which does not contain $H$ as a subgraph.
Lidick\'{y}, Liu and Palmer determined $ex(n, F_m)$ for $n$ sufficiently large
and proved that the extremal graph is unique, where $F_m$ is disjoint paths of
$P_{k_1}, \ldots, P_{k_m}$ [Lidick\'{y},B., Liu,H. and Palmer,C. (2013). On the
Tur\'{a}n number of forests. Electron. J. Combin. 20(2) Paper 62, 13 pp]. In
this paper, by mean of a different approach, we determine $ex(n, F_m)$ for all
integers $n$ with minor conditions, which extends their partial results.
Furthermore, we partly confirm the conjecture proposed by Bushaw and Kettle for
$ex(n, k\cdot P_l)$ [Bushaw,N. and Kttle,N. (2011) Tur\'{a}n numbers of
multiple paths and equibipartite forests. Combin. Probab. Comput. 20 837-853].
Moreover, we show that there exist two family graphs $F_m$ and $F_m^{\prime}$
such that $ex(n, F_m)=ex(n, F_m^{\prime})$ for all integers $n$, which is
related to an old problem of Erd\H{o}s and Simonovits.


  Analyzing the effective conformal field theory for the parafermionic Hall
states, corresponding to filling fractions nu_k=2+k/(kM+2), k=2,3,..., M odd,
we show that the even k plateaux are expected to be more stable than their odd
k neighbors. The reason is that the parafermion chiral algebra can be locally
extended for k even. This reconciles the theoretical implication, that the
bigger the k the less stable the fluid, with the experimental fact that, for
M=1, the k=2 and k=4 plateaux are already observed at electron temperature
T_e~8 mK, while the Hall resistance for k=3 is not precisely quantized at that
temperature in the sample of Pan et al. Using a heuristic gap ansatz we
estimate the activation energy gap for nu_3=13/5 to be approximately 0.015 K,
which implies that the quantization of the Hall conductance could be observed
for temperature below 1 mK in the same sample. We also find an appealing exact
relation between the fractional electric charge and fractional statistics of
the quasiholes. Finally, we argue that besides the Moore-Read phase for the
nu_2=5/2 state there is another relevant phase, in which the fundamental
quasiholes obey abelian statistics and carry half-integer electric charge.


  Deterministic photon sources allow long-term advancements in quantum optics.
A single quantum emitter embedded in a photonic resonator or waveguide may be
triggered to emit one photon at a time into a desired optical mode. By
coherently controlling a single spin in the emitter, multi-photon entanglement
can be realized. We demonstrate a deterministic source of three-qubit
entanglement based on a single electron spin trapped in a quantum dot embedded
in a planar nanophotonic waveguide. We implement nuclear spin narrowing to
increase the spin dephasing time to $T_2^* \simeq 33$ ns, which enables
high-fidelity coherent optical spin rotations, and realize a spin-echo pulse
sequence for sequential generation of high-fidelity spin-photon and
spin-photon-photon entanglement. The emitted photons are highly
indistinguishable, which is a key requirement for subsequent photon fusions to
realize larger entangled states. This work presents a scalable deterministic
source of multi-photon entanglement with a clear pathway for further
improvements, offering promising applications in photonic quantum computing or
quantum networks.


  Magnetic monopoles, despite their ongoing experimental search as elementary
particles, have inspired the discovery of analogous excitations in condensed
matter systems. In chiral condensed matter systems, emergent monopoles are
responsible for the onset of transitions between topologically distinct states
and phases, like in the case of transitions from helical and conical phase to
A-phase comprising periodic arrays of skyrmions. By combining numerical
modeling and optical characterizations, we describe how different geometrical
configurations of skyrmions terminating at monopoles can be realized in liquid
crystals and liquid crystal ferromagnets. We demonstrate how such complex
structures can be effectively manipulated by external magnetic and electric
fields. Furthermore, we discuss how our findings may hint at similar dynamics
in other physical systems, and their potential applications.


  In this paper, we analyze the constraints imposed by unitarity and crossing
symmetry on conformal theories in large dimensions. In particular, we show that
in a unitary conformal theory in large dimension $D$, the four-point function
of identical scalar operators $\phi$ with scaling dimension $\Delta_\phi$ such
that $\Delta_\phi/D<3/4$, is necessarily that of the generalized free field
theory. This result follows only from crossing symmetry and unitarity. In
particular, we do not impose the existence of a conserved spin two operator
(stress tensor). We also present an argument to extend the applicability of
this result to a larger range of conformal dimensions, namely to
$\Delta_\phi/D<1$. This extension requires some reasonable assumptions about
the spectrum of light operators. Together, these results suggest that if there
is a non-trivial conformal theory in large dimensions, not necessarily having a
stress tensor, then its relevant operators must be exponentially weakly coupled
with the rest.


  In this paper, we propose a methodology for the analysis of questionnaire
data along with its application on discovering insights from investor data
motivated by a day trading competition. The questionnaire includes categorical
questions, which are reduced to binary questions, 'yes' or 'no'. The
methodology reduces dimensionality by grouping questions and participants with
similar responses using clustering analysis. Rule discovery was performed by
using a conversion rate metric. Innovative visual representations were proposed
to validate the cluster analysis and the relation discovery between questions.
When crossing with financial data, additional insights were revealed related to
the recognized clusters.


  This work devotes to investigations of solar corona and solar wind plasma by
the method of radio probing with using of very long baseline interferometry
(VLBI). We performed the theoretical calculation of power spectrum of
interferometric response to radio source emission, passed through the turbulent
medium. Data of theoretical analysis are compared with results of international
VLBI experiments on investigations of solar wind plasma. The observations were
realized in 1998, 1999, 2000 with participation of radio telescopes, included
at Low Frequency VLBI Network (LFVN): Bear Lakes (RT-64, Russia), Puschino
(RT-22, Russia), Urumqi (RT-25, China), Noto (RT-32, Italy), Shanghai (RT-25,
China) and others. Preprocessing was carried out with using of S2 correlator at
Penticton (Canada). Post processing of experimental data was performed at RRI
(Russia) and was aimed to obtain value of solar wind velocity and index of
spatial spectrum of electron density fluctuations.


  We have measured, in real time, individual quasiparticle tunneling in a
single Cooper pair transistor, using rf reflectometry on the supercurrent
branch. We have extracted the even-to-odd and odd-to-even transition rates
directly by analyzing the distributions of dwell times in the even and odd
states of the transistor. We discuss both the measurement and analysis
techniques and report on the temperature and gate dependence of the
quasiparticle tunneling rates.


  A mechanism for generating massive but naturally light Dirac neutrinos is
proposed. It involves composite Higgs within the standard model as well as some
new interaction beyond the standard model. According to this scenario, a
neutrino mass of 0.1 eV or higher, signals new physics at energies of 10--100
TeV or lower.


  We study the dynamics of entanglement for a one-dimensional spin chain with a
nearest neighbor time dependent Heisenberg coupling J(t) between the spins in
presence of a time dependent external magnetic field h(t) at zero and finite
temperatures. We consider different forms of time dependence for the coupling
and magnetic field; exponential, hyperbolic and periodic. We examined the
system size effect on the entanglement asymptotic value. It was found that for
a small system size the entanglement starts to fluctuate within a short period
of time after applying the time dependent coupling. The period of time
increases as the system size increases and disappears completely as the size
goes to infinity. We also found that when J(t) is periodic the entanglement
shows a periodic behavior with the same period, which disappears upon applying
periodic magnetic field with the same frequency. Solving the particular case
where J(t) and h(t) are proportional exactly, we showed that the asymptotic
value of entanglement depends only on the initial conditions regardless of the
form of J(t) and h(t) applied at t > 0.


  We employ a first-principles computational workflow to screen for optically
accessible, high-spin point defects in wide band gap two-dimensional (2D)
crystals. Starting from an initial set of 5388 point defects, comprising both
intrinsic and extrinsic, single and double defects in ten previously
synthesised 2D host materials, we identify 596 defects with a triplet ground
state. For these defects, we calculate the defect formation energy, the
hyperfine (HF) coupling, and the zero-field splitting (ZFS) tensors. For 39
triplet transitions exhibiting particularly low Huang-Rhys factors, we
calculate the full photo-luminescence (PL) spectrum. Our approach reveals many
new spin defects with narrow PL line shapes and emission frequencies covering a
broad spectral range. Most of the defects are hosted in hexagonal BN, which we
ascribe to its high stiffness, but some are also found in MgI2, MoS2, MgBr2 and
CaI2. As specific examples, we propose the defects vSMoS0 and NiSMoS0 in MoS2
as interesting candidates with potential applications to magnetic field sensors
and quantum information technology. All the data will be made available in the
open access database QPOD.


