  We analyze optical and near infrared spectra of intermediate and high
resolution of the eclipsing symbiotic system AR Pavonis. We have obtained the
radial velocity curves for the red and the hot component from the M-giant
absorption lines and from the wings of Halpha, H and He II4686 emission
profiles, respectively. From the orbital elements we have derived the masses,
Mgiant=2.5 and Mhot =1.0 solar masses, for the red giant and the hot component,
respectively. We also present and discuss radial velocity patterns in the blue
cF absorption spectrum as well as various emission lines. In particular, we
confirm that the blue absorption lines are associated with the hot component.
The radial velocity curve of the blue absorption system, however, does not
track the hot companion's orbital motion in a straightforward way, and its
departures from an expected circular orbit are particularly strong when the hot
component is active. We suggest that the cF-type absorption system is formed in
material streaming from the giant presumably in a region where the stream
encounters an accretion disk or an extended envelope around the hot component.
The broad emission wings originate from the inner accretion disk or the
envelope around the hot star.We also suggest that the central absorption in H
profiles is formed in a neutral portion of the cool giant's wind which is
strongly concentrated towards the orbital plane. The nebula in AR Pav seems to
be bounded by significant amount of neutral material in the orbital plane. The
forbidden emission lines are probably formed in low density ionized regions
extended in polar directions and/or the wind-wind interaction zone.


  We study multi-player turn-based games played on (potentially infinite)
directed graphs. An outcome is assigned to every play of the game. Each player
has a preference relation on the set of outcomes which allows him to compare
plays. We focus on the recently introduced notion of weak subgame perfect
equilibrium (weak SPE). This is a variant of the classical notion of SPE, where
players who deviate can only use strategies deviating from their initial
strategy in a finite number of histories. Having an SPE in a game implies
having a weak SPE but the contrary is generally false.
  We propose general conditions on the structure of the game graph and on the
preference relations of the players that guarantee the existence of a weak SPE,
that additionally is finite-memory. From this general result, we derive two
large classes of games for which there always exists a weak SPE: (i) the games
with a finite-range outcome function, and (ii) the games with a finite
underlying graph and a prefix-independent outcome function. For the second
class, we identify conditions on the preference relations that guarantee
memoryless strategies for the weak SPE.


  Motivated by the recent theoretical studies on a two-dimensional (2D) chiral
Hamiltonian based on the Su-Schrieffer-Heeger chains, we experimentally and
computationally demonstrate that topological flat frequency bands can occur at
open edges of 2D planar metamaterials and at antiphase boundary seams of
ring-shaped or tubular metamaterials. Specifically, using mechanical systems
made of magnetically coupled spinners, we reveal that the presence of the edge
or seam bands that are flat in the entire projected reciprocal space follows
the predictions based on topological winding numbers. The edge-to-edge distance
sensitively controls the flatness of the edge bands and the localization of
excitations. The analogue of the fractional charge state is also observed.
Possible realizations of flat bands in a large class of metamaterials,
including photonic crystals and electronic metamaterials, are discussed.


  This paper proposes a novel scheme which can efficiently reduce the energy
consumption of Optical Line Terminals (OLTs) in Time Division Multiplexing
(TDM) Passive Optical Networks (PONs) such as EPON and GPON. Currently, OLTs
consume a significant amount of energy in PON, which is one of the major FTTx
technologies. To be environmentally friendly, it is desirable to reduce energy
consumption of OLT as much as possible; such requirement becomes even more
urgent as OLT keeps increasing its provisioning data rate, and higher data rate
provisioning usually implies higher energy consumption. In this paper, we
propose a novel energy-efficient OLT structure which guarantees services of end
users with the smallest number of power-on OLT line cards. More specifically,
we adapt the number of power-on OLT line cards to the real-time incoming
traffic. Also, in order to avoid service disruption resulted by powering off
OLT line cards, proper optical switches are equipped in OLT to dynamically
configure the communications between OLT line cards and ONUs.


  CMOS pixel sensors (CPS) represent a novel technological approach to building
charged particle detectors. CMOS processes allow to integrate a sensing volume
and readout electronics in a single silicon die allowing to build sensors with
a small pixel pitch ($\sim 20 \mu m$) and low material budget ($\sim 0.2-0.3\%
X_0$) per layer. These characteristics make CPS an attractive option for
vertexing and tracking systems of high energy physics experiments. Moreover,
thanks to the mass production industrial CMOS processes used for the
manufacturing of CPS the fabrication construction cost can be significantly
reduced in comparison to more standard semiconductor technologies. However, the
attainable performance level of the CPS in terms of radiation hardness and
readout speed is mostly determined by the fabrication parameters of the CMOS
processes available on the market rather than by the CPS intrinsic potential.
  The permanent evolution of commercial CMOS processes towards smaller feature
sizes and high resistivity epitaxial layers leads to the better radiation
hardness and allows the implementation of accelerated readout circuits. The
TowerJazz $0.18 \mu m$ CMOS process being one of the most relevant examples
recently became of interest for several future detector projects. The most
imminent of these project is an upgrade of the Inner Tracking System (ITS) of
the ALICE detector at LHC. It will be followed by the Micro-Vertex Detector
(MVD) of the CBM experiment at FAIR. Other experiments like ILD consider CPS as
one of the viable options for flavour tagging and tracking sub-systems.


  A graph $G$ is {\em $k$-choosable} if for every assignment of a set $S(v)$ of
$k$ colors to every vertex $v$ of $G$, there is a proper coloring of $G$ that
assigns to each vertex $v$ a color from $S(v)$. We consider the complexity of
deciding whether a given graph is $k$-choosable for some constant $k$. In
particular, it is shown that deciding whether a given planar graph is
4-choosable is NP-hard, and so is the problem of deciding whether a given
planar triangle-free graph is 3-choosable. We also obtain simple constructions
of a planar graph which is not 4-choosable and a planar triangle-free graph
which is not 3-choosable.


  We calculate the possible interaction between a superconductor and the static
Earth's gravitational fields, making use of the gravito-Maxwell formalism
combined with the time-dependent Ginzburg-Landau theory. We try to estimate
which are the most favourable conditions to enhance the effect, optimizing the
superconductor parameters characterizing the chosen sample. We also give a
qualitative comparison of the behaviour of high-$T_\text{c}$ and classical
low-$T_\text{c}$ superconductors with respect to the gravity/superfluid
interplay.


  Since 1883, Picard-Vessiot theory had been developed as the Galois theory of
differential field extensions associated to linear differential equations.
Inspired by categorical Galois theory of Janelidze, and by using novel methods
of precategorical descent applied to algebraic-geometric situations, we develop
a Galois theory that applies to morphisms of differential schemes, and vastly
generalises the linear Picard-Vessiot theory, as well as the strongly normal
theory of Kolchin.


  In this work we explore the interplay between global symmetry and the
mobility of quasiparticle excitations. We show that fractonic matter naturally
appears in a three dimensional U(1) gauge theory, enriched by global U(1) and
translational symmetries, via the mechanism of anyonic spin-orbital coupling.
We develop a systematic understanding of such symmetry-enforced mobility
restrictions in terms of the classification of U(1) gauge theories enriched by
U(1) and translational symmetries. We provide a unified construction of these
phases by gauging layered symmetry-protected topological phases.


  Steel and Welch have shown that K is \Sigma^1_3 correct if the reals are
closed under sharps but 0^\pistol doesn't exist. We'll give a simple and purely
combinatorial proof of the following: K is \Sigma^1_3 correct if the reals are
closed under sharps, there is no inner model with a Woodin cardinal, K exists,
and * holds. Here, * is an assertion which can easily be verified if 0^\pistol
doesn't exist. We conjecture that * holds outright. (* is denoted by \clubsuit
in the paper.)


  We present the first model-agnostic analysis of the complete set of Sloan
Digital Sky Survey III (BOSS) and -IV (eBOSS) catalogues of luminous red galaxy
and quasar clustering in the redshift range $0.2\leq z \leq 2.2$ (10 billion
years of cosmic evolution), which consistently includes the baryon acoustic
oscillations (BAO), redshift space distortions (RSD) and the shape of the
transfer function signatures, from pre- and post-reconstructed catalogues in
Fourier space. This approach complements the standard analyses techniques which
only focus on the BAO and RSD signatures, and the full-modeling approaches
which assume a specific underlying cosmology model to perform the analysis.
These model-independent results can then easily be interpreted in the context
of the cosmological model of choice. In particular, when combined with $z>2.1$
Ly-$\alpha$ BAO measurements, the clustering BAO, RSD and {\it Shape}
parameters can be interpreted within a flat-$\Lambda$CDM model yielding
$h=0.6816\pm0.0067$, $\Omega_{\rm m}=0.3001\pm0.0057$ and $10^{9}\times A_s=
2.43\pm0.20$ (or $\sigma_8=0.858\pm0.036$) with a Big Bang Nucleosynthesis
prior on the baryon density. Without any external dataset, the BOSS and eBOSS
data alone imply $\Omega_{\rm m}=0.2971\pm 0.0061$ and $10^{9}\times
A_s=2.39^{+0.24}_{-0.43}$ (or $\sigma_8=0.857\pm0.040$). For models beyond
$\Lambda$CDM, eBOSS data alone (in combination with Planck) constrain the sum
of neutrino mass to be $\Sigma m_\nu< 0.40$ eV with a BBN prior ($\Sigma m_\nu
<0.082$ eV) at 95\% CL, the curvature energy density to $\Omega_\mathrm{k} =
-0.022_{-0.038}^{+0.032}$ ($\Omega_\mathrm{k} = 0.0015\pm 0.0016$) and the dark
energy equation of state parameter to $w=-0.998_{-0.073}^{+0.085}$
($w=-1.093_{-0.044}^{+0.048}$) at 68\% CL without a BBN prior.


