  Massive multiple-input multiple-output (MIMO) is a key technology for fifth
generation (5G) communication system. MIMO symbol detection is one of the most
computationally intensive tasks for a massive MIMO baseband receiver. In this
paper, we analyze matrix decomposition algorithms for massive MIMO systems,
which were traditionally used for small-scale MIMO detection due to their
numerical stability and modular design. We present the computational complexity
of linear detection mechanisms based on QR, Cholesky and LDL-decomposition
algorithms for different massive MIMO configurations. We compare them with the
state-of-art approximate inversion-based massive MIMO detection methods. The
results provide important insights for system and very large-scale integration
(VLSI) designers to select appropriate massive MIMO detection algorithms
according to their requirement.


  In magnetic configurations with two or three q=1 (with q being the safety
factor) resonant surfaces in a tokamak plasma, resistive magnetohydrodynamic
modes with poloidal mode numbers m much larger than 1 are found to be linearly
unstable. It is found that these high-m double or triple tearing modes
significantly enhance through nonlinear interactions, the growth of the m=1
mode. This may account for the sudden onset of the internal resistive kink,
i.e., the fast sawtooth trigger. Based on the subsequent reconnection dynamics
that can proceed without formation of the m=1 islands, it is proposed that
high-m triple tearing modes are a possible mechanism for precursor-free partial
collapses during sawtooth oscillations.


  In this paper a multi-objective mathematical model has been used to optimize
grinding parameters include workpiece speed, depth of cut and wheel speed which
highly affect the final surface quality. The mathematical model of the
optimization problem consists of three conflict objective functions subject to
wheel wear and production rate constraints. Exact methods can solve the NLP
model in few seconds, therefore using Meta-heuristic algorithms which provide
near optimal solutions in not suitable. Considering this, five Multi-Objective
Decision Making methods have been used to solve the multi-objective
mathematical model using GAMS software to achieve the optimal parameters of the
grinding process. The Multi-Objective Decision Making methods provide different
effective solutions where the decision maker can choose each solution in
different situations. Different criteria have been considered to evaluate the
performance of the five Multi-Objective Decision Making methods. Also,
Technique for Order of Preference by Similarity to Ideal Solution method has
been used to obtain the priority of each method and determine which
Multi-Objective Decision Making method performs better considering all criteria
simultaneously. The results indicated that Weighted Sum Method and Goal
programming method are the best Multi-Objective Decision Making methods. The
Weighted Sum Method and Goal programming provided solutions which are
competitive to each other. In addition, these methods obtained solutions which
have minimum grinding time, cost and surface roughness among other
Multi-Objective Decision Making methods.


  Markov state models (MSMs) have been broadly adopted for analyzing molecular
dynamics trajectories, but the approximate nature of the models that results
from coarse-graining into discrete states is a long-known limitation. We show
theoretically that, despite the coarse graining, in principle MSM-like analysis
can yield unbiased estimation of key observables. We describe unbiased
estimators for equilibrium state populations, for the mean first-passage time
(MFPT) of an arbitrary process, and for state committors - i.e., splitting
probabilities. Generically, the estimators are only asymptotically unbiased but
we describe how extension of a recently proposed reweighting scheme can
accelerate relaxation to unbiased values. Exactly accounting for 'sliding
window' averaging over finite-length trajectories is a key, novel element of
our analysis. In general, our analysis indicates that coarse-grained MSMs are
asymptotically unbiased for steady-state properties only when appropriate
boundary conditions (e.g., source-sink for MFPT estimation) are applied
directly to trajectories, prior to calculation of the appropriate transition
matrix.


  The cross section of X-ray phase contrast caused by these low-Z elements is
greatly bigger than the absorption. Therefore, in the field of X-ray imaging,
the phase shift information can offer better imaging contrast. In this paper,
we present a data transmission system for the detectors of a phase contrast
X-ray human computed tomography prototype. This system contains 3 data
collecting boards (DCB) and one data transmitting board (DTB). A slip ring is
used to transmit the data from the rotator side to the stator side over a
nowadays commonly used multi-mode fiber (MMF). On the rotator side, 3 DCBs act
as the controller of these detectors. The function of the DTB is to store all
image data from 3 DCBs and implement the commutation with PC. The test shows
that this system can meet the requirement of the prototype.


  Radio waves are strongly scattered in the solar wind, so that their apparent
sources seem to be considerably larger and shifted than the actual ones. Since
the scattering depends on the spectrum of density turbulence, better
understanding of the radio wave propagation provides indirect information on
the relative density fluctuations $\epsilon=\langle\delta n\rangle/\langle
n\rangle$ at the effective turbulence scale length. Here, we have analyzed 30
type III bursts detected by Parker Solar Probe (PSP). For the first time, we
have retrieved type III burst decay times $\tau_{\rm{d}}$ between 1 MHz and 10
MHz thanks to an unparalleled temporal resolution of PSP. We observed a
significant deviation in a power-law slope for frequencies above 1 MHz when
compared to previous measurements below 1 MHz by the twin-spacecraft Solar
TErrestrial RElations Observatory (STEREO) mission. We note that altitudes of
radio bursts generated at 1 MHz roughly coincide with an expected location of
the Alfv\'{e}n point, where the solar wind becomes super-Alfv\'{e}nic. By
comparing PSP observations and Monte Carlo simulations, we predict relative
density fluctuations $\epsilon$ at the effective turbulence scale length at
radial distances between 2.5$R_\odot$ and 14$R_\odot$ to range from $0.22$ and
$0.09$. Finally, we calculated relative density fluctuations $\epsilon$
measured in situ by PSP at a radial distance from the Sun of $35.7$~$R_\odot$
during the perihelion \#1, and the perihelion \#2 to be $0.07$ and $0.06$,
respectively. It is in a very good agreement with previous STEREO predictions
($\epsilon=0.06-0.07$) obtained by remote measurements of radio sources
generated at this radial distance.


  In this work we present a molecular dynamics simulation of a FFM experiment.
The tip-sample interaction is studied by varying the normal force in the tip
and the temperature of the surface. The friction force, cA, at zero load and
the friction coefficient, $\mu$, were obtained. Our results strongly support
the idea that the effective contact area, A, decreases with increasing
temperature and the friction coefficient presents a clear signature of the
premelting process of the surface.


  The compound, Nd2PdSi3, belonging to R2PdSi3 family (R = rare-earths) has
been known to exhibit exotic behavior due to unusual Nd 4f hybridization. Here,
we study the electronic properties of Nd2RhSi3 employing ac and dc
magnetization, heat-capacity, electrical resistivity and magnetoresistance
measurements, as Nd 4f hybridization is expected to be slightly different due
to the changes in the 4d element. The experimental results establish that, like
the Pd analogue, this compound also exhibits ferromagnetic ordering at a rather
high temperature of 16.5 K, unlike many other rare-earth members of this family
which are antiferromagnetic, with a complex magnetism at further lower
temperatures (less than 10 K). There are differences in the measured properties
with respect to the Pd analogue, the most important one being the observation
of spin-glass features at a temperature significantly higher than the Curie
temperature. This is attributed to a gradual evolution of cluster magnetism
with decreasing temperature. We infer that the changes in Nd 4f hybridization
due to Rh 4d (instead of Pd 4d) plays a role in some fashion for such
differences. These properties are attributed to the competing magnetic ground
states due to geometrical frustration arising out of triangular arrangement of
Nd ions with a bond disorder.


  The fraction of local dwarf galaxies that hosts massive black holes is
arguably the cleanest diagnostic of the dominant seed formation mechanism of
today's supermassive black holes. A 5 per cent constraint on this quantity can
be achieved with AXIS observations of 3300 galaxies across the mass spectrum
through a combination of serendipitous extra-galactic fields plus a dedicated 1
Msec GO program.


  With the growing efforts in isolating solid-state qubits from external
decoherence sources, the material-inherent sources of noise start to play
crucial role. One representative example is electron traps in the device
material or substrate. Electrons can tunnel or hop between a charged and an
empty trap, or between a trap and a gate electrode. A single trap typically
produces telegraph noise and can hence be modeled as a bistable fluctuator.
Since the distribution of hopping rates is exponentially broad, many traps
produce flicker-noise with spectrum close to 1/f. Here we develop a theory of
decoherence of a qubit in the environment consisting of two-state fluctuators,
which experience transitions between their states induced by interaction with
thermal bath. Due to interaction with the qubit the fluctuators produce
1/f-noise in the qubit's eigenfrequency. We calculate the results of qubit
manipulations - free induction and echo signals - in such environment. The main
problem is that in many important cases the relevant random process is both
non-Markovian and non-Gaussian. Consequently the results in general cannot be
represented by pair correlation function of the qubit eigenfrequency
fluctuations. Our calculations are based on analysis of the density matrix of
the qubit using methods developed for stochastic differential equations. The
proper generating functional is then averaged over different fluctuators using
the so-called Holtsmark procedure. The analytical results are compared with
simulations allowing checking accuracy of the averaging procedure and
evaluating mesoscopic fluctuations. The results allow understanding some
observed features of the echo decay in Josephson qubits.


  We report observations of transitions between excited states in the
Jaynes-Cummings ladder of circuit quantum electrodynamics with electron spins
(spin circuit QED). We show that unexplained features in recent experimental
work correspond to such transitions and present an input-output framework that
includes these effects. In new experiments, we first reproduce previous
observations and then reveal both excited-state transitions and multiphoton
transitions by increasing the probe power and using two-tone spectroscopy. This
ability to probe the Jaynes-Cummings ladder is enabled by improvements in the
coupling-to-decoherence ratio, and shows an increase in the maturity of spin
circuit QED as an interesting platform for studying quantum phenomena.


  We propose an approach to 3D reconstruction via inverse procedural modeling
and investigate two variants of this approach. The first option consists in the
fitting set of input parameters using a genetic algorithm. We demonstrate the
results of our work on tree models, complex objects, with the reconstruction of
which most existing methods cannot handle. The second option allows us to
significantly improve the precision by using gradients within memetic
algorithm, differentiable rendering and also differentiable procedural
generators. In our work we see 2 main contributions. First, we propose a method
to join differentiable rendering and inverse procedural modeling. This gives us
an opportunity to reconstruct 3D model more accurately than existing approaches
when a small number of input images are available (even for single image).
Second, we join both differentiable and non-differentiable procedural
generators in a single framework which allow us to apply inverse procedural
modeling to fairly complex generators: when gradient is available,
reconstructions is precise, when gradient is not available, reconstruction is
approximate, but always high quality without visual artifacts.