  The SHApe Recovery from Partial textured 3D scans challenge, SHARP 2020, is
the first edition of a challenge fostering and benchmarking methods for
recovering complete textured 3D scans from raw incomplete data. SHARP 2020 is
organised as a workshop in conjunction with ECCV 2020. There are two
complementary challenges, the first one on 3D human scans, and the second one
on generic objects. Challenge 1 is further split into two tracks, focusing,
first, on large body and clothing regions, and, second, on fine body details. A
novel evaluation metric is proposed to quantify jointly the shape
reconstruction, the texture reconstruction and the amount of completed data.
Additionally, two unique datasets of 3D scans are proposed, to provide raw
ground-truth data for the benchmarks. The datasets are released to the
scientific community. Moreover, an accompanying custom library of software
routines is also released to the scientific community. It allows for processing
3D scans, generating partial data and performing the evaluation. Results of the
competition, analysed in comparison to baselines, show the validity of the
proposed evaluation metrics, and highlight the challenging aspects of the task
and of the datasets. Details on the SHARP 2020 challenge can be found at
https://cvi2.uni.lu/sharp2020/.


  In this paper we derive quantitative conditions under which a compactly
supported drift term blocks the propagation of a traveling wave in a straight
cylinder in dimension $n \geq 3$ under the condition that the drift has a
potential.


  The Lane-Emden system is written as \begin{equation*} \begin{cases} -\Delta u
= v^p &\text{in } \Omega,\\ -\Delta v = u^q &\text{in } \Omega,\\ u, v > 0
&\text{in } \Omega,\\ u = v = 0 &\text{on } \partial \Omega \end{cases}
\end{equation*} where $\Omega$ is a smooth bounded domain in the Euclidean
space $\mathbb{R}^n$ for $n \ge 3$ and $0< p< q <\infty$. The asymptotic
behavior of least energy solutions near the critical hyperbola was studied by
Guerra \cite{G} when $p \geq 1$ and the domain is convex. In this paper, we
cover all the remaining cases $p < 1$ and extend the results to any smooth
bounded domain.


  Reconfigurable intelligent surface (RIS) is a key technology to control the
communication environment in future wireless networks. Recently, beyond
diagonal RIS (BD-RIS) emerged as a generalization of RIS achieving larger
coverage through additional tunable impedance components interconnecting the
RIS elements. However, conventional RIS and BD-RIS can effectively serve only
users in their proximity, resulting in limited coverage. To overcome this
limitation, in this paper, we investigate distributed RIS, whose elements are
distributed over a wide region, in opposition to localized RIS commonly
considered in the literature. The scaling laws of distributed BD-RIS reveal
that it offers significant gains over distributed conventional RIS and
localized BD-RIS, enabled by its interconnections allowing signal propagation
within the BD-RIS. To assess the practical performance of distributed BD-RIS,
we model and optimize BD-RIS with lossy interconnections through transmission
line theory. Our model accounts for phase changes and losses over the BD-RIS
interconnections arising when the interconnection lengths are not much smaller
than the wavelength. Numerical results show that the performance of localized
BD-RIS is only slightly impacted by losses, given the short interconnection
lengths. Besides, distributed BD-RIS can achieve orders of magnitude of gains
over conventional RIS, even in the presence of low losses.


  In this work we show how a vector-valued version of Schechtman's empirical
method can be used to reduce the number of inputs in a nonlocal game $G$ while
preserving the quotient $\beta^*(G)/\beta(G)$ of the quantum over the classical
bias. We apply our method to the Khot-Vishnoi game, with exponentially many
questions per player, to produce another game with polynomially many ($N\approx
n^8$) questions so that the quantum over the classical bias is $\Omega
(n/\log^2 n)$.


  We consider abelian length categories, a generalization of module categories
over Artin algebras. Let $\mathcal{A}$ be an abelian length category of colocal
type. We show that the lattice $\mathsf{S}(\mathcal{A})$ of full additive
subobject closed subcategories of $\mathcal{A}$ is distributive. Furthermore,
we give a characterization of abelian length categories of colocal type.
  If $A$ is an algebra of colocal type over an algebraically closed field, then
this characterization is especially simple and we can describe the lattice
$\mathsf{S(mod} ~A)$ up to isomorphism.


  We give a selection of major open problems involving selective properties,
diagonalizations, and covering properties for sets of real numbers.
  This is a revision of the version published as a chapter in the book
\textbf{Open Problems in Topology II} (E. Pearl, ed.), Elsevier B.V., 2007,
91--108. The present version reports solutions of some problems, uses
up-to-date notation, and update bibliography.
  Comments and further updates would be appreciated.


  In this paper we study global nonlinear stability for a system of semilinear
wave and Klein-Gordon equations with quadratic nonlinearities. We consider
nonlinearities of the type of wave-Klein-Gordon interactions where there are no
derivatives on the wave component. The initial data are assumed to have a
suitable polynomial decay at infinity, but are not necessarily compactly
supported. We prove small data global existence, sharp pointwise decay
estimates and linear scattering results for the solutions. We give a sufficient
condition which combines the Sobolev norms of the nonlinearities on flat time
slices outside the light cone and the norms of them on truncated hyperboloids
inside the light cone, for the linear scattering of the solutions.


  Extended versions of the noncommutative(nc) KP equation and the nc mKP
equation are constructed in a unified way, for which two types of
quasideterminant solutions are also presented. In commutative setting, the
quasideterminant solutions provide the known and unknown Wronskian and Grammian
solutions for the bilinear KP equation with self-consistent sources and the
bilinear mKP equation with self-consistent sources, respectively. Miura
transformation is established for the extended nc KP and nc mKP equations.


  The hadronic contributions to the anomalous magnetic moments of the leptons
and to the effective fine structure constant at the Z-mass are reevaluated
using all presently available $e^+ e^-$ data.


  For the first time, we use the Gamma-ray Burst Monitor (GBM) on-board the
Fermi satellite to search for sterile neutrino decay lines in the energy range
10-25 keV corresponding to sterile neutrino mass range 20-50 keV. This energy
range has been out of reach of traditional X-ray satellites such as Chandra,
Suzaku, XMM-Newton, and gamma-ray satellites such as INTEGRAL. Furthermore, the
extremely wide field of view of the GBM opens a large fraction of the Milky Way
dark matter halo to be probed. We start with 1601 days worth of GBM data,
implement stringent data cuts, and perform two simple line search analyses on
the reduced data: in the first, the line flux is limited without background
modeling, and in the second, the background is modeled as a power-law. We find
no significant excess lines in both our searches. We set new limits on sterile
neutrino mixing angles, improving on previous limits by approximately an order
of magnitude. Better understanding of detector and astrophysical backgrounds,
as well as detector response, can further improve the limit.


  The causal structure for measurement bias (MB) remains controversial. Aided
by the Directed Acyclic Graph (DAG), this paper proposes a new structure for
measuring one singleton variable whose MB arises in the selection of an
imperfect I/O device-like measurement system. For effect estimation, however,
an extra source of MB arises from any redundant association between a measured
exposure and a measured outcome. The misclassification will be bidirectionally
differential for a common outcome, unidirectionally differential for a causal
relation, and non-differential for a common cause between the measured exposure
and the measured outcome or a null effect. The measured exposure can actually
affect the measured outcome, or vice versa. Reverse causality is a concept
defined at the level of measurement. Our new DAGs have clarified the structures
and mechanisms of MB.


  In this article, we give a natural geometric interpretation of Kirillov's
conjecture for tempered representations in the framework of orbit method. This
interpretation can also be considered as a first generalization of Duflo's
conjecture to non-discrete series representations.


  Compressed air energy storage is suitable for large-scale electrical energy
storage, which is important for integrating renewable energy sources into
electric power systems. A typical compressed air energy storage plant consists
of compressors, expanders, caverns, and a motor/generator set. Current cavern
models used for compressed air energy storage are either accurate but highly
nonlinear or linear but inaccurate. The application of highly nonlinear cavern
models in power system optimization problems renders them computationally
challenging to solve. In this regard, an accurate bilinear cavern model for
compressed air energy storage is proposed in this paper. The charging and
discharging processes in a cavern are divided into several real/virtual states.
The first law of thermodynamics and ideal gas law are then utilized to derive a
cavern model, i.e., a model for the variation of temperature and pressure in
these processes. Thereafter, the heat transfer between the air in the cavern
and the cavern wall is considered and integrated into the cavern model. By
subsequently eliminating several negligible terms, the cavern model reduces to
a bilinear model. The accuracy of the bilinear cavern model is verified via
comparison with both an accurate nonlinear model and two sets of field-measured
data. The bilinear cavern model can be easily linearized and is then suitable
for integration into optimization problems considering compressed air energy
storage. This is verified via comparatively solving a self-scheduling problem
of compressed air energy storage using different cavern models.