  We present the first study of production of $\psi (4040)$, $\psi (4160)$, and
$\psi (4415)$ mesons in hadronic matter. Quark interchange between two
colliding charmed mesons leads to the production of the three mesons. We
calculate unpolarized cross sections for the reactions, $D\bar{D} \to \rho R$,
$D\bar{D}^* \to \pi R$, $D\bar{D}^* \to \rho R$, $D^*\bar{D} \to \pi R$,
$D^*\bar{D} \to \rho R$, $D^*\bar{D}^* \to \pi R$, and $D^*\bar{D}^* \to \rho
R$, where $R$ stands for $\psi (4040)$, $\psi (4160)$, and $\psi (4415)$. In
the temperature region covering hadronic matter the peak cross sections of
producing $\psi (4040)$ are similar to or larger than the ones of producing
$\psi (4415)$, and the latter are generally larger than those of producing
$\psi (4160)$. With the cross sections we establish new master rate equations
for $\psi (4040)$, $\psi (4160)$, and $\psi (4415)$. The equations are solved
for central Pb-Pb collisions at $\sqrt{s_{NN}}=5.02$ TeV at the Large Hadron
Collider. Solutions of the equations show that the $\psi (4040)$ number density
at kinetic freeze-out of hadronic matter is larger than the $\psi (4415)$
number density which is larger than the $\psi (4160)$ number density.


  We present X-ray and radio observations of the recently-discovered bow shock
pulsar wind nebula associated with PSR J0002+6216, characterizing the PWN
morphology, which was unresolved in previous studies. The multi-frequency,
multi-epoch Very Large Array radio observations reveal a cometary tail trailing
the pulsar and extending up to 5.3', with multiple kinks along the emission.
The presented radio continuum images from multi-configuration broadband VLA
observations are one of the first results from the application of multi-term
multi-frequency synthesis deconvolution in combination with the awproject
gridder implemented in the Common Astronomy Software Applications package
(CASA). The X-ray emission observed with Chandra extends to only 21'', fades
quickly, and has some hot spots present along the extended radio emission.
These kinks could indicate the presence of density variation in the local ISM
or turbulence. The bow shock standoff distance estimates a small bow shock
region with a size 0.003-0.009 pc, consistent with the pulsar spin-down power
of Edot=1.51x10^35 ergs/s estimated from timing. The high-resolution radio
image reveals the presence of an asymmetry in the bow shock region which is
also present in the X-ray image. The broadband radio image shows an unusually
steep spectrum along with a flat-spectrum sheath, which could indicate varying
opacity or energy injection into the region. Spatially-resolved X-ray spectra
provide marginal evidence of synchrotron cooling along the extended tail. Our
analysis of the X-ray data also shows that this pulsar has a low spin-down
power and one of the lowest X-ray efficiencies observed in these objects.


  Much of our understanding of critical phenomena is based on the notion of
Renormalization Group (RG), but the actual determination of its fixed points is
usually based on approximations and truncations, and predictions of physical
quantities are often of limited accuracy. The RG fixed points can be however
given a fully rigorous and non-perturbative characterization, and this is what
is presented here in a model of symplectic fermions with a nonlocal
("long-range") kinetic term depending on a parameter $\varepsilon$ and a
quartic interaction. We identify the Banach space of interactions, which the
fixed point belongs to, and we determine it via a convergent approximation
scheme. The Banach space is not limited to relevant interactions, but it
contains all possible irrelevant terms with short-ranged kernels, decaying like
a stretched exponential at large distances. As the model shares a number of
features in common with $\phi^4$ or Ising models, the result can be used as a
benchmark to test the validity of truncations and approximations in RG studies.
The analysis is based on results coming from Constructive RG to which we
provide a tutorial and self-contained introduction. In addition, we prove that
the fixed point is analytic in $\varepsilon$, a somewhat surprising fact
relying on the fermionic nature of the problem.


  Rejection of unmitigated vibrational disturbances represents an ongoing
dilemma in complex linkage systems. In this work, we present an inherent and
self-reliant vibration isolation mechanism in architected periodic chains of
serially pivoted pendulums. Absorption of external excitations is achieved by
virtue of Bragg-type band gaps which stem from the emergent chain dynamics.
Owing to its coupled dynamics, the self-repeating cell of a Phononic Crystal
(PC) is not trivial and cannot be readily identified from the periodic
arrangement by inspection. As such, this work entails the extraction of a
"pseudo" unit cell of an equivalent PC lattice from the derived motion
equations of a finite chain, which departs from traditional wave dispersion
methods. The model presented herein comprises a chain of linked pendulums with
periodic variations of inertial/geometrical properties, carrying a payload at
one end. We ultimately show evidence of forbidden wave propagation in
prescribed frequency regimes, reminiscent of band gaps in PC lattices. The
presented framework can be invaluable in applications that require vibration
reduction in the delivery of payloads including gantry cranes, robotic arms and
space tethers.


  We study Hamilton-Jacobi equations in [0, +$\infty$) of evolution type with
nonlinear boundary conditions of Neumann type in the case where the Hamiltonian
is non necessarily convex with respect to the gradient variable. In this paper,
we give two main results. First, we prove a classification of boundary
condition result for a nonconvex, coercive Hamiltonian, in the spirit of the
flux-limited formulation for quasi-convex Hamilton-Jacobi equations on networks
recently introduced by Imbert and Monneau. Second, we give a comparison
principle for a nonconvex and noncoercive Hamiltonian where the boundary
condition can have flat parts.


  Recently, an increasingly growing number of companies is focusing on
achieving self-driving systems towards SAE level 3 and higher. Such systems
will have much more complex capabilities than today's advanced driver
assistance systems (ADAS) like adaptive cruise control and lane-keeping
assistance. For complex software systems in the Web-application domain, the
logical successor for Continuous Integration and Deployment (CI/CD) is known as
Continuous Experimentation (CE), where product owners jointly with engineers
systematically run A/B experiments on possible new features to get quantifiable
data about a feature's adoption from the users. While this methodology is
increasingly adopted in software-intensive companies, our study is set out to
explore advantages and challenges when applying CE during the development and
roll-out of functionalities required for self-driving vehicles. This paper
reports about the design and results from a multiple case study that was
conducted at four companies including two automotive OEMs with a long history
of developing vehicles, a Tier-1 supplier, and a start-up company within the
area of automated driving systems. Unanimously, all expect higher quality and
fast roll-out cycles to the fleet; as major challenges, however, safety
concerns next to organizational structures are mentioned.


  A general framework of personalized federated multi-armed bandits (PF-MAB) is
proposed, which is a new bandit paradigm analogous to the federated learning
(FL) framework in supervised learning and enjoys the features of FL with
personalization. Under the PF-MAB framework, a mixed bandit learning problem
that flexibly balances generalization and personalization is studied. A lower
bound analysis for the mixed model is presented. We then propose the
Personalized Federated Upper Confidence Bound (PF-UCB) algorithm, where the
exploration length is chosen carefully to achieve the desired balance of
learning the local model and supplying global information for the mixed
learning objective. Theoretical analysis proves that PF-UCB achieves an
$O(\log(T))$ regret regardless of the degree of personalization, and has a
similar instance dependency as the lower bound. Experiments using both
synthetic and real-world datasets corroborate the theoretical analysis and
demonstrate the effectiveness of the proposed algorithm.


  We consider a class $G(S^n)$ of orientation preserving Morse-Smale
diffeomorphisms of the sphere $S^{n}$ of dimension $n>3$ in assumption that
invariant manifolds of different saddle periodic points have no intersection.
We put in a correspondence for every diffeomorphism $f\in G(S^n)$ a colored
graph $\Gamma_f$ enriched by an automorphism $P_f$. Then we define the notion
of isomorphism between two colored graphs and prove that two diffeomorphisms
$f, f'\in G(S^n)$ are topologically conjugated iff the graphs $\Gamma_f$,
$\Gamma_f'$ are isomorphic. Moreover we establish the existence of a
linear-time algorithm for distinguishing two colored graphs of diffeomorphisms
from the class $G(S^n)$.


  We calculate the diffusion thermopower of the degenerate two-dimensional hole
gas in a $p-$type Si/Si$_{1-x}$Ge$_x$ lattice mismatched heterostructure at low
temperatures and zero magnetic field. The effects of possible scatterings, e.g.
remote impurity, alloy disorder, interface roughness, deformation potential,
and random piezoelectric on the hole mobility and the diffusion thermopower are
examined. Calculated results are well fitted to the experimental data recently
reported. In addition, we predict a possibility for the diffusion thermopower
to change its sign as the SiGe layer thickness changes, the effect has not been
discussed yet.


  D3-branes are often a necessary ingredient in global compactifications of
F-theory. In minimal realizations of flavor hierarchies in F-theory GUT models,
suitable fluxes are turned on, which in turn attract D3-branes to the Yukawa
points. Of particular importance are ``E-type'' Yukawa points, as they are
required to realize a large top quark mass. In this paper we study the
worldvolume theory of a D3-brane probing such an E-point. D3-brane probes of
isolated exceptional singularities lead to strongly coupled N = 2 CFTs of the
type found by Minahan and Nemeschansky. We show that the local data of an
E-point probe theory determines an N = 1 deformation of the original N = 2
theory which couples this strongly interacting CFT to a free hypermultiplet.
Monodromy in the seven-brane configuration translates to a novel class of
deformations of the CFT. We study how the probe theory couples to the Standard
Model, determining the most relevant F-term couplings, the effect of the probe
on the running of the Standard Model gauge couplings, as well as possible
sources of kinetic mixing with the Standard Model.


  The data clustering problem consists in dividing a data set into prescribed
groups of homogeneous data. This is a NP-hard problem that can be relaxed in
the spectral graph theory, where the optimal cuts of a graph are related to the
eigenvalues of graph $1$-Laplacian. In this paper, we firstly give new
notations to describe the paths, among critical eigenvectors of the graph
$1$-Laplacian, realizing sets with prescribed genus.
  We introduce the pseudo-orthogonality to characterize $m_3(G)$, a special
eigenvalue for the graph $1$-Laplacian. Furthermore, we use it to give an upper
bound for the third graph Cheeger constant $h_3(G)$, that is $h_3(G) \le
m_3(G)$. This is a first step for proving that the $k$-th Cheeger constant is
the minimum of the $1$-Laplacian Raylegh quotient among vectors that are
pseudo-orthogonal to the vectors realizing the previous $k-1$ Cheeger
constants.
  Eventually, we apply these results to give a method and a numerical algorithm
to compute $m_3(G)$, based on a generalized inverse power method.


  Semigroup C*-algebras for right-angled Artin monoids were introduced and
studied by Crisp and Laca. In the paper at hand, we are able to present the
complete answer to their question of when such C*-algebras are isomorphic. The
answer to this question is presented both in terms of properties of the graph
defining the Artin monoids as well as in terms of classification by K-theory,
and is obtained using recent results from classification of non-simple
C*-algebras.
  Moreover, we are able to answer another natural question: Which of these
semigroup C*-algebras for right-angled Artin monoids are isomorphic to graph
algebras? We give a complete answer, and note the consequence that many of the
C*-algebras under study are semiprojective.