  We introduce a filter using a noise-free quantum buffer with large optical
bandwidth that can both filter temporal-spectral modes, as well as
inter-convert them and change their frequency. We show that such quantum
buffers optimally filter out temporal-spectral noise; producing identical
single-photons from many distinguishable noisy single-photon sources with the
minimum required reduction in brightness. We then experimentally demonstrate a
noise-free quantum buffer in a warm atomic system that is well matched to
quantum dots and can outperform all intensity (incoherent) filtering schemes
for increasing indistinguishability.


  We study supersymmetric boundary conditions in 3-dimensional N = 2
Landau-Ginzburg models and abelian gauge theories. In the Landau-Ginzburg model
the boundary conditions that preserve (1,1) supersymmetry (A-type) and (2,0)
supersymmetry (B-type) on the boundary are classified in terms of subspaces of
the target space ("brane"). An A-type brane is a Lagrangian submanifold on
which the imaginary part of the superpotential is constant, while a B-type
brane is a holomorphic submanifold on which the superpotential is constant. We
also consider the N = 2 Maxwell theory with boundary and the abelian duality.
Finally we make some comments on N = 2 SQED with boundary condition and the
mirror symmetry.


  We study the linear stability of nonrelativistic $\ell$-boson stars,
describing static, spherically symmetric configurations of the
Schr\"odinger-Poisson system with multiple wave functions having the same value
of the angular momentum $\ell$. In this work we restrict our analysis to
time-dependent perturbations of the radial profiles of the $2\ell+1$ wave
functions, keeping their angular dependency fixed. Based on a combination of
analytic and numerical methods, we find that for each $\ell$, the ground state
is linearly stable, whereas the $n$'th excited states possess $2n$ unstable
(exponentially in time growing) modes. Our results also indicate that all
excited states correspond to saddle points of the conserved energy functional
of the theory.


  On 17 August 2017, the LIGO and Virgo observatories made the first direct
detection of gravitational waves from the coalescence of a neutron star binary
system. The detection of this gravitational-wave signal, GW170817, offers a
novel opportunity to directly probe the properties of matter at the extreme
conditions found in the interior of these stars. The initial,
minimal-assumption analysis of the LIGO and Virgo data placed constraints on
the tidal effects of the coalescing bodies, which were then translated to
constraints on neutron star radii. Here, we expand upon previous analyses by
working under the hypothesis that both bodies were neutron stars that are
described by the same equation of state and have spins within the range
observed in Galactic binary neutron stars. Our analysis employs two methods:
the use of equation-of-state-insensitive relations between various macroscopic
properties of the neutron stars and the use of an efficient parametrization of
the defining function $p(\rho)$ of the equation of state itself. From the LIGO
and Virgo data alone and the first method, we measure the two neutron star
radii as $R_1=10.8^{+2.0}_{-1.7}$ km for the heavier star and $R_2=
10.7^{+2.1}_{-1.5}$ km for the lighter star at the 90% credible level. If we
additionally require that the equation of state supports neutron stars with
masses larger than $1.97 \,M_\odot$ as required from electromagnetic
observations and employ the equation-of-state parametrization, we further
constrain $R_1= 11.9^{+1.4}_{-1.4}$ km and $R_2= 11.9^{+1.4}_{-1.4}$ km at the
90% credible level. Finally, we obtain constraints on $p(\rho)$ at supranuclear
densities, with pressure at twice nuclear saturation density measured at
$3.5^{+2.7}_{-1.7}\times 10^{34} \,\mathrm{dyn}/\mathrm{cm}^{2}$ at the 90%
level.


  The different definitions for the equation of state of a non-minimally
coupled scalar field that have been introduced in the literature are analyzed.
Particular emphasis is made upon those features that could yield to an
observable way of distinguishing non-minimally coupled theories from General
Relativity, with the same or with alternate potentials. It is found that some
earlier claims on that super-quintessence, a stage of super-accelerated
expansion of the universe, is possible within realistic non-minimally coupled
theories are the result of an arguable definition of the equation of state. In
particular, it is shown that these previous results do not import any
observable consequence, i.e. that the theories are observationally identical to
General Relativity models and that super-quintessence is not more than a
mathematical outcome. Finally, in the case of non-minimally coupled theories
with coupling $F=1+\xi \phi^2$ and tracking potentials, it is shown that no
super-quintessence is possible.


  We examine electronic states of antiferromagnetic phase in iron pnictides by
mean-field calculations of the optical conductivity. We find that a five-band
model exhibiting a small magnetic moment, inconsistent with the
first-principles calculations, reproduces well the excitation spectra
characterized by a multi-peak structure emerging below the N\'{e}el temperature
at low energy, together with an almost temperature-independent structure at
high energy. Investigating the interlayer magnetoresistance for this model, we
also predict its characteristic field dependence reflecting the Fermi surface.


  We first derive the Hamiltonian for Lovelock gravity and find that it takes
the same form as in general relativity when written in terms of the
Misner-Sharp mass function. We then minimally couple the action to matter
fields to find Hamilton's equations of motion. These are gauge fixed to be in
the Painlev\'e-Gullstrand co-ordinates and are well suited to numerical studies
of black hole formation.
  We then use these equations of motion for the massless scalar field to study
the formation of general relativistic black holes in four to eight dimensions
and Einstein-Gauss-Bonnet black holes in five and six dimensions. We study
Choptuik scaling, a phenomenon which relates the initial conditions of a matter
distribution to the final observables of small black holes.
  In both higher dimensional general relativity and Einstein-Gauss-Bonnet
gravity we confirm the existence of cusps in the mass scaling relation which
had previously only been observed in four dimensional general relativity. In
the general relativistic case we then calculate the critical exponents for four
to eight dimensions and find agreement with previous calculations by Bland et.
al. but not Sorkin et. al. who both worked in null co-ordinates.
  For the Einstein-Gauss-Bonnet case we find that the self-similar behaviour
seen in the general relativistic case is destroyed. We find that it is replaced
by some other form of scaling structure. In five dimensions we find that the
period of the critical solution at the origin is proportional to roughly the
cube root of the Gauss-Bonnet parameter and that there is evidence for a
minimum black hole radius. In six dimensions we see evidence for a new type of
scaling. We also show, from the equations of motion, that there is reason to
expect qualitative differences between five and higher dimensions.


  In this paper, we generalise the formula for the fourth moment of a random
determinant to account for entries with asymmetric distribution. We also derive
the second moment of a random Gram determinant.


  Identifying individual animals is crucial for many biological investigations.
In response to some of the limitations of current identification methods, new
automated computer vision approaches have emerged with strong performance.
Here, we review current advances of computer vision identification techniques
to provide both computer scientists and biologists with an overview of the
available tools and discuss their applications. We conclude by offering
recommendations for starting an animal identification project, illustrate
current limitations and propose how they might be addressed in the future.


  From the disk of normal galaxies to the nucleus of prototype active sources,
we review the wealth of results and new understanding provided by recent
infrared probes and, in particular, the four instruments on-board of ISO.


  We calculate the D-brane superpotentials for two non-Fermat type compact
Calabi-Yau manifolds which are the hypersurfaces of the weighed projective
spaces in type II string theory. By constructing the open-closed mirror maps,
we also compute the Ooguri-Vafa invariants, which are related to the open
Gromov-Witten invariants.


  Short and ultra-short planets are a peculiar type of exoplanets with periods
as short as a few days or less. Although it is challenging to detect them,
already several are observed with many additional candidates. If these planets
have formation pathways to their longer period counterparts, they are predicted
to reside in multi-planet systems. Thus, gravitational perturbation from
potential planetary neighbors may affect their orbital configuration. However,
due to their close proximity to their host star, they are also subjects to
general relativity precession and torques from the stellar spin quadrupole
moment ($J_2$). Here we show that an evolving $J_2$ due to magnetic braking,
affects the magnitude and location of secular resonances of the short period
planet in a multi-planet system. Thus, driving the short period planet into and
out of a secular resonance, exciting the planet's eccentricity and inclination.
The high inclination can hinder transit observation, and, in some cases, the
high eccentricity may result in an unstable configuration. We propose that
evolving $J_2$ in a multi-planet system can be critical in understanding the
detectability and stability of short-period planets.


  We provide related Dehn surgery descriptions for rational homology spheres
and a class of their regular finite cyclic covering spaces. As an application,
we use the surgery descriptions to relate the Casson invariants of the covering
spaces to that of the base space. Finally, we show that this places
restrictions on the number of finite and cyclic Dehn fillings of the knot
complements in the covering spaces beyone those imposed by
Culler-Gordon-Luecke-Shalen and Boyer-Zhang.


  This paper summarizes the motivations and results obtained so far in the
frame of a particular non-linearization of Classical Electrodynamics, which was
called Extended Electrodynamics. The main purpose pursued with this non-linear
extension of the classical Maxwell's equations is to have a reliable
field-theoretical approach in describing (3+1) soliton-like electromagnetic
formations, in particular, to build an extended and finite field model of free
photons and photon complexes. The first chapter gives a corresponding analysis
of Maxwell theory and introduces the new equations. The second chapter gives a
full account of the results, including the photon-like solutions, in the vacuum
case. A new concept, called scale factor, is defined and successfully used. Two
ways for describing the intrinsic angular momentum are given. Interference of
two photon-like solutions is also considered. The third chapter considers
interaction with external fields (continuous media) on the base of establishing
correspondence between the physical concept of nondissipation and the
mathematical concept of integrability of Pfaff systems. A large family of
solutions is found, allowing a (3+1) interpretation of all known (1+1) soliton
solutions.