  Let $X$ be a K3 surface, let $C$ be a smooth curve of genus $g$ on $X$, and
let $A$ be a line bundle of degree $d$ on $C$. Then a line bundle $M$ on $X$
with $M\otimes\mathcal{O}_C=A$ is called a lift of $A$ . In this paper, we
prove that if the dimension of the linear system $|A|$ is $r\geq2$,
$g>2d-4+r(r-1)$, $d\geq 2r+4$, and $A$ computes the Clifford index of $C$, then
there exists a base point free lift $M$ of $A$ such that the general member of
$|M|$ is a smooth curve of genus $r$. In particular, if $|A|$ is a base point
free net which defines a double covering $\pi:C\longrightarrow C_0$ of a smooth
curve $C_0\subset\mathbb{P}^2$ of degree $k\geq 4$ branched at distinct $6k$
points on $C_0$, then, by using the aforementioned result, we can also show
that there exists a 2:1 morphism $\tilde{\pi}:X\longrightarrow \mathbb{P}^2$
such that $\tilde{\pi}|_C=\pi$.


  This work aims to study the dislocation or nodal lines of 3D Berry's random
wave model. Their expected length is computed both in the isotropic and
anisotropic cases, being them compared. Afterwards, in the isotropic case the
asymptotic variance and distribution of the length are obtained as the domain
grows to the whole space. Under some integrability condition on the covariance
function, a central limit theorem is established. The study includes the
Berry's monochromatic random waves, the Bargmann-Fock model and the Black-Body
radiation as well as a power law model that exhibits an unusual asymptotic
behaviour and yields a non-central limit theorem.


  Enhancement is an important step in post-processing digital images for
personal use, in medical imaging, and for object recognition. Most existing
manual techniques rely on region selection, similarity, and/or thresholding for
editing, never really considering the topological structure of the image. In
this paper, we leverage the contour tree to extract a hierarchical
representation of the topology of an image. We propose 4 topology-aware
transfer functions for editing features of the image using local topological
properties, instead of global image properties. Finally, we evaluate our
approach with grayscale and color images.


  In the management of lung nodules, we are desirable to predict nodule
evolution in terms of its diameter variation on Computed Tomography (CT) scans
and then provide a follow-up recommendation according to the predicted result
of the growing trend of the nodule. In order to improve the performance of
growth trend prediction for lung nodules, it is vital to compare the changes of
the same nodule in consecutive CT scans. Motivated by this, we screened out
4,666 subjects with more than two consecutive CT scans from the National Lung
Screening Trial (NLST) dataset to organize a temporal dataset called NLSTt. In
specific, we first detect and pair regions of interest (ROIs) covering the same
nodule based on registered CT scans. After that, we predict the texture
category and diameter size of the nodules through models. Last, we annotate the
evolution class of each nodule according to its changes in diameter. Based on
the built NLSTt dataset, we propose a siamese encoder to simultaneously exploit
the discriminative features of 3D ROIs detected from consecutive CT scans. Then
we novelly design a spatial-temporal mixer (STM) to leverage the interval
changes of the same nodule in sequential 3D ROIs and capture spatial
dependencies of nodule regions and the current 3D ROI. According to the
clinical diagnosis routine, we employ hierarchical loss to pay more attention
to growing nodules. The extensive experiments on our organized dataset
demonstrate the advantage of our proposed method. We also conduct experiments
on an in-house dataset to evaluate the clinical utility of our method by
comparing it against skilled clinicians.


  The multimodal web elements such as text and images are associated with
inherent memory costs to store and transfer over the Internet. With the limited
network connectivity in developing countries, webpage rendering gets delayed in
the presence of high-memory demanding elements such as images (relative to
text). To overcome this limitation, we propose a Canonical Correlation Analysis
(CCA) based computational approach to replace high-cost modality with an
equivalent low-cost modality. Our model learns a common subspace for low-cost
and high-cost modalities that maximizes the correlation between their visual
features. The obtained common subspace is used for determining the low-cost
(text) element of a given high-cost (image) element for the replacement. We
analyze the cost-saving performance of the proposed approach through an
eye-tracking experiment conducted on real-world webpages. Our approach reduces
the memory-cost by at least 83.35% by replacing images with text.


  We survey and compare recent approaches to the computation of the partition
functions and correlators of chiral BPS observables in $\mathcal{N}=2$ gauge
theories on ALE spaces based on quiver varieties and the minimal resolution
$X_k$ of the $A_{k-1}$ toric singularity $\mathbb{C}^2/\mathbb{Z}_k$, in light
of their recently conjectured duality with two-dimensional coset conformal
field theories. We review and elucidate the rigorous constructions of gauge
theories for a particular family of ALE spaces, using their relation to the
cohomology of moduli spaces of framed torsion free sheaves on a suitable
orbifold compactification of $X_k$. We extend these computations to generic
$\mathcal{N}=2$ superconformal quiver gauge theories, obtaining in these
instances new constraints on fractional instanton charges, a rigorous proof of
the Nekrasov master formula, and new quantizations of Hitchin systems based on
the underlying Seiberg-Witten geometry.


  (abbreviated) I will describe my work on proton Compton scattering in a
Unified Proton-Delta theory and on the computation of scattering amplitudes in
Yang-Mills theory.
  We study proton Compton scattering in the first resonance region in an
effective field theory approach with adviser Dr. Konstantin G. Savvidy. Proton
and $\Delta^+$ are naturally unified in the generalized Rarita-Schwinger theory
proposed by Savvidy. We introduce six non-minimal electromagnetic
interactions--with their coefficients being called "form factors"--and bare
polarizabilities in an effective Lagrangian. We express proton and Delta
magnetic moments and the electromagnetic polarizabilities in terms of the bare
polarizabilities and the form factors. We fit the form factors and bare
polarizabilities using experimental data and derive Delta magnetic moment from
the best fit values of the parameters.
  Then I present our joint work with adviser Dr. Gang Chen on the study of
boundary behavior of off-shell Yang-Mills amplitudes with a pair of external
momenta complexified. In Feynman gauge, we introduce a set of "reduced
vertices" which can capture the boundary behavior up to the first two leading
orders. We then prove a theorem on permutation sum for a given color ordering,
and use it to analyze the boundary behavior of amplitudes with two non-adjacent
legs complexified. Then we construct off-shell Britto-Cachazo-Feng-Witten
(BCFW) recursion relations and study relations between off-shell amplitudes.
  Finally, we study the recursion relations for off-shell Yang-Mills amplitudes
at tree and one loop levels as deduced from imposing complexified Ward
identity, also in collaboration with Dr. Gang Chen.


  The KATRIN experiment will determine the effective electron anti-neutrino
mass with a sensitivity of 200 meV/c$^2$ at 90% CL. The energy analysis of
tritium $\beta$-decay electrons will be performed by a tandem setup of
electrostatic retarding spectrometers which have to be operated at very low
background levels of $<10^{-2}$ counts per second. This benchmark rate can be
exceeded by background processes resulting from the emanation of single
$^{219,220}$Rn atoms from the inner spectrometer surface and an array of
non-evaporable getter strips used as main vacuum pump. Here we report on a the
impact of a cryogenic technique to reduce this radon-induced background in
electrostatic spectrometers. It is based on installing a liquid nitrogen cooled
copper baffle in the spectrometer pump port to block the direct line of sight
between the getter pump, which is the main source of $^{219}$Rn, and the
sensitive flux tube volume. This cold surface traps a large fraction of
emanated radon atoms in a region outside of the active flux tube, preventing
background there. We outline important baffle design criteria to maximize the
efficiency for the adsorption of radon atoms, describe the baffle implemented
at the KATIRN Pre-Spectrometer test set-up, and report on its initial
performance in suppressing radon-induced background.