  Many data analysis problems rely on dynamic networks, such as social or
communication network analyses. Providing a scalable overview of long sequences
of such dynamic networks remains challenging due to the underlying large-scale
data containing elusive topological changes. We propose two complementary
pixel-based visualizations, which reflect occurrences of selected sub-networks
(motifs) and provide a time-scalable overview of dynamic networks: a
network-level census (motif significance profiles) linked with a node-level
sub-network metric (graphlet degree vectors) views to reveal structural
changes, trends, states, and outliers. The network census captures
significantly occurring motifs compared to their expected occurrences in random
networks and exposes structural changes in a dynamic network. The sub-network
metrics display the local topological neighborhood of a node in a single
network belonging to the dynamic network. The linked pixel-based visualizations
allow exploring motifs in different-sized networks to analyze the changing
structures within and across dynamic networks, for instance, to visually
analyze the shape and rate of changes in the network topology. We describe the
identification of visual patterns, also considering different reordering
strategies to emphasize visual patterns. We demonstrate the approach's
usefulness by a use case analysis based on real-world large-scale dynamic
networks, such as the evolving social networks of Reddit or Facebook.


  Modern neural-network-based no-reference image- and video-quality metrics
exhibit performance as high as full-reference metrics. These metrics are widely
used to improve visual quality in computer vision methods and compare video
processing methods. However, these metrics are not stable to traditional
adversarial attacks, which can cause incorrect results. Our goal is to
investigate the boundaries of no-reference metrics applicability, and in this
paper, we propose a fast adversarial perturbation attack on no-reference
quality metrics. The proposed attack (FACPA) can be exploited as a
preprocessing step in real-time video processing and compression algorithms.
This research can yield insights to further aid in designing of stable
neural-network-based no-reference quality metrics.


  Gravitational lensing is a good probe into the topological structure of dark
gravitating celestial objects. In this paper, we investigate the light curve of
a light ray that passes through the throat of an Ellis wormhole, the simplest
example of traversable wormholes. The method developed here is also applicable
to other traversable wormholes. To study whether the light curve of a light ray
that passes through a wormhole throat is distinguishable from that which does
not, we also calculate light curves without the passage of a throat for an
Ellis wormhole, a Schwarzschild black hole, and an ultrastatic wormhole with
the spatial geometry identical to that of the Schwarzschild black hole in the
following two cases: (i) "microlensing," where the source, lens, and observer
are almost aligned in this order and the light ray starts at the source,
refracts in the weak gravitational field of the lens with a small deflection
angle, and reaches the observer, and (ii) "retrolensing," where the source,
observer, and lens are almost aligned in this order, and the light ray starts
at the source, refracts in the vicinity of the light sphere of the lens with a
deflection angle very close to $\pi$, and reaches the observer. We find that
the light curve of the light ray that passes through the throat of the Ellis
wormhole is clearly distinguishable from that by the microlensing but not from
that by the retrolensing. This is because the light curve of a light ray that
passes by a light sphere of a lens with a large deflection angle has common
characters, irrespective of the details of the lens object. This implies that
the light curves of the light rays that pass through the throat of more general
traversable wormholes are qualitatively the same as that of the Ellis wormhole.


  We propose and develop a novel and effective perfect sampling methodology for
simulating from posteriors corresponding to mixtures with either known (fixed)
or unknown number of components. For the latter we consider the Dirichlet
process-based mixture model developed by these authors, and show that our ideas
are applicable to conjugate, and importantly, to non-conjugate cases. As to be
expected, and, as we show, perfect sampling for mixtures with known number of
components can be achieved with much less effort with a simplified version of
our general methodology, whether or not conjugate or non-conjugate priors are
used. While no special assumption is necessary in the conjugate set-up for our
theory to work, we require the assumption of bounded parameter space in the
non-conjugate set-up. However, we argue, with appropriate analytical,
simulation, and real data studies as support, that such boundedness assumption
is not unrealistic and is not an impediment in practice. Not only do we
validate our ideas theoretically and with simulation studies, but we also
consider application of our proposal to three real data sets used by several
authors in the past in connection with mixture models. The results we achieved
in each of our experiments with either simulation study or real data
application, are quite encouraging.


  Chemotherapy is one of the most important therapeutic options used to treat
human cancers, either alone or in combination with radiation therapy and
surgery. Recent studies have indicated that intra-tumoural heterogeneity has a
significant role in driving resistance to chemotherapy in many human
malignancies. Multiple factors including the internal cell-cycle dynamics and
the external microenvironement contribute to the intra-tumoural heterogeneity.
In this paper we present a hybrid, multiscale, individual-based mathematical
model, incorporating internal cell-cycle dynamics and changes in oxygen
concentration, to study the effects of delivery of several different
chemotherapeutic drugs on the heterogeneous subpopulations of cancer cells with
varying cell-cycle dynamics. The computational simulation results from the
multiscale model are in good agreement with available experimental data and
support the hypothesis that slow-cycling sub-populations of tumour cells within
a growing tumour mass can induce drug resistance to chemotherapy and thus the
use of conventional chemotherapy may actually result in the emergence of
dominant, therapy-resistant, slow-cycling subpopulations of tumour cells. Our
results indicate that the appearance of this chemotherapeutic resistance is
mainly due to the inability of the administered drug to target all cancer cells
irrespective of the stage in the cell-cycle they are in i.e. most
chemotherapeutic drugs target cells in a particular phase/phases of the
cell-cycle, and hence always spare some cancer cells that are not in the
targeted cell-cycle phase/phases. The results also suggest that this
cell-cycle-mediated drug resistance may be overcome by using multiple doses of
cell-cycle, phase-specific chemotherapy that targets cells in all phases and
its appropriate sequencing and scheduling.


  Functional data analysis has been extensively conducted. In this study, we
consider a partially functional model, under which some covariates are scalars
and have linear effects, while some other variables are functional and have
unspecified nonlinear effects. Significantly advancing from the existing
literature, we consider a model with interactions between the functional and
scalar covariates. To accommodate long-tailed error distributions which are not
uncommon in data analysis, we adopt the quantile technique for estimation. To
achieve more interpretable estimation, and to accommodate many practical
settings, we assume that the functional covariate effects are locally sparse
(that is, there exist subregions on which the effects are exactly zero), which
naturally leads to a variable/model selection problem. We propose respecting
the "main effect, interaction" hierarchy, which postulates that if a subregion
has a nonzero effect in an interaction term, then its effect has to be nonzero
in the corresponding main functional effect. For estimation, identification of
local sparsity, and respect of the hierarchy, we propose a penalization
approach. An effective computational algorithm is developed, and the
consistency properties are rigorously established under mild regularity
conditions. Simulation shows the practical effectiveness of the proposed
approach. The analysis of the Tecator data further demonstrates its practical
applicability. Overall, this study can deliver a novel and practically useful
model and a statistically and numerically satisfactory estimation approach.


  For first passage percolation (FPP) on integer lattice with i.i.d. passage
time distributions, in order to show existence of semi-infinite geodesics along
a fixed direction, one requires unproven assumptions on the limiting shape. We
consider FPP on two-dimensional integer lattice with i.i.d. passage times
distributed as Durrett-Liggett class of measures. For this model, we show that
along any direction in a deterministic angular sector (known as percolation
cone), starting from every lattice point there exists an infinite geodesic
along that direction and such directed geodesics coalesce almost surely. We
prove that for this model, bi-infinite geodesics exist almost surely. Our proof
does not require any assumption on the limiting shape.


  This paper reports a detailed analysis of the optical light curve of PSR
B0540-69, the second brightest pulsar in the visible band, obtained in 2009
(Jan. 18 and 20, and Dec. 14, 15, 16, 18) with the very high speed photon
counting photometer Iqueye mounted at the ESO 3.6-m NTT in La Silla (Chile).
The optical light curve derived by Iqueye shows a double structure in the main
peak, with a raising edge steeper than the trailing edge. The double peak can
be fitted by two Gaussians with the same height and FWHM of 13.3 and 15.5 ms
respectively. Our new values of spin frequencies allow to extend by 3.5 years
the time interval over which a reliable estimate of frequency first and second
derivatives can be performed. A discussion of implications on the braking index
and age of the pulsar is carried out. A value of n = 2.087 +/- 0.007 for the
overall braking index from 1987 to 2009 is derived. The braking index corrected
age is confirmed around 1700 years.


  We investigate the ground state properties of an ultracold atom system
consisting of many-body polarons, quasiparticles formed by impurity atoms in
optical lattices immersing in a Bose-Einstein condensate. We find the
nearest-neighbor attractive interaction between polarons can give rise to rich
physics that is peculiar to this system. In a relatively shallow optical
lattice, the attractive interaction can drive the system being in a self-bound
superfluid phase with its particle density distribution manifesting a
self-concentrated structure. While in a relatively deep optical lattice, the
attractive interaction can drive the system forming the Mott-insulator phase
even though the global filling factor is not integer. Interestingly, in the
Mott-insulator regime, the system can support a series of different
Mott-insulators with their effective density manifesting a devil's staircase
structure with respect to the strength of attractive interaction. Detailed
estimation on relevant experimental parameters shows that these rich physics
can be readily observed in current experimental setups.


  The motion of a satellite around a planet can be studied by the Hill model,
which is a modification of the restricted three body problem pertaining to
motion of a satellite around a planet. Although the dynamics of the circular
Hill model have been extensively studied in the literature, only few results
about the dynamics of the elliptic model were known up to now, namely the
equations of motion and few unstable families of periodic orbits. In the
present study we extend these results by computing a large set of families of
periodic orbits and their linear stability and classify them according to their
resonance condition. Although most of them are unstable, we were able to find a
considerable number of stable ones. By computing appropriate maps of dynamical
stability, we study the effect of the planetary eccentricity on the stability
of satellite orbits. We see that, even for large values of the planetary
eccentricity, regular orbits can be found in the vicinity of stable periodic
orbits. The majority of irregular orbits are escape orbits.