  The observed extragalactic background light (EBL) is affected by light
attenuation due to absorption of light by galactic and intergalactic dust in
the Universe. Even galactic opacity of 10-20 percent and minute universe
intergalactic opacity of $0.01\,\mathrm{mag}\,h\,\mathrm{Gpc}^{-1}$ at the
local Universe have a significant impact on the EBL because obscuration of
galaxies and density of intergalactic dust increase with redshift as
$\left(1+z\right)^3$. Consequently, intergalactic opacity increases and the
Universe becomes considerably opaque at $z > 3$. Adopting realistic values for
galactic and intergalactic opacity, the estimates of the EBL for the expanding
dusty universe are close to observations. The luminosity density evolution fits
well measurements. The model reproduces a steep increase of the luminosity
density at $z<2$, its maximum at $z=2-3$, and its decrease at higher redshifts.
The increase of the luminosity density at low $z$ is not produced by the
evolution of the star formation rate but by the fact that the Universe occupied
a smaller volume in previous epochs. The decline of the luminosity density at
high $z$ originates in the opacity of the Universe. The calculated bolometric
EBL ranges from 100 to 200 $\mathrm{n W m}^{-2}\mathrm{sr}^{-1}$ and is within
the limits of 40 and 200 $\mathrm{n W m}^{-2}\mathrm{sr}^{-1}$ of current EBL
observations. The model predicts 98\% of the EBL coming from radiation of
galaxies at $z<3.5$. Accounting for light extinction by intergalactic dust
implies that the Universe was probably more opaque than dark for $z>3.5$.


  Detailed dependence of resonant spin-flavor (RSF) conversion of supernova
neutrinos on electron mole fraction Ye is investigated. Supernova explosion
forms a hot-bubble and neutrino-driven wind region of which electron mole
fraction exceeds 0.5 in several seconds after the core collapse. When a higher
resonance of the RSF conversion is located in the innermost region, flavor
change of the neutrinos strongly depends on the sign of 1-2Ye. At an adiabatic
high RSF resonance the flavor conversion of bar{nu}_e -> nu_{mu,tau} occurs in
Ye < 0.5 and normal mass hierarchy or in Ye > 0.5 and inverted mass hierarchy.
In other cases of Ye values and mass hierarchies, the conversion of nu_e ->
bar{nu}_{mu,tau} occurs. The final bar{nu}_e spectrum is evaluated in the cases
of Ye < 0.5 and Ye > 0.5 taking account of the RSF conversion. Based on the
obtained result, time variation of the event number ratios of low bar{nu}_e
energy to high bar{nu}_e energy is discussed. In normal mass hierarchy, an
enhancement of the event ratio should be seen in the period when the electron
fraction in the innermost region exceeds 0.5. In inverted mass hierarchy, on
the other hand, a dip of the event ratio should be observed. Therefore, the
time variation of the event number ratio is useful to investigate the effect of
the RSF conversion.


  This paper is concerned with a stochastic recursive optimal control problem
with time delay, where the controlled system is described by a stochastic
differential delayed equation (SDDE) and the cost functional is formulated as
the solution to a backward SDDE (BSDDE). When there are only the pointwise and
distributed time delays in the state variable, a generalized
Hamilton-Jacobi-Bellman (HJB) equation for the value function in finite
dimensional space is obtained, applying dynamic programming principle. This
generalized HJB equation admits a smooth solution when the coefficients satisfy
a particular system of first order partial differential equations (PDEs). A
sufficient maximum principle is derived, where the adjoint equation is a
forward-backward SDDE (FBSDDE). Under some differentiability assumptions, the
relationship between the value function, the adjoint processes and the
generalized Hamiltonian function is obtained. A consumption and portfolio
optimization problem with recursive utility in the financial market, is
discussed to show the applications of our result. Explicit solutions in a
finite dimensional space derived by the two different approaches, coincide.


  We report on the follow-up XMM-Newton observation of the planet-hosting star
HD 189733 we obtained in April 2011. We observe a flare just after the
secondary transit of the hot Jupiter. This event shares the same phase and many
of the characteristics of the flare we observed in 2009. We suggest that a
systematic interaction between planet and stellar magnetic fields when the
planet passes close to active regions on the star can lead to periodic
variability phased with planetary motion. By mean of high resolution X-ray
spectroscopy with RGS we determine that the corona of this star is unusually
dense.


  We investigate the heat flow of a qubit coupled to heat baths under
continuous quantum measurement. In the steady-state limit, we show that heat
always flows from the measurement apparatus into the qubit regardless of the
measured qubit state and derive lower and upper bounds for the heat current
between the qubit and the measurement apparatus. Furthermore, we study the
transient dynamics of the heat current and the excess heat during the transient
regime.


  In this report I summarize contributions on the highest energy cosmic rays to
the 28th International Cosmic Ray Conference in Tsukuba, Japan, Sections HE
1.3, 1.4 and 1.5 involved over 80 oral presentations and about 120 posters.
This large body of work attests to the vitality of a field committed to
resolving the mystery of the origin of ultra-high energy cosmic rays. These
cosmic rays with energies well above $10^{18}$ eV are messengers of an unknown
extremely high-energy universe.


  We have built and operated a crystalline/vapor xenon TPC, with the goal of
improving searches for dark matter. The motivation for this instrument is the
fact that beta decays from the radon decay chain to the ground state presently
limit the state-of-the-art liquid/vapor xenon experiments. In contrast, a
crystalline xenon target has the potential to tag and reject radon-chain
backgrounds, due to the time and energy signature of their decays. The present
article is the first demonstration of a crystalline/vapor xenon TPC with
electroluminescence (gas gain) for the electron signal readout. It also shows
that the scintillation yield in crystalline xenon appears to be identical to
that in liquid xenon, in contrast to previous results.


  We present large-scale Monte Carlo results for the dynamical critical
exponent z and the spatio-temporal two-point correlation function of a
(2+1)-dimensional quantum XY model with bond dissipation, proposed to describe
a quantum critical point in high-Tc cuprates near optimal doping. The phase
variables of the model, originating with a parametrization of circulating
currents within the CuO_2 unit cells in cuprates, are compact,
{\theta_{r,\tau}} \in [-\pi,\pi>. The dynamical critical exponent is found to
be z \approx 1, and the spatio-temporal correlation functions are explicitly
demonstrated to be isotropic in space-imaginary time. The model thus has a
fluctuation spectrum where momentum and frequency enter on equal footing,
rather than having the essentially momentum-independent marginal Fermi
liquid-like fluctuation spectrum previously reported for the same model.


  This paper addresses computational challenges in estimating Quantile
Regression with Selection (QRS). The estimation of the parameters that model
self-selection requires the estimation of the entire quantile process several
times. Moreover, closed-form expressions of the asymptotic variance are too
cumbersome, making the bootstrap more convenient to perform inference. Taking
advantage of recent advancements in the estimation of quantile regression,
along with some specific characteristics of the QRS estimation problem, I
propose streamlined algorithms for the QRS estimator. These algorithms
significantly reduce computation time through preprocessing techniques and
quantile grid reduction for the estimation of the copula and slope parameters.
I show the optimization enhancements with some simulations. Lastly, I show how
preprocessing methods can improve the precision of the estimates without
sacrificing computational efficiency. Hence, they constitute a practical
solutions for estimators with non-differentiable and non-convex criterion
functions such as those based on copulas.


  The application machine learning (ML) algorithms to turbulence modeling has
shown promise over the last few years, but their application has been
restricted to eddy viscosity based closure approaches. In this article we
discuss rationale for the application of machine learning with high-fidelity
turbulence data to develop models at the level of Reynolds stress transport
modeling. Based on these rationale we compare different machine learning
algorithms to determine their efficacy and robustness at modeling the different
transport processes in the Reynolds Stress Transport Equations. Those data
driven algorithms include Random forests, gradient boosted trees and neural
networks. The direct numerical simulation (DNS) data for flow in channels is
used both as training and testing of the ML models. The optimal
hyper-parameters of the ML algorithms are determined using Bayesian
optimization. The efficacy of above mentioned algorithms is assessed in the
modeling and prediction of the terms in the Reynolds stress transport
equations. It was observed that all the three algorithms predict the turbulence
parameters with acceptable level of accuracy. These ML models are then applied
for prediction of the pressure strain correlation of flow cases that are
different from the flows used for training, to assess their robustness and
generalizability. This explores the assertion that ML based data driven
turbulence models can overcome the modeling limitations associated with the
traditional turbulence models and ML models trained with large amounts data
with different classes of flows can predict flow field with reasonable accuracy
for unknown flows with similar flow physics. In addition to this verification
we carry out validation for the final ML models by assessing the importance of
different input features for prediction.


  We present a systematic, and fully analytic, study of the ratio R_{pA}
between the gluon distribution in a nucleus and that in a proton scaled up by
the atomic number A. We consider initial conditions of the McLerran-Venugopalan
type, and quantum evolution in the Color Glass Condensate, with both fixed and
running coupling. We perform an analytic study of the Cronin effect in the
initial conditions and point out an interesting difference between saturating
effects and twist effects in the nuclear gluon distribution. We show that the
distribution of the gluons which make up the condensate in the initial
conditions is localized at low momenta, but this particular feature does not
survive after the quantum evolution. We demonstrate that the rapid suppression
of the ratio R_{pA} in the early stages of the evolution is due to the
DGLAP-like evolution of the proton, whose gluon distribution grows much faster
than that in the nucleus because of the large separation between the respective
saturation momenta. The flattening of the Cronin peak, on the other hand, is
due to the evolution of the nucleus. We show that the running coupling effects
slow down the evolution, but eventually lead to a stronger suppression in
R_{pA} at sufficiently large energies.


  The development of the manufacturing systems has made it increasingly
necessary to monitor the data generated by multiple interconnected subsystems
with rapid incoming of samples. Based on incremental Singular Value
Decomposition (ISVD), we develop a general online monitoring approach for the
relationship of data generated from two interconnected subsystems, where each
subsystem produces big data streams with several variation patterns in normal
working condition. When special situation happens and new associations occur, a
very small amount of computation is sufficient to update the system status and
compute the control statistics by using this approach. The proposed method
reduces computational overhead and retains only a small number of pairs of
possible dependent patterns at each step. The validation of the method through
simulation studies and a case study on semiconductor manufacturing processes
further supports its effectiveness.