  We derive a corrected analytical solution for the propagation and enhanced
phase mixing of torsional Alfv\'en waves, in a potential magnetic field with
exponentially divergent field lines, embedded in a stratified solar corona.
Further we develop a code named TAWAS which calculates the analytic solution
describing torsional Alfv\'en waves using IDL software language. We then use
TAWAS to demonstrate that both our correction to the analytic solution and the
inclusion of wave reflection have a significant impact on Alfv\'en wave
damping. We continue to utilise TAWAS by performing a parameter study in order
to identify the conditions under which enhanced phase mixing is strongest. We
find that phase mixing is the strongest for high frequency Alfv\'en waves in
magnetic fields with highly divergent field lines and without density
stratification. We then present a finite difference solver, Wigglewave, which
solves the linearised evolution equations for the system directly. Comparing
solutions from TAWAS and Wigglewave we see that our analytical solution is
accurate within the limits of the WKB approximation but under-reports the wave
damping, caused by enhanced phase mixing, beyond the WKB limit. Both TAWAS and
Wigglewave solve the linearised governing equations and not the complete
nonlinear MHD equations. Paper II will consider simulations that solve the full
MHD equations including important nonlinear effects.


  The description of design of advanced technological setup for the synthesis
of composite long-length superconducting tape on the basis of Nb3Sn is
presented. The design of setup has allowed us to produce the Nb3Sn tape with
the record magnitudes of density of critical current Jc in the magnetic fields
H of above 10 T (H > 10 T). The high current density conductivity property is
reached as a result of both the optimization of technological process of the
Nb3Sn tape synthesis and the increase of thickness of superconductor layer,
which is characterized by the homogeneous physical properties.


  We present a direct proof of the non-degeneracy of the harmonic structures on
the level-$n$ Sierpinski gaskets for any $n\geq 2$, which was conjectured by
Hino in [H1,H2] and confirmed to be true by Tsougkas [T] very recently using
Tutte's spring theorem.


  In this short essay we review the arguments showing that black hole entropy
is, at least in part, ``entanglement entropy", i.e., missing information
contained in correlations between quantum field fluctuations inside and outside
the event horizon. Although the entanglement entropy depends upon the matter
field content of the theory, it turns out that so does the Bekenstein-Hawking
entropy $A/4\hbar G_{ren}$, in precisely the same way, because the effective
gravitational constant $G_{ren}$ is renormalized by the very same quantum
fluctuations. It appears most satisfactory if the entire gravitational action
is ``induced", in the manner suggested by Sakharov, since then the black hole
entropy is purebred entanglement entropy, rather than being hybrid with bare
gravitational entropy (whatever that might be.)


  Different from the traditional recommender system, the session-based
recommender system introduces the concept of the session, i.e., a sequence of
interactions between a user and multiple items within a period, to preserve the
user's recent interest. The existing work on the session-based recommender
system mainly relies on mining sequential patterns within individual sessions,
which are not expressive enough to capture more complicated dependency
relationships among items. In addition, it does not consider the cross-session
information due to the anonymity of the session data, where the linkage between
different sessions is prevented. In this paper, we solve these problems with
the graph neural networks technique. First, each session is represented as a
graph rather than a linear sequence structure, based on which a novel Full
Graph Neural Network (FGNN) is proposed to learn complicated item dependency.
To exploit and incorporate cross-session information in the individual
session's representation learning, we further construct a Broadly Connected
Session (BCS) graph to link different sessions and a novel Mask-Readout
function to improve session embedding based on the BCS graph. Extensive
experiments have been conducted on two e-commerce benchmark datasets, i.e.,
Yoochoose and Diginetica, and the experimental results demonstrate the
superiority of our proposal through comparisons with state-of-the-art
session-based recommender models.


  We consider an unanswered question in the discourse processing community: why
do relation classifiers trained on explicit examples (with connectives removed)
perform poorly in real implicit scenarios? Prior work claimed this is due to
linguistic dissimilarity between explicit and implicit examples but provided no
empirical evidence. In this study, we show that one cause for such failure is a
label shift after connectives are eliminated. Specifically, we find that the
discourse relations expressed by some explicit instances will change when
connectives disappear. Unlike previous work manually analyzing a few examples,
we present empirical evidence at the corpus level to prove the existence of
such shift. Then, we analyze why label shift occurs by considering factors such
as the syntactic role played by connectives, ambiguity of connectives, and
more. Finally, we investigate two strategies to mitigate the label shift:
filtering out noisy data and joint learning with connectives. Experiments on
PDTB 2.0, PDTB 3.0, and the GUM dataset demonstrate that classifiers trained
with our strategies outperform strong baselines.


  We extend an operator P\'{o}lya--Szeg\"{o} type inequality involving the
operator geometric mean to any arbitrary operator mean under some mild
conditions. Utilizing the Mond--Pe\v{c}ari\'c method, we present some other
related operator inequalities as well.


  We briefly review some of the progress made in the last decade in the study
of the X-ray properties of the quasar population from the luminous, local
objects observed by BeppoSAX to the large, rapidly increasing population of z>4
quasars detected by Chandra and XMM-Newton in recent years.


  We present a comprehensive study of static and dynamic magnetic properties in
the Ising-like dipolar antiferromagnet (AFM) DyScO$_3$\ by means of DC and AC
magnetization measurements supported by classical Monte-Carlo calculations. Our
AC-susceptibility data show that the magnetic dynamics exhibit a clear
crossover from an Arrhenius-like regime to quantum tunneling of magnetization
(QTM) at $T^* = 10$ K. Below $T_{\mathrm{N}} = 3.2$ K DyScO$_3$ orders in an
antiferromagnetic $GxAy$-type magnetic structure and the magnetization dynamics
slow down to the minute timescale. The low-temperature magnetization curves
exhibit complex hysteretic behavior, which depends strongly on the magnetic
field sweep rate. We demonstrate that the low-field anomalies on the
magnetization curve are related to the metamagnetic transition, while the
hysteresis at higher fields is induced by a strong magnetocaloric effect. Our
theoretical calculations, which take into account dipolar interaction between
Dy$^{3+}$ moments, reproduce essential features of the magnetic behavior of
DyScO$_3$. We demonstrate that DyScO$_3$ represents a rare example of inorganic
compound, which exhibits QTM at a single-ion level and magnetic order due to
classical dipolar interaction.


  We present PLUTO, a powerful framework that pushes the limit of imitation
learning-based planning for autonomous driving. Our improvements stem from
three pivotal aspects: a longitudinal-lateral aware model architecture that
enables flexible and diverse driving behaviors; An innovative auxiliary loss
computation method that is broadly applicable and efficient for batch-wise
calculation; A novel training framework that leverages contrastive learning,
augmented by a suite of new data augmentations to regulate driving behaviors
and facilitate the understanding of underlying interactions. We assessed our
framework using the large-scale real-world nuPlan dataset and its associated
standardized planning benchmark. Impressively, PLUTO achieves state-of-the-art
closed-loop performance, beating other competing learning-based methods and
surpassing the current top-performed rule-based planner for the first time.
Results and code are available at https://jchengai.github.io/pluto.


  We show that a compound Poisson distribution holds for scaled exceedances of
observables $\phi$ uniquely maximized at a periodic point $\zeta$ in a variety
of two-dimensional hyperbolic dynamical systems with singularities $(M,T,\mu)$,
including the billiard maps of Sinai dispersing billiards in both the finite
and infinite horizon case. The observable we consider is of form $\phi (z)=-\ln
d(z,\zeta)$ where $d$ is a metric defined in terms of the stable and unstable
foliation. The compound Poisson process we obtain is a P\'olya-Aeppli
distibution of index $\theta$. We calculate $\theta$ in terms of the derivative
of the map $T$. Furthermore if we define $M_n=\max\{\phi,\ldots,\phi\circ
T^n\}$ and $u_n (\tau)$ by $\lim_{n\to \infty} n\mu (\phi >u_n (\tau) )=\tau$
the maximal process satisfies an extreme value law of form $\mu (M_n \le
u_n)=e^{-\theta \tau}$. These results generalize to a broader class of
functions maximized at $\zeta$, though the formulas regarding the parameters in
the distribution need to be modified.


  We have produced sensitive, high-resolution radio maps of 12 SMGs in the
Lockman Hole using combined MERLIN and VLA data at a frequency of 1.4 GHz.
Integrating for 350hr yielded an r.m.s. noise of 6.0 uJy/beam and a resolution
of 0.2-0.5". For the first time, wide-field data from the two arrays have been
combined in the (u,v) plane and the bandwidth smearing response of the VLA data
has been removed. All of the SMGs are detected in our maps as well as sources
comprising a non-submm luminous control sample. We find evidence that SMGs are
more extended than the general uJy radio population and that therefore, unlike
in local ULIRGs, the starburst component of the radio emission is extended and
not confined to the galactic nucleus. For the eight sources with redshifts we
measure linear sizes between 1 and 8 kpc with a median of 5 kpc. Therefore,
they are in general larger than local ULIRGs which may support an early-stage
merger scenario for the starburst trigger. X-rays betray AGN in six of the 33
sources in the combined sample. All but one of these are in the control sample,
suggesting a lower incidence of AGN amongst the submm-luminous galaxies which
is, in turn, consistent with increased X-ray absorption in these dust-obscured
starbursts. Only one of our sources is resolved into multiple, distinct
components with our high-resolution data. Finally, compared to a previous study
of faint radio sources in the GOODS-N field we find systematically smaller
source sizes and no evidence for a tail extending to ~4". Possible reasons for
this are discussed.