  The concepts of symmetry and symmetry groups are at the heart of several
developments in modern theoretical and mathematical physics. The present paper
is devoted to a number of selected topics within this framework: Euclidean and
rotation groups; the properties of fullerenes in physical chemistry; Galilei,
Lorentz and Poincare groups; conformal transformations and the Laplace
equation; quantum groups and Sklyanin algebras. For example, graphite can be
vaporized by laser irradiation, producing a remarkably stable cluster
consisting of 60 carbon atoms. The corresponding theoretical model considers a
truncated icosahedron, i.e. a polygon with 60 vertices and 32 faces, 12 of
which are pentagonal and 20 hexagonal. The Carbon 60 molecule obtained when a
carbon atom is placed at each vertex of this structure has all valences
satisfied by two single bonds and one double bond. In other words, a structure
in which a pentagon is completely surrounded by hexagons is stable. Thus, a
cage in which all 12 pentagons are completely surrounded by hexagons has
optimum stability. On a more formal side, the exactly solvable models of
quantum and statistical physics can be studied with the help of the quantum
inverse problem method. The problem of enumerating the discrete quantum systems
which can be solved by the quantum inverse problem method reduces to the
problem of enumerating the operator-valued functions that satisfy an equation
involving a fixed solution of the quantum Yang--Baxter equation. Two basic
equations exist which provide a systematic procedure for obtaining completely
integrable lattice approximations to various continuous completely integrable
systems. This analysis leads in turn to the discovery of Sklyanin algebras.


  We propose a cross-correlation method for the searches of ultra-light fields,
in particular, with a space network of atomic sensors. The main motivation of
the approach is cancellation of uncorrelated noises in the observation data and
unique pattern the fields leave on the cross-spectrum, depending on their
nature (i.e., scalar, vector or tensor). In particular, we analytically derive
a dependence of the cross-spectrum on the angle between two pairs of detectors.
We then confirm obtained angular curves with a numerical simulation. We imply
application of the method to the detection of dark matter and gravitational
waves.


  Given a simple polygon $\cal P$, in the Art Gallery problem the goal is to
find the minimum number of guards needed to cover the entire $\cal P$, where a
guard is a point and can see another point $q$ when $\overline{pq}$ does not
cross the edges of $\cal P$.
  This paper studies a variant of the Art Gallery problem in which guards are
restricted to lie on a dense grid inside $\cal P$. In the general problem,
guards can be anywhere inside or on the boundary of $\cal P$. The general
problem is called the \emph{point} guarding problem. It was proved that the
point guarding problem is APX-complete, meaning that we cannot do better than a
constant-factor approximation algorithm unless $P = NP$.
  A huge amount of research is committed to the studies of combinatorial and
algorithmic aspects of this problem, and as of this time, we could not find a
constant factor approximation for simple polygons. The last best-known
approximation factor for point guarding a simple polygon was $\mathcal{O}(\log
(|OPT|))$ introduced by E. Bonnet and T. Miltzow in 2020, where $|OPT|$ is the
size of the optimal solution. Here, we propose an algorithm with a constant
approximation factor for the point guarding problem where the location of
guards is restricted to a grid. The running time of the proposed algorithm
depends on the number of cells of the grid. The approximation factor is
constant regardless of the grid we use, the running time could be
super-polynomial if the grid size becomes exponential.


  Device fingerprinting combined with Machine and Deep Learning (ML/DL) report
promising performance when detecting cyberattacks targeting data managed by
resource-constrained spectrum sensors. However, the amount of data needed to
train models and the privacy concerns of such scenarios limit the applicability
of centralized ML/DL-based approaches. Federated learning (FL) addresses these
limitations by creating federated and privacy-preserving models. However, FL is
vulnerable to malicious participants, and the impact of adversarial attacks on
federated models detecting spectrum sensing data falsification (SSDF) attacks
on spectrum sensors has not been studied. To address this challenge, the first
contribution of this work is the creation of a novel dataset suitable for FL
and modeling the behavior (usage of CPU, memory, or file system, among others)
of resource-constrained spectrum sensors affected by different SSDF attacks.
The second contribution is a pool of experiments analyzing and comparing the
robustness of federated models according to i) three families of spectrum
sensors, ii) eight SSDF attacks, iii) four scenarios dealing with unsupervised
(anomaly detection) and supervised (binary classification) federated models,
iv) up to 33% of malicious participants implementing data and model poisoning
attacks, and v) four aggregation functions acting as anti-adversarial
mechanisms to increase the models robustness.


  We generalize the notion of Ekedahl-Oort strata to elements in the loop group
of any connected reductive group, and call the resulting discrete invariant the
truncation of level 1 of the element. We give conditions for the Newton points
occurring among the elements of a given truncation of level 1 and especially
for the generic Newton point in a given truncation stratum. We prove that
truncation strata are locally closed and give a description of the closure of
each stratum. We also translate our results back to the original Ekedahl-Oort
stratification of the reduction modulo p of Shimura varieties.


  In this paper, we analyze the adequacy and applicability of readership
statistics recorded in social reference management systems for creating
knowledge domain visualizations. First, we investigate the distribution of
subject areas in user libraries of educational technology researchers on
Mendeley. The results show that around 69% of the publications in an average
user library can be attributed to a single subject area. Then, we use
co-readership patterns to map the field of educational technology. The
resulting visualization prototype, based on the most read publications in this
field on Mendeley, reveals 13 topic areas of educational technology research.
The visualization is a recent representation of the field: 80% of the
publications included were published within ten years of data collection. The
characteristics of the readers, however, introduce certain biases to the
visualization. Knowledge domain visualizations based on readership statistics
are therefore multifaceted and timely, but it is important that the
characteristics of the underlying sample are made transparent.


  By a coupling method, we prove that a family of stochastic partial
differential equations (SPDEs) driven by highly degenerate pure jump L\'evy
noises are exponential mixing. These pure jump L\'evy noises include
$\alpha$-stable process with $\alpha \in (0,2)$


  We use the Keck Deep Fields UGRI catalog of z~4, 3, and 2 UV-selected
galaxies to study the evolution of the rest-frame 1700A luminosity density at
high redshift. The ability to reliably constrain the contribution of faint
galaxies is critical and our data do so as they reach to M*+2 even at z~4 and
deeper still at lower redshifts. We find that the luminosity density at high
redshift is dominated by the hitherto poorly studied galaxies fainter than L*,
and, indeed, the the bulk of the UV light in the high-z Universe comes from
galaxies in the luminosity range L=0.1-1L*. It is these faint galaxies that
govern the behavior of the total UV luminosity density. Overall, there is a
gradual rise in luminosity density starting at z~4 or earlier, followed by a
shallow peak or a plateau within z~3--1, and then followed by the well-know
plunge at lower redshifts. Within this total picture, luminosity density in
sub-L* galaxies evolves more rapidly at high redshift, z>~2, than that in more
luminous objects. However, this is reversed at lower redshifts, z<~1, a
reversal that is reminiscent of galaxy downsizing. Within the context of the
models commonly used in the observational literature, there seemingly aren't
enough faint or bright LBGs to maintain ionization of intergalactic gas even as
late as z~4. This is particularly true at earlier epochs and even more so if
the faint-end evolutionary trends we observe at z~3 and 4 continue to higher
redshifts. Apparently the Universe must be easier to reionize than some recent
studies have assumed. Nevertheless, sub-L* galaxies do dominate the total UV
luminosity density at z>~2 and this dominance further highlights the need for
follow-up studies that will teach us more about these very numerous but thus
far largely unexplored systems.


  Spectral properties and performance of multi-pulse impulse radio
ultra-wideband systems with pulse-based polarity randomization are analyzed.
Instead of a single type of pulse transmitted in each frame, multiple types of
pulses are considered, which is shown to reduce the effects of multiple-access
interference. First, the spectral properties of a multi-pulse impulse radio
system is investigated. It is shown that the power spectral density is the
average of spectral contents of different pulse shapes. Then, approximate
closed-form expressions for bit error probability of a multi-pulse impulse
radio system are derived for RAKE receivers in asynchronous multiuser
environments. The theoretical and simulation results indicate that impulse
radio systems that are more robust against multiple-access interference than a
"classical" impulse radio system can be designed with multiple types of
ultra-wideband pulses.


  The pulsations of X-ray pulsars carry information about the accretion and
magnetic field geometry. Here we present a study and classification of energy
resolved pulse profiles of a sample of X-ray pulsars, focusing on high-mass
X-ray binaries. Our goal is to perform a classification of X-ray pulsars based
on their observed pulse profiles and look for correlations between this
classification and their principle physical observables. The analysis pipeline
is available online. We analysed the pulse profiles of a sample of X-ray
pulsars using data obtained with the XMM-Newton and NuSTAR. We fit the energy
resolved pulse profiles with a Fourier series of up to five harmonics. We
investigate relationships between the pulse profile properties and other
observables of the systems (e.g., orbital period, magnetic field strength, and
luminosity) to study the extreme physics of these systems. The sources were
divided into three groups by a classification based on the shape, the dominance
of the fitted Fourier harmonics and their respective evolution with energy. We
do not find a conclusive correlation between the pulse profile shapes or groups
and other parameters of the systems. However, a weak trend was found when
comparing our classification to the sources' location in the spin
period-orbital period diagram. Further studies are required to confirm this
trend. Despite the large variety of pulse profiles of the X-ray pulsars, we
found that with our approach clear categories emerge which we use to classify
their behavior as function of energy. As we do not find a clear relationship
between our classification scheme and other parameters we conclude that X-ray
pulse profiles are influenced by other hidden variables.


  This paper proposes a fractional-order reset element whose architecture
allows for the suppression of nonlinear effects for a range of frequencies.
Suppressing the nonlinear effects of a reset element for the desired frequency
range while maintaining it for the rest is beneficial, especially when it is
used in the framework of a "Constant in gain, Lead in phase" (CgLp) filter.
CgLp is a newly introduced nonlinear filter, bound to circumvent the well-known
linear control limitation -- the waterbed effect. The ideal behaviour of such a
filter in the frequency domain is unity gain while providing a phase lead for a
broad range of frequencies. However, CgLp's ideal behaviour is based on the
describing function, which is a first-order approximation that neglects the
effects of the higher-order harmonics in the output of the filter. Although
CgLp is fundamentally a nonlinear filter, its nonlinearity is not required for
all frequencies. Thus, it is shown in this paper that using the proposed reset
element architecture, CgLp gets closer to its ideal behaviour for a range of
frequencies, and its performance will be improved accordingly.