  The GALEX Arecibo SDSS Survey (GASS) is an ambitious program designed to
investigate the cold gas properties of massive galaxies, a challenging
population for HI studies. Using the Arecibo radio telescope, GASS is gathering
high-quality HI-line spectra for an unbiased sample of ~1000 galaxies with
stellar masses greater than 10^10 Msun and redshifts 0.025 < z < 0.05,
uniformly selected from the SDSS spectroscopic and GALEX imaging surveys. The
galaxies are observed until detected or until a low gas mass fraction limit
(1.5-5%) is reached. We present initial results based on the first Data
Release, which consists of ~20% of the final GASS sample. We use this data set
to explore the main scaling relations of HI gas fraction with galaxy structure
and NUV-r colour, and show our best fit plane describing the relation between
gas fraction, stellar mass surface density and NUV-r colour. Interesting
outliers from this plane include gas-rich red sequence galaxies that may be in
the process of regrowing their disks, as well as blue, but gas-poor spirals.


  Human motion prediction is a stochastic process: Given an observed sequence
of poses, multiple future motions are plausible. Existing approaches to
modeling this stochasticity typically combine a random noise vector with
information about the previous poses. This combination, however, is done in a
deterministic manner, which gives the network the flexibility to learn to
ignore the random noise. In this paper, we introduce an approach to
stochastically combine the root of variations with previous pose information,
which forces the model to take the noise into account. We exploit this idea for
motion prediction by incorporating it into a recurrent encoder-decoder network
with a conditional variational autoencoder block that learns to exploit the
perturbations. Our experiments demonstrate that our model yields high-quality
pose sequences that are much more diverse than those from state-of-the-art
stochastic motion prediction techniques.


  A linear system of differential equations describing a joint motion of
thermoelastic porous body and thermofluid occupying porous space is considered.
Although the problem is linear, it is very hard to tackle due to the fact that
its main differential equations involve non-smooth oscillatory coefficients,
both big and small, under the differentiation operators. The rigorous
justification, under various conditions imposed on physical parameters, is
fulfilled for homogenization procedures as the dimensionless size of the pores
tends to zero, while the porous body is geometrically periodic. As the results,
we derive Biot's like system of equations of thermo-poroelasticity, system of
equations of thermo-viscoelasticity, or decoupled system consisting of
non-isotropic Lam\'{e}'s equations for thermoelastic solid and Darcy's system
of filtration for thermofluid, depending on ratios between physical parameters.
The proofs are based on Nguetseng's two-scale convergence method of
homogenization in periodic structures.


  We study the geometry of manifolds carrying symplectic pairs consisting of
two closed 2-forms of constant ranks, whose kernel foliations are
complementary. Using a variation of the construction of Boothby and Wang we
build contact-symplectic and contact pairs from symplectic pairs.


  High-resolution spectropolarimetric observations provide simultaneous
information about stellar magnetic field topologies and three-dimensional
distributions of chemical elements. Here we present analysis of a unique full
Stokes vector spectropolarimetric data set, acquired for the cool magnetic Ap
star HD 24712. The goal of our work is to examine circular and linear
polarization signatures inside spectral lines and to study variation of the
stellar spectrum and magnetic observables as a function of rotational phase. HD
24712 was observed with the HARPSpol instrument at the 3.6-m ESO telescope over
a period of 2010-2011. The resulting spectra have S/N ratio of 300-600 and
resolving power exceeding 100000. The multiline technique of least-squares
deconvolution (LSD) was applied to combine information from the spectral lines
of Fe-peak and rare-earth elements. We used the HARPSPol spectra of HD 24712 to
study the morphology of the Stokes profile shapes in individual spectral lines
and in LSD Stokes profiles corresponding to different line masks. From the LSD
Stokes V profiles we measured the longitudinal component of the magnetic field,
<Bz>, with an accuracy of 5-10 G. We also determined the net linear
polarization from the LSD Stokes Q and U profiles. We determined an improved
rotational period of the star, P_rot = 12.45812 +/- 0.00019d. We measured <Bz>
from the cores of Halpha and Hbeta lines. The analysis of <Bz> measurements
showed no evidence for a significant radial magnetic field gradient in the
atmosphere of HD 24712. We used our <Bz> and net linear polarization
measurements to determine parameters of the dipolar magnetic field topology. We
found that magnetic observables can be reasonably well reproduced by the
dipolar model. We discovered rotational modulation of the Halpha core and
related it a non-uniform surface distribution of rare-earth elements.


  Context. Open clusters provide valuable information on stellar
nucleosynthesis and the chemical evolution of the Galactic disc, as their age
and distances can be measured more precisely with photometry than for field
stars. Aims. Our aim is to study the chemical distribution of the Galactic disc
using open clusters by analysing the existence of gradients with Galactocentric
distance, azimuth or height from the plane and dependency with age. Methods.
High-resolution spectra (R>60 000) of 194 stars belonging to 36 open clusters
are used to determine atmospheric parameters and chemical abundances with two
independent methods: equivalent widths and spectral synthesis. The sample has
been complemented with 63 clusters with high-resolution spectroscopy from
literature. Results. We measure local thermodynamic equilibrium abundances for
21 elements: {\alpha} (Mg, Si, Ca, and Ti), odd-Z (Na and Al), Fe-peak (Fe, Sc,
V, Cr, Mn, Co, Ni, Cu, and Zn), and neutron-capture (Sr, Y, Zr, Ba, Ce, and
Nd). We also provide non-local thermodynamic equilibrium abundances for
elements when corrections are available. We find inner disc young clusters
enhanced in [Mg/Fe] and [Si/Fe] compared to other clusters of their age. For
[Ba/Fe] we report an age trend flattening for older clusters (age<2.5 Ga). The
studied elements follow the expected radial gradients as a function of their
nucleosynthesis groups, which are significantly steeper for the oldest systems.
For the first time, we investigate the existence of an azimuthal gradient,
finding some hints of its existence among the old clusters (age>2 Ga).


  In this paper, we analyze a chain-linked triple-cavity photonic molecule
(TCPM) with controllable coupling strengths between the cavities on their
spectral properties and field (energy) distributions by solving eigenvalues and
eigenvectors of the Hamiltonian matrix based on coupled mode theory. Phase
transition is extended from double-cavity photonic molecules (DCPMs) to TCPMs,
and evolutions of the supermode frequencies and linewidths are analyzed, which
have synchronous relations with the degree of coherence between adjacent
optical microcavities and energy distributions in the three cavities,
respectively. We develop a superposition picture for the three supermodes of
the TCPM, as interferences between supermodes of sub-DCPMs. In particular, we
demonstrate the abnormal properties of the central supermode in TCPMs, such as
dark state in middle cavity and phase shift when energy flowing between side
cavities, which are promising in information processing and remote control of
energy. General properties of TCPMs are summarized and limitation on linewidths
are given. Finally, we make an interesting analog to intracavity
electromagnetically induced transparency in multi-level atomic systems using
the flexible TCPM platform under appropriate conditions.


  A quantized version of the Sierpinski gasket is proposed, on purely
topological grounds, as a $C^*$-algebra $\mathcal{A}_\infty$ with a suitable
form of self-similarity. Several properties of $\mathcal{A}_\infty$ are
studied, in particular its nuclearity, the structure of ideals as well as the
description of irreducible representations and extremal traces. A harmonic
structure is introduced, giving rise to a self-similar Dirichlet form
$\mathcal{E}$. A spectral triple is also constructed, extending one already
known for the classical gasket, from which $\mathcal{E}$ can be reconstructed.
Moreover we show that $\mathcal{A}_\infty$ is a compact quantum metric space.


  The recently discovered protostellar jet known as HH212 is beautifully
symmetric, with a series of paired shock knots and bow shocks on either side of
the exciting source region, IRAS 05413-0104 (Zinnecker et al. 1998). We present
VLA ammonia maps of the IRAS 05413-0104 molecular gas envelope in which the
protostellar jet source is embedded. We find that the envelope, with mass of
0.2 M(sun) detected by the interferometer, is flattened perpendicular to the
jet axis with a FWHM diameter of 12000 AU and an axis ratio of 2:1, as seen in
NH3 (1,1) emission. There is a velocity gradient of about 4-5 km sec^-1 pc^-1
across the flattened disk-like core, suggestive of rotation around an axis
aligned with the jet. Flux-weighted mean velocities increase smoothly with
radius with a roughly constant velocity gradient. In young (Class 0) systems
such as HH212, a significant amount of material is still distributed in a large
surrounding envelope, and thus the observable kinematics of the system may
reflect the less centrally condensed, youthful state of the source and
obscuration of central dynamics. The angular momentum of this envelope material
may be released from infalling gas through rotation in the HH212 jet, as recent
observations suggest (Davis et al. 2000). A blue-shifted wisp or bowl of
emitting gas appears to be swept up along the blue side of the outflow,
possibly lining the cavity of a wider angle wind around the more collimated
shock jet axis. Our ammonia (2,2)/(1,1) ratio map indicates that this very cold
core is heated to 14 Kelvin degrees in a centrally condensed area surrounding
the jet source. This edge-on core and jet system appears to be young and deeply
embedded. This environment, however, is apparently not disrupting the pristine
symmetry and collimation of the jet.


  We present new results from our ongoing study of the SU(3) sextet model with
two flavors in the two-index symmetric representation of the gauge group. In
the simulations use unimproved Wilson fermions to investigate the infrared
properties of the model. We have previously presented results for the spectrum
of the model in the weak coupling regime. Here, to better understand the
overall behavior of the lattice model, we map its non-trivial phase structure
in the space of bare parameters. At strong coupling, we observe a first order
phase transition when decreasing the bare quark mass. This first order
transition weakens when moving towards weaker couplings with an endpoint at a
finite value of the bare coupling, after which it appears to be a continuous
transition. We also investigate the behavior of the mass spectrum and
scale-setting observable, as a function of the quark mass, and show that their
qualitative behavior change significantly when moving from the strong coupling
into the weak coupling phase.