  In this work, we propose a new recurrent autoencoder architecture, termed
Feedback Recurrent AutoEncoder (FRAE), for online compression of sequential
data with temporal dependency. The recurrent structure of FRAE is designed to
efficiently extract the redundancy along the time dimension and allows a
compact discrete representation of the data to be learned. We demonstrate its
effectiveness in speech spectrogram compression. Specifically, we show that the
FRAE, paired with a powerful neural vocoder, can produce high-quality speech
waveforms at a low, fixed bitrate. We further show that by adding a learned
prior for the latent space and using an entropy coder, we can achieve an even
lower variable bitrate.


  Let $\mathbb{Q}_3$ be the complex 3-quadric endowed with its standard complex
conformal structure. We study the complex conformal geometry of isotropic
curves in $\mathbb{Q}_3$. By an isotropic curve we mean a nonconstant
holomorphic map from a Riemann surface into $\mathbb{Q}_3$, null with respect
to the conformal structure of $\mathbb{Q}_3$. The relations between isotropic
curves and a number of relevant classes of surfaces in Riemannian and
Lorentzian spaceforms are discussed.


  The purpose of this work is two-fold: (1) to quantify the occurrence of
ultra-steep spectrum remnant FRII radio galaxies in a 74 MHz flux limited
sample, and (2) perform Monte-Carlo simulations of the population of active and
remnant FRII radio galaxies to confront models of remnant lobe evolution, and
provide guidance for further investigation of remnant radio galaxies. We find
that fewer than 2$\%$ of FRII radio galaxies with S$_{ \rm74~MHz} > 1.5$ Jy are
candidate ultra-steep spectrum remnants, where we define ultra-steep spectrum
as $\alpha_{\rm 74~MHz}^{\rm 1400~MHz} > 1.2$. Our Monte-Carlo simulations
demonstrate that models involving Sedov-like expansion in the remnant phase,
resulting in rapid adiabatic energy losses, are consistent with this upper
limit, and predict the existence of nearly twice as many remnants with normal
(not ultra-steep) spectra in the observed frequency range as there are
ultra-steep spectrum remnants. This model also predicts an ultra-steep remnant
fraction approaching 10$\%$ at redshifts $z < 0.5$. Importantly, this model
implies the lobes remain over-pressured with respect to the ambient medium well
after their active lifetime, in contrast with existing observational evidence
that many FRII radio galaxy lobes reach pressure equilibrium with the external
medium whilst still in the active phase. The predicted age distribution of
remnants is a steeply decreasing function of age. In other words young remnants
are expected to be much more common than old remnants in flux limited samples.
For this reason, incorporating higher frequency data $\gtrsim 5$ GHz will be of
great benefit to future studies of the remnant population.


  In this study, we investigated the effects of self-reflection in large
language models (LLMs) on problem-solving performance. We instructed nine
popular LLMs to answer a series of multiple-choice questions to provide a
performance baseline. For each incorrectly answered question, we instructed
eight types of self-reflecting LLM agents to reflect on their mistakes and
provide themselves with guidance to improve problem-solving. Then, using this
guidance, each self-reflecting agent attempted to re-answer the same questions.
Our results indicate that LLM agents are able to significantly improve their
problem-solving performance through self-reflection ($p < 0.001$). In addition,
we compared the various types of self-reflection to determine their individual
contribution to performance. All code and data are available on GitHub at
https://github.com/matthewrenze/self-reflection


  Unpaired image translation algorithms can be used for sim2real tasks, but
many fail to generate temporally consistent results. We present a new approach
that combines differentiable rendering with image translation to achieve
temporal consistency over indefinite timescales, using surface consistency
losses and \emph{neural neural textures}. We call this algorithm TRITON
(Texture Recovering Image Translation Network): an unsupervised, end-to-end,
stateless sim2real algorithm that leverages the underlying 3D geometry of input
scenes by generating realistic-looking learnable neural textures. By settling
on a particular texture for the objects in a scene, we ensure consistency
between frames statelessly. Unlike previous algorithms, TRITON is not limited
to camera movements -- it can handle the movement of objects as well, making it
useful for downstream tasks such as robotic manipulation.


  This paper presents a novel methodology of Indic handwritten script
recognition using Recurrent Neural Networks and addresses the problem of script
recognition in poor data scenarios, such as when only character level online
data is available. It is based on the hypothesis that curves of online
character data comprise sufficient information for prediction at the word
level. Online character data is used to train RNNs using BLSTM architecture
which are then used to make predictions of online word level data. These
prediction results on the test set are at par with prediction results of models
trained with online word data, while the training of the character level model
is much less data intensive and takes much less time. Performance for
binary-script models and then 5 Indic script models are reported, along with
comparison with HMM models.The system is extended for offline data prediction.
Raw offline data lacks the temporal information available in online data and
required for prediction using models trained with online data. To overcome
this, stroke recovery is implemented and the strokes are utilized for
predicting using the online character level models. The performance on
character and word level offline data is reported.


  Superconductor electronics (SCE) promise computer systems with orders of
magnitude higher speeds and lower energy consumption than their complementary
metal-oxide semiconductor (CMOS) counterparts. At the same time, the
scalability and resource utilization of superconducting systems are major
concerns. Some of these concerns come from device-level challenges and the gap
between SCE and CMOS technology nodes, and others come from the way Josephson
Junctions (JJs) are used. Towards this end, we notice that a considerable
fraction of hardware resources are not involved in logic operations, but rather
are used for fan-out and buffering purposes. In this paper, we ask if there is
a way to reduce these overheads, propose the use of JJs at the cell boundaries
to increase the number of outputs that a single stage can drive, and establish
a set of rules to discretize critical currents in a way that is conducive to
this assignment. Finally, we explore the design trade-offs that the presented
approach opens up and demonstrate its promise through detailed analog
simulations and modeling analyses. Our experiments indicate that the introduced
method leads to a 48% savings in the JJ count for a tree with a fan-out of
1024, as well as an average of 43% of the JJ count for signal splitting and 32%
for clock splitting in ISCAS'85 benchmarks.


  In lieu of an abstract here is the first paragraph: No other species remotely
approaches the human capacity for the cultural evolution of novelty that is
accumulative, adaptive, and open-ended (i.e., with no a priori limit on the
size or scope of possibilities). By culture we mean extrasomatic
adaptations--including behavior and technology--that are socially rather than
sexually transmitted. This chapter synthesizes research from anthropology,
psychology, archaeology, and agent-based modeling into a speculative yet
coherent account of two fundamental cognitive transitions underlying human
cultural evolution that is consistent with contemporary psychology. While the
chapter overlaps with a more technical paper on this topic (Gabora & Smith
2018), it incorporates new research and elaborates a genetic component to our
overall argument. The ideas in this chapter grew out of a non-Darwinian
framework for cultural evolution, referred to as the Self-other Reorganization
(SOR) theory of cultural evolution (Gabora, 2013, in press; Smith, 2013), which
was inspired by research on the origin and earliest stage in the evolution of
life (Cornish-Bowden & C\'ardenas 2017; Goldenfeld, Biancalani, & Jafarpour,
2017, Vetsigian, Woese, & Goldenfeld 2006; Woese, 2002). SOR bridges
psychological research on fundamental aspects of our human nature such as
creativity and our proclivity to reflect on ideas from different perspectives,
with the literature on evolutionary approaches to cultural evolution that
aspire to synthesize the behavioral sciences much as has been done for the
biological scientists. The current chapter is complementary to this effort, but
less abstract; it attempts to ground the theory of cultural evolution in terms
of cognitive transitions as suggested by archaeological evidence.


  Let $G$ be a connected reductive subgroup of a complex connected reductive
group $\hat{G}$. We are interested in the branching problem. Fix maximal tori
and Borel subgroups of $G$ and $\hat G$. Consider the cone $lr(G,\hat G)$
generated by the pairs $(\nu,\hat nu)$ of dominant characters such that
$V_\nu^*$ is a submodule of $V_{\hat nu}$. It is known that $lr(G,\hat G)$ is a
closed convex polyhedral cone. In this work, we show that every regular face of
$lr(G,\hat G)$ gives rise to a {\it reduction rule} for multiplicities. More
precisely, we prove that for $(\nu,\hat nu)$ on such a face, the multiplicity
of $V_\nu^*$ in $V_{\hat nu}$ equal to a similar multiplicity for
representations of Levi subgroups of $G$ and $\hat G$. This generalizes, by
different methods, results obtained by Brion, Derksen-Weyman, Roth...