  The benefits of autonomous vehicles (AVs) are widely acknowledged, but there
are concerns about the extent of these benefits and AV risks and unintended
consequences. In this article, we first examine AVs and different categories of
the technological risks associated with them. We then explore strategies that
can be adopted to address these risks, and explore emerging responses by
governments for addressing AV risks. Our analyses reveal that, thus far,
governments have in most instances avoided stringent measures in order to
promote AV developments and the majority of responses are non-binding and focus
on creating councils or working groups to better explore AV implications. The
US has been active in introducing legislations to address issues related to
privacy and cybersecurity. The UK and Germany, in particular, have enacted laws
to address liability issues, other countries mostly acknowledge these issues,
but have yet to implement specific strategies. To address privacy and
cybersecurity risks strategies ranging from introduction or amendment of non-AV
specific legislation to creating working groups have been adopted. Much less
attention has been paid to issues such as environmental and employment risks,
although a few governments have begun programmes to retrain workers who might
be negatively affected.


  Large deviation theory is a branch of probability theory that is devoted to a
study of the "rate" at which empirical estimates of various quantities converge
to their true values. The object of study in this paper is the rate at which
estimates of the doublet frequencies of a Markov chain over a finite alphabet
converge to their true values. In case the Markov process is actually an
i.i.d.\ process, the rate function turns out to be the relative entropy (or
Kullback-Leibler divergence) between the true and the estimated probability
vectors. This result is a special case of a very general result known as
Sanov's theorem and dates back to 1957. Moreover, since the introduction of the
"method of types" by Csisz\'{a}r and his co-workers during the 1980s, the proof
of this version of Sanov's theorem has been "elementary," using some
combinatorial arguments. However, when the i.i.d.\ process is replaced by a
Markov process, the available proofs are far more complex. The main objective
of this paper is therefore to present a first-principles derivation of the LDP
for finite state Markov chains, using only simple combinatorial arguments
(e.g.\ the method of types), thus gathering in one place various arguments and
estimates that are scattered over the literature.


  A planetary system may undergo significant radial rearrangement during the
early part of its lifetime. Planet migration can come about through interaction
with the surrounding planetesimal disk and the gas disk--while the latter is
still present--as well as through planet-planet interactions. We review the
major proposed migration mechanisms in the context of the planet formation
process, in our Solar System as well as in others.


  The friends-of-friends algorithm (hereafter, FOF) is a percolation algorithm
which is routinely used to identify dark matter halos from N-body simulations.
We use results from percolation theory to show that the boundary of FOF halos
does not correspond to a single density threshold but to a range of densities
close to a critical value that depends upon the linking length parameter, b. We
show that for the commonly used choice of b = 0.2, this critical density is
equal to 81.62 times the mean matter density. Consequently, halos identified by
the FOF algorithm enclose an average overdensity which depends on their density
profile (concentration) and therefore changes with halo mass contrary to the
popular belief that the average overdensity is ~180. We derive an analytical
expression for the overdensity as a function of the linking length parameter b
and the concentration of the halo. Results of tests carried out using simulated
and actual FOF halos identified in cosmological simulations show excellent
agreement with our analytical prediction. We also find that the mass of the
halo that the FOF algorithm selects crucially depends upon mass resolution. We
find a percolation theory motivated formula that is able to accurately correct
for the dependence on number of particles for the mock realizations of
spherical and triaxial Navarro-Frenk-White halos. However, we show that this
correction breaks down when applied to the real cosmological FOF halos due to
presence of substructures. Given that abundance of substructure depends on
redshift and cosmology, we expect that the resolution effects due to
substructure on the FOF mass and halo mass function will also depend on
redshift and cosmology and will be difficult to correct for in general.
Finally, we discuss the implications of our results for the universality of the
mass function.


  With the increasing reliance of self-driving and similar robotic systems on
robust 3D vision, the processing of LiDAR scans with deep convolutional neural
networks has become a trend in academia and industry alike. Prior attempts on
the challenging Semantic Scene Completion task - which entails the inference of
dense 3D structure and associated semantic labels from "sparse" representations
- have been, to a degree, successful in small indoor scenes when provided with
dense point clouds or dense depth maps often fused with semantic segmentation
maps from RGB images. However, the performance of these systems drop
drastically when applied to large outdoor scenes characterized by dynamic and
exponentially sparser conditions. Likewise, processing of the entire sparse
volume becomes infeasible due to memory limitations and workarounds introduce
computational inefficiency as practitioners are forced to divide the overall
volume into multiple equal segments and infer on each individually, rendering
real-time performance impossible. In this work, we formulate a method that
subsumes the sparsity of large-scale environments and present S3CNet, a sparse
convolution based neural network that predicts the semantically completed scene
from a single, unified LiDAR point cloud. We show that our proposed method
outperforms all counterparts on the 3D task, achieving state-of-the art results
on the SemanticKITTI benchmark. Furthermore, we propose a 2D variant of S3CNet
with a multi-view fusion strategy to complement our 3D network, providing
robustness to occlusions and extreme sparsity in distant regions. We conduct
experiments for the 2D semantic scene completion task and compare the results
of our sparse 2D network against several leading LiDAR segmentation models
adapted for bird's eye view segmentation on two open-source datasets.


  This paper gives upper and lower bounds for the degree of the field of
definition of a singular K3 surface, generalising a recent result by Shimada.
We use work of Shioda-Mitani and Shioda-Inose and classical theory of complex
multiplication.


  Self-testing refers to the phenomenon that certain extremal quantum
correlations (almost) uniquely identify the quantum system under consideration.
For instance observing the maximal violation of the CHSH inequality certifies
that the two parties share a singlet. While self-testing results are known for
several classes of states, in many cases they are only applicable if the
observed statistics are almost perfect, which makes them unsuitable for
practical applications. Practically relevant self-testing bounds are much less
common and moreover they all result from a single numerical method (with one
exception which we discuss in detail). In this work we present a new technique
for proving analytic self-testing bounds of practically relevant robustness. We
obtain improved bounds for the case of self-testing the singlet using the CHSH
inequality (in particular we show that non-trivial fidelity with the singlet
can be achieved as long as the violation exceeds $\beta^{*} = (16 + 14
\sqrt{2})/17 \approx 2.11$). In case of self-testing the tripartite GHZ state
using the Mermin inequality we derive a bound which not only improves on
previously known results but turns out to be tight. We discuss other scenarios
to which our technique can be immediately applied.


  We strictly define two set Wave-function Renormalization Constants (WRC)
under the LSZ reduction formula for unstable particles at the first time. Then
by introducing antiparticle's WRC and the CPT conservation law we obtain a new
wave-function renormalization condition which can be used to totally determine
the two set WRC. We calculate two physical processes to manifest the
consistence of the present wave-function renormalization prescription with the
gauge theory in standard model. We also prove that the conventional
wave-function renormalization prescription which discards the imaginary part of
unstable particle's WRC leads to physical amplitude gauge dependent.


  We present a symbolic representation for the poly-Bernoulli numbers. This
allows us to prove several new iterated integral representations for the
poly-Bernoulli numbers, including an integral transform of the Bernoulli-Barnes
numbers. We also deduce some new recurrences for the poly-Bernoulli numbers.
Finally, we use these results to present a new iterated integral representation
for the Arakawa-Kaneko zeta function, including a nonlinear integral transform
of the Barnes zeta function.


  We study models where the gauge coupling constants, masses, etc are functions
of some conserved charge in the universe. We first consider the standard Dirac
action, but where the mass and the electromagnetic coupling constant are a
function of the charge in the universe and afterwards extend this scalar
fields. For Dirac field in the flat space formulation, the formalism is not
manifestly Lorentz invariant, however Lorentz invariance can be restored by
performing a phase transformation of the Dirac field. In the case where scalar
field are considered, there is the new feature that an initial condition for
the scalar field is derived from the action. In the case of the Higgs field,
the initial condition require, that the universe be at the false vacuum state
at a certain time slice, which is quite important for inflation scenarios. Also
false vacuum branes will be studied in a similar approach. We discuss also the
use of "spoiling terms", that violate gauge invariant to introduce these
initial condition.


  It is shown that a ferroelastic lattice distortion is associated with the
superconducting transition both in low- and high-temperature superconductors. A
low-temperature ferroelastic transition in crystalline solids produces also a
maximum in the temperature dependence of their thermal conductivity. In layered
tetragonal superconductors with a sufficiently high transition temperature, a
ferroelastic distortion is improper and is caused by an out-of-plane charge
ordering. The relation between the out-of-plane charge gap and the maximum
superconducting transition temperature for these superconductors is obtained.


  The dominant source of decoherence for an electron spin in a quantum dot is
the hyperfine interaction with the surrounding bath of nuclear spins. The
decoherence process may be slowed down by subjecting the electron spin to
suitable sequences of external control pulses. We investigate the performance
of a variety of dynamical decoupling protocols using exact numerical
simulation. Emphasis is given to realistic pulse delays and the long-time
limit, beyond the domain where available analytical approaches are guaranteed
to work. Our results show that both deterministic and randomized protocols are
capable to significantly prolong the electron coherence time, even when using
control pulse separations substantially larger than what expected from the {\em
upper cutoff} frequency of the coupling spectrum between the electron and the
nuclear spins. In a realistic parameter range, the {\em total width} of such a
coupling spectrum appears to be the physically relevant frequency scale
affecting the overall quality of the decoupling.


  Many researchers have been concerned with whether social media has a negative
impact on the well-being of their audience. With the popularity of social
networking sites (SNS) steadily increasing, psychological and social sciences
have shown great interest in their effects and consequences on humans. In this
work, we investigate Facebook using the tools of HCI to find connections
between interface features and the concerns raised by these domains. Using an
empirical design analysis, we identify interface interferences impacting users'
online privacy. Through a subsequent survey (n=116), we find usage behaviour
changes due to increased privacy concerns and report individual cases of
addiction and mental health issues. These observations are the results of a
rapidly changing SNS creating a gap of understanding between users'
interactions with the platform and future consequences. We explore how HCI can
help close this gap and work towards more ethical user interfaces in the
future.


  We derive the potential modular symmetries of heterotic string theory. For a
toroidal compactification with Wilson line modulus, we obtain the Siegel
modular group $\mathrm{Sp}(4,\mathbb{Z})$ that includes the modular symmetries
$\mathrm{SL}(2,\mathbb{Z})_T$ and $\mathrm{SL}(2,\mathbb{Z})_U$ (of the
"geometric" moduli $T$ and $U$) as well as mirror symmetry. In addition, string
theory provides a candidate for a CP-like symmetry that enhances the Siegel
modular group to $\mathrm{GSp}(4,\mathbb{Z})$.