  Atomic nanowires on semiconductor surfaces induced by the adsorption of
metallic atoms have attracted a lot of attention as possible hosts of the
elusive, Tomonaga-Luttinger liquid. The Au/Ge(100) system in particular is the
subject of controversy as to whether the Au-induced nanowires do indeed host
exotic, 1D metallic states. We report on a thorough study of the electronic
properties of high quality nanowires formed at the Au/Ge(100) surface. High
resolution ARPES data show the low-lying Au-induced electronic states to
possess a dispersion relation that depends on two orthogonal directions in
k-space. Comparison of the E(k$_x$,k$_y$) surface measured using ARPES to
tight-binding calculations yields hopping parameters in the two different
directions that differ by a factor of two. We find that the larger of the two
hopping parameters corresponds, in fact, to the direction perpendicular to the
nanowires (t$_{\perp}$). This, the topology of the $E$=$E_F$ contour in
k$_{\||}$, and the fact that $t_{\||}$/$t_{\perp}\sim 0.5$ proves that the
Au-induced electron pockets possess a 2D, closed Fermi surface, this firmly
places the Au/Ge(100) nanowire system outside being a potential hosts of a
Tomonaga-Luttinger liquid. We combine these ARPES data with STS measurements of
the spatially-resolved electronic structure and find that the spatially
straight conduction channels observed up to energies of order one electron volt
below the Fermi level do not originate from the Au-induced states seen in the
ARPES data. The former are more likely to be associated with bulk Ge states
that are localized to the subsurface region. Despite our proof of the 2D nature
of the Au-induced nanowire and sub-surface Ge-related states, an anomalous
suppression of the density of states at the Fermi level is observed in both the
STS and ARPES data, this phenomenon is discussed in the light of the effects of
disorder.


  Let $\triangleleft$ be a relation between graphs. We say a graph $G$ is
\emph{$\triangleleft$-ubiquitous} if whenever $\Gamma$ is a graph with $nG
\triangleleft \Gamma$ for all $n \in \mathbb{N}$, then one also has $\aleph_0 G
\triangleleft \Gamma$, where $\alpha G$ is the disjoint union of $\alpha$ many
copies of $G$.
  The \emph{Ubiquity Conjecture} of Andreae, a well-known open problem in the
theory of infinite graphs, asserts that every locally finite connected graph is
ubiquitous with respect to the minor relation.
  In this paper, which is the first of a series of papers making progress
towards the Ubiquity Conjecture, we show that all trees are ubiquitous with
respect to the topological minor relation, irrespective of their cardinality.
This answers a question of Andreae from 1979.


  Automatic clinical diagnosis of retinal diseases has emerged as a promising
approach to facilitate discovery in areas with limited access to specialists.
We propose a novel visual-assisted diagnosis hybrid model based on the support
vector machine (SVM) and deep neural networks (DNNs). The model incorporates
complementary strengths of DNNs and SVM. Furthermore, we present a new clinical
retina label collection for ophthalmology incorporating 32 retina diseases
classes. Using EyeNet, our model achieves 89.73% diagnosis accuracy and the
model performance is comparable to the professional ophthalmologists.


  How to effectively exploit spatio-temporal information is crucial to capture
target appearance changes in visual tracking. However, most deep learning-based
trackers mainly focus on designing a complicated appearance model or template
updating strategy, while lacking the exploitation of context between
consecutive frames and thus entailing the \textit{when-and-how-to-update}
dilemma. To address these issues, we propose a novel explicit visual prompts
framework for visual tracking, dubbed \textbf{EVPTrack}. Specifically, we
utilize spatio-temporal tokens to propagate information between consecutive
frames without focusing on updating templates. As a result, we cannot only
alleviate the challenge of \textit{when-to-update}, but also avoid the
hyper-parameters associated with updating strategies. Then, we utilize the
spatio-temporal tokens to generate explicit visual prompts that facilitate
inference in the current frame. The prompts are fed into a transformer encoder
together with the image tokens without additional processing. Consequently, the
efficiency of our model is improved by avoiding \textit{how-to-update}. In
addition, we consider multi-scale information as explicit visual prompts,
providing multiscale template features to enhance the EVPTrack's ability to
handle target scale changes. Extensive experimental results on six benchmarks
(i.e., LaSOT, LaSOT\rm $_{ext}$, GOT-10k, UAV123, TrackingNet, and TNL2K.)
validate that our EVPTrack can achieve competitive performance at a real-time
speed by effectively exploiting both spatio-temporal and multi-scale
information. Code and models are available at
https://github.com/GXNU-ZhongLab/EVPTrack.


  In this work, the polar tetrahedron [PN$_2$O$_2$] was revealed as a new
deep-ultraviolet (deep-UV) nonlinear optically active unit. Accordingly, a
thermodynamically stable compound (PNO) consisting of the polar [PN$_2$O$_2$]
units was predicted and suggested as a promising candidate of deep-UV nonlinear
optical (NLO) material. Compared with other deep-UV materials known to date,
PNO possesses the strongest second harmonic generation (SHG) coefficient (about
6 times that of KH$_2$PO$_4$ (KDP)). Moreover, its three-dimensional
connectivity endows it with good mechanical and thermal properties. Therefore,
PNO should be a new option for non-$\pi$-conjugated deep-UV NLO materials.


  Focusing on the fourth-order wave equation $u_{tt} + \Delta^2 u + f(u)= 0$,
we prove the existence of ground state solutions $u=u(x+ct)$ for an optimal
range of speeds $c\in\mathbb{R}^n$ and a variety of nonlinearities $f$.


  X-ray fluorescence holography (XFH) is a method for obtaining
diffraction-limited images of the local atomic structure around a given type of
emitter. The reconstructed wave-field represents a distorted image of the
scatterer electron density distribution; {\it i.e.} it is a convolution of the
charge density distribution with a point spread function characteristic of the
measurement. We here consider several methods for the iterative deconvolution
of such XFH holograms, and via theoretical simulations evaluate them from the
point of view of going beyond the diffraction limit so as to image the electron
charge density. Promising results for future applications are found for certain
methods, and other possible image-enhancement techniques are also discussed.


  We discuss Casimir phenomena which are dominated by long-range fluctuations.
A prime example is given by "geothermal" Casimir phenomena where thermal
fluctuations in open Casimir geometries can induce significantly enhanced
thermal corrections. We illustrate the underlying mechanism with the aid of the
inclined-plates configuration, giving rise to enhanced power-law temperature
dependences compared to the parallel-plates case. In limiting cases, we find
numerical evidence even for fractional power laws induced by long-range
fluctuations. We demonstrate that thermal energy densities for open geometries
are typically distributed over length scales of 1/T. As an important
consequence, approximation methods for thermal corrections based on local
energy-density estimates such as the proximity-force approximation are expected
to become unreliable even at small surface separations.


  A comprehensive uncertainty quantification framework has been developed for
integrating computational and experimental kinetic data and to identify active
sites and reaction mechanisms in catalysis. Three hypotheses regarding the
active site for the water-gas shift reaction on Pt/TiO2 catalysts are tested -
Pt(111), an edge interface site, and a corner interface site. Uncertainties
associated with DFT calculations and model errors of microkinetic models of the
active sites are informed and verified using Bayesian inference and predictive
validation. Significant evidence is found for the role of the oxide support in
the mechanism. Positive evidence is found in support of the edge interface
active site over the corner interface site. For the edge interface site, the
CO-promoted redox mechanism is found to be the dominant pathway and only at
temperatures above 573 K does the classical redox mechanism contribute
significantly to the overall rate. At all reaction conditions, water and
surface O-H bond dissociation steps at the Pt/TiO2 interface are the main rate
controlling steps.


  We propose a method that uses near-infrared plus uvby photometry to identify
potentially extensive circumstellar dusty environment about F and A stars. The
method has been applied to a sample of ~900 metal rich reddened F stars with
2MASS and uvby data, suggesting the presence of circumstellar dust emitting in
the near infrared for ~70 stars. The log T_e - M_V diagram suggests that most,
if not all, of them are likely pre-mainsequence (PMS). They seem to be
consistent with being a continuation of the class of Herbig Ae/Be PMS stars
into the spectral type F. Their number drops sharply downward of log T_e ~ 3.84
(spectral types later than ~F5), which may provide new clues to the PMS
evolution of stars with 1 to 2 solar mass. We present a list of 21 most
conspicuous candidate stars with circumstellar dust. About half of them are
associated with the extended star-forming region around rho Oph. The brightest
of these 21 stars, with V < 7.5, turn out to be IRAS sources, suggesting the
presence of heated dust emitting in the far infrared. Also in this list, HD
81270 is reported as a very unusual star moving away from the Galactic plane at
a projected speed of 70 km/sec.


  Nonlinear simulations of the early ELM phase based on a typical type-I ELMy
ASDEX Upgrade discharge have been carried out using the reduced MHD code JOREK.
The analysis is focused on the evolution of the toroidal Fourier spectrum. It
is found that during the nonlinear evolution, linearly subdominant low-n
Fourier components, in particular the n = 1, grow to energies comparable with
linearly dominant harmonics. A simple model is developed, based on the idea
that energy is transferred among the toroidal harmonics via second order
nonlinear interaction. The simple model reproduces and explains very well the
early nonlinear evolution of the toroidal spectrum in the JOREK simulations.
Furthermore, it is shown for the n = 1 harmonic, that its spatial structure
changes significantly during the transition from linear to nonlinearly driven
growth. The rigidly growing structure of the linearly barely unstable n = 1
reaches far into the plasma core. In contrast, the nonlinearly driven n = 1 has
a rigidly growing structure localized at the plasma edge, where the dominant
toroidal harmonics driving the n = 1 are maximal and in phase. The presented
quadratic coupling model might explain the recent experimental observation of
strong low-n components in magnetic measurements [Wenninger et al., Non-linear
magnetic perturbations during edge localized modes in TCV dominated by low n
mode components, submitted to Nuclear Fusion].


  In this paper we analyse giant gap-opening planet migration in protoplanetary
discs, focusing on the type II migration regime. According to standard type II
theory, planets migrate at the same rate as the gas in the disc, as they are
coupled to the disc viscous evolution; however, recent studies questioned this
paradigm, suggesting that planets migrate faster than the disc material. We
study the problem through 2D long-time simulations of systems consistent with
type II regime, using the hydrodynamical grid code FARGO3D. Even though our
simulations confirm the presence of an initial phase characterised by fast
migration, they also reveal that the migration velocity slows down and
eventually reaches the theoretical prediction if we allow the system to evolve
for enough time. We find the same tendency to evolve towards the theoretical
predictions at later times when we analyse the mass flow through the gap and
the torques acting on the planet. This transient is related to the initial
conditions of our (and previous) simulations, and is due to the fact that the
shape of the gap has to adjust to a new profile, once the planet is set into
motion. Secondly, we test whether the type II theory expectation that giant
planet migration is driven by viscosity is consistent with our simulation by
comparing simulations with the same viscosity and different disc mass (or
viceversa). We find a good agreement with the theory, since when the discs are
characterised by the same viscosity, the migration properties are the same.