  Due to the recent groundbreaking developmentsof nanotechnologies,it became
possible to create intrinsically quantum systems able to serve as
high-directional antennas in THz, infrared and optical ranges. Actually, the
quantum antennas,as devices shaping light on thelevel of single
quanta,havealreadybecomethe key elements in nanooptics and nanoelectronics. The
quantum antennas are actively researched for possible implementations in
quantum communications, quantum imaging and sensing,andenergy harvesting.
However, the design and optimization of these emitting/receivingdevices
arestill rather undevelopedin comparisonwith the well-known methods for
conventional radio-frequency antennas. This review provides a discussion of the
recent achievements in the concept of the quantum antenna as an open quantum
systememitting via interaction with a photonic reservoir. We focuson bridging
the gap between quantum antennas and their macroscopic classical analogues. We
also discuss the ways of quantum-antennaimplementation for different
configurations basedon such materials, as plasmonic metals, carbon nanotubes,
and semiconductor quantum dots.


  A principal component analysis (PCA) of clean microcalorimeter pulse records
can be a first step beyond statistically optimal linear filtering of pulses
towards a fully non-linear analysis. For PCA to be practical on spectrometers
with hundreds of sensors, an automated identification of clean pulses is
required. Robust forms of PCA are the subject of active research in machine
learning. We examine a version known as coherence pursuit that is simple, fast,
and well matched to the automatic identification of outlier records, as needed
for microcalorimeter pulse analysis.


  The method of negative-tone-PMMA electron-beam lithography is investigated to
improve the performance of nanowire-based superconducting detectors. Using this
approach, the superconducting nanowire single-photon detectors (SNSPDs) have
been fabricated from thick 5-nm NbN film sputtered at the room temperature. To
investigate the impact of this process, SNSPDs were prepared by positive-tone
and negative-tone-PMMA lithography, and their electrical and photodetection
characteristics at 4.2 K were compared. The SNSPDs made by negative-tone-PMMA
lithography show higher critical-current density and higher photon count rate
at various wavelengths. Our results suggest a higher negative-tone-PMMA
technology may be preferable to the standard positive-tone-PMMA lithography for
this application.


  To a symplectic Lefschetz pencil on a monotone symplectic manifold, we
associate an algebraic structure, which is a pencil of categories in the sense
of noncommutative geometry. One fibre of this "noncommutative pencil" is
related to the Fukaya category of the open (meaning, with the base locus
removed, and hence exact symplectic) fibre of the original Lefschetz pencil;
the other fibres are newly constructed kinds of Fukaya categories.


  There has been a recent upsurge of interest in the quantum properties of
magnons for quantum information processing. An important issue is to examine
the stability of quantum states of magnons against various relaxation and
dephasing channels. Since the interaction of magnons in magnetic systems may
fall in the ultra-strong and even deep-strong coupling regimes, the relaxation
process of magnon states is quite different from the more common quantum
optical systems. Here we study the relaxation and dephasing of magnons based on
the Lindblad formalism and derive a generalized master equation that describes
the quantum dynamics of magnons. Employing this master equation, we identify
two distinct dissipation channels for squeezed magnons, i.e., the local
dissipation and collective dissipation, which play a role for both ferromagnets
and antiferromagnets. The local dissipation is caused by the independent
exchange of angular momentum between the magnonic system and the environment,
while the collective dissipation is dressed by the parametric interactions of
magnons and it enhances the quantumness and thermal stability of squeezed
magnons. Further, we show how this formalism can be applied to study the pure
dephasing of magnons caused by four-magnon scattering and magnon-phonon
interactions. Our results provide the theoretical tools to study the
decoherence of magnons within a full quantum-mechanical framework and further
benefit the use of quantum states of magnons for information processing.


  Quantifying the heterogeneity is an important issue in meta-analysis, and
among the existing measures, the $I^2$ statistic is the most commonly used
measure in the literature. In this paper, we show that the $I^2$ statistic was,
in fact, defined as problematic or even completely wrong from the very
beginning. To confirm this statement, we first present a motivating example to
show that the $I^2$ statistic is heavily dependent on the study sample sizes,
and consequently it may yield contradictory results for the amount of
heterogeneity. Moreover, by drawing a connection between ANOVA and
meta-analysis, the $I^2$ statistic is shown to have, mistakenly, applied the
sampling errors of the estimators rather than the variances of the study
populations. Inspired by this, we introduce an Intrinsic measure for
Quantifying the heterogeneity in meta-analysis, and meanwhile study its
statistical properties to clarify why it is superior to the existing measures.
We further propose an optimal estimator, referred to as the IQ statistic, for
the new measure of heterogeneity that can be readily applied in meta-analysis.
Simulations and real data analysis demonstrate that the IQ statistic provides a
nearly unbiased estimate of the true heterogeneity and it is also independent
of the study sample sizes.


  We report the quench cooling experiments performed with liquid O2 under
different levels of gravity simulated with the magnetic gravity compensation. A
copper disk is quenched from 270K to 90K. It is found that the cooling time in
microgravity is very long in comparison with any other gravity level. This
phenomenon is explained by the isolation effect of the gas surrounding the
disk. The liquid subcooling is shown to drastically improuve the heat exchange
thus reducing the cooling time (about 20 times). The effect of subcooling on
the heat transfer is analyzed at different gravity levels. It is shown that
such type of experiments cannot be used for the analysis of the critical heat
flux (CHF) of the boiling crisis. The minimum heat flux (MHF) of boiling is
analyzed instead.


  We introduce the notion of skew-holomorphic Lie algebroid on a complex
manifold, and explore some cohomologies theories that one can associate to it.
Examples are given in terms of holomorphic Poisson structures of various sorts.


  We present a theoretical investigation of reactive and non-reactive
collisions of Li and Rb atoms with C$_{2}^{-}$ molecular anions at low
temperatures in the context of sympathetic cooling in hybrid trap experiments.
Based on recently reported accurate potential energy surfaces for the singlet
and triplet states of the Li-C$_{2}^{-}$ and Rb-C$_{2}^{-}$ systems, we show
that the associative electronic detachment reaction is slow if the colliding
partners are in their ground state, but fast if they are excited. The results
are expected to be representative of the alkali-metal series. We also
investigate rotationally inelastic collisions in order to explore the cooling
of the translational and rotational degrees of freedom of C$_2^-$ in hybrid
ion-atom traps. The effect of micromotion is taken into account by considering
Tsallis distributions of collision energies. We show that the translational
cooling occurs much more rapidly than rotational cooling and that the presence
of excited atoms leads to losses of anions on a timescale comparable to that of
rotational cooling.


  We propose a simple model with two infective classes in order to model the
cholera epidemic in Haiti. We include the impact of environmental events
(rainfall, temperature and tidal range) on the epidemic in the Artibonite and
Ouest regions by introducing terms in the transmission rate that vary with
environmental conditions. We fit the model on weekly data from the beginning of
the epidemic until December 2013, including the vaccination programs that were
recently undertaken in the Ouest and Artibonite regions. We then modified these
projections excluding vaccination to assess the programs' effectiveness. Using
real-time daily rainfall, we found lag times between precipitation events and
new cases that range from 3.4 to 8.4 weeks in Artibonite and 5.1 to 7.4 in
Ouest. In addition, it appears that, in the Ouest region, tidal influences play
a significant role in the dynamics of the disease. Intervention efforts of all
types have reduced case numbers in both regions; however, persistent outbreaks
continue. In Ouest, where the population at risk seems particularly besieged
and the overall population is larger, vaccination efforts seem to be taking
hold more slowly than in Artibonite, where a smaller core population was
vaccinated. The models including the vaccination programs predicted that a year
and six months later, the mean number of cases in Artibonite would be reduced
by about two thousand cases, and in Ouest by twenty four hundred cases below
that predicted by the models without vaccination. We also found that
vaccination is best when done in the early spring, and as early as possible in
the epidemic. Comparing vaccination between the first spring and the second,
there is a drop of about 40% in the case reduction due to the vaccine and about
10% per year after that.