  The spin-1/2 quantum anisotropic XY spin chain in a transverse random
magnetic field parallel to the z axis is numerically studied by means of the
density-matrix renormalization group. The dependence of the spontaneous
magnetization and the energy gap on both the strength of the random magnetic
field and the factor of anisotropy is determined. The critical line for the
order-disorder phase transition is obtained and the resulting phase diagram is
drawn. Our results are compatible with the fact that models with different
factors of anisotropy fall within the same universality class as the quantum
Ising model in a transverse random field.


  We have simulated QCD using 2+1 flavors of domain wall quarks on a $(2.74
{\rm fm})^3$ volume with an inverse lattice scale of $a^{-1} = 1.729(28)$ GeV.
The up and down (light) quarks are degenerate in our calculations and we have
used four values for the ratio of light quark masses to the strange (heavy)
quark mass in our simulations: 0.217, 0.350, 0.617 and 0.884. We have measured
pseudoscalar meson masses and decay constants, the kaon bag parameter $B_K$ and
vector meson couplings. We have used SU(2) chiral perturbation theory, which
assumes only the up and down quark masses are small, and SU(3) chiral
perturbation theory to extrapolate to the physical values for the light quark
masses. While next-to-leading order formulae from both approaches fit our data
for light quarks, we find the higher order corrections for SU(3) very large,
making such fits unreliable. We also find that SU(3) does not fit our data when
the quark masses are near the physical strange quark mass. Thus, we rely on
SU(2) chiral perturbation theory for accurate results. We use the masses of the
$\Omega$ baryon, and the $\pi$ and $K$ mesons to set the lattice scale and
determine the quark masses. We then find $f_\pi = 124.1(3.6)_{\rm
stat}(6.9)_{\rm syst} {\rm MeV}$, $f_K = 149.6(3.6)_{\rm stat}(6.3)_{\rm syst}
{\rm MeV}$ and $f_K/f_\pi = 1.205(0.018)_{\rm stat}(0.062)_{\rm syst}$. Using
non-perturbative renormalization to relate lattice regularized quark masses to
RI-MOM masses, and perturbation theory to relate these to $\bar{\rm MS}$ we
find $ m_{ud}^{\bar{\rm MS}}(2 {\rm GeV}) = 3.72(0.16)_{\rm stat}(0.33)_{\rm
ren}(0.18)_{\rm syst} {\rm MeV}$ and $m_{s}^{\bar{\rm MS}}(2 {\rm GeV}) =
107.3(4.4)_{\rm stat}(9.7)_{\rm ren}(4.9)_{\rm syst} {\rm MeV}$.


  Semantic segmentation models struggle to generalize in the presence of domain
shift. In this paper, we introduce contrastive learning for feature alignment
in cross-domain adaptation. We assemble both in-domain contrastive pairs and
cross-domain contrastive pairs to learn discriminative features that align
across domains. Based on the resulting well-aligned feature representations we
introduce a label expansion approach that is able to discover samples from hard
classes during the adaptation process to further boost performance. The
proposed approach consistently outperforms state-of-the-art methods for domain
adaptation. It achieves 60.2% mIoU on the Cityscapes dataset when training on
the synthetic GTA5 dataset together with unlabeled Cityscapes images.


  The ground state and zero-temperature magnetization process of the spin-1/2
Ising-Heisenberg model on two-dimensional triangles-in-triangles lattices is
exactly calculated using eigenstates of the smallest commuting spin clusters.
Our ground-state analysis of the investigated classical--quantum spin model
reveals three unconventional dimerized or trimerized quantum ground states
besides two classical ground states. It is demonstrated that the spin
frustration is responsible for a variety of magnetization scenarios with up to
three or four intermediate magnetization plateaus of either quantum or
classical nature. The exact analytical results for the Ising-Heisenberg model
are confronted with the corresponding results for the purely quantum Heisenberg
model, which were obtained by numerical exact diagonalizations based on the
Lanczos algorithm for finite-size spin clusters of 24 and 21 sites,
respectively. It is shown that the zero-temperature magnetization process of
both models is quite reminiscent and hence, one may obtain some insight into
the ground states of the quantum Heisenberg model from the rigorous results for
the Ising-Heisenberg model even though exact ground states for the
Ising-Heisenberg model do not represent true ground states for the pure quantum
Heisenberg model.


  A gamma-ray halo in a nearby starburst galaxy NGC 253 was found by the
CANGAROO-II Imaging Atmospheric Cherenkov Telescope (IACT). By fitting the
energy spectrum with expected curves from Cold Dark Matter (CDM) annihilations,
we constrain the CDM-annihilation rate in the halo of NGC 253. Upper limits for
the CDM density were obtained in the wide mass range between 0.5 and 50 TeV.
Although these limits are higher than the expected values, it is complementary
important to the other experimental techniques, especially considering the
energy coverage. We also investigate the next astronomical targets to improve
these limits.


  The discovery of the youngest Galactic supernova remnant (SNR) G1.9+0.3 has
allowed a look at a stage of SNR evolution never before observed. We analyze
the 50 ks Chandra observation with particular regard to spectral variations.
The very high column density ($N_H \sim 6 \times 10^{22}$ cm$^{-2}$) implies
that dust scattering is important, and we use a simple scattering model in our
spectral analysis. The integrated X-ray spectrum of G1.9+0.3 is well described
by synchrotron emission from a power-law electron distribution with an
exponential cutoff. Using our measured radio flux and including scattering
effects, we find a rolloff frequency of $5.4 (3.0, 10.2) \times 10^{17}$ Hz ($h
\nu_{\rm roll} = 2.2$ keV). Including scattering in a two-region model gives
lower values of \nu_roll by over a factor of 2. Dividing G1.9+0.3 into six
regions, we find a systematic pattern in which spectra are hardest (highest
\nu_roll) in the bright SE and NW limbs of the shell. They steepen as one moves
around the shell or into the interior. The extensions beyond the bright parts
of the shell have the hardest spectra of all. We interpret the results in terms
of dependence of shock acceleration properties on the obliquity angle
$\theta_{\rm Bn}$ between the shock velocity and a fairly uniform upstream
magnetic field. This interpretation probably requires a Type Ia event. If
electron acceleration is limited by synchrotron losses, the spectral variations
require obliquity-dependence of the acceleration rate independent of the
magnetic-field strength.


  We study a mixed boundary value problem for the quasilinear elliptic equation
$\mathop{\rm div}\mathcal{A}(x,\nabla u(x))=0$ in an open infinite circular
half-cylinder with prescribed continuous Dirichlet data on a part of the
boundary and zero conormal derivative on the rest. We prove the existence and
uniqueness of bounded weak solutions to the mixed problem and characterize the
regularity of the point at infinity in terms of \p-capacities. For solutions
with only Neumann data near the point at infinity we show that they behave in
exactly one of three possible ways, similar to the alternatives in the
Phragm\'en--Lindel\"of principle.


  Search is an important tool for computing effective policies in single- and
multi-agent environments, and has been crucial for achieving superhuman
performance in several benchmark fully and partially observable games. However,
one major limitation of prior search approaches for partially observable
environments is that the computational cost scales poorly with the amount of
hidden information. In this paper we present \emph{Learned Belief Search}
(LBS), a computationally efficient search procedure for partially observable
environments. Rather than maintaining an exact belief distribution, LBS uses an
approximate auto-regressive counterfactual belief that is learned as a
supervised task. In multi-agent settings, LBS uses a novel public-private model
architecture for underlying policies in order to efficiently evaluate these
policies during rollouts. In the benchmark domain of Hanabi, LBS can obtain 55%
~ 91% of the benefit of exact search while reducing compute requirements by
$35.8 \times$ ~ $4.6 \times$, allowing it to scale to larger settings that were
inaccessible to previous search methods.


  Soft X-ray resonant scattering (XRS) has been used to observe directly, for
the first time, the ordering of localized electronic states on both the Mn and
Tb sites in multiferroic TbMnO$_3$. Large resonant enhancement of the X-ray
scattering cross-section were observed when the incident photon energy was
tuned to either the Mn $L$ or Tb $M$ edges which provide information on the Mn
3d and Tb $4f$ electronic states, respectively. The temperature dependence of
the XRS signal establishes, in a model independent way, that in the
high-temperature phase (28 K $\leq$ T $\leq$ 42 K) the Mn 3d sublattices
displays long-range order. The Tb $4f$ sublattices are found to order only on
entering the combined ferroelectric/magnetic state below 28 K. Our results are
discussed with respect to recent hard XRS experiments (sensitive to spatially
extended orbitals) and neutron scattering.


  We report the discovery of 5 new Herbig Ae/Be candidate stars in the Small
Magellanic Cloud in addition to the 2 reported in Beaulieu et al. (2001). We
discuss these 7 HAeBe candidate stars in terms of (1) their irregular
photometric variability, (2) their near infrared emission, (3) their Halpha
emission and (4) their spectral type. One star has the typical photometric
behaviour that is observed only among Pre-Main Sequence UX Orionis type stars.
The objects are more luminous than Galactic HAeBe stars and Large Magellanic
Cloud HAeBe candidates of the same spectral type. The stars were discovered in
a systematic search for variable stars in a subset of the EROS2 database
consisting of 115,612 stars in a field of 24x24 arcmin in the Small Magellanic
Cloud. In total we discovered 504 variable stars. After classifying the
different objects according to their type of variability, we concentrate on 7
blue objects with irregular photometric behaviour. We cross-identified these
objects with emission line catalogues from Simbad and JHK photometry from
2MASS. The analysis is supplemented with obtained narrow and broad band
imaging. We discuss their variability in terms of dust obscuration and
bound-free and free-free emission. We estimate the influence of metallicity on
the circumstellar dust emission from pre-main sequence stars.