  This paper describes an application of the Cartographer graph SLAM stack as a
pose sensor in a UAV feedback control loop, with certain application-specific
changes in the SLAM stack such as smoothing of the optimized pose. Pose
estimation is performed by fusing 3D LiDAR/IMU-based proprioception with GPS
position measurements by means of pose graph optimisation. Moreover, partial
environment maps built from the LiDAR data (submaps) within the Cartographer
SLAM stack are marshalled into OctoMap, an Octree-based voxel map
implementation. The OctoMap is further used for navigation tasks such as path
planning and obstacle avoidance.


  In single unit-cell FeSe grown on SrTiO3, the superconductivity transition
temperature features a significant enhancement. Local phonon modes at the
interface associated with electron-phonon coupling may play an important role
in the interface-induced enhancement. However, such phonon modes have eluded
direct experimental observations. Indeed, the complicated atomic structure of
the interface brings challenges to obtain the accurate structure-phonon
relation knowledge from either experiment or theory, thus hindering our
understanding of the enhancement mechanism. Here, we achieve direct
characterizations of atomic structure and phonon modes at the FeSe/SrTiO3
interface with atomically resolved imaging and electron energy loss
spectroscopy in a scanning transmission electron microscope. We find several
phonon modes highly localized (~1.3 nm) at the unique double layer Ti-O
termination at the interface, one of which (~ 83 meV) engages in strong
interactions with the electrons in FeSe based on ab initio calculations. The
electron-phonon coupling strength for such a localized interface phonon with
short-range interactions is comparable to that of Fuchs-Kliewer (FK) phonon
mode with long-rang interactions. Thus, our atomic-scale study provides new
insights into understanding the origin of superconductivity enhancement at the
FeSe/SrTiO3 interface.


  Iterative methods have led to better understanding and solving problems such
as missing sampling, deconvolution, inverse systems, impulsive and Salt and
Pepper noise removal problems. However, the challenges such as the speed of
convergence and or the accuracy of the answer still remain. In order to improve
the existing iterative algorithms, a non-linear method is discussed in this
paper. The mentioned method is analyzed from different aspects, including its
convergence and its ability to accelerate recursive algorithms. We show that
this method is capable of improving Iterative Method (IM) as a non-uniform
sampling reconstruction algorithm and some iterative sparse recovery algorithms
such as Iterative Reweighted Least Squares (IRLS), Iterative Method with
Adaptive Thresholding (IMAT), Smoothed l0 (SL0) and Alternating Direction
Method of Multipliers (ADMM) for solving LASSO problems family (including Lasso
itself, Lasso-LSQR and group-Lasso). It is also capable of both accelerating
and stabilizing the well-known Chebyshev Acceleration (CA) method. Furthermore,
the proposed algorithm can extend the stability range by reducing the
sensitivity of iterative algorithms to the changes of adaptation rate.


  The permutability equation G(G(x,y),z) = G(G(x,z),y) is satisfied by many
scientific and geometric laws. A few examples among many are: The
Lorentz-FitzGerald Contraction, Beer's Law, the Pythagorean Theorem, and the
formula for computing the volume of a cylinder. We prove here a representation
theorem for the permutability equation, which generalizes a well-known result.
The proof is based on a bounded version of Holder's Theorem.


  We studied the construction problem of the unextendible product basis (UPB).
We mainly give a method to construct a UPB of a quantum system through the UPBs
of its subsystem. Using this method and the UPBs which are known for us, we
construct different kinds of UPBs in general bipartite quantum system. Then we
use these UPBs to construct a family of UPBs in multipartite quantum system.
The UPBs can be used to construct the bound entangled states with different
ranks.


  Speden is a computer program that reconstructs the electron density of single
particles from their x-ray diffraction patterns, using a single-particle
adaptation of the Holographic Method in crystallography. (Szoke, A., Szoke, H.,
and Somoza, J.R., 1997. Acta Cryst. A53, 291-313.) The method, like its parent,
is unique that it does not rely on ``back'' transformation from the diffraction
pattern into real space and on interpolation within measured data. It is
designed to deal successfully with sparse, irregular, incomplete and noisy
data. It is also designed to use prior information for ensuring sensible
results and for reliable convergence. This article describes the theoretical
basis for the reconstruction algorithm, its implementation and quantitative
results of tests on synthetic and experimentally obtained data. The program
could be used for determining the structure of radiation tolerant samples and,
eventually, of large biological molecular structures without the need for
crystallization.


  Background-Foreground classification is a well-studied problem in computer
vision. Due to the pixel-wise nature of modeling and processing in the
algorithm, it is usually difficult to satisfy real-time constraints. There is a
trade-off between the speed (because of model complexity) and accuracy.
Inspired by the rejection cascade of Viola-Jones classifier, we decompose the
Gaussian Mixture Model (GMM) into an adaptive cascade of Gaussians(CoG). We
achieve a good improvement in speed without compromising the accuracy with
respect to the baseline GMM model. We demonstrate a speed-up factor of 4-5x and
17 percent average improvement in accuracy over Wallflowers surveillance
datasets. The CoG is then demonstrated to over the latent space representation
of images of a convolutional variational autoencoder(VAE). We provide initial
results over CDW-2014 dataset, which could speed up background subtraction for
deep architectures.


  Harmonic generation mechanisms are of great interest in nanoscience and
nanotechnology, since they allow generating visible light by using
near-infrared radiation, which is particularly suitable for its endless
applications in bio-nanophotonics and opto-electronics. In this context,
multilayer metal-dielectric nanocavities are widely used for light confinement
and waveguiding at the nanoscale. They exhibit intense and localized resonances
that can be conveniently tuned in the near-infrared and are therefore ideal for
enhancing nonlinear effects in this spectral range. In this work, we
experimentally investigate the nonlinear optical response of multilayer
metal-dielectric nanocavities. By engineering their absorption efficiency and
exploiting their intrinsic interface-induced symmetry breaking, we achieve one
order of magnitude higher second-harmonic generation efficiency compared to
gold nanostructures featuring the same geometry and resonant behavior. In
particular, while the third order nonlinear susceptibility is comparable with
that of bulk Au, we estimate a second order nonlinear susceptibility of the
order of 1 pm/V, which is comparable with that of typical nonlinear crystals.
We envision that our system, which combines the advantages of both plasmonic
and dielectric materials, might enable the realization of composite and
multi-functional nano-systems for an efficient manipulation of nonlinear
optical processes at the nanoscale.


  Computing persistence over changing filtrations give rise to a stack of 2D
persistence diagrams where the birth-death points are connected by the
so-called `vines'. We consider computing these vines over changing filtrations
for zigzag persistence. We observe that eight atomic operations are sufficient
for changing one zigzag filtration to another and provide update algorithms for
each of them. Six of these operations that have some analogues to one or
multiple transpositions in the non-zigzag case can be executed as efficiently
as their non-zigzag counterparts. This approach takes advantage of a recently
discovered algorithm for computing zigzag barcodes by converting a zigzag
filtration to a non-zigzag one and then connecting barcodes of the two with a
bijection. The remaining two atomic operations do not have a strict analogue in
the non-zigzag case. For them, we propose algorithms based on explicit
maintenance of representatives (homology cycles) which can be useful in their
own rights for applications requiring explicit updates of representatives.


  Magnetism in the insulating BaFe$_2$Se$_3$ was examined through
susceptibility, specific heat, resistivity and neutron diffraction
measurements. After formation of a short-range magnetic correlation, a
long-range ordering was observed below $T_{\rm N}\sim 255$ K. The transition is
obscured by bulk properties. Magnetic moments ($\parallel a$) are arranged to
form a Fe$_4$ ferromagnetic unit, and each Fe$_4$ stacks antiferromagnetically.
This block magnetism is of the third type among magnetic structures of ferrous
materials. The magnetic ordering drives unusually large distortion via
magnetoelastic coupling.


  We establish a class of area-angular momentum-charge inequalities satisfied
by stable marginally outer trapped surfaces in 5-dimensional minimal
supergravity which admit a $U(1)^2$ symmetry. A novel feature is the fact that
such surfaces can have the nontrivial topologies $S^1 \times S^2$ and $L(p,q)$.
In addition to two angular momenta, they may be characterized by `dipole
charge' as well as electric charge. We show that the unique geometries which
saturate the inequalities are the horizon geometries corresponding to extreme
black hole solutions. Analogous inequalities which also include contributions
from a positive cosmological constant are also presented.


  We develop the formalism of derived divided power algebras, and revisit the
theory of derived De Rham and derived crystalline cohomology in this framework.
We characterize derived De Rham cohomology of a derived commutative algebra $A$
over a base $R$, together with the Hodge filtration on it, in terms of the
universal property as the largest filtered divided power thickening of $A$. We
show that our approach recovers the classical De Rham cohomology in the case of
a smooth map $R\rightarrow A$, and therefore in general, recovers the derived
De Rham cohomology in the sense of Illusie. Along the way, we develop some
generalities on square-zero extensions and derivations in derived algebraic
geometry and apply them to give the universal property of the first Hodge
truncation of the derived De Rham cohomology. Finally, we define derived
crystalline cohomology relative to a general divided power base, show that it
satisfies the main properties of the crystalline cohomology and coincides with
the classical crystalline cohomology in the smooth case.


  IceTop is a 1 km^2 air shower detector presently under construction as a part
of the IceCube Observatory at South Pole. It will consist of 80 detector
stations, each equipped with two ice Cherenkov tanks, which cover 1 km^2. In
2008, the detector is half completed. One of the design goals of the detector
is to investigate cosmic rays in the energy range from the knee up to
approaching 1 EeV and study the mass composition of primary cosmic rays.
  In this report the performance of IceTop, the shower reconstruction
algorithms and first results, obtained with one month of data with an array of
26 stations operated in 2007, will be presented. Preliminary results are shown
for the cosmic ray energy spectrum in the range of 1 to 80 PeV. Being located
at an atmospheric depth of only 700 g/cm^2 at the South Pole, a high
sensitivity of the zenith angle distribution to the mass composition is
observed.
  The main advantage of IceTop, compared to other detectors in this energy
range, is the possibility to measure highly energetic muons from air showers in
coincidence with the IceCube detector. The muon rate at a given air shower
energy is sensitive to mass composition. The prospects of this method and
alternative methods to scrutinise different composition models will be
presented.