  We investigate the impact of galactic environment on the properties of
simulated giant molecular clouds formed in a M83-type barred spiral galaxy. Our
simulation uses a rotating stellar potential to create the grand design
features and resolves down to 1.5 pc. From the comparison of clouds found in
the bar, spiral and disc regions, we find that the typical GMC is environment
independent, with a mass of 5e+5 Msun and radius 11 pc. However, the fraction
of clouds in the property distribution tails varies between regions, with
larger, more massive clouds with a higher velocity dispersion being found in
greatest proportions in the bar, spiral and then disc. The bar clouds also show
a bimodality that is not reflected in the spiral and disc clouds except in the
surface density, where all three regions show two distinct peaks. We identify
these features as being due to the relative proportion of three cloud types,
classified via the mass-radius scaling relation, which we label A, B and C.
Type A clouds have the typical values listed above and form the largest
fraction in each region. Type B clouds are massive giant molecular associations
while Type C clouds are unbound, transient clouds that form in dense filaments
and tidal tails. The fraction of each clouds type depends on the cloud-cloud
interactions, which cause mergers to build up the GMA Type Bs and tidal
features in which the Type C clouds are formed. The number of cloud
interactions is greatest in the bar, followed by the spiral, causing a higher
fraction of both cloud types compared to the disc. While the cloud types also
exist in lower resolution simulations, their identification becomes more
challenging as they are not well separated populations on the mass-radius
relation or distribution plots. Finally, we compare the results for three star
formation models to estimate the star formation rate and efficiency in each
region.


  Chaotic evolutions exhibit exponential sensitivity to initial conditions.
This suggests that even very small perturbations resulting from weak coupling
of a quantum chaotic environment to the position of a system whose state is a
non-local superposition will lead to rapid decoherence. However, it is also
known that quantum counterparts of classically chaotic systems lose exponential
sensitivity to initial conditions, so this expectation of enhanced decoherence
is by no means obvious. We analyze decoherence due to a "toy" quantum
environment that is analytically solvable, yet displays the crucial phenomenon
of exponential sensitivity to perturbations. We show that such an environment,
with a single degree of freedom, can be far more effective at destroying
quantum coherence than a heat bath with infinitely many degrees of freedom.
This also means that the standard "quantum Brownian motion" model for a
decohering environment may not be as universally applicable as it once was
conjectured to be.


  We generalize an existing low-cost analog signal processing concept that
takes advantage of the periodicity of vehicle-to-vehicle broadcast service to
the transmitter side. In particular, we propose to process multiple antennas
using either an analog beamforming network (ABN) of phase shifters, or an an
antenna switching network (ASN) that periodically alternate between the
available antennas, to transmit periodic messages to receivers that have an
analog combining network (ACN) of phase shifters, which has been proposed in
earlier work. To guarantee robustness, we aim to minimize the burst error
probability for the worst receiving vehicular user, in a scenario of bad
propagation condition that is modeled by a single dominant path between the
communicating vehicles. In absence of any form of channel knowledge, we
analytically derive the optimal parameters of both ABN and ASN. The ABN
beamforming vector is found to be optimal for all users and not only for the
worst receiving user. Further, we demonstrate that Alamouti scheme for the
special case of two transmit antennas yields similar performance to ABN and
ASN. At last, we show that the derived parameters of the two proposed
transmission strategies are also optimal when hybrid ACN-maximal ratio
combining is used at the receiver.


  This work presents the concept of kernel mean embedding and kernel
probabilistic programming in the context of stochastic systems. We propose
formulations to represent, compare, and propagate uncertainties for fairly
general stochastic dynamics in a distribution-free manner. The new tools enjoy
sound theory rooted in functional analysis and wide applicability as
demonstrated in distinct numerical examples. The implication of this new
concept is a new mode of thinking about the statistical nature of uncertainty
in dynamical systems.


  To study the nature of Bulge AGB stars and in particular their circumstellar
dust, we have analysed mid-infrared spectra obtained with the ISOCAM CVF
spectrometer in three Bulge fields. The ISOCAM 5-16.5 micron CVF spectra were
obtained as part of the ISOGAL infrared survey of the inner Galaxy. A
classification of the shape of the 10 micron dust feature was made for each
case. The spectra of the individual sources were modelled using a radiative
transfer model. Different combinations of amorphous silicates and
aluminium-oxide dust were used in the modelling. Spectra were obtained for 29
sources of which 26 are likely to be Bulge AGB stars. Our modelling shows that
the stars suffer mass loss rates in the range of 10^{-8} - 5 x 10^{-7} Msun /
yr, which is at the low end of the mass-loss rates experienced on the Thermally
Pulsing AGB. The luminosities range from 1,700 to 7,700 Lsun as expected for a
population of AGB stars with Minit of 1.5 - 2Msun. In agreement with the
condensation sequence scenario, we find that the dust content is dominated by
Al_2O_3 grains in this sample of low mass-loss rate stars.


  The vortex system in a high-T_c superconductor has been studied numerically
using the mapping to 2D bosons and the path-integral Monte Carlo method. We
find a single first-order transition from an Abrikosov lattice to an entangled
vortex liquid. The transition is characterized by an entropy jump dS = 0.4 k_B
per vortex and layer (parameters for YBCO) and a Lindemann number c_L = 0.25.
The increase in density at melting is given by d\rho = 6.0*10^{-4} /
\lambda(T)^2. The vortex liquid corresponds to a bosonic superfluid, with
\rho_s = \rho even in the limit \lambda -> \infty.


  The muon collider provides a unique opportunity to study the vector boson
scattering processes and dimension-8 operators contributing to anomalous
quartic gauge couplings~(aQGCs). Because of the cleaner final state, it is
easier to decode subprocess and certain operator couplings at a muon collider.
We attempt to identify the anomalous $WWWW$ coupling in the exclusive $WW\to
WW$ scattering in this paper. Since one aQGC can be induced by multiple
dimension-8 operators, the study of one coupling can help to confine different
operators. Meanwhile, singling out the $WW\to WW$ process can help to study the
unitarity bounds. The vector boson scattering process corresponding to the
anomalous $WWWW$ coupling is $\mu^+\mu^-\to
\nu\nu\bar{\nu}\bar{\nu}\ell^+\ell^-$, with four (anti-)neutrinos in the final
state, which brings troubles in phenomenological studies. In this paper, the
machine learning method is used to tackle this problem. We find that, using the
artificial neural network can extract the $W^+W^-\to W^+W^-$ contribution, and
is helpful to reconstruct the center of mass energy of the subprocess which is
important in the study of the Standard Model effective field theory. The
sensitivities and the expected constraints on the dimension-8 operators at the
muon collider with $\sqrt{s}=30$ TeV are presented. We demonstrate that the
artificial neural networks exhibit great potential in the phenomenological
study of processes with multiple neutrinos in the final state.


  We propose a simple criterion to identify when Nambu-Goldstone bosons (NGBs)
for different symmetries are redundant. It solves an old mystery why crystals
have phonons for spontaneously broken translations but no gapless excitations
for equally spontaneously broken rotations. Similarly for a superfluid, the NGB
for spontaneously broken Galilean symmetry is redundant with phonons. The most
nontrivial example is Tkachenko mode for a vortex lattice in a superfluid,
where phonons are redundant to the Tkachenko mode which is identified as the
Boboliubov mode.


  High-resolution satellite imagery has proven useful for a broad range of
tasks, including measurement of global human population, local economic
livelihoods, and biodiversity, among many others. Unfortunately,
high-resolution imagery is both infrequently collected and expensive to
purchase, making it hard to efficiently and effectively scale these downstream
tasks over both time and space. We propose a new conditional pixel synthesis
model that uses abundant, low-cost, low-resolution imagery to generate accurate
high-resolution imagery at locations and times in which it is unavailable. We
show that our model attains photo-realistic sample quality and outperforms
competing baselines on a key downstream task -- object counting -- particularly
in geographic locations where conditions on the ground are changing rapidly.


  The process of crumpling a sheet and compacting it into a ball is dependent
on many parameters that are difficult to disentangle. We study the effect of
plasticity on the crumpling process, and disentangle the effects of plasticity
and dimensionality of compaction by performing isotropic compaction experiments
on various materials with different elastoplasticities. The force required to
crumple a sheet into a ball as well as the number of layers inside the ball
have a power-law dependence on the size of the crumpled ball, each with its own
power-law exponent. We experimentally determine both exponents and find that
they are linearly proportional to and decrease with increasing plasticity of
the material. Finally we provide a scaling argument predicting a linear
relation between the two exponents with a coefficient of 3.5 in excellent
agreement with our experimental results.