  Grounded video description (GVD) encourages captioning models to attend to
appropriate video regions (e.g., objects) dynamically and generate a
description. Such a setting can help explain the decisions of captioning models
and prevents the model from hallucinating object words in its description.
However, such design mainly focuses on object word generation and thus may
ignore fine-grained information and suffer from missing visual concepts.
Moreover, relational words (e.g., "jump left or right") are usual
spatio-temporal inference results, i.e., these words cannot be grounded on
certain spatial regions. To tackle the above limitations, we design a novel
relational graph learning framework for GVD, in which a language-refined scene
graph representation is designed to explore fine-grained visual concepts.
Furthermore, the refined graph can be regarded as relational inductive
knowledge to assist captioning models in selecting the relevant information it
needs to generate correct words. We validate the effectiveness of our model
through automatic metrics and human evaluation, and the results indicate that
our approach can generate more fine-grained and accurate description, and it
solves the problem of object hallucination to some extent.


  Open quantum systems display unusual phenomena not seen in closed systems,
such as new topological phases and unconventional phase transitions. An
interesting example was studied for a quantum spin liquid in the Kitaev model
[K. Yang, S. C. Morampudi, and E. J. Bergholtz, Phys. Rev. Lett. ${\bf 126}$,
077201 (2021)]; an effective non-Hermitian Kitaev model, which incorporates
dissipation effects, was shown to give rise to a gapless spin liquid state with
exceptional points in the Majorana dispersions. Given that an external magnetic
field induces a gapped Majorana topological state in the Hermitian case, the
exceptional points may bring about intriguing quantum phenomena under a
magnetic field. Here we investigate the non-Hermitian Kitaev model perturbed by
the magnetic field. We show that the exceptional points remain gapless up to a
finite critical magnetic field, in stark contrast to the Hermitian case where
an infinitesimal field opens a gap. The gapless state is stable over a wide
range of the magnetic field for some particular parameter sets, and in special
cases, undergoes topological transitions to another gapless state with
different winding number around the exceptional points without opening a gap.
In addition, in the system with edges, we find that the non-Hermitian skin
effect is induced by the magnetic field, even for the parameters where the skin
effect is absent at zero field. The chirality of edge states is switched
through the exceptional points, similarly to the surface Fermi arcs connected
by the Weyl points in three-dimensional Weyl semimetals. Our results provide a
new possible route to stabilize topological gapless quantum spin liquids under
the magnetic field in the presence of dissipation.


  To effectively tackle the security threats towards the Internet of things, we
propose a SOM-based DDoS defense mechanism using software-defined networking
(SDN) in this paper. The main idea of the mechanism is to deploy a SDN-based
gateway to protect the device services in the Internet of things. The gateway
provides DDoS defense mechanism based on SOM neural network. By means of
SOM-based DDoS defense mechanism, the gateway can effectively identify the
malicious sensing devices in the IoT, and automatically block those malicious
devices after detecting them, so that it can effectively enforce the security
and robustness of the system when it is under DDoS attacks. In order to
validate the feasibility and effectiveness of the mechanism, we leverage POX
controller and Mininet emulator to implement an experimental system, and
further implement the aforementioned security enforcement mechanisms with
Python. The final experimental results illustrate that the mechanism is truly
effective under the different test scenarios.


  We consider an optimal control on networks in the spirit of the works of
Achdou et al. (2013) and Imbert et al. (2013). The main new feature is that
there are entry (or exit) costs at the edges of the network leading to a
possible discontinuous value function. We characterize the value function as
the unique viscosity solution of a new Hamilton-Jacobi system. The uniqueness
is a consequence of a comparison principle for which we give two different
proofs, one with arguments from the theory of optimal control inspired by
Achdou et al. (2014) and one based on partial differential equations techniques
inspired by a recent work of Lions and Souganidis (2016).


  We study the thermodynamic behavior of the random chain model proposed by
Iori, Marinari and Parisi, and how this depends on the actual sequence of
interactions along the chain. The properties of randomly chosen sequences are
compared to those of designed ones, obtained through a simulated annealing
procedure in sequence space. We show that the transition to the folded phase
takes place at a smaller strength of the quenched disorder for designed
sequences. As a result, folding can be relatively fast for these sequences.


  It has been found in recent heavy-ion experiments that the second and the
third flow harmonics of direct photons are larger than most theoretical
predictions. In this study, I construct effective parton phase-space
distributions with in-medium interaction using quasi-particle models so that
they are consistent with a lattice QCD equation of state. Then I investigate
their effects on thermal photons using a hydrodynamic model. Numerical results
indicate that elliptic flow and transverse momentum spectra are modified by the
corrections to Fermi-Dirac and Bose-Einstein distributions.


  We establish the reciprocity law along a vertical curve for residues of
differential forms on arithmetic surfaces, and describe Grothendieck's trace
map of the surface as a sum of residues. Points at infinity are then
incorporated into the theory and the reciprocity law is extended to all curves
on the surface. Applications to adelic duality for the arithmetic surface are
discussed.


  We present a nanoscale color detector based on a single-walled carbon
nanotube functionalized with azobenzene chromophores, where the chromophores
serve as photoabsorbers and the nanotube as the electronic read-out. By
synthesizing chromophores with specific absorption windows in the visible
spectrum and anchoring them to the nanotube surface, we demonstrate the
controlled detection of visible light of low intensity in narrow ranges of
wavelengths. Our measurements suggest that upon photoabsorption, the
chromophores isomerize from the ground state trans configuration to the excited
state cis configuration, accompanied by a large change in dipole moment,
changing the electrostatic environment of the nanotube. All-electron ab initio
calculations are used to study the chromophore-nanotube hybrids, and show that
the chromophores bind strongly to the nanotubes without disturbing the
electronic structure of either species. Calculated values of the dipole moments
support the notion of dipole changes as the optical detection mechanism.


  The first loading of gadolinium (Gd) into Super-Kamiokande in 2020 was
successful, and the neutron capture efficiency on Gd reached 50\%. To further
increase the Gd neutron capture efficiency to 75\%, 26.1 tons of $\rm Gd_2(\rm
SO_4)_3\cdot \rm 8H_2O$ was additionally loaded into Super-Kamiokande (SK) from
May 31 to July 4, 2022. As the amount of loaded $\rm Gd_2(\rm SO_4)_3\cdot \rm
8H_2O$ was doubled compared to the first loading, the capacity of the powder
dissolving system was doubled. We also developed new batches of gadolinium
sulfate with even further reduced radioactive impurities. In addition, a more
efficient screening method was devised and implemented to evaluate these new
batches of $\rm Gd_2(\rm SO_4)_3\cdot \rm 8H_2O$. Following the second loading,
the Gd concentration in SK was measured to be $333.5\pm2.5$ ppm via an Atomic
Absorption Spectrometer (AAS). From the mean neutron capture time constant of
neutrons from an Am/Be calibration source, the Gd concentration was
independently measured to be 332.7 $\pm$ 6.8(sys.) $\pm$ 1.1(stat.) ppm,
consistent with the AAS result. Furthermore, during the loading the Gd
concentration was monitored continually using the capture time constant of each
spallation neutron produced by cosmic-ray muons,and the final neutron capture
efficiency was shown to become 1.5 times higher than that of the first loaded
phase, as expected.


  The past decade has seen vast progress in deep reinforcement learning (RL) on
the back of algorithms manually designed by human researchers. Recently, it has
been shown that it is possible to meta-learn update rules, with the hope of
discovering algorithms that can perform well on a wide range of RL tasks.
Despite impressive initial results from algorithms such as Learned Policy
Gradient (LPG), there remains a generalization gap when these algorithms are
applied to unseen environments. In this work, we examine how characteristics of
the meta-training distribution impact the generalization performance of these
algorithms. Motivated by this analysis and building on ideas from Unsupervised
Environment Design (UED), we propose a novel approach for automatically
generating curricula to maximize the regret of a meta-learned optimizer, in
addition to a novel approximation of regret, which we name algorithmic regret
(AR). The result is our method, General RL Optimizers Obtained Via Environment
Design (GROOVE). In a series of experiments, we show that GROOVE achieves
superior generalization to LPG, and evaluate AR against baseline metrics from
UED, identifying it as a critical component of environment design in this
setting. We believe this approach is a step towards the discovery of truly
general RL algorithms, capable of solving a wide range of real-world
environments.


  We present new results based on RXTE observations of SAX J1808.4-3658. The
X-ray spectrum can be fitted by a two-component model. We interpret the soft
component as blackbody emission from a heated spot on the neutron star, and the
hard component as coming from Comptonization in plasma heated by the accretion
shock as the material collimated by the magnetic field impacts onto the neutron
star surface. The hotspot is probably the source of seed photons for
Comptonization. The hard component illuminates the disc, giving rise to a
reflected spectrum. The inferred evolution of the inner radius is not
consistent with the magnetic field truncating the disc. Instead it seems more
likely that the inner disc radius is set by some much longer time-scale
process, most probably connected to the overall evolution of the accretion
disc. This disc truncation mechanism would then have to be generic in all low
mass accretion rate flows both in disc accreting neutron stars and black hole
systems. The phase resolved spectra show clearly that the blackbody and hard
Comptonized spectra pulse independently. This obviously gives an energy
dependent phase lag. Full general relativistic effects are not required to
explain this. We do not detect Compton reflection from the neutron star
surface, though we predict that it should be present in the X-ray spectrum.
This would give an unambiguous observational measure of M/R if there is any
iron on the neutron star surface which is not completely ionized.


  The study of synchronization among genetic oscillators is essential for the
understanding of the rhythmic phenomena of living organisms at both molecular
and cellular levels. Genetic networks are intrinsically noisy due to natural
random intra- and inter-cellular fluctuations. Therefore, it is important to
study the effects of noise perturbation on the synchronous dynamics of genetic
oscillators. From the synthetic biology viewpoint, it is also important to
implement biological systems that minimizing the negative influence of the
perturbations. In this paper, based on systems biology approach, we provide a
general theoretical result on the synchronization of genetic oscillators with
stochastic perturbations. By exploiting the specific properties of many genetic
oscillator models, we provide an easy-verified sufficient condition for the
stochastic synchronization of coupled genetic oscillators, based on the Lur'e
system approach in control theory. A design principle for minimizing the
influence of noise is also presented. To demonstrate the effectiveness of our
theoretical results, a population of coupled repressillators is adopted as a
numerical example. In summary, we present an efficient theoretical method for
analyzing the synchronization of genetic oscillator networks, which is helpful
for understanding and testing the synchronization phenomena in biological
organisms. Besides, the results are actually applicable to general oscillator
networks.