  In todays competitive business world, being aware of customer needs and
market-oriented production is a key success factor for industries. To this aim,
the use of efficient analytic algorithms ensures a better understanding of
customer feedback and improves the next generation of products. Accordingly,
the dramatic increase in using social media in daily life provides beneficial
sources for market analytics. But how traditional analytic algorithms and
methods can scale up for such disparate and multi-structured data sources is
the main challenge in this regard. This paper presents and discusses the
technological and scientific focus of the SoMABiT as a social media analysis
platform using big data technology. Sentiment analysis has been employed in
order to discover knowledge from social media. The use of MapReduce and
developing a distributed algorithm towards an integrated platform that can
scale for any data volume and provide a social media-driven knowledge is the
main novelty of the proposed concept in comparison to the state-of-the-art
technologies.


  Recently, Ban\~{a}dos, Silk and West (BSW) demonstrated that the extremal
Kerr black hole can act as a particle accelerator with arbitrarily high
center-of-mass energy ($E_{CM}$) when the collision takes place near the
horizon. The rotating Hayward's regular black hole, apart from Mass ($M$) and
angular momentum ($a$), has a new parameter $g$ ($g>0$ is a constant) that
provides a deviation from the Kerr black hole. We demonstrate that for each
$g$, with $M=1$, there exist critical $a_{E}$ and $r_{H}^{E}$, which
corresponds to a regular extremal black hole with degenerate horizon, and
$a_{E}$ decreases and $r_{H}^{E}$ increases with increase in $g$. While
$a<a_{E}$ describe a regular non-extremal black hole with outer and inner
horizons. We apply BSW process to the rotating Hayward's regular black hole,
for different $g$, and demonstrate numerically that $E_{CM}$ diverges in the
vicinity of the horizon for the extremal cases, thereby suggesting that a
rotating regular black hole can also act as a particle accelerator and thus in
turn may provide a suitable framework for Plank-scale physics. For a
non-extremal case, there always exist a finite upper bound of $E_{CM}$, which
increases with deviation parameter $g$.


  Reasoning about the effect of interventions and counterfactuals is a
fundamental task found throughout the data sciences. A collection of
principles, algorithms, and tools has been developed for performing such tasks
in the last decades (Pearl, 2000). One of the pervasive requirements found
throughout this literature is the articulation of assumptions, which commonly
appear in the form of causal diagrams. Despite the power of this approach,
there are significant settings where the knowledge necessary to specify a
causal diagram over all variables is not available, particularly in complex,
high-dimensional domains. In this paper, we introduce a new graphical modeling
tool called cluster DAGs (for short, C-DAGs) that allows for the partial
specification of relationships among variables based on limited prior
knowledge, alleviating the stringent requirement of specifying a full causal
diagram. A C-DAG specifies relationships between clusters of variables, while
the relationships between the variables within a cluster are left unspecified,
and can be seen as a graphical representation of an equivalence class of causal
diagrams that share the relationships among the clusters. We develop the
foundations and machinery for valid inferences over C-DAGs about the clusters
of variables at each layer of Pearl's Causal Hierarchy (Pearl and Mackenzie
2018; Bareinboim et al. 2020) - L1 (probabilistic), L2 (interventional), and L3
(counterfactual). In particular, we prove the soundness and completeness of
d-separation for probabilistic inference in C-DAGs. Further, we demonstrate the
validity of Pearl's do-calculus rules over C-DAGs and show that the standard ID
identification algorithm is sound and complete to systematically compute causal
effects from observational data given a C-DAG. Finally, we show that C-DAGs are
valid for performing counterfactual inferences about clusters of variables.


  The Coulomb drag effect arises due to electron-electron interactions, when
two metallic conductors are placed in close vicinity to each other. It
manifests itself as a charge current or voltage drop induced in one of the
conductors, if the current flows through the second one. Often it can be
interpreted as an effect of rectification of the non-equilibrium $quantum$
noise of current. Here, we investigate the Coulomb drag effect in mesoscopic
electrical circuits and show that it can be mediated by $classical$
fluctuations of the circuit collective mode. Moreover, by considering this
phenomenon in the context of the full counting statistics of charge transport
we demonstrate that not only the noise power, but also the third cumulant of
current may contribute to the drag current. We discuss the situations, where
this contribution becomes dominant.


  We describe three-dimensional general relativistic magnetohydrodynamic
simulations of a geometrically thin accretion disk around a non-spinning black
hole. The disk has a thickness $h/r\sim0.05-0.1$ over the radial range
$(2-20)GM/c^2$. In steady state, the specific angular momentum profile of the
inflowing magnetized gas deviates by less than 2% from that of the standard
thin disk model of
  Novikov & Thorne (1973). Also, the magnetic torque at the radius of the
innermost stable circular orbit (ISCO) is only $\sim2%$ of the inward flux of
angular momentum at this radius. Both results indicate that magnetic coupling
across the ISCO is relatively unimportant for geometrically thin disks.


  In this paper, we propose a lightweight yet powerful dynamic epistemic logic
that captures not only the distinction between de dicto and de re knowledge but
also the distinction between de dicto and de re updates. The logic is based on
the dynamified version of an epistemic language extended with the assignment
operator borrowed from dynamic logic, following the work of Wang and Seligman
(Proc. AiML 2018). We obtain complete axiomatizations for the counterparts of
public announcement logic and event-model-based DEL based on new reduction
axioms taking care of the interactions between dynamics and assignments.


  Zonotopes are studied from the point of view of central symmetry and how
volumes of facets and the angles between them determine a zonotope uniquely.
New proofs are given for theorems of Shephard and McMullen characterizing a
zonotope by the central symmetry of faces of a fixed dimension. When a zonotope
is regarded as the Minkowski sum of line segments determined by the columns of
a defining matrix, the product of the transpose of that matrix and the matrix
acts as a shape matrix containing information about the edges of the zonotope
and the angles between them. Congruence between zonotopes is determined by
equality of shape matrices. This condition is used, together with volume
computations for zonotopes and their facets, to obtain results about rigidity
and about the uniqueness of a zonotope given arbitrary normal-vector and
facet-volume data. These provide direct proofs in the case of zonotopes of more
general theorems of Alexandrov on the rigidity of convex polytopes, and
Minkowski on the uniqueness of convex polytopes given certain normal-vector and
facet-volume data. For a zonotope, this information is encoded in the
next-to-highest exterior power of the defining matrix.


  Dental diseases have a significant impact on a considerable portion of the
population, leading to various health issues that can detrimentally affect
individuals' overall well-being. The integration of automated systems in oral
healthcare has become increasingly crucial. Machine learning approaches offer a
viable solution to address challenges such as diagnostic difficulties,
inefficiencies, and errors in oral disease diagnosis. These methods prove
particularly useful when physicians struggle to predict or diagnose diseases at
their early stages. In this study, thirteen different machine learning, deep
learning, and large language models were employed to determine the severity
level of oral health issues based on radiologists' reports. The results
revealed that the Few-shot learning with SBERT and Multi-Layer Perceptron model
outperformed all other models across various experiments, achieving an
impressive accuracy of 94.1% as the best result. Consequently, this model
exhibits promise as a reliable tool for evaluating the severity of oral
diseases, enabling patients to receive more effective treatment and aiding
healthcare professionals in making informed decisions regarding resource
allocation and the management of high-risk patients.


  We study linear stability of planar travelling waves for a scalar
reaction-diffusion equation with non-linear anisotropic diffusion. The
mathematical model is derived from the full thermo-hydrodynamical model
describing the process of Inertial Confinement Fusion. We show that solutions
of the Cauchy problem with physically relevant initial data become planar
exponentially fast with rate $s(\eps',k)>0$, where
$\eps'=\frac{T_{min}}{T_{max}}\ll 1$ is a small temperature ratio and $k\gg 1$
the transversal wrinkling wavenumber of perturbations. We rigorously recover in
some particular limit $(\eps',k)\rightarrow (0,+\infty)$ a dispersion relation
$s(\eps',k)\sim \gamma_0 k^{\alpha}$ previously computed heuristically and
numerically in some physical models of Inertial Confinement Fusion.


  A key challenge in machine learning is to design interpretable models that
can reduce their inputs to the best subset for making transparent predictions,
especially in the clinical domain. In this work, we propose a certifiably
optimal feature selection procedure for logistic regression from a
mixed-integer conic optimization perspective that can take an auxiliary cost to
obtain features into account. Based on an extensive review of the literature,
we carefully create a synthetic dataset generator for clinical prognostic model
research. This allows us to systematically evaluate different heuristic and
optimal cardinality- and budget-constrained feature selection procedures. The
analysis shows key limitations of the methods for the low-data regime and when
confronted with label noise. Our paper not only provides empirical
recommendations for suitable methods and dataset designs, but also paves the
way for future research in the area of meta-learning.


  Girard's Light linear logic (LLL) characterized polynomial time in the
proof-as-program paradigm with a bound on cut elimination. This logic relied on
a stratification principle and a "one-door" principle which were generalized
later respectively in the systems L^4 and L^3a. Each system was brought with
its own complex proof of Ptime soundness.
  In this paper we propose a broad sufficient criterion for Ptime soundness for
linear logic subsystems, based on the study of paths inside the proof-nets,
which factorizes proofs of soundness of existing systems and may be used for
future systems. As an additional gain, our bound stands for any reduction
strategy whereas most bounds in the literature only stand for a particular
strategy.


  In this work, we answer three fundamental questions concerning monostable
travelling fronts for the scalar Kolmogorov ecological equation with diffusion
and spatiotemporal interaction: these are the questions about their existence,
uniqueness and geometric shape. In the particular case of the food-limited
model, we give a rigorous proof of the existence of a peculiar, yet substantive
non-linearly determined class of non-monotone and non-oscillating wavefronts.
As regards to the scalar models coming from applications, this kind of wave
solutions is analyzed here for the first time.