  Robotic-assisted minimally invasive surgery (MIS) has enabled procedures with
increased precision and dexterity, but surgical robots are still open loop and
require surgeons to work with a tele-operation console providing only limited
visual feedback. In this setting, mechanical failures, software faults, or
human errors might lead to adverse events resulting in patient complications or
fatalities. We argue that impending adverse events could be detected and
mitigated by applying context-specific safety constraints on the motions of the
robot. We present a context-aware safety monitoring system which segments a
surgical task into subtasks using kinematics data and monitors safety
constraints specific to each subtask. To test our hypothesis about context
specificity of safety constraints, we analyze recorded demonstrations of
dry-lab surgical tasks collected from the JIGSAWS database as well as from
experiments we conducted on a Raven II surgical robot. Analysis of the
trajectory data shows that each subtask of a given surgical procedure has
consistent safety constraints across multiple demonstrations by different
subjects. Our preliminary results show that violations of these safety
constraints lead to unsafe events, and there is often sufficient time between
the constraint violation and the safety-critical event to allow for a
corrective action.


  We establish Bernstein's inequalities for functions of general
(general-state-space and possibly non-reversible) Markov chains. These
inequalities achieve sharp variance proxies and encompass the classical
Bernstein inequality for independent random variables as special cases. The key
analysis lies in bounding the operator norm of a perturbed Markov transition
kernel by the exponential of sum of two convex functions. One coincides with
what delivers the classical Bernstein inequality, and the other reflects the
influence of the Markov dependence. A convex analysis on these two functions
then derives our Bernstein inequalities. As applications, we apply our
Bernstein inequalities to the Markov chain Monte Carlo integral estimation
problem and the robust mean estimation problem with Markov-dependent samples,
and achieve tight deviation bounds that previous inequalities can not.


  In this paper we perform a comparative study of the forward and backward
Liouville mapping applied to the modeling of ring-shaped and non-gyrotropic
velocity distribution functions of particles injected in a sheared
electromagnetic field. The test-kinetic method is used to compute the velocity
distribution function in various areas of a proton cloud moving in the vicinity
of a region with a sharp transition of the magnetic field and a non-uniform
electric field. In the forward approach the velocity distribution function is
computed for a two-dimensional spatial bin, while in the backward approach the
distribution function is averaged over a spatial bin with the same size as for
the forward method and using a two-dimensional trapezoidal integration scheme.
It is shown that the two approaches lead to similar results for spatial bins
where the velocity distribution function varies smoothly. On the other hand,
with bins covering regions of configuration space characterized by sharp
spatial gradients of the velocity distribution function, the forward and
backward approaches will generally provide different results.


  The properties of Population III (Pop III) stars impact many aspects of
primeval structure formation such as the onset of cosmological reionization and
early chemical enrichment. However, in spite of over twenty years of numerical
simulations and attempts to constrain the Pop III initial mass function (IMF)
by stellar archaelogy, little is known of the masses of the first stars for
certain. Here, we model the effect of Pop III IMF on the properties of primeval
galaxies with a suite of high-resolution radiation-hydrodynamical simulations
with ENZO. We find that a top-heavy Pop III IMF results in earlier star
formation but dimmer galaxies than a more conventional Salpeter-type IMF
because explosions of massive Pop III stars produce more turbulence that
suppresses high-mass second-generation star formation. Our models suggest that
the Pop III IMF could therefore be inferred from detections of primordial
galaxies, which will be principal targets of the James Webb Space Telescope and
extremely large telecopes on the ground in the coming decade.


  In this work, we present a new stabilization method aimed at removing
spurious oscillations in the pressure approximation of Biot's model for
poroelasticity with low permeabilities and/or small time steps. We consider
different finite-element discretizations and illustrate how not only does such
a stabilized scheme provide numerical solutions that are free of non-physical
oscillations, but it also allows one to iterate the fluid and mechanics
problems in a fashion similar to the well-known fixed-stress split method. The
resulting solution method is convergent without the necessity for additional
terms to stabilize the iteration. Finally, we present numerical results
illustrating the robust behavior of both the stabilization and iterative solver
with respect to the physical and discretization parameters of the model.


  A recently proposed modified perturbative expansion for QCD incorporating
gluon condensation is employed to evaluate the quark and gluon self-energy
corrections in the first approximations. The results predict mass values of 1/3
of the nucleon mass for the light quarks u, d, and s and a monotonously growing
variation with the current mass. The only phenomenological input consists in
that <G^2> is evaluated up to order g^2 as a function of the unique parameter C
defining the modified propagator and then C is fixed to give a current estimate
of <g^2 G^2>. The light quarks u and d result to be confined and the s, c, b
and t ones show damped propagation modes, then suggesting a model for the large
differences in stability between the nucleons and the higher resonances. The
above properties of quark modes diverge from the fully confinement result
following from the similar gluon propagator previously considered by Munczek
and Nemirovski. On another hand, the condensate effects on the gluon
self-energy furnish a tachionic mass shell as predicted by the Fukuda analysis
of gluon condensation in QCD.


  In the last decade, several works have focused on exploring the material and
electrical properties of $\text{GeTe/Sb}_{2}\text{Te}_{3}$ superlattices (SLs)
in particular because of some first device implementations demonstrating
interesting performances such as fast switching speed, low energy consumption,
and non-volatility. However, the switching mechanism in such SL-based devices
remains under debate. In this work, we investigate the prototype
$\text{GeTe/Sb}_{2}\text{Te}_{3}$ SLs, to analyze fundamentally their
electronic and thermal properties by ab initio methods. We find that the
resistive contrast is small among the different phases of
$\text{GeTe/Sb}_{2}\text{Te}_{3}$ because of a small electronic gap (about 0.1
eV) and a consequent semi-metallic-like behavior. At the same time the
out-of-plane lattice thermal conductivity is rather small, while varying up to
four times among the different phases, from 0.11 to 0.45 W/m$^{-1}$K$^{-1}$,
intimately related to the number of Van der Waals (VdW) gaps in a unit block.
Such findings confirm the importance of the thermal improvement achievable in
$\text{GeTe/Sb}_{2}\text{Te}_{3}$ super-lattices devices, highlighting the
impact of the material stacking and the role of VdW gaps on the thermal
engineering of the Phase-Change Memory cell.


  Molecular line images of 13CO, C18O, CN, CS, CH3OH, and HNCO are obtained
toward the spiral arm of M51 at a 7" times 6" resolution with the Combined
Array for Research in Millimeter-wave Astronomy (CARMA). Distributions of the
molecules averaged over a 300 pc scale are found to be almost similar to one
another and to essentially trace the spiral arm. However, the principal
component analysis shows a slight difference of distributions among molecular
species particularly for CH3OH and HNCO. These two species do not correlate
well with star-formation rate, implying that they are not enhanced by local
star-formation activities but by galactic-scale phenomena such as spiral
shocks. Furthermore, the distribution of HNCO and CH3OH are found to be
slightly different, whose origin deserves further investigation. The present
results provide us with an important clue to understanding the 300 pc scale
chemical composition in the spiral arm and its relation to galactic-scale
dynamics.


  We perform fine-grained land use mapping at the city scale using ground-level
images. Mapping land use is considerably more difficult than mapping land cover
and is generally not possible using overhead imagery as it requires close-up
views and seeing inside buildings. We postulate that the growing collections of
georeferenced, ground-level images suggest an alternate approach to this
geographic knowledge discovery problem. We develop a general framework that
uses Flickr images to map 45 different land-use classes for the City of San
Francisco. Individual images are classified using a novel convolutional neural
network containing two streams, one for recognizing objects and another for
recognizing scenes. This network is trained in an end-to-end manner directly on
the labeled training images. We propose several strategies to overcome the
noisiness of our user-generated data including search-based training set
augmentation and online adaptive training. We derive a ground truth map of San
Francisco in order to evaluate our method. We demonstrate the effectiveness of
our approach through geo-visualization and quantitative analysis. Our framework
achieves over 29% recall at the individual land parcel level which represents a
strong baseline for the challenging 45-way land use classification problem
especially given the noisiness of the image data.


  The existence of a discontinuity in the inverse dielectric constant of the
two-dimensional Coulomb gas is demonstrated on purely numerical grounds. This
is done by expanding the free energy in an applied twist and performing a
finite-size scaling analysis of the coefficients of higher-order terms. The
phase transition, driven by unbinding of dipoles, corresponds to the
Kosterlitz-Thouless transition in the 2D XY model. The method developed is also
used for investigating the possibility of a Kosterlitz-Thouless phase
transition in a three-dimensional system of point charges interacting with a
logarithmic pair-potential, a system related to effective theories of
low-dimensional strongly correlated systems. We also contrast the finite-size
scaling of the fluctuations of the dipole moments of the two-dimensional
Coulomb gas and the three-dimensional logarithmic system to those of the
three-dimensional Coulomb gas.