  Many inference problems, such as sequential decision problems like A/B
testing, adaptive sampling schemes like bandit selection, are often online in
nature. The fundamental problem for online inference is to provide a sequence
of confidence intervals that are valid uniformly over the growing-into-infinity
sample sizes. To address this question, we provide a near-optimal confidence
sequence for bounded random variables by utilizing Bentkus' concentration
results. We show that it improves on the existing approaches that use the
Cram{\'e}r-Chernoff technique such as the Hoeffding, Bernstein, and Bennett
inequalities. The resulting confidence sequence is confirmed to be favorable in
both synthetic coverage problems and an application to adaptive stopping
algorithms.


  Pedestrian detection plays an important role in many applications such as
autonomous driving. We propose a method that explores semantic segmentation
results as self-attention cues to significantly improve the pedestrian
detection performance. Specifically, a multi-task network is designed to
jointly learn semantic segmentation and pedestrian detection from image
datasets with weak box-wise annotations. The semantic segmentation feature maps
are concatenated with corresponding convolution features maps to provide more
discriminative features for pedestrian detection and pedestrian classification.
By jointly learning segmentation and detection, our proposed pedestrian
self-attention mechanism can effectively identify pedestrian regions and
suppress backgrounds. In addition, we propose to incorporate semantic attention
information from multi-scale layers into deep convolution neural network to
boost pedestrian detection. Experiment results show that the proposed method
achieves the best detection performance with MR of 6.27% on Caltech dataset and
obtain competitive performance on CityPersons dataset while maintaining high
computational efficiency.


  This paper is concerned with a partially observed hybrid optimal control
problem, where continuous dynamics and discrete events coexist and in
particular, the continuous dynamics can be observed while the discrete events,
described by a Markov chain, is not directly available. Such kind of problem is
first considered in the literature and has wide applications in finance,
management, engineering, and so on. There are three major contributions made in
this paper: First, we develop a novel non-linear filtering method to convert
the partially observed problem into a completely observed one. Our method
relies on some delicate stochastic analysis technique related to hybrid
diffusions and is essentially different from the traditional filtering
approaches. Second, we establish a new maximum principle based on the
completely observed problem, whose two-dimensional state process consists of
the continuous dynamics and the optimal filter. An important advantage of the
maximum principle is that it takes a simple form and is convenient to
implement. Finally, in order to illustrate the theoretical results, we solve a
linear quadratic (LQ) example using the derived maximum principle to get some
observable optimal controls.


  The quantum dissipative dynamics of a tunneling process through double
barrier structures is investigated on the basis of non-perturbative and
non-Markovian treatment. We employ a Caldeira-Leggett Hamiltonian with an
effective potential calculated self-consistently, accounting for the electron
distribution. With this Hamiltonian, we use the reduced hierarchy equations of
motion in the Wigner space representation to study non-Markovian and
non-perturbative thermal effects at finite temperature in a rigorous manner. We
study current variation in time and the current-voltage (I-V) relation of the
resonant tunneling diode for several widths of the contact region, which
consists of doped GaAs. Hysteresis and both single and double plateau-like
behavior are observed in the negative differential resistance (NDR) region.
While all of the current oscillations decay in time in the NDR region in the
case of a strong system-bath coupling, there exist self-excited high-frequency
current oscillations in some parts of the plateau in the NDR region in the case
of weak coupling. We find that the effective potential in the oscillating case
possesses a basin-like form on the emitter side (emitter basin) and that the
current oscillation results from tunneling between the emitter basin and the
quantum well in the barriers. We find two distinct types of current
oscillations, with large and small oscillation amplitudes, respectively. These
two types of oscillation appear differently in the Wigner space, with one
exhibiting tornado-like motion and the other exhibiting a two piston
engine-like motion.


  5d Yang-Mills theory with an Sp(N) gauge group admits a discrete analog of
the theta parameter. We describe the origin of this parameter in N=1 theories
from Type I' string theory, and study its effect on the 5d superconformal fixed
point theories with an Sp(1)=SU(2) gauge group by computing the superconformal
index. Our result confirms the lack of global symmetry enhancement in the
so-called \tilde{E}_1 theory.


  We present a novel introspective variational autoencoder (IntroVAE) model for
synthesizing high-resolution photographic images. IntroVAE is capable of
self-evaluating the quality of its generated samples and improving itself
accordingly. Its inference and generator models are jointly trained in an
introspective way. On one hand, the generator is required to reconstruct the
input images from the noisy outputs of the inference model as normal VAEs. On
the other hand, the inference model is encouraged to classify between the
generated and real samples while the generator tries to fool it as GANs. These
two famous generative frameworks are integrated in a simple yet efficient
single-stream architecture that can be trained in a single stage. IntroVAE
preserves the advantages of VAEs, such as stable training and nice latent
manifold. Unlike most other hybrid models of VAEs and GANs, IntroVAE requires
no extra discriminators, because the inference model itself serves as a
discriminator to distinguish between the generated and real samples.
Experiments demonstrate that our method produces high-resolution
photo-realistic images (e.g., CELEBA images at \(1024^{2}\)), which are
comparable to or better than the state-of-the-art GANs.


  We investigate a novel mechanism of dynamical tuning of a flat potential in
the open string landscape within the context of warped brane-antibrane
inflation in type IIB string theory. Because of competing effects between
interactions with the moduli stabilizing D7-branes in the warped throat and
anti-D3-branes at the tip, a stack of branes gives rise to a local minimum of
the potential, holding the branes high up in the throat. As branes successively
tunnel out of the local minimum to the bottom of the throat the potential
barrier becomes lower and is eventually replaced by a flat inflection point,
around which the remaining branes easily inflate. This dynamical flattening of
the inflaton potential reduces the need to fine tune the potential by hand, and
also leads to successful inflation for a larger range of inflaton initial
conditions, due to trapping in the local minimum.


  Indoor scene augmentation has become an emerging topic in the field of
computer vision and graphics with applications in augmented and virtual
reality. However, current state-of-the-art systems using deep neural networks
require large datasets for training. In this paper we introduce GSACNet, a
contextual scene augmentation system that can be trained with limited scene
priors. GSACNet utilizes a novel parametric data augmentation method combined
with a Graph Attention and Siamese network architecture followed by an
Autoencoder network to facilitate training with small datasets. We show the
effectiveness of our proposed system by conducting ablation and comparative
studies with alternative systems on the Matterport3D dataset. Our results
indicate that our scene augmentation outperforms prior art in scene synthesis
with limited scene priors available.


  The complete forms of the S-matrix elements of a transverse scalar field, two
world volume gauge fields, and a Potential $C_{n-1}$ Ramond-Ramond (RR) form
field are investigated. In order to find an infinite number of $t,s,
(t+s+u)$-channel bulk singularity structures of this particular mixed
open-closed amplitude, we employ all the conformal field theory techniques to
$<V_{C^{-2}}V_{\phi ^{0}} V_{A^{0}} V_{A^{0}}>$, exploring all the entire
correlation functions and all order $\alpha'$ contact interactions to these
supersymmetric Yang-Mills (SYM) couplings. Singularity and contact term
comparisons with the other symmetric analysis, $<V_{C^{-1}}V_{\phi ^{0}}
V_{A^{-1}} V_{A^{0}}>$ and $<V_{C^{-1}}V_{\phi ^{-1}} V_{A^{0}} V_{A^{0}}>$ are
also carried out in detail. Various couplings from pull-Back of branes, Myers
terms and several generalized Bianchi identities should be taken into account
to be able to reconstruct all order $\alpha'$ bulk singularities of type IIB
(IIA) superstring theory. Finally, we make a comment on how to derive without
any ambiguity all order $\alpha'$ contact terms of this S-matrix which carry
momentum of RR in transverse directions.


  To date, no framework combining quantum field theory and general relativity
and hence unifying all four fundamental interactions, exists. Violations of the
Einstein's equivalence principle (EEP), being the foundation of general
relativity, may hold the key to a theory of quantum gravity. The universality
of free fall (UFF), which is one of the three pillars of the EEP, has been
extensively tested with classical bodies. Quantum tests of the UFF, e.g. by
exploiting matter wave interferometry, allow for complementary sets of test
masses, orders of magnitude larger test mass coherence lengths and
investigation of spin-gravity coupling. We review our recent work towards
highly sensitive matter wave tests of the UFF on ground. In this scope, the
first quantum test of the UFF utilizing two different chemical elements, Rb-87
and K-39, yielding an E\"otv\"os ratio $\eta_{\,\text{Rb,K}}=(0.3\pm 5.4)\times
10^{-7}$ has been performed. We assess systematic effects currently limiting
the measurement at a level of parts in $10^8$ and finally present our
strategies to improve the current state-of-the-art with a test comparing the
free fall of rubidium and ytterbium in a very long baseline atom interferometry
setup. Here, a 10 m baseline combined with a precise control of systematic
effects will enable a determination of the E\"otv\"os ratio at a level of parts
in $10^{13}$ and beyond, thus reaching and overcoming the performance limit of
the best classical tests.


  In a recent paper, Krapivsky and Redner (Phys. Rev. E, 71 (2005) 036118)
proposed a new growing network model with new nodes being attached to a
randomly selected node, as well to all ancestors of the target node. The model
leads to a sparse graph with an average degree growing logarithmically with the
system size. Here we present compeling evidence for software networks being the
result of a similar class of growing dynamics. The predicted pattern of network
growth, as well as the stationary in- and out-degree distributions are
consistent with the model. Our results confirm the view of large-scale software
topology being generated through duplication-rewiring mechanisms. Implications
of these findings are outlined.


  Evolution of the spatial arrangement of cells in a primary culture of cardiac
tissue derived from newborn rats was studied experimentally over extended
period. It was found that cells attract each other spontaneously to form a
clustered structure over the timescale of several days. These clusters exhibit
spontaneous rhythmic contraction and have been confirmed to consist of cardiac
muscle cells. Addition of a contraction inhibitor (2,3-butanedione-2-monoxime)
to the culture medium resulted in the inhibition of both the spontaneous
contractions exhibited by the cells as well as the formation of clusters.
Furthermore, the formation of clusters is suppressed when high concentrations
of collagen are used for coating the substratum to which the cells adhere. From
these experimental observations, it was deduced that the cells are mechanically
stressed by the tension associated with repeated contractions and that this
results in the cells becoming compact and attracting each other, finally
resulting in the formation of clusters. This process can be interpreted as
modulation of a cellular network by the activity associated with contraction,
which could be employed to control cellular networks by modifying the dynamics
associated with the contractions in cardiac tissue culture.