  Oscillations in a power system can be categorized into free oscillations and
forced oscillations. Many algorithms have been developed to estimate the modes
of free oscillations in a power system. Recently, forced oscillations caught
many attentions. Techniques are proposed to detect forced oscillations and
locate their sources. In addition, forced oscillations may have negative impact
on the estimation of mode and mode-shape if they are not properly accounted
for. To improve the power system reliability and dynamic properties, it is
important to first distinguish forced oscillations from free oscillations and
then locate the sources of forced oscillations in timely manner. The negative
impact of forced oscillation can be mitigated when they are detected and
located. This paper provides an overview on the analysis technique of forced
oscillations in power systems. In addition, some future opportunities are
discussed on forced oscillation studies.


  In this note we present numerical study of spin dynamics of
$\vartheta$-soliton in Homogeneously precessing domain (HPD) in superfluid
$^3$He-B. The soliton consists of a small heavy core and long tails, in 1D
simulation we observe their mutual motion. We also discuss mass density and
tension of the soliton membrane and its 3D oscillations in a cylindrical cell.


  We present a test to quantify how well some approximate methods, designed to
reproduce the mildly non-linear evolution of perturbations, are able to
reproduce the clustering of DM halos once the grouping of particles into halos
is defined and kept fixed. The following methods have been considered:
Lagrangian Perturbation Theory (LPT) up to third order, Truncated LPT,
Augmented LPT, MUSCLE and COLA. The test runs as follows: halos are defined by
applying a friends-of-friends (FoF) halo finder to the output of an N-body
simulation. The approximate methods are then applied to the same initial
conditions of the simulation, producing for all particles displacements from
their starting position and velocities. The position and velocity of each halo
are computed by averaging over the particles that belong to that halo,
according to the FoF halo finder. This procedure allows us to perform a
well-posed test of how clustering of the matter density and halo density fields
are recovered, without asking to the approximate method an accurate
reconstruction of halos. We have considered the results at $z=0,0.5,1$, and we
have analysed power spectrum in real and redshift space, object-by-object
difference in position and velocity, density Probability Distribution Function
(PDF) and its moments, phase difference of Fourier modes. We find that higher
LPT orders are generally able to better reproduce the clustering of halos,
while little or no improvement is found for the matter density field when going
to 2LPT and 3LPT. Augmentation provides some improvement when coupled with
2LPT, while its effect is limited when coupled with 3LPT. Little improvement is
brought by MUSCLE with respect to Augmentation. The more expensive
particle-mesh code COLA outperforms all LPT methods [abridged]


  We present a technique to measure lightcurves of time-variable point sources
on a spatially structured background from imaging data. The technique was
developed to measure light curves of SNLS supernovae in order to infer their
distances. This photometry technique performs simultaneous PSF photometry at
the same sky position on an image series. We describe two implementations of
the method: one that resamples images before measuring fluxes, and one which
does not. In both instances, we sketch the key algorithms involved and present
the validation using semi-artificial sources introduced in real images in order
to assess the accuracy of the supernova flux measurements relative to that of
surrounding stars. We describe the methods required to anchor these PSF fluxes
to calibrated aperture catalogs, in order to derive SN magnitudes. We find a
marginally significant bias of 2 mmag of the after-resampling method, and no
bias at the mmag accuracy for the non-resampling method. Given surrounding star
magnitudes, we determine the systematic uncertainty of SN magnitudes to be less
than 1.5 mmag, which represents about one third of the current photometric
calibration uncertainty affecting SN measurements. The SN photometry delivers
several by-products: bright star PSF flux mea- surements which have a
repeatability of about 0.6%, as for aperture measurements; we measure relative
astrometric positions with a noise floor of 2.4 mas for a single-image bright
star measurement; we show that in all bands of the MegaCam instrument, stars
exhibit a profile linearly broadening with flux by about 0.5% over the whole
brightness range.


  The Kazakov--Migdal (KM) Model is a U(N) Lattice Gauge Theory with a Scalar
Field in the adjoint representation but with no kinetic term for the Gauge
Field. This model is formally soluble in the limit $N\rightarrow \infty$ though
explicit solutions are available for a very limited number of scalar
potentials. A ``Double Penner'' Model in which the potential has two
logarithmic singularities provides an example of a explicitly soluble model. We
begin by reviewing the formal solution to this Double Penner KM Model. We pay
special attention to the relationship of this model to an ordinary (one) matrix
model whose potential has two logarithmic singularities (the Double Penner
Model). We present a detailed analysis of the large N behavior of this Double
Penner Model. We describe the various one cut and two cut solutions and we
discuss cases in which ``eigenvalue condensation'' occurs at the singular
points of the potential. We then describe the consequences of our study for the
KM Model described above. We present the phase diagram of the model and
describe its critical regions.


  I review the latest heavy flavor measurements at RHIC experiments.
Measurements from RHIC together with preliminary results from LHC offer us an
opportunity to systematically study the sQGP medium properties. In the end, I
will outlook a prospective future on precision heavy flavor measurements with
detector upgrades at RHIC.


  Mechanisms proposed to explain the jet-related correlation of long range in
rapidity (the ridge) observed in high-energy heavy-ion collisions are reviewed.
Limitations of a model using the combined effect of transverse flow and a
direction bias of partons suffering energy loss are discussed. The influence of
the time scale of the correlation mechanism on the rapidity range is
investigated.


  Responsible artificial intelligence guidelines ask engineers to consider how
their systems might harm. However, contemporary artificial intelligence systems
are built by composing many preexisting software modules that pass through many
hands before becoming a finished product or service. How does this shape
responsible artificial intelligence practice? In interviews with 27 artificial
intelligence engineers across industry, open source, and academia, our
participants often did not see the questions posed in responsible artificial
intelligence guidelines to be within their agency, capability, or
responsibility to address. We use Suchman's "located accountability" to show
how responsible artificial intelligence labor is currently organized and to
explore how it could be done differently. We identify cross-cutting social
logics, like modularizability, scale, reputation, and customer orientation,
that organize which responsible artificial intelligence actions do take place
and which are relegated to low status staff or believed to be the work of the
next or previous person in the imagined "supply chain." We argue that current
responsible artificial intelligence interventions, like ethics checklists and
guidelines that assume panoptical knowledge and control over systems, could be
improved by taking a located accountability approach, recognizing where
relations and obligations might intertwine inside and outside of this supply
chain.


  The swelling of the viscosity radius, $\alpha_\eta$, and the universal
viscosity ratio, $U_{\eta R}$, have been determined experimentally for linear
DNA molecules in dilute solutions with excess salt, and numerically by Brownian
dynamics simulations, as a function of the solvent quality. In the latter
instance, asymptotic parameter free predictions have been obtained by
extrapolating simulation data for finite chains to the long chain limit.
Experiments and simulations show a universal crossover for $\alpha_\eta$ and
$U_{\eta R}$ from $\theta$ to good solvents in line with earlier observations
on synthetic polymer-solvent systems. The significant difference between the
swelling of the dynamic viscosity radius from the observed swelling of the
static radius of gyration, is shown to arise from the presence of hydrodynamic
interactions in the non-draining limit. Simulated values of $\alpha_\eta$ and
$U_{\eta R}$ are in good agreement with experimental measurements in synthetic
polymer solutions reported previously, and with the measurements in linear DNA
solutions reported here.


  In many data exploration tasks it is meaningful to identify groups of
attribute interactions that are specific to a variable of interest. For
instance, in a dataset where the attributes are medical markers and the
variable of interest (class variable) is binary indicating presence/absence of
disease, we would like to know which medical markers interact with respect to
the binary class label. These interactions are useful in several practical
applications, for example, to gain insight into the structure of the data, in
feature selection, and in data anonymisation. We present a novel method, based
on statistical significance testing, that can be used to verify if the data set
has been created by a given factorised class-conditional joint distribution,
where the distribution is parametrised by a partition of its attributes.
Furthermore, we provide a method, named ASTRID, for automatically finding a
partition of attributes describing the distribution that has generated the
data. State-of-the-art classifiers are utilised to capture the interactions
present in the data by systematically breaking attribute interactions and
observing the effect of this breaking on classifier performance. We empirically
demonstrate the utility of the proposed method with examples using real and
synthetic data.


  Given two positive integers $n$ and $k$, we obtain a formula for the base
size of the symmetric group of degree $n$ in its action on $k$-subsets. Then,
we use this formula to compute explicitly the base size for each $n$ and for
each $k\le 14$.


  Algorithmic information theory studies description complexity and randomness
and is now a well known field of theoretical computer science and mathematical
logic. There are several textbooks and monographs devoted to this theory where
one can find the detailed exposition of many difficult results as well as
historical references. However, it seems that a short survey of its basic
notions and main results relating these notions to each other, is missing.
  This report attempts to fill this gap and covers the basic notions of
algorithmic information theory: Kolmogorov complexity (plain, conditional,
prefix), Solomonoff universal a priori probability, notions of randomness
(Martin-L\"of randomness, Mises--Church randomness), effective Hausdorff
dimension. We prove their basic properties (symmetry of information, connection
between a priori probability and prefix complexity, criterion of randomness in
terms of complexity, complexity characterization for effective dimension) and
show some applications (incompressibility method in computational complexity
theory, incompleteness theorems). It is based on the lecture notes of a course
at Uppsala University given by the author.


  We present the Ba even-to-odd isotope abundance ratios in 25 cool dwarf stars
with the metallicity [Fe/H] ranged between 0.25 and --1.35. Our method takes
advantage of the hyperfine structure (HFS) affecting the \ion{Ba}{ii} resonance
line of the odd isotopes. The fractional abundance of the odd isotopes of Ba is
derived from a requirement that Ba abundances from the resonance line $\lambda
4554$ and subordinate lines $\lambda 5853$ and $\lambda 6496$ must be equal.
The results are based on NLTE line formation and analysis of high resolution (R
$\sim60000$) high signal-to-noise (S/N $\ge 200$) observed spectra. We find
that the fraction of the odd isotopes of Ba grows toward the lower Ba abundance
(or metallicity) and the mean value in the thick disk stars equals 33 $\pm$ 4%.
This indicates the higher contribution of the $r-$process to barium in the
thick disk stars compared to the solar system matter. The obtained fraction
increases with the [Eu/Ba] abundance ratio growth in agreement with
expectations. A significant fraction of the \emph{even} isotopes of Ba found in
old Galactic stars (the thick disk stars), $\sim67$%, is in contrast to the
prediction of the "classical" model of the $s-$process and favors the value
predicted by the "stellar" models of Arlandini et al. (1999) and Travaglio et
al. (1